by Kunjumon Vadakkan
Welcome!
Objective: To solve the nervous system—specifically, to understand how first-person inner sensations (what we refer to as the "mind") occur during brain functions such as memory and perception, both by itself and along with third-person observable motor actions like speech and behavior.
What is this website about?
For students: What makes us feel, think, and remember things? The semblance hypothesis is a new idea that explains how these inner experiences are formed in the brain. It has found that when we learn something, tiny new connections form between brain cells (not the already known synaptic connections), which later help us remember things in a very peculiar way that we never thought before. Since only the owner of the brain can feel the inner experiences, a researcher coming from outside cannot study these. So how do we go from here? There are three ways. 1) We can test whether we will be able to explain all the findings of the system in an interconnected manner using these new connections. 2) We can test for these connections. 3) We can verify testable predictions given by the hypothesis.
For researchers: Since first-person property is the brain’s most important and unique function—yet cannot be directly tested—it requires an unconventional approach to solve this system. This relies on a theoretical solution that can provide testable predictions. Validity of the solution depends on (a) its ability to offer a mechanistic explanation for how inner sensations arise in a network of cells in close conjunction with motor actions (specifically, a few milliseconds beforehand), and (b) whether this mechanism can provide coherent interconnected explanations to satisfy the constraints derived from findings across all levels of brain function. If these conditions are met, the proposed mechanism is likely to be accurate, and its testable predictions can be verified—it is the strength of this approach. The semblance hypothesis has successfully met the first criterion and continues to pursue interconnected explanations for various empirical findings, guided by the principle of falsifiability.
In simple words, what is semblance hypothesis?
Scientists study most parts of the body by looking at them from the outside. For example, they can see how the heart pumps blood, how the kidneys clean it, or how DNA helps make proteins. These are all things that can be studied using a third-person point of view — like an outside observer looking in. But the brain is different. Some of its most important jobs, like how we see, remember, or feel things, are inner experiences — what we call first-person sensations. These are things only the person having them can truly feel. Even though scientists can’t directly access these feelings, they have been trying to study them by looking at the brain from the outside. They’ve used many methods — like checking brain chemicals, cells, electrical signals, brain scans, and even behavior — to try to understand how the brain works. But these methods still can’t really explain what inner experiences feel like. To truly understand these personal, inner sensations, a scientist would need to somehow experience the brain from the inside — like becoming part of another person’s brain. But that’s not possible. Because of this, our current ways of studying the brain have hit a limit.
This work tries to go beyond that limit using a new idea: a theoretical approach — thinking through how things might work. We’ve never studied a system that creates inner feelings before. So, we must prepare ourselves to look for a unique mechanism — something hiding in plain sight — that has the ability to evade our attention! When approached in this way, it was possible to find a feasible mechanism that can generate first-person inner sensations within the neuronal network. A particular manner in which neurotransmission takes place at the synaptic junctions, and a new theoretically possible connection can allow the nervous system to produce first-person property. If this is true, then this central feature should allow us to interconnect all the findings of the nervous system from different levels and should be able to explain neurological and psychiatric disorders. This work has been successful in achieving these goals until now. Best of all, the theory makes predictions that scientists can test in future experiments.
Are there different ways to view this hypothesis? One, Two
Can you explain the hypothesis using a figure? To understand how this works, the first step is to find the exact place in the neuronal network that learning-related changes can happen. After that, we have to examine this location for a feasible mechanism that can generate memories as first-person inner sensations. When we look closely at the mechanism, we should be able to appreciate why we’ve had such a hard time noticing it before. We’ve made some diagrams to help explain this idea: Figure 1 shows the basic idea of the hypothesis — how changes in brain connections might work during learning and memory. Figure 2 shows more details about the black box problem we’re trying to solve (Figure 2 is more technical & you may skip it for now). You can check out Figure 20 on the FAQ page of this website for the solution for the black box problem.
Figure 1. Black box where certain changes take place during learning. A) In a conditioned learning experiment, two different types of stimuli are used that can create both feelings (like emotions or thoughts) and actions (like movement). For example, a bell ringing (called the Conditioned Stimulus or CS) and the sight of food (called the Unconditioned Stimulus or US). When these stimuli are shown independently, only the food causes a reaction, like salivating or getting excited (Even though an animal can turn its head towards the source of bell, it is often ignored). Now we can make a connection between these two stimuli by showing them at the same time to the animal. Here, we are teaching the animal to associate the sound of the bell with food — meaning that each time the animal hears the bell, food will be there. This learning event will create certain changes in the brain of the animal. We want to find out the location and the mechanism of this change. B) After learning, just hearing the bell (CS) can cause the output features in response to food (and sound) — even without the food. So how does the brain connect the sound of the bell with the idea of food? Scientists believe there's a hidden area — called a “black box” — between the brain pathways that handle the sound and the food. Inside this black box, something changes during learning. These changes must happen really fast (within milliseconds), and they must be simple and something evolution would naturally select. The big question is: Where and what kind of learning mechanism can allow the bell-sound alone to cause the same reaction as the food? A possible answer to this is explained by the present work, and a summary of it is shown in Figure 20 on the FAQ page.
Figure 2. How to solve the black box of the nervous system? Let us imagine that associative learning takes place between two sensory stimuli. Stimulus 1 and Stimulus 2 activate their corresponding sensory receptors, and the stimulus-induced depolarizations propagate through their synaptically-connected neuronal paths (Neurons along the pathways of Stimulus 1 and Stimulus 2 are marked N1 to N5 and N6 to N9 respectively). We want to know the location & the type of change that occurs during learning. It is reasonable to expect that learning cause certain changes at the location of convergence of Stimulus 1 and Stimulus 2. After learning, when Stimulus 1 arrives (as a cue stimulus), it should be able to generate internal sensation of features of Stimulus 2, which we call as memory of Stimulus 2. The learning mechanism at the location of convergence should also explain how the cue stimulus (Stimulus 1) can produce behavioral motor actions reminiscent of Stimulus 2. If we can provide explanations for these, then we are moving in the right direction for solving the system. Our task is to find the exact location where and how the learning-change is occurring that allows Stimulus 1 to spark memory of the associatively learned Stimulus 2 in physiological timescales of milliseconds along with provision for generating behavioral motor actions reminiscent of the arrival of Stimulus 2. Note that neuron N5 has two dendritic spines on its dendrite. Also note that the mean inter-spine distance between adjacent spines on a dendrite is more than the mean spine diameter. Where should neurons N5 and N9 connect OR interact, that will later allow Stimulus 1 to generate units of first-person inner sensations of memory of Stimulus 2, and also produce motor actions reminiscent of the arrival of Stimulus 2? This learning change should have the ability to get stabilized for long-term memory. Inset: A synaptic junction between neurons N4 and N5 (marked Pre 1 and Post 1) along the path through which Stimulus 1 propagates is shown. The still unknown mechanism is shown as a large black box next to this synaptic junction. To decipher the secret, it is necessary to view memories as first-person inner sensations generated within milliseconds using a learning mechanism also capable of taking place in milliseconds. Semblance hypothesis has provided a solution for the contents in this black box that can explain how 1) the association between Stimulus 1 and Stimulus 2 is completed during learning within milliseconds, and 2) at a later time when the Stimulus 1 arrives (as a cue stimulus) how does it generate inner sensation of memory of Stimulus 2 within milliseconds and generates motor actions reminiscent of the arrival of Stimulus 2. It is hoped that the readers will be able to find a testable mechanism by the end of reading FAQ page of this website. A possible answer to the Black box problem is given n Figure 20 on the FAQ page.
How should we understand the current challenges in neuroscience?
The functions of the nervous system are studied across multiple levels by various scientific disciplines—including biochemistry, cell biology, electrophysiology, systems neuroscience, psychology, imaging, behavioral science, and consciousness research. Different findings from these fields form a complex, multidimensional puzzle. Solving this puzzle requires fitting the right pieces at the correct levels to reveal how the system operates as a whole. If we focus only on one or a few levels, we might arrive at partial solutions that apply only to those areas. Features at unexamined levels will likely remain unexplained, leaving the overall system unresolved. The diversity of findings across different levels suggests that the true solution will be both unique and, paradoxically, simple. To uncover the correct mechanism, we must study representative functions from all levels simultaneously.
A second perspective begins with a comparison: we observe the heart pumping blood and the kidneys filtering waste from third-person viewpoints. Our understanding of these organs has been sufficient to replicate their functions through technologies like the artificial heart and dialysis. But what operational mechanism must we understand in the brain to replicate or replace it? The brain generates an internal experience of the external world during perception, stores sensory information through associative learning, and later generates memories as inner sensations when triggered by cues. It also produces thoughts that link different learned events—functions that are inherently first-person and inaccessible to third-person observation. From the perspective of an outside observer, the only available clues to these internal processes come through surrogate markers like speech and behavior. Therefore, any model of brain function must be able to account for both first-person experiences and third-person observable outputs.
A third perspective arises when we approach the problem as engineers aiming to replicate the brain in an artificial system. Since even lower animals exhibit intentional behaviors necessary for survival and reproduction, there must be a conserved neural mechanism responsible for generating internal sensations across species. Because first-person experiences cannot be directly studied from the outside, they are difficult to access in biological systems. For this reason, replicating the brain’s mechanism in engineered systems should be considered the gold standard. These systems must be designed to produce measurable readouts of internal sensations. As builders, we are driven to discover the brain’s operational logic by exploring all possible mechanisms and identifying the correct one. Our focus is on explaining how inner sensations form in real time, and we must sketch the design of such a system before we can begin to build it.
A fourth viewpoint emerges when examining the system through its dysfunctions at various levels. Observing these “loss of function” states can offer crucial insights into the nature of the puzzle's components. In the early days of genetics, research into “inborn errors” of metabolism helped unravel the organization of genes. Similarly, by analyzing neurological and psychiatric disorders—and the ways in which they alter brain function—we may be able to deduce the brain’s underlying operational mechanism.
What makes solving the nervous system so difficult?
1. The frame of reference problem: Throughout history, whenever we've encountered a frame of reference issue, scientific progress has required a shift in perspective. A classic example is our inability to sense the Earth's rotation—despite the Earth spinning at about 1670 km/h. We don’t feel this motion because we are rotating with the Earth; we share the same frame of reference. In neuroscience, the fact that third-person observers cannot directly access or experience a subject's first-person inner sensations presents a similar problem. It’s a mismatch of perspective: an internal, subjective experience being studied from an external, objective viewpoint. In physics, inaccessible truths are often inferred using constraints from observable phenomena. For instance, Galileo proposed that the Sun was at the center of the universe (at the time) based on indirect but consistent observational evidence. A similar shift in perspective may be needed to understand the brain's inner workings.
2. The challenge of studying the “virtual” nature of inner sensations: We are no strangers to virtual constructs. Numbers, for example, are not physically real—they are mental constructs that help us represent real-world quantities. Negative numbers are even more abstract, existing only in the mind, yet they’re essential in mathematics. We’ve gone further by inventing complex numbers using imaginary components, allowing us to solve previously intractable problems like the square roots of negative numbers. These virtual tools have advanced science dramatically. In the same way, once we understand where and how units of inner sensation are generated in the nervous system, we may be able to conceptualize a “virtual space” in which these sensations exist. This could allow us to map, track, and understand different forms and dynamics of inner experience.
3. The problem of access: How do we study something that our senses can’t directly perceive? This isn’t a new issue in science. We can't see DNA with the naked eye, but by staining it with ethidium bromide, we can make it visible under UV light. This principle—using indirect techniques to access what is otherwise inaccessible—is a powerful one. Similarly, understanding inner sensations will likely require indirect, or even multi-step indirect, approaches. These methods might feel unfamiliar at first, but over time, they could become standard tools in neuroscience, just as staining methods became routine in molecular biology.
How did Galileo teach us to infer the unseen from observations?
When we collect multiple observations from a system, combining them can lead to powerful insights—sometimes ones that go beyond what our senses alone can directly detect. Galileo Galilei provided a classic example of this in the early 17th century. In 1610, while observing Jupiter through a telescope, Galileo discovered four moons orbiting the planet. This was groundbreaking. If these moons were circling Jupiter, it challenged the long-held belief that everything in the universe revolved around the Earth. The existence of objects orbiting something other than Earth strongly suggested that Earth might not be the center of the universe after all.
Galileo’s observations of Venus offered even more compelling evidence. He noticed that Venus went through phases similar to the Moon—New, Full, and in between. More interestingly, Venus appeared largest when it was in the New phase (closer to Earth) and smallest when Full (farther away). From this, Galileo deduced that Venus must be orbiting the Sun. The only model that could explain these changes in size and illumination was one where the Sun, not Earth, was at the center. This also implied that Earth and the other planets must likewise orbit the Sun. What Galileo couldn’t see directly with his senses, he inferred logically through the combination of multiple observations. For instance, we now know that when Venus is in its New phase, it is between Earth and the Sun, blocking more light and appearing larger. When it’s in its Full phase, it is on the far side of the Sun, making it appear smaller and fully illuminated from our perspective. These conclusions led Galileo to reject the geocentric model. He saw the elegance and simplicity in a heliocentric system where all planets orbit the Sun. Despite knowing that many would resist this idea, he persisted, using logic and evidence to build his case.
This method—gathering observations and integrating them to reach conclusions beyond direct sensory experience—is a cornerstone of scientific thinking. It highlights how science allows us to discover truths that may not be intuitively obvious or immediately visible.
Footnotes: While Galileo was instrumental in supporting the heliocentric model, it was Nicolaus Copernicus who first proposed that the Sun was stationary and that Earth and the other planets revolve around it. Additionally, although Galileo believed the planets moved in circular orbits, it was Johannes Kepler who later discovered that they follow elliptical paths.
How can we solve the nervous system?
To approach a solution for the nervous system, we must begin by asking three fundamental questions:
1. How can we understand how the nervous system works, even without fully replicating its mechanisms in engineered systems?
2. What kind of explanation for first-person inner sensations can coherently integrate all findings from different levels of investigation?
3. How can we arrive at a solution that leads to testable predictions?
The key challenge lies in accounting for all available observations across the system. Therefore, it is essential to examine findings from various levels—molecular, cellular, systemic, behavioral, and experiential—simultaneously. Since there is likely only one correct, unified explanation, a solution that successfully interconnects observations from all levels is a strong candidate for being accurate. From there, we must use the proposed solution to generate testable predictions and validate them through experimentation.
As we venture further from directly observable realities, logical reasoning becomes increasingly important (see an excerpt from Krakauer et al., 2017, Neuron). The true structure-function mechanism of the nervous system must offer a coherent framework that connects diverse pieces of evidence. Given the virtual and inaccessible nature of first-person experiences, our approach should borrow from the principles of physics—where indirect reasoning and inference are often necessary (see Table 1). While research today tends to move toward increasing specialization, solving this puzzle may require going in the opposite direction: integrating knowledge across disciplines. Recognizing this need for a unifying, cross-level perspective is the first and most critical step toward uncovering the nervous system’s underlying logic.
| Physics | Neuroscience | |
|---|---|---|
| 1 | First, a large number of observations are collected that seem unrelated in nature, meaning they cannot be explained using one another. | Neuroscience includes many seemingly unrelated findings (see Table 2) that require a unifying explanation. For example, how are system-level functions connected to sleep and the electrophysiological phenomenon of long-term potentiation (LTP)? |
| 2 | This suggests the existence of a fundamental underlying principle that can unify these disparate observations. | A fundamental underlying principle should exist that connects all the observations listed in Table 2. |
| 3 | Some features of the elements associated with this underlying principle—such as particles and fields—cannot be directly perceived by our sensory systems. | There exists a principle whose products—such as inner sensations—are not accessible to third-person sensory systems. Nevertheless, the mechanism behind this principle should be capable of coherently explaining and linking all observed findings. |
| 4 | Constraints from disparate observations should help guide us toward a solution. This process often begins with logical deduction, followed by mathematical approximations—as seen in the development of theories like special and general relativity or the prediction of the Higgs boson. | A structure-function mechanism should be pursued through logical deduction combined with trial-and-error methods. The numerous constraints provided by diverse findings can help shape and guide the search for a solution. Success depends on following a path that remains consistent with all these constraints. Only when the correct solution is found will it be possible to coherently explain and interconnect all the observations. |
| 5 | The solution is confirmed by testing the predictions that can be verified. | The predictions generated by the derived mechanism can be tested and verified. |
Table 1. Offers a comparison between the approaches taken in physics and neuroscience when addressing the challenge of unifying disparate findings—particularly when those findings involve phenomena inaccessible to our sensory systems, such as subatomic particles, fields, or first-person internal sensations.
Drawing parallels between solving the nervous system and linear algebra
The deep principles underlying many discoveries in physics bear a strong resemblance to the methods used in linear algebra—specifically, in solving large systems of linear equations that have a unique solution. In such systems, the relationships between variables in each equation offer crucial clues that guide us toward the final answer. To solve for all variables, the system must contain at least as many independent equations as there are unknowns. Similarly, the nervous system presents us with a vast array of findings across many different levels—molecular, cellular, systems, behavioral, and experiential. By identifying and using even subtle interconnections among these observations, we can begin to piece together the full picture. This is an enormous challenge, especially since biology lacks the neat, standardized methods that exist in mathematics. However, understanding the logic behind linear algebraic solutions can provide a useful conceptual framework.
Take, for example, the Gauss-Jordan elimination method in linear algebra—a tool designed to systematically solve a system of linear equations. It was developed by someone who not only grasped the deeper principles behind such systems but also worked to simplify the process for others. Although linear algebra problems can also be solved by trial-and-error, such methods become inefficient as the number of variables increases. Availability of Gauss-Jordan method even makes us to forget that a system of linear equations can be solved by trial-and-error method. By viewing nervous system as a large system of equations (both linear and non-linear) and there is no short-cut method like Gauss-Jordan to solve it, it needs to be solved by trial-and-error method. When dealing with a complex system containing many distinct observations (akin to equations), the true solution will be the one that ties all of them together. One practical approach is to work with subsets of findings—looking for solutions that can explain a few observations at a time (see FAQ section of this website). In linear algebra, different subsets of equations will likely give many solutions—and from these, a common solution for all the variables may be found. A similar approach can be undertaken for the nervous system. Alternatively, sets of findings having all the variables in them can be used to find a unique solution.
Encouragingly, the complexity of the nervous system doesn't mean endless ambiguity. On the contrary, if there is only one unique solution, incorrect ones can often be ruled out quickly. Importantly, some components of this mechanism may remain imperceptible to our sensory systems, even after they are identified (see Fig. 4). However, we expect these components to show testable changes during learning, which are reactivated during memory retrieval, triggering the basic units of internal sensation. The integration of these units is expected to result in the qualia of memory—the subjective experience associated with remembering.
Figure 4. Method for deriving a solution to the system based on third-party observed findings. A) The features of the system are detected either directly (represented by the capital letter K) through our sensory systems or indirectly (represented by the capital letters D, E, G, H) through findings such as protein staining or behavioral observations. These features are connected through smaller letters (u, w, v, x), which represent relationships between the features (e.g., the observation of u enables the detection of D). B) By utilizing both commonly employed direct and indirect methods, three clusters of interconnected findings (depicted by dotted lines) are identified across different levels (observations from various fields of brain science). In many instances, it is not possible to establish connections between these clusters. For example, no direct connection was found between: 1) the changes in learning and the internal sensations of memory occurring at millisecond timescales, and 2) sleep and long-term potentiation (LTP). However, by examining the constraints within each cluster, we can assess whether they can be unified through a common operational mechanism. In the context of the nervous system, a vast array of findings and the constraints they provide can be explored. C) By leveraging the constraints from certain features within each cluster of seemingly unrelated findings (e.g., A, B, and C), we aim to derive a deep underlying principle (a structure-function solution m) that enables their interconnection. This solution is expected to offer a mechanism for generating internal sensations at millisecond timescales. D) The solution m provides an explanation of how the various findings within each cluster are interrelated with one another and with findings from other clusters, as shown in B). Although it remains undetectable by current biological investigation methods, the ability of solution m to integrate findings across all clusters makes it a further verifiable solution (Figure from Vadakkan, 2019).
There is an extensive collection of observations across different levels of the nervous system's functions (Table 2). An analogy with store receipts store receipts—drawing from the fundamental principles used in some physical sciences to understand nature—provides confirmatory evidence that a correct final solution can be reached. This is possible if we gather a large number of findings that account for all the system's variables.
Progress: Constraints were derived from a wide range of experimental findings that used behavior as an externally measurable outcome. Based on these findings, a solution was formulated. Upon exploring the vicinity of the solution, a mechanism capable of generating first-person properties was discovered. For more details, please refer to the FAQ page.
The following are key findings observed across various levels of nervous system function, each offering specific operational constraints. The semblance hypothesis offers a unifying explanatory framework that accounts for these findings, thereby supporting its potential validity. This convergence supports its plausibility and underscores the need to test its predictions—especially given the difficulty of probing subjective experience directly. | |||
| Findings across multiple levels of the nervous system | Constraints derived from the findings (listed on the left) help guide the inquiry toward the correct solution. | It is important to note that all explanations must be interconnected to support the claim that a solution has been found (see Fig.4 above). (Please read this column after reviewing the hypothesis on the FAQ page) | |
| 1 | Both associatively learned stimuli & the prompt (cue) stimulus propagate through synaptically connected neuronal circuits. | Mechanism should operate synchronously with the synaptically connected circuitry. | Inter-neuronal inter-postsynaptic functional LINKs (IPLs) form and operate only when synaptic transmission takes place (Vadakkan, 2007; 2013) between connected neurons. |
| 2 | Memories are virtual first-person inner sensations. | It is essential to identify both the location & the mechanism responsible for its generation. | In the background state, the spine head (postsynaptic terminal) undergoes continuous depolarization due to the quantum release of neurotransmitter molecules. In addition, there is intermittent arrival of large potentials triggered by action potentials at the presynaptic terminal. In this context, the lateral entry of depolarization into an inter-LINKed spine via an inter-postsynaptic functional LINK (IPL) is expected to mislead the inter-LINKed spine (and the system as a whole), causing it to 'hallucinate' that it is receiving inputs from lower neuronal orders through its presynaptic terminal that eventually reach the sensory receptors. Content of the hallucination consists of sensory stimuli needed to stimulate those receptors & is first-person inner sensation of memory. |
| 3 | Learning-induced changes take place on physiological timescales, occurring within milliseconds. Foot note 1 | A learning-induced mechanism that initiates & completes within physiological timescales. | IPL formation is expected to occur within milliseconds between abutted spines at points where the pathways of associated stimuli converge. |
| 4 | Memory retrieval occurs on a millisecond timescale. | Since the memory of a learned association can be retrieved immediately after learning, it is essential to demonstrate a retrieval mechanism that operates within milliseconds. | The propagation of potentials across IPLs to inter-LINKed spines—leading to the generation of first-person inner sensations—is expected to occur within physiological timescales of milliseconds. (Vadakkan, 2007; 2013). |
| 5 | After associative learning between two items, the presentation of one item triggers the memory of the other. | The learning mechanism must be capable of explaining how either item in an associative pair can serve as a cue to evoke the memory of the other. Therefore, the mechanism must inherently support bidirectional activation. | An IPL can be reactivated from either side, inducing semblance on the inter-LINKed spine on the opposite side (Vadakkan, 2010; 2013). Several learning events lead to the formation of IPLs between a large number of abutted spines forming islets of inter-LINKed spines. The propagation of potentials across IPLs, even to a distantly located spine within the same islet, can generate semblance, facilitating the formation of memory. |
| 6 | Even partial features of one associatively learned item can trigger the memory of the second item. | The mechanism must include features that explain how stimuli derived from partial aspects of one item can retrieve the memory of the second associatively learned item. | Partial stimuli propagate to generate numerous units of inner sensations across multiple inter-LINKed spines. Since extrapolation from these inter-LINKed spines to sensory receptors inevitably results in significant overlap of semblances (see Figs. 9 and 10 in the FAQ section), the net inner sensation is expected to contain nearly all the features of the item whose memory is being retrieved (Vadakkan, 2010; 2013; 2019). |
| 7 | Memories that can be retrieved long after learning were also capable of being accessed immediately following the learning process (working memory). | Changes generated by learning can be used for immediate memory retrieval (working memory). These changes must be able to remain stable over time, supporting long-term memory (LTM). | IPL formation occurs during learning. When the IPL is reversed, the short-term function of an inter-LINKed spine contributes only to working memory. The long-term stabilization of IPLs allows them to be used for memory retrieval (via a cue stimulus) over extended periods, supporting long-term memory (LTM) (Vadakkan, 2010; 2013). |
| 8 | Gradual changes in the qualia of the inner sensation of memory occur as the cue stimulus changes progressively. | It is expected that there is a mechanism to integrate individual elements in order to generate the inner sensation of memory. | The integration of units of inner sensations is expected to be facilitated by oscillating potentials within the connected elements of the system, reflected in the extracellular matrix by the oscillations of extracellular potentials. As the cue stimulus changes, new sets of specific units of inner sensations are generated and integrated (Vadakkan, 2010). |
| 9 | Absence of cellular changes during memory retrieval. | Memory retrieval should involve the passive reactivation of changes that occurred during learning, which induces units of internal sensations. | Since inter-LINKed spines persist from the time of learning, the propagation of depolarization across the IPLs and the reactivation of inter-LINKed spines to generate units of inner sensations do not require any new cellular changes (Vadakkan, 2010). |
| 10 | The capacity to store extensive sets of learning-induced changes underlies the ability to retrieve a large number of memories. | Since the brain has a finite set of neuronal processes and cells, storing a vast number of memories requires an explanation of a combinatorial mechanism. This mechanism allows a specific cue stimulus to trigger a specific set of unitary processes, which are integrated to generate a specific memory. | Since sensory stimuli from items or events consist of combinations of various sensory inputs, different cue stimuli are expected to activate distinct combinations of inter-LINKed spines, thereby generating corresponding memories. From this, it can be inferred that the system operates in a way that is equivalent to storing and retrieving a vast number of memories (Vadakkan, 2010). |
| 11 | Instant access to very large memory stores. | It is essential to explain how a vast number of memories can be retrieved instantly. This requires demonstrating an instantaneous combinatorial mechanism of unitary operations that occurs without delay. | A specific cue stimulus can reactivate a particular set of IPLs and generate units of inner sensations within milliseconds. The instantaneous integration of these units enables immediate access to a large number of memories (Vadakkan, 2010). |
| 12 | Transfer of learning (Dahlin et al., 2008). | It is important to demonstrate how the criterion and transfer tasks engage specific overlapping processing components and brain regions (Dahlin et al., 2008). It is reasonable to expect the generation of a surplus number of unitary elements from different locations. | Memory is the integrated units of inner sensations. These unitary elements can originate from different locations. Oscillating extracellular potentials, which form a continuum across multiple brain areas, integrate these unitary elements (Vadakkan, 2013). The generation of a surplus number of unitary elements from various brain regions allows them to substitute for one another. |
| 13 | During memory retrieval, a subset of neurons that were previously unresponsive to the cue stimulus become active. | It is necessary to provide an explanation that learning opens new pathways, allowing the cue stimulus to propagate depolarization through these channels. This provides additional input to a subset of neurons that were previously held in a sub-threshold state (not firing), bringing them to the firing threshold during memory retrieval. | The formation of IPLs during learning enables the propagation of depolarization to inter-LINKed spines, providing additional input to their associated neurons. If this input is sufficient to bring the neurons to threshold, it may trigger their firing (Vadakkan, 2013). |
| 14 | The brain operates in a narrow range of frequencies of extracellularly recorded oscillating potentials. | The operational mechanism is expected to generate vector components of the oscillating extracellular potentials, accompanied by corresponding intracellular ionic concentration changes within the neuronal processes of the involved neurons. | Synaptic transmission, along with the near-perpendicular propagation of depolarization across the IPL, can contribute vector components to oscillating extracellular potentials (Vadakkan, 2010). These oscillating potentials are thought to have the capacity to bind specific units of inner sensations associated with particular cue stimuli. |
| 15 | Motivation enhances learning and is associated with the release of dopamine, which activates dopamine receptors in various regions of the brain (lino et al., 2020). | Motivation is likely linked to specific factors whose actions are expected to enhance learning-induced changes and potentially sustain these changes for a longer duration compared to when such factors are absent. | Dopamine has been shown to induce spine expansion (Yagishita et al., 2014). The expansion of spines is expected to enhance IPL formation & help maintain these IPLs over time, potentially initiating stabilization processes. |
| 16 | Most excitatory glutamatergic synapses are located on dendritic spines, which enlarge during learning. Glutamate induces spine enlargement in both hippocampal slices (95%) (Matsuzaki et al., 2004) & the neocortex in vivo (22%) (Noguchi et al.,2019). | Spine enlargement is thought to serve specific functional purposes, particularly in regions where the extracellular matrix (ECM) is thin. | Enlarging spines in regions with densely packed neuronal processes can promote IPL formation when two abutted spines, receiving converging associatively learned stimuli, come into contact. |
| 17 | The internal sensations associated with working, short-term, and long-term memories share similar qualia, which contribute to the formation of comparable memories. | The learning-induced change is retained for varying durations. Long-term memory loses clarity due to the loss of some unitary mechanisms and the dilution of specificity, as it blends with newly formed units of inner sensations at the islets of inter-LINKed spines. | Memory retrieval at different intervals after learning occurs through the reactivation of inter-LINKed spines, with depolarization propagating across the IPLs to generate units of inner sensations (Vadakkan, 2010; 2013). As a result, the same memory is retrieved, but with varying clarity. |
| 18 | Most learning events result in a working memory that lasts only for a short period and does not evolve into long-term memory. | The change induced by learning must involve a mechanism that is quickly reversible. | IPL formation is an energy-intensive process, as demonstrated in experiments with artificial membranes (Rand & Parsegian, 1984; Martens & McMahon, 2008; Harrison, 2015). As a result, most IPLs are expected to reverse rapidly, restoring the hydration layer between the membranes. |
| 19 | Some memories that are initially retrieved as working memories can later be retrieved as long-term memories, even after extended periods following learning. | It should be possible to explain how the learning-induced change undergoes certain modifications that allow it to be maintained over an extended period. | The stabilization of IPLs over long periods can evoke the same units of inner sensation throughout this time. If the number of inter-LINKed spines that can be reactivated by a cue stimulus decreases over time, the qualia of the memory will deteriorate (Vadakkan, 2010; 2013). |
| 20 | The simultaneous presence of the two conditions described above within the system. | The learning-induced mechanism should initially involve a quickly reversible change. However, under certain conditions, some of these changes can become stabilized for extended periods. | When memories of beneficial or harmful events become crucial for survival, the IPLs associated with these memories are stabilized for long periods (Vadakkan, 2010; 2013). In contrast, IPLs formed in response to even novel associations with no survival relevance reverse quickly. |
| 21 | Previous finding that memories involve time-dependent “tritrace” mechanisms (McGaugh, 1966) | A mechanistic explanation is needed for the findings that led to this previous inference. | IPLs are inherently rapidly reversible, so the majority will reverse after learning. However, some will persist for a short time, while others will be stabilized for longer periods. This explains the formation of short- and long-term memories. |
| 22 | The ability to store new memories without overwriting existing ones. | The system is expected to share unitary mechanisms for common features while also allowing the formation of new units with novel associations. Additionally, there must be a mechanism to integrate all unitary elements in response to specific cue stimuli, thereby preventing the overwriting of old memories. | Inter-LINKed spines within islets of inter-LINKed spines can be shared by any stimuli that reach them, eliminating the need to overwrite old memories. New associations lead to the formation of additional spines that link to the existing inter-LINKed spines (Vadakkan, 2010; 2013). |
| 23 | Memory consolidation refers to the apparent transfer of memory storage from the hippocampus to the cortex over a span of 5 to 8 years. | Specific learning-induced changes are added to the cortex over the course of years through a similar unitary operational mechanism in the hippocampus. The ability to generate memory relies on a global integrating mechanism that utilizes unitary elements from various brain regions. This process must involve a stage characterized by an excess of unitary mechanisms. | The convergence of pathways from different sensations in the hippocampus leads to the formation of large islets of inter-LINKed spines. Sparse convergence of these pathways in the cortex also generates IPLs. When associative learning events containing shared elements occur, coupled with the insertion of new neurons in the granule layer of the hippocampus, it results in the formation of a surplus of new sparse IPLs in the cortex over time (Vadakkan, 2011). Over the course of several years, these events contribute to the formation of a net semblance of memory for the item, localized in the cortex alone, which can be triggered by a cue stimulus. |
| 24 | The mechanism utilizes pre-existing schemas (Tse et al., 2007), which are expected to be used interchangeably. | Changes induced by one learning event can be shared with another event. For this to happen, there must be shared unitary mechanisms that facilitate the retrieval of different memories | Inter-LINKed spines can be activated by any cue stimulus that reaches them, generating similar units of inner sensations and allowing the shared use of unitary structural operations. In other words, pre-existing inter-LINKed spines are utilized by similar sensory elements present in a new learning event (Vadakkan, 2010a; 2013). |
| 25 | A dynamically adapting circuit mechanism. | The system should have provisions to accommodate a large number of new learning events, as well as a mechanism for the reversal of learning, which would explain the process of forgetting. | Each spine is abutted by several other spines from different neurons, facilitating the formation of IPLs between then during different learning events leading to islets of inter-LINKed spines (Vadakkan, 2010; 2013). While most newly formed IPLs are reversible, they also have the potential to stabilize. As a result, inter-spine links are highly dynamic." |
| 26 | A framework for a mechanism that enables the system to generate hypotheses. | When one of the basic mechanisms involved in an associative learning event between two items (1 and 2) becomes associated with a third item during a subsequent learning event (e.g., between 2 and 3), it creates an interconnected chain of associations LINKing 1, 2, and 3. Here, the system gains the ability to generate a hypothesis about a potential relationship between items 1 and 3. It is necessary to show that the system generates this ability. | When a spine from each of two islets of inter-LINKed spines becomes interconnected, every spine in the first islet forms a relationship with every spine in the second. This mechanism underlies the generation of hypotheses about possible relationships between stimuli arriving at one islet and those arriving at the other. Such unexpected associations between stimuli—formed when two separate islets become inter-LINKed during specific associative learning events—form the foundation for hypothesis generation (Vadakkan, 2010; 2013). |
| 27 | The system requires a sleep state for approximately one-third of its operating time. | It is essential to explain why the system cannot function or sustain itself without sleep—that is, to provide a rationale for the fundamental role that sleep plays in its operation. Sleep must serve a substantive, irreplaceable function; otherwise, dedicating nearly one-third of the system's operational time to this state would not be evolutionarily viable or energetically justified. | A state of sleep is necessary to maintain postsynaptic depolarization induced by the presynaptic terminal as the system's dominant state. This dominance is crucial for enabling a cue stimulus to evoke a memory. When a cue stimulus crosses the IPL, it triggers lateral activation of the inter-LINKed postsynaptic terminal, leading to the generation of units of inner sensation corresponding to the associatively learned second stimulus—even in its absence (Vadakkan, 2016). Therefore, only a system that undergoes sleep can exhibit this memory-generating capability (Minsky, 1980). |
| 28 | While living aboard a space station, the need for sleep decreases by more than an hour (Dijk et al., 2001; Gonfalone, 2016). | A mechanistic explanation is needed to clarify why reduced sensory stimuli in space lead to a decreased need for sleep. | Due to the reduced sensory stimuli in space, the frequency of reactivation of inter-LINKed spines is significantly lowered. As a result, less time of sleep is required to restore the system to its baseline dominant state, where postsynaptic terminals are depolarized by their presynaptic counterparts (Vadakkan, 2016). |
| 29 | During memory retrieval, the inner sensation of memory can occur either with or without motor actions, such as speech or behavioral movements. | The mechanism responsible for generating the inner sensation of memory must be connected to the mechanism that produces motor actions. Additionally, there should be a means to selectively disable this connection when needed. | The IPL mechanism can generate both units of first-person inner sensations and provide signals to motor neurons, triggering motor actions that mimic the arrival of the item whose memory is being retrieved. Additionally, motor outputs can receive inputs to voluntarily inhibit motor actions while the inner sensation is being generated (Vadakkan, 2010; 2013). |
| 30 | It is challenging to inhibit a memory once it is being retrieved. | A structural mechanistic explanation is needed. | The IPL is an inter-membrane connection. Once established and functional, it is not possible to voluntarily inhibit its activity. However, an additional inter-spine link with an inhibitory spine can be introduced through future associative learning events (Vadakkan, 2007; 2010). |
| 31 | The mean inter-spine distance on the dendrite of a pyramidal neuron exceeds the mean spine diameter (Konur et al., 2003). | A mechanistic explanation for this organization is required. It is reasonable to assume that this scheme of inter-spine spacing holds some functional significance. | This organization allows for neuronal processes from other neurons to occupy the inter-spine space. Since spines from different neurons share this space and the extracellular matrix (ECM) is often negligible (see Fig. 13 in FAQ), some spines from different neurons may remain abutted to one another. This proximity facilitates inter-neuronal inter-spine interactions, which form the basis for IPL formation, as proposed by the semblance hypothesis. (Vadakkan, 2010; 2013). |
| 32 | Learning and memory retrieval are associated with the activation of different sets of neurons. | Learning is expected to create new channels. The passage of potentials through these channels—both during learning and memory retrieval—facilitates the activation of neurons that are held at a sub-threshold level, allowing them to reach the threshold and fire a new set of neurons. | This process can be either a cause or an effect, depending on the spatial relationship of the neurons to the locations where specific learning changes occur. During learning, sensory stimuli trigger action potentials (neuron firing) that reach the sites of learning-related changes. The outputs from these neurons enable potentials to propagate through newly formed IPLs established during learning. This allows neurons, which are held at sub-threshold activation levels, to fire action potentials (Vadakkan, 2010; 2013). During memory retrieval, the presence of only one associated stimulus reduces the number of neurons firing. However, re-activation of the channel formed during learning can trigger neuronal firing in the post-channel area. |
| 33 | Place cells (CA1 neurons that fire in response to an animal's specific spatial location) are activated by particular spatial stimuli. | A mechanism that generates the inner sensation of memory for a location is likely to be mechanistically connected to the firing of a set of CA1 neurons. | Place cells are CA1 pyramidal neurons. When islets of inter-LIMKed spines from overlapping dendrites of different CA1 neurons receive spatial inputs, they provide additional potentials to their postsynaptic CA1 neurons. If these CA1 neurons are being held at subthreshold activation levels, they will fire in response to a specific location. This mechanism explains the firing of place cells (Vadakkan, 2013; 2016). |
| 34 | Hippocampal neurons in chickadees exhibit patterns of CA1 neuronal activity that are specific to the locations of hidden food, which result from the retrieval of specific memories of stored food. These patterns, however, are independent of place fields—the set of CA1 neurons that fire when the bird reaches the same location during a casual flight (Chettih et al., 2024). | An explanation is needed to clarify how different neurons fire during a visit to a location where food is hidden (presumably to check the safety of the food) compared to a casual visit to the same location. Since the location presents the same stimulus, what accounts for the differences in the firing patterns of the neurons? | According to the semblance hypothesis, the operation of inner sensations (semblance) occurs at the inter-LINKed spines. CA1 neurons are expected to have several inter-LINKed spines in clusters called islets of inter-LINKed spines. Based on the inputs reaching an islet, potentials that reach each postsynaptic CA1 neuron vary. Hence, depending on the inputs arrived and sub-threshold activation states, different sets of CA1 neurons are activated. Although the same location provides similar sensory inputs to a set of islets, additional inter-LINKed spines are activated to generate the inner sensation of food search, verification, threat, or safety. As a result, the set of postsynaptic CA1 neurons firing during these two events is likely to differ. |
| 35 | An inhibitor of AMPA receptor (AMPAR) endocytosis partially rescued long-term memory deficits in mice with elevated levels of amyloid-β (Yan et al., 2024). | A mechanistic explanation is required to understand this finding. | Endocytosis of AMPARs involves the use of membrane segments from the lateral spine membranes to form endosomes. This process results in a reduction in the size of spine heads and reverses the IPLs formed during learning. Therefore, inhibition of AMPAR endocytosis helps maintain spine heads at their maximum size, thereby facilitating the formation of IPLs. |
| 36 | Mice injected with histone acetyltransferase (HAT) exhibited enhanced fear memory. Neurons in which HAT was overexpressed are part of the engram (Santoni et al., 2024). | The removal of histones from DNA enhanced fear memory. An explanation is needed to clarify how exposing DNA by removing histones increases fear memory. It is important to demonstrate how histone acetyltransferase (HAT) facilitates the expression of genes, whose protein products are essential for memory storage. Alternatively, if other factors support this, memory may also be stored in DNA itself. | To preserve the IPLs formed during fear learning (which are essential for maintaining memory related to survival actions), neuronal cells likely adapt evolutionarily by restricting the use of membrane segments from spines for endocytosis. Instead, the synthesis of more phospholipid molecules is expected to occur, generating lipid membrane segments that help retain the IPLs. This process involves the synthesis of fatty acids (primarily palmitic acid) through a multi-enzyme complex composed of seven different enzymes, followed by the actions of desaturase and elongase enzymes, the synthesis of phospholipids, and their transport and incorporation into plasma membranes. In this context, HAT is expected to remove histones from the DNA sequences corresponding to these enzymes, thereby facilitating their expression. |
| 37 | The firing of an ensemble of neurons during a higher brain function. | The inner sensation generated during a higher brain function is linked to the firing of an ensemble of neurons. | Reactivation of IPLs during a higher brain function (which generates units of inner sensation) enables potentials to propagate from inter-LINKed spines to their postsynaptic neurons. If these potentials bring the neurons to threshold, they will fire (Vadakkan, 2010; 2016). |
| 38 | The firing of distinct sets of neurons during learning and memory retrieval. | Associative learning between two stimuli is expected to trigger the firing of a specific set of neurons. When only one of the learned stimuli is present to retrieve the memory of the second, only a subset of the neurons that fired during learning is expected to fire during memory retrieval. | During learning, two associating stimuli propagate depolarization along their respective pathways, resulting in the firing of a specific set of neurons. During memory retrieval, only one stimulus, or a partial feature of it, is present. During memory retrieval, in addition to the firing of neurons along the path of the cue stimulus, potentials propagating through the IPLs formed during learning will activate a set of neurons along the pathway through which the item being remembered previously propagated (Vadakkan, 2010; 2016). |
| 39 | Rapid changes in both the magnitude & correlational structure of cortical network activity (Benisty et al., 2024). | Rapidly time-varying functional connectivity is responsible for these changes. | Changes in environmental stimuli, self-triggered thought processes, and various inner sensations such as fear, anticipation, hunger, and comfort fluctuate moment by moment, indicating the formation and reactivation of new sets of IPLs. These fluctuations continue to modify the network activity (Vadakkan, 2019). |
| 40 | A cortical pyramidal neuron in one neuronal layer receives input from multiple neurons in lower layers (Ecker et al., 2010). | It is most likely that, at rest, pyramidal neurons are held in a sub-threshold state. If a cue-induced memory retrieval mechanism triggers the firing of a specific set of neurons that did not fire prior to learning (in response to the cue stimulus alone), it is necessary to demonstrate that learning generates a channel capable of being re-activated during memory retrieval. This reactivation would provide potentials to postsynaptic neurons, potentially bringing them to the threshold and enabling them to fire. | Recent modeling studies have shown that a pyramidal neuron can fire an action potential through spatial summation (simultaneous summation) of nearly 140 EPSPs at the axonal hillock, originating from randomly located dendritic spines (Palmer et al., 2014; Eyal et al., 2018). However, based on energy calculations per bit of information, around 2,000 synaptic inputs are required for neuronal firing (Levy & Calvert, 2021). The IPL mechanism explains how learning-induced changes can generate cue-induced inner sensations, as well as motor responses reminiscent of the arrival of the item whose memory is being retrieved. Furthermore, it also facilitates the firing of a new set of neurons. |
| 41 | Any set of 140 input signals arriving from random locations across the dendritic tree can trigger the firing of a neuron (Palmer et al., 2014; Eyal et al., 2018). This results in extreme degeneracy of input signals in neuronal firing. As there is no input specificity required for firing a neuron, information could potentially be lost. Nevertheless, a system operating under this scheme was selected from a range of variations because it provides functional advantages to the system. | Since such a scheme is expected to be used specifically, a plausible scenario must exist: If a neuron is held at a sub-threshold level by receiving nearly 130 inputs, then it will only fire if a specific set of 10 input signals arrive. This should be verifiable. It is important to provide an explanation of how information loss is prevented in this process. Additionally, an explanation is needed of how this operational scheme offers certain advantages. | Islets of inter-LINKed spines pool potentials, which can then be delivered in a summated manner. The high potential reaching the axonal hillock efficiently triggers the firing of motor neurons, leading to a motor effect. The inter-LINKing of spines that receive different neurotransmitters helps regulate these islets (Vadakkan, 2016). The limited number of muscles in the body must execute a vast array of motor outputs in response to a large number of sensory inputs. Therefore, the degeneracy of inputs required for neuronal firing, along with combinatorial motor unit activation, can be viewed as a means to enhance efficiency (for example, the muscles of the face and tongue generating speech). Since the reactivation of an IPL generates units of inner sensation, the information retrieved is specific to the spine. The integration of these units enables the generation of information in response to a specific cue stimulus, which is experienced as a first-person property. |
| 42 | Many neurons are being held in a sub-threshold activation state. | By holding a neuron at a specific potential below the threshold, it is possible to regulate its output, contingent upon the arrival of a certain number of inputs. This mechanism is crucial for generating specific motor outputs, such as speech and behavioral actions. | Several neurons are held at sub-threshold activation states (Seong et al., 2014). Islets of inter-LINKed spines facilitate the summation of potentials when many of their inter-LINKed spines receive simultaneous inputs, which can help the neuron reach the threshold to fire output neurons. However, if only a few inputs arrive at a large islet, the output to its postsynaptic neurons may be attenuated due to the propagation of potentials across all the inter-LINKed spines within the islet. |
| 43 | An operational mechanism is expected to occur in an energy-efficient location. | Input signals (postsynaptic potentials) have their maximum strength at the site of origin, which is the spine head. As these potentials propagate along the dendrite towards the neuronal cell body, they become attenuated. Additionally, signals from different spines mix within the dendrite. Therefore, the most likely location for a learning mechanism that maintains specificity until retrieval is expected to be in the spine head region. | IPLs are formed between the head regions of abutted spines that belong to different neurons (Vadakkan, 2010; 2016). Therefore, information arriving at the input regions is best preserved when learning-related changes occur at the spine head region. (Note that any set of nearly 140 input signals can trigger the same neuronal firing (Palmer et al., 2014; Eyal et al., 2018), meaning neuronal firing is non-specific with respect to specific input signals. This, however, leads to a loss of specificity in the information. Hence, it is reasonable to expect a mechanism that recovers or compensates for the lost information during memory retrieval.) |
| 44 | A dendritic spike occurs when the summation of approximately 10 to 50 postsynaptic potentials (on the spines) takes place at the dendritic region (Antic et al., 2010). | It is essential to clarify which spines contribute to the potentials and discuss their significance. | The Semblance hypothesis explains that the potentials contributing to a dendritic spike primarily originate from the spines of different neurons, which can form an inter-LINKed cluster of spines (Vadakkan, 2016). |
| 45 | Some dendritic spikes do not lead to somatic action potentials (Golding & Spruston, 1998). | It is conventionally believed that dendritic spikes are effective detectors of specific input patterns, ensuring neuronal output (action potential) (Gasparini et al., 2004). Therefore, an explanation is needed for the leakage of potentials from the dendritic area, apart from their propagation toward the soma. | The islet of inter-LINKed spines (IILSs) provides pathways for a dendritic spike to propagate. A dendritic spike can spread to all the inter-LINKed spines within an IILS (which offer lower resistance routes) towards the dendritic trees of the neurons within those IILSs. As a result, dendritic spikes may not always be followed by somatic action potentials in all the neurons whose spines are inter-LINKed. |
| 46 | When current is injected into the dendrites of human layer 2/3 neurons, they generate repetitive trains of fast dendritic calcium spikes, which can occur independently of somatic action potentials (Gidon et al., 2020). | It is important to explain the pathways through which the high potential of a dendritic spike propagates without reaching the cell body to trigger a somatic action potential (neuronal firing). | An islet of inter-LINKed spines can explain the generation of dendritic spikes. The net potential of a dendritic spike may drain through some of the inter-LINKed spines to their respective neuronal cell bodies, which are not being recorded. Additionally, some of the inter-LINKed spines may receive inhibitory inputs (Vadakkan, 2016). |
| 47 | The inner experience of certain higher brain functions can occur without any accompanying motor actions. | The mechanism that generates inner sensations must be capable of demonstrating either that no behavioral motor actions are produced alongside a particular inner sensation, or that the motor action can be voluntarily suppressed. | It has been shown that the apical dendrites in human layer 5 neurons are electrically isolated from the somatic compartment (Beaulieu-Laroche et al., 2018). This suggests the possibility of independent operations occurring in islets of inter-LINKed spines within those distal dendritic regions. |
| 48 | When two differential electrodes are placed at separate extracellular locations, the potential difference between them can be recorded as oscillating waveforms. The brain operates effectively only when the frequency of these oscillations stays within a narrow range. | It is essential to demonstrate that the vector components contributing to these oscillations are likely involved in generating both inner sensations and the associated behavioral motor actions. (Note: oscillating extracellular potentials are expected to induce reciprocal ionic changes within the cytoplasm of cell processes, primarily neurons). | While synaptic transmission provides one vector component, other components are likely involved, which are expected to occur nearly perpendicular to the direction of synaptic transmission. The propagation of depolarization along the IPL corresponds to this latter component (Vadakkan, 2010; 2013). |
| 49 | The apical tuft regions of neurons across all cortical neuronal orders are anchored to the inner pial surface, leading to the overlap of dendritic arbors from neurons of different orders. This arrangement results from a sequence of movements of neuronal precursors during development. | Dendritic spines of neurons, belonging primarily to the same neuronal order but also to different orders, overlap with each other to perform specific functions. | The overlap of dendrites from different neurons across various cortical layers facilitates the formation of inter-neuronal inter-spine LINKs (Vadakkan, 2016, 2019). The anchoring of apical tuft regions from all cortical neuronal orders promotes inter-order neuronal inter-spine LINKs. Since inputs from distant locations typically reach the 2nd and 3rd cortical neuronal orders, and since upper motor neurons (UMNs) are located in the 5th layer, this organization enables the integration of inner sensation units and supports behavioral motor actions, such as speech and other motor functions. |
| 50 | Following learning, there is initially conscious retrieval of memory in response to a cue stimulus. With repeated retrievals, this process eventually becomes subconscious. | The process by which repeated retrievals of a memory in response to a cue stimulus lead to its subconscious nature must align with a framework that explains the mechanism of consciousness. | This is explained by the Semblance Hypothesis (Vadakkan, 2010; 2019). A routinely arriving cue stimulus may become neither essential nor detrimental to survival. As a result, the units of inner sensations evoked by its IPL reactivations merge with the overall semblance of consciousness, of which the system remains unaware. Consequently, memories triggered by repeated innocuous or non-beneficial cues remain subconscious. |
| 51 | Activity-dependent structural remodeling has been proposed as a cellular basis for learning and memory. (Yuste & Bonhoeffer, 2001). | Certain specific mechanical changes are expected to underlie the cellular basis of learning and memory. | Simultaneous activation of two synapses whose postsynaptic terminals (spines) can lead to IPL (inter-postsynaptic functional link) formation during learning. Although displacing the hydration layer between closely apposed spines requires significant energy, specific molecular events are expected to overcome this barrier (Vadakkan, 2019). |
| 52 | Several seizures spread laterally to adjacent cortical regions. Focal seizures may present with a Jacksonian march, affecting both sensory and motor functions. | The cellular mechanism responsible for seizures should be capable of explaining the lateral spread. | Seizures can be explained as the rapid, chain-like formation of IPLs in the cortex (Vadakkan, 2016). This mechanism accounts for the propagation of sensory and motor features across adjacent cortical areas, following the sequential organization represented in the sensory and motor homunculi. |
| 53 | Various seizures are associated with distinct types of hallucinations. | A plausible explanation should account for how seizure activity reaches different sensory cortices and evokes the internal sensations of sensory stimuli in the absence of external input. | The lateral spread of seizures via rapid IPL formation across the sensory cortices provides a mechanism for the internal perception of various sensations (Vadakkan, 2016). |
| 54 | The pathological changes associated with amyotrophic lateral sclerosis (ALS) spread laterally. | It is essential to explain how specific alterations in the normal operational mechanisms contribute to the lateral spread of neurodegenerative changes in ALS. | IPL formation represents a spectrum of inter-membrane changes, with structural stability maintained only until the stage of inter-spine membrane hemifusion. Any alterations in membrane structure or the presence of viral fusion proteins can convert the hemifused membrane structures to undergo fusion. This conversion occurring between spines that belong to different neurons leads to mixing of their cytoplasm, which in turn lead to lateral spread of pathological changes such as spine loss and, ultimately, neuronal degeneration, as seen in ALS (Vadakkan, 2016). |
| 55 | In animal models of seizures, the transfer of injected dye from one CA1 neuron to neighboring CA1 neurons has been observed (Colling et al., 1996). | CA1 neurons are located laterally to one another within the CA1 region of the hippocampus. Therefore, it is essential to explain the physical pathway through which dye can spread between these laterally positioned CA1 neurons. | Excessive excitation of CA1 neurons can result in the pathological conversion of IPLs—whose structures are normally limited to inter-spine membrane hemifusion—into inter-neuronal inter-spine membrane fusion (Vadakkan, 2016). This process can explain the observed dye spread between neurons. |
| 56 | Loss of dendritic spines occurs after kindling, during seizures, and following the induction of long-term potentiation (LTP). | A mechanism should be identified that explains the loss of dendritic spines following kindling, during seizures, and after LTP induction in an interconnected manner. Additionally, it is important to determine any potential benefits that neurons may gain from the loss of spines. | Inter-neuronal inter-spine fusion can lead to the mixing of cytoplasmic contents between neurons. Given that the expression profiles of even adjacent neurons of the same type can differ (Kamme et al., 2003; Cembrowski et al., 2016), such cytoplasmic mixing is likely pathogenic for both neurons. Consequently, homeostatic mechanisms would likely favor the loss of spines involved in fusion to protect neurons from further damage (Vadakkan, 2016). |
| 57 | The CA2 region of the hippocampus is resistant to seizures. | It is essential to propose a mechanism for seizures that aligns with the constraints revealed by the disorder, and to identify a specific property of the CA2 region that enables it to resist seizures. | Perineuronal net proteins surrounding the spine heads in the CA2 region (Dansie & Ethell, 2011) can inhibit IPL formation between spines of different neurons, offering an explanation for the region's resistance to seizures (Vadakkan, 2016). |
| 58 | The CA2 region of the hippocampus is spared in different models of hypoxia or ischemia (Kirino, 1982; Sadowski et al., 1999) | Since the CA2 region is resistant to both LTP induction and seizure generation, it is possible to examine whether the same cause is also responsible for resistance to hypoxia. | An explanation for the Golgi staining reaction led to the inference that oxygen plays a role in reversing IPLs (Vadakkan, 2021). Conversely, hypoxia can promote increased IPL formation, potentially progressing to membrane fusion. However, the CA2 region is resistant to IPL formation due to the presence of perineuronal net proteins surrounding the spine heads (Dansie & Ethell, 2011). This structural feature may explain why the CA2 region is spared in various models of hypoxia. |
| 59 | Seizures and memory loss are caused by herpes simplex viral (HSV) encephalitis. | Mechanistic explanation for both these features is expected to provide information about the relationship between these findings in HSV encephalitis. | HSV fusion proteins cause rapid formation of large number of non-specific IPLs & rapid inflammatory changes causing seizures. It also leads to conversion of IPL hemifusion state to the fusion state. This will lead to mixing of cytoplasms of different neurons. Since expression profiles of even adjacent neurons of the same type are different (Kamme et al., 2003; Cembrowski et al., 2016), homeostatic mechanisms are expected to favor loss of spines involved in fusion. If not successful, it can lead to neuronal death leading to cognitive defects (Vadakkan, 2016). |
| 60 | Anesthetic agents are known to alleviate seizures. | The mechanism of action of anesthetic agents should be able to account for how they halt both the generation and propagation of seizures. | Anesthetic molecules generate a large number of non-specific IPLs, linking multiple islets of already interconnected spines. This widespread linkage enhances the horizontal component of oscillating potentials, significantly lowering the frequency of extracellular oscillations. Consequently, both specific inner sensations and motor actions are suppressed (Vadakkan, 2016). Notably, the paradoxical excitation observed during the early stages of anesthesia can be explained by the initial increase in IPL formation by the anesthetic agents (Vadakkan, 2016). |
| 61 | Memory impairment is a common symptom observed in patients with seizure disorders (Mazarati, 2008). | It is essential to explain how the mechanisms underlying learning, memory retrieval, and behavioral motor actions are disrupted by the pathophysiological processes involved in seizures. | Seizure pathology involves the rapid formation of numerous non-specific IPLs, as well as IPL fusion between spines, which can result in spine loss and even neuronal degeneration. The formation of non-specific IPLs, along with the loss of spines and neurons, reduces the availability of specific IPLs required for cognitive functions, thereby contributing to memory impairment and deficits in learning and behavior (Vadakkan, 2016). |
| 62 | The intracellular electrophysiological correlate of epileptiform activity is the paroxysmal depolarizing shift (PDS), characterized as a giant excitatory postsynaptic potential (EPSP) (Johnson & Brown, 1981). | A mechanistic explanation is needed for the generation of a giant EPSP at the dendritic spine area during a seizure, particularly given its propensity to propagate laterally to adjacent cortical regions. Such a mechanism should account for how synchronized activity and structural changes at the level of IPLs amplify excitatory input, leading to a PDS and facilitating lateral spread. | Results strongly suggest that a large EPSP is generated through a postsynaptic mechanism (Johnson & Brown, 1981). Since distal dendrites typically generate EPSPs with amplitudes around 10 mV (Spruston, 2008), and the maximum voltage of a PDS can reach up to 50 mV, spatial summation of multiple EPSPs presents a plausible mechanism for the PDS. In this context, IPL formation between spines of different neurons may provide an explanation for the PDS observed during seizures (Vadakkan, 2016). |
| 63 | Although a simultaneous decrease in extracellular Ca²⁺ and an increase in K⁺ during seizures can impede action potential propagation along axons (Seignuer & Timofeev, 2011), seizure activity persists in status epilepticus. | It is therefore necessary to propose an alternative pathway that facilitates the spread of seizure activity. Given that a paroxysmal depolarization shift (PDS) represents a giant excitatory postsynaptic potential (EPSP), it is important to explain how such large EPSPs continue to be generated and propagated. | The formation of a large number of non-specific IPLs between closely apposed spines of different neurons offers an alternative pathway that can facilitate the summation of excitatory postsynaptic potentials (EPSPs) and enable the propagation of PDS-like activity across the cortex (Vadakkan, 2016). |
| 64 | Cell swelling is commonly observed during the "spreading depression" phase of seizures (Kempski et al., 2000; Olsson et al., 2006; Colbourn et al., 2021). | It is important to determine whether cell swelling is a cause of seizure-related changes—occurring prior to seizure onset—or a consequence resulting from seizure activity. | Enlargement of dendritic spines is likely to displace the hydration layer of the extracellular matrix (ECM) between abutted spines. This may promote the formation of non-specific IPLs, particularly in the presence of additional factors that facilitate seizure generation. |
| 65 | The ketogenic diet is commonly used to prevent seizures (Martin-McGill et al., 2020; Kossoff et al., 2021). It has been shown to increase the serum concentration of long-chain polyunsaturated fatty acids (LC-PUFA) (Anderson et al., 2001; Fraser et al., 2002). | It is essential to provide an integrated explanation of how long-chain polyunsaturated fatty acids (LC-PUFAs) influence key cellular structures in a manner that contributes to seizure prevention | The membrane lipid composition remains optimal when dietary n-3 polyunsaturated fatty acids (PUFAs) account for more than 10% of total PUFAs (Abbott et al., 2012). Long-chain PUFAs (LC-PUFAs) from the ketogenic diet, or their modified forms form ester bonds on the triglyceride backbone of lipid membranes. Triglycerides predominantly with LC-PUFAs may prevent the formation of non-specific IPLs between spine membranes, thereby helping to prevent seizures (Vadakkan, 2016). |
| 66 | Seizure disorders are often linked to neurodegenerative changes (Farrell et al., 2017). | It is essential to provide an explanation of how seizures contribute to neurodegeneration. | Seizure disorders can be characterized by the rapid formation of IPLs in the cortex. Although IPL changes may typically remain limited to the hemifusion stage, alterations in cell membrane composition and the frequency of seizure repetition can promote IPL fusion. When the cytoplasms of different neurons merge, this can lead to spine loss and subsequent neuronal degeneration (Vadakkan, 2016). |
| 67 | Loss of consciousness is a common feature during complex seizures. | It is essential to provide a framework that explains the generation of the first-person inner experience of consciousness and how seizure activity contributes to the loss of consciousness. | The reactivation of a large number of IPLs in response to both internal and external stimuli generate a background semblance that contributes to the inner experience of consciousness. The rapid formation of numerous IPLs during seizures induces a multitude of non-specific semblances, disrupting the coherence of the semblance necessary for maintaining consciousness and leading to its loss (Vadakkan, 2016). |
| 68 | Multiple vertical subpial resections have been shown to alleviate seizures (Morrell et al, 1989). | During vertical resections, some structural connections are severed. Neurons in the cortex are organized into six layers vertically downward with its dendrites towards the cortical surface and axons towards the direction of the ventricles. Therefore, it is essential to explain which lateral connections are disrupted by this procedure. | Both recurrent collaterals and IPLs that form horizontal connections can be cut. Severing the IPLs is expected to inhibit IPL-mediated rapid chain lateral propagation of seizure activity (Vadakkan, 2016). |
| 69 | In status epilepticus (continuous seizures), anesthetics are administered to achieve a state of "burst suppression" in the EEG. This condition is characterized by intermittent periods of electrical inactivity lasting several seconds, alternating with high-voltage bursts of activity (Meierkord et al., 2010). | It is essential to provide a feasible explanation of how the induction of a "burst suppression" state with anesthetics helps control seizures and may prevent cortical damage associated with status epilepticus. | Anesthetic agents are expected to induce the rapid formation of a large number of non-specific IPLs, a process that is reversible. The formation of such a vast number of IPLs is anticipated to create a substantial horizontal component, causing oscillating extracellular potentials to flatten into a straight line. This mechanism could explain the reversible state of "burst suppression." As a result, the firing of downstream neurons is reduced, leading to a decrease in the muscle contractions associated with seizures (Vadakkan, 2016). |
| 70 | The ictal (during seizure) and postictal characteristics observed in electroconvulsive therapy (ECT) are essentially similar to those seen in patients with generalized tonic-clonic seizures (Pottkämper et al., 2021). | An explanation is needed regarding how the high energy levels used in older electroconvulsive therapy (ECT) procedures led to generalized convulsions. | The high energy used in electroconvulsive therapy (ECT) induces the rapid formation of a large number of non-specific IPLs. It has previously been shown that seizures are triggered by the rapid chain formation of IPLs along cortical synaptic regions (Vadakkan, 2016). |
| 71 | Electroconvulsive therapy (ECT) has been shown to alleviate endogenous depression (Subramanian et al., 2022) and has remained a standard treatment for the past 70 years. | A mechanistic explanation for the effectiveness of electroconvulsive therapy (ECT) in treating depression is needed. | Depression is characterized by the inner sensation of a depressed mood. It is plausible to infer that the net qualia of semblances from one or more brain regions contribute to this state. The application of substantial energy to cortical regions can induce the formation of a large number of non-specific inter-postsynaptic functional links (IPLs) between adjacent spines. This disruption alters the net semblance responsible for generating the depressive state. |
| 72 | Short-term memory loss has been observed following electroconvulsive therapy (ECT) using methods employed before the 1980s (Duncan, 1949; Squire, 1977; Frith et al., 1983). However, with the introduction of low-energy ECT in the 1990s, memory impairment has been significantly reduced (Meeter et al., 2011). | A mechanistic explanation for this effect is required. | The application of substantial energy to cortical regions can lead to the formation of a large number of non-specific IPLs between adjacent spines. Consequently, in addition to the reactivation of specific IPLs, a specific cue stimulus will also reactivate a large number of non-specific IPLs. This dilution of the specific semblance impairs the formation of a coherent, specific memory. |
| 73 | Neurodegenerative disorders are characterized by the loss of dendritic spines and neuronal death. | An explanation is needed for the contiguous spread of pathology that leads to spine loss and neuronal death. Causative factors must act at specific locations to account for all the observed features of the disease. | Changes in lipid membrane composition, viral fusion proteins, and other factors can drive the pathological progression of inter-postsynaptic functional links (IPLs) toward a fusion state. This fusion results in the mixing of the cytoplasms of two distinct neurons. In response, the neurons initiate homeostatic mechanisms to seal the fusion site. If this is not possible, they will attempt to remove the fused spines. If one of the fused spines cannot be eliminated, the process may eventually lead to neuronal death (Vadakkan, 2016). |
| 74 | Dementia is a common feature of neurodegenerative disorders, where the loss of dendritic spines and, eventually, neuronal death are frequently observed. | An explanation is required regarding the role of dendritic spines in both the generation of the inner experience of memory and the associated behavioral motor activity. | The loss of dendritic spines and neurons leads to a reduction in the number of specific inter-postsynaptic functional links (IPLs) required to generate the distinct units of inner sensation associated with a specific memory (Vadakkan, 2016). |
| 75 | Perception as an inner sensation experienced from a first-person perspective. | A variant or modification of the mechanism that induces the inner sensation of memory should also be capable of explaining the first-person inner sensation of perception. | This can be explained by the unique property of the IPL, which can be stimulated from both sides by stimuli originating from two adjacent locations of an item, thereby generating units of the inner sensation of perception (Vadakkan, 2015). |
| 76 | The perceived location of the stimulus differs from its actual location. | A mechanism capable of inducing units of inner sensation must be able to account for why the perceived location of a stimulus differs from its actual location. | The inner sensation of a percept is produced by the integration of multiple units of perception, known as perceptons. Consequently, the perceived location of an object may not correspond to its actual location, as illustrated by various examples (Vadakkan, 2015). |
| 77 | A stimulus presented at a frequency above the flicker fusion threshold is perceived as a homogeneous, continuous percept. | A mechanism that integrates discrete units of inner sensation is necessary to produce the uninterrupted, continuous visual perception of an object presented above the flicker fusion frequency. | Since units of perception (perceptons) from IPLs in different regions are generated in a temporal pattern in response to a single flicker, perceptons from consecutive flickers overlap, resulting in a continuous percept (Vadakkan, 2015). |
| 78 | Perception of object borders. | A mechanistic explanation is needed to account for the formation of the first-person percept of object borders. | The percept of a stimulus must be generated from the stimuli at the borders of an object that reach the brain. When perceptons formed from these stimuli integrate, they produce the inner sensation of a percept, thereby defining the border. Similarly, stimuli from outside the borders contribute to the formation of a contrasting border with the background (Vadakkan, 2015). |
| 79 | First-person inner sensation of pressure-induced phosphenes. | The mechanism behind the generation of first-person inner sensations is expected to explain phosphenes triggered by pressure applied to the eyeball. | Stimulation of sensory pathways at any point along their trajectory (such as the retina), before their convergence in the visual cortex, can reactivate IPLs, thereby generating perceptons (Vadakkan, 2015). |
| 80 | Continuous perceptions of moving objects without interruption. | It is essential to explain how the percept remains consistent as the object moves. | The perception of a moving object depends on its speed and distance from the eyes. Smooth pursuit eye movements enable visual stimuli to fall on either side of the same set of IPLs in the visual cortex. If the object moves faster than a certain threshold, saccadic eye movements are triggered, ensuring the overlap of perceptons for continuous perception. |
| 81 | There are various types of perception, such as vision and olfaction, which operate through distinct pathways that reach different cortical areas. | It is essential to provide evidence for the presence of comparable neural circuitry for two different sensations, preferably in two distinct nervous systems. | The circuitry for perception was initially hypothesized for vision in mammalian brains, and evidence for a comparable circuitry for olfactory perception was demonstrated in the nervous system of the fly Drosophila (Vadakkan, 2015). |
| 82 | It is possible to discriminate between two odorants when sniffed at a 60-millisecond interval (Wu et al., 2024) | The mechanism of perception should provide explanatory evidence to support this finding. | Perception occurs through the rapid, reversible formation of IPLs. Once the stimulus is removed, the IPLs immediately revert to their normal state. This allows for the formation of new sets of IPLs upon the arrival of the second odorant, generating distinct perceptons responsible for the perception of the second odor (Vadakkan, 2015). |
| 83 | Orientation tuning of a population of neurons in V1, before and after training on a visuo-motor task, revealed different sets of neurons responding (Failor et al., 2021). | It is essential to demonstrate how the firing of neurons in the primary visual cortex changes over time in response to identical visual stimuli. | The primary mechanism of perception occurs through the rapid formation of IPLs between adjacent spines in the visual cortex, which generate perceptons. Whether the postsynaptic visual cortical neurons fire depends on: a) the additional depolarization that reaches these neurons during IPL formation, and b) the sub-threshold activation state of the neurons. This explains the lack of consistency in the set of neurons that fire in response to the same visual stimuli (Vadakkan, 2015). |
| 84 | A moving object that abruptly appears and begins to move is initially invisible for some distance, a phenomenon known as the Frohlich effect (Frohlich, 1929). There is a delay of at least 100ms between retinal photoreceptor cell stimulation and conscious perception. (De Valois & De Valois, 1991; Nijhawan 2008). | There are five synapses from the rods and cones to the visual cortical neurons, with each synapse contributing a delay of approximately 1–2 ms, totaling 5–10 ms. Additionally, conduction through the 10 cm myelinated optic nerve introduces about a 1 ms delay. Together, these account for a total delay of 6–11 ms. Therefore, an explanation is needed for the remaining ~90 ms, which constitutes roughly 90% of the total delay. | Synaptic and conduction delays constitute only a minor portion—approximately 10%—of the total delay. The majority of the delay can be attributed to IPL formation and reactivation, the generation of perceptons, and their subsequent integration to produce the percept. This provides a plausible explanation for the Frohlich effect. |
| 85 | A moving object is perceived slightly beyond the endpoint of its actual trajectory (Hubbard, 2005), and this percept decays within a few hundred milliseconds after the object disappears (Hubbard, 2018). | It is essential to ensure that the proposed operational mechanism can account for this observation | At the final moment of stimulus arrival from a moving object, percept formation is delayed not only by synaptic and conduction delays but also by the reactivation of continuously maintained IPLs, as well as the formation and integration of perceptons. These latter three processes—accounting for the majority of the delay (approximately 90%)—are responsible for the perception of the object extending beyond the end of its actual trajectory. |
| 86 | Observers do not perceive an object as extending beyond the point at which it changes direction (Eagleman & Sejnowski, 2000). | An explanation is required for why an object is not perceived beyond the point at which it changes direction. | When no stimulus is present beyond a certain point, no further IPL formation or percept generation occurs. As a result, perception ceases instantaneously (after the normal perception delay) when the already-formed IPLs from the moving object are reversed. Consequently, there is no perception beyond the object's location—only a delay in perception. |
| 87 | The flash-lag effect (FLE) occurs when a flash is briefly presented at a specific location adjacent to the path of a uniformly moving object, causing the flash to be perceived as lagging behind the object. | An explanatory mechanism based on the induction of units of inner sensation is needed to explain how perception is influenced by the relative timing of stimulus arrival. | For a newly appearing flash, there is a delay of approximately 70ms for depolarization to travel from the retina to the visual cortex, leading to percept formation (Lamme & Roelfesma, 2000). Of this delay, approximately 12ms is attributed to synaptic delays across 5 synapses and conduction delays through neurons. The remaining delay is due to IPL formation, reactivation, generation of perceptons, and the integration of these processes for percept formation (Vadakkan, 2022). However, continuous perception of a moving object can leverage already formed IPLs, enabling its perception before the flash. |
| 88 | No flash-lag effect (FLE) is perceived when both the moving object and the flash disappear simultaneously (Eagleman & Sejnowski, 2000). | An explanation is needed based on what happens to the final stimuli from both sources. | Each percept is formed by the integration of perceptons that are generated temporally. A continuously moving object generates IPLs in a more temporally dispersed manner compared to a flash. When both the moving object and the flash stop simultaneously, the integration of perceptons from the moving object completes later than that of the flash. In other words, the formation of the last percepton by the moving object occurs almost simultaneously with the formation of the last percepton by the flash. This explanation also provides insight into the mechanism of integration of perceptons. |
| 89 | The flash-lag effect (FLE) is not perceived if the moving object stops at the same time the flash is presented as a stationary object (Kanai et al., 2004; Hubbard 2014). | An explanation is required as to why there is no Flash-Lag Effect (FLE) in this situation. | When a moving object stops, its perception persists for a short period due to delays in synaptic transmission, conduction, and perceptual integration. A stationary flash, on the other hand, experiences a delay in perception caused by synaptic transmission, conduction, IPL formation, and perceptual integration delays. When these delays align, the Flash-Lag Effect (FLE) does not occur (Vadakkan, 2022). |
| 90 | In the 'high-ϕ illusion,' when a rotating texture is abruptly replaced by a random texture, the observer perceives the texture as jerking backward (Wexler et al., 2013). | It is essential to demonstrate that the sudden appearance of a random texture requires extra time for its perception. | IPLs formed by a rotating texture are expected to be continuously maintained throughout the rotation. However, a newly arriving random texture requires time for the formation of new IPLs, their reactivation, and the formation of perception. As a result, the observer perceives the texture as jerking backward (Vadakkan, 2022). |
| 91 | The Flash-Lag Effect (FLE) increases as the distance between the moving object and the flash increases (Hubbard, 2014). | It should be possible to provide a mechanistic explanation for the effect of distance on the time interval between the perception of the moving object and the flash. | Two explanations are possible. 1) Immediate neighborhood through which activity propagates will a) lead to the occurrence of firing of neurons located in the lateral directions beyond their expected paths in the visual cortex (Chettih & Harvey, 2019) due to the presence of IPLs, & b) hold more neurons at sub-threshold activation states such that they can be fired by signals arriving from the flash. This will allow the nearby flash to get propagated through more neurons and reach up to more abutted spines in the visual cortex to generate more IPLs fast and generate more perceptons to generate a percept faster compared to a flash that appears far from the moving object. 2) Stimuli from a moving object heavily rely on the mechanism of integration of perceptons to create a continuous percept. When the flash occurs near the moving object, elements of the same integrative percept formation mechanism can be engaged, reducing the FLE, compared to when the flash is farther away. This explanation also helps to clarify the integration of perceptons. |
| 92 | Perception of a stimulus can be blocked or modified if it is followed in rapid succession by a second stimulus, which is called backward masking (Bachmann, 1994). | It is necessary to explain certain mechanism that occurs in between two successive stimuli. | Nerve conduction through neuronal paths takes place at slightly different speeds & hence integration of perceptons for the first stimulus can be overlapped by integration of perceptons by the second stimulus. Also, many of the same IPLs that generate perceptons of the first stimulus are likely involved in percept formation for the second stimulus (Vadakkan, 2022). |
| 93 | When successive stimuli are presented at frequencies above the critical flicker frequency, they are perceived as a single continuous stimulus (Jensen, 2006). | An explanation is required for how perceptual fusion takes place. | Many of the same dendritic spines that form IPLs to generate perceptons for the first stimulus are likely also involved in generating perceptons for the second, resulting in an overlap where the perceptons of the second stimulus override those of the first (Vadakkan, 2022). |
| 94 | When a stationary object is presented for 2.5 seconds, then briefly removed for a short interval—such as 30 milliseconds—and subsequently reappears in motion, it may be perceived as moving continuously (Whitney & Cavanagh, 2000). | It is necessary to provide a mechanistic explanation of how perceptual fusion takes place. | Some of the perceptons generated by the first stimulus are likely overlapped by those of the second stimulus, resulting in the perception of a continuous stimulus (Vadakkan, 2022). |
| 95 | When a flash stimulus reaches the retinal periphery, making it more eccentric compared to one that reaches the fovea, it leads to poorer performance on visual tasks (Staugaard et al., 2016). Moreover, the flash-lag effect (FLE) increases with greater eccentricity (Hubbard, 2014). | It is essential to explain why the image of a flash stimulus falling on the retinal periphery leads to an increased flash-lag effect (FLE). | The fovea is a region of the retina where photoreceptors are densely packed (Kolb et al., 2020). In contrast, photoreceptor density is relatively lower at the periphery. As a result, stimuli reaching the fovea can generate a greater number of IPLs in the visual cortex, while stimuli reaching the retinal periphery lead to a sparser formation of IPLs. This difference may result in a longer time required for the integration of perceptons to generate a percept of an eccentric flash (Vadakkan, 2022). |
| 96 | The flash-lag effect (FLE) is more pronounced when the flash is less predictable (Hubbard, 2014). | It is necessary to explain why the flash-lag effect (FLE) is less pronounced when flashes occur at fixed, predictable intervals. | More predictable flashes activate specific reverberating circuits, delivering sub-threshold potentials to neurons along the pathway through which light stimuli propagate. When the next predictable flash arrives, it activates these neurons more quickly, facilitating the formation of IPLs between abutted spines in the visual cortex and rapidly generating the percept. This leads to a reduction in the flash-lag effect (FLE). |
| 97 | Predictable moving dots at the leading edge are associated with suppressed blood oxygenation level-dependent (BOLD) responses (Schellekens et al., 2016). | An explanation is needed for the favorable mechanistic changes that occur during anticipation and how these are associated with reduced BOLD signals. | An explanation of the Golgi staining reaction led to the inference that oxygen plays a role in reversing IPLs (Vadakkan, 2021). This suggests that suppressed BOLD signals indicate that reduced oxygen release helps maintain IPLs during the observation of a moving object. |
| 98 | A percept occurs even when an object moves into the peripheral regions of the blind spot (Maus & Nijhawan, 2008). | A blind spot is observed when only one eye is open, and the individual fixates on a single point in the visual field. Under these conditions, the blind spot is a region of the visual field where a visual stimulus cannot be perceived. Hence, an appropriate mechanistic explanation is needed for the above observation. | Perception occurs even when an object moves into the peripheral regions of the blind spot (Maus & Nijhawan, 2008). Blind spot corresponds to the location of the optic disc (optic nerve head) on the retina, which lacks photoreceptors. However, the blind spot is not experienced during binocular vision. Pyramidal neurons in the visual cortex possess branched dendritic arbors that extensively overlap. When a visual stimulus reaches the peripheral regions of a blind spot, it triggers the formation of several inter-postsynaptic functional links (IPLs) in the visual cortex, enabling perception. According to the semblance hypothesis, retrograde extrapolation from interlinked spines on either side of the newly formed IPLs leads to the formation of a percept at a spatial location determined by the integrated perceptons (Vadakkan, 2015a). Therefore, an object moving into the blind spot can still be perceived. |
| 99 | Brain inflammation can lead to psychosis (Comer et al., 2020; Crespi et al., 2024) | It is essential to provide a mechanistic explanation for changes in brain inflammation and how these changes can lead to the perception of stimuli in their absence. | Inflammation leads to the swelling of cells and their processes, which predisposes adjacent dendritic spines to form non-specific IPLs, triggering inner sensations in the absence of external sensory stimuli (hallucinations). Specific hallucinations may arise when inflammation occurs in particular brain regions. |
| 100 | Inner sensations of consciousness. | It is expected that a continuous operational mechanism exists for generating inner sensations, likely giving rise to the inner sense of being conscious. | A large number of non-deleterious and non-beneficial stimuli from the environment and body do not require the generation of separate inner sensations. Instead, it is essential to suppress the formation of percepts and memories in response to each of these stimuli. Consequently, the units of inner sensations generated by the continuous reactivation of numerous IPLs in response to background stimuli are integrated to produce a non-specific inner sensation of consciousness called C-semblance (Vadakkan, 2010; Vadakkan, 2015). This will enable the system to focus on unique stimuli arriving from the environment that will help its survival. Inner sensations formed from newly learned associations will be initially perceived. But continuous use of it will allow them to get incorporated into the C-semblance, of which the system will become eventually unaware of. |
| 101 | Loss of consciousness induced by anesthetic agents. | It is first necessary to establish a framework for the mechanism that generates the first-person properties of consciousness, followed by an explanation of how anesthetic agents disrupt this mechanism. | A framework for understanding consciousness has been described previously (see above; (Vadakkan, 2010; Vadakkan, 2015). Anesthetic agents, upon entering from the extracellular matrix (ECM) space, initially interact with the outer leaflet of the lipid bilayer, inducing spontaneous curvature that creates asymmetry between the outer and inner leaflets (Lipowsky, 2014). Additionally, lipophilic anesthetics partition into the hydrophobic core of the lipid membrane, particularly in regions of membrane reorganization on the lateral aspects of dendritic spines. This process results in dehydration of the inter-membrane ECM space, ultimately leading to physical contact between abutted spine membranes. The consequence is the formation of numerous non-specific IPLs, which in turn alters the inner sensation of consciousness. |
| 102 | The potency of an inhaled anesthetic agent is proportional to its partition coefficient—the concentration ratio between olive oil and water—which reflects its hydrophobic solubility. This relationship has a correlation coefficient of 0.997 (Firestone et al., 1986), representing one of the strongest correlations observed in biological systems (Halsey, 1992). | It is essential to demonstrate that the mechanism of anesthetic action is directly proportional to lipid solubility. | According to the semblance hypothesis, lipid solubility influences membrane properties in a manner that proportionally promotes the formation of non-specific IPLs. The non-specific semblances generated across the inter-LINKed spines of these IPLs result in a corresponding loss of consciousness (Vadakkan, 2015). |
| 103 | Anesthetic agents are known to exert diverse actions, including functioning as GABA-A receptor agonists, alpha-adrenergic receptor agonists, NMDA receptor antagonists, dopamine receptor antagonists, and opioid receptor agonists (Kopp et al., 2009). | It is essential to demonstrate either that all of these receptor-mediated actions converge on a common pathway responsible for consciousness, or that these agents act through a shared underlying mechanism independent of their known receptor targets. | A framework for consciousness has been previously described (see above; (Vadakkan, 2010; Vadakkan, 2015). The anesthetic effects of general anesthetics are strongly correlated with their lipid solubility, exhibiting a remarkably high correlation coefficient of 0.997. Upon entering from the extracellular matrix (ECM) space, anesthetic agents interact with the outer leaflet of the lipid bilayer, inducing spontaneous curvature that creates asymmetry between the outer and inner leaflets (Lipowsky, 2014). This membrane alteration facilitates the formation of a large number of non-specific IPLs, contributing to the disruption of the mechanism underlying consciousness. (Vadakkan, 2015). |
| 104 | General anesthesia induced by anesthetic agents can be reversed by applying external pressure to an animal enclosed in a sealed container—achieved by increasing air pressure for terrestrial animals or water pressure for aquatic animals (Lever et al., 1971; Halsey et al., 1986). | It should be possible to identify a mechanism through which the actions of anesthetic agents can be reversed in response to external pressure. | External pressure propagates through the middle ear, perilymph, cerebrospinal fluid (CSF), and paravascular space, ultimately reaching neuronal processes (Iliff et al., 2012). According to Le Chatelier’s principle, when a system at equilibrium is subjected to a disturbance, the equilibrium position will shift in a direction that mitigates the effect of the applied pressure. In this case, the pressure increase causes anesthetic molecules to be displaced from the lipid membranes into the extracellular matrix (ECM), from where they escape through the paravenular space into the venous system (Iliff et al., 2012). This process results in the reversal of the non-specific IPLs generated by the anesthetics (Vadakkan, 2015). |
| 105 | Only reduced amounts of anesthetic agents are required to induce anesthesia in the presence of levodopa (Segal et al., 1990). | It is essential to explain the specific mechanism of action of dopamine that enhances the effects of anesthetic agents. | It is known that dopamine can induce the enlargement of dendritic spines (Yagishita et al., 2014). This enlargement facilitates the formation of a large number of non-specific IPLs by anesthetic agents. As a result, the concentration of anesthetic agents required to achieve a specific level of anesthesia is reduced compared to conditions without dopamine. |
| 106 | Low doses of anesthetics preserve short-term memory to the point where patients can engage in conversation and appear lucid (Wang & Orser, 2011). However, as the anesthetic dose gradually increases, there is a progressive decline in short-term memory, along with a shortening of the time interval between learning and the retrieval of memories. | It is necessary to explain why low doses of anesthetic agents do not alter the operational mechanism of memory, whereas increasing doses start affecting memory. | Since IPLs are highly reversible, newly formed non-specific IPLs by the anesthetic agents reverse back. Hence, low dose of anesthetic agents may not affect short-term memories. But at higher doses, formation of more non-specific IPLs will generate more non-specific semblances along with generation of specific semblances in response to a specific cue stimulus. Hence, formation of relatively more non-specific semblances in response to high concentrations of anesthetic agents will prevent retrieval of specific memories (Vadakkan, 2015). |
| 107 | Low doses of anesthetics leave very short-term memory intact, so that patients can carry on a conversation & appear to be lucid (Wang & Orser, 2011). A gradual increase in the anesthetic dose produces a gradual worsening of short-term memory & a gradual shortening of the time interval after which memories can be retrieved (Andrade et al.,1994). | It is essential to explain why low doses of anesthetic agents do not alter the operational mechanism of memory, while higher doses begin to affect memory function. | Since IPLs are highly reversible, newly formed non-specific IPLs induced by anesthetic agents can return to their baseline state. As a result, low doses of anesthetic agents may not significantly affect short-term memory. However, at higher doses, the formation of additional non-specific IPLs generates more non-specific semblances, alongside the generation of specific semblances in response to a particular cue stimulus. This interferes with the retrieval of specific memories (Vadakkan, 2015). |
| 108 | General anesthetics typically do not impair existing long-term memory (Bramham & Srebro, 1989). | It is essential to explain how the mechanism responsible for retaining long-term memory remains unaffected by general anesthetics. | IPLs responsible for maintaining long-term memory are well stabilized through stable inter-membrane interactions at the IPL sites, as explained by the semblance hypothesis (see Fig. 12D in the FAQ section) (Vadakkan, 2015). Therefore, these stable regions are not affected by anesthetic agents. |
| 109 | There have been several reports of cognitive decline following surgeries involving the use of general anesthetic agents. | It is essential to provide a plausible explanation of how the normal mechanisms responsible for memory may be affected by a common factor present in all these surgical cases. | Since IPLs are responsible for memory formation and anesthesia induces the creation of a large number of non-specific IPLs, it is possible that the extension of IPL structures leading to IPL fusion (see Fig. 12F in the FAQ section) may result in spine and neuronal loss as a consequence (Vadakkan, 2015). This can explain cognitive impairment following general anesthesia. |
| 110 | As the dose of anesthetic is increased, patients may enter a state of excitation characterized by euphoria or dysphoria, defensive or purposeless movements, and incoherent speech. This phase is referred to as "paradoxical" because, although the anesthetic is intended to induce unconsciousness, it initially produces a state of heightened neural activity and excitation. (Brown et al., 2010). | It is necessary to provide an explanation for the emergence of new inner sensations and motor actions observed during the early stages of anesthesia. | Motor neurons in layer 5 of the motor cortex are typically maintained at a sub-threshold level of activation, allowing them to fire when additional excitatory inputs arrive. During the initial stages of anesthesia, the induction of numerous non-specific IPLs can generate certain inner sensations and simultaneously cause the firing of these sub-threshold-activated motor neurons, leading to unintended motor activity. |
| 111 | Loss of consciousness occurs during a generalized seizure and typically resolves once the seizure ends. | The mechanism of seizure generation should account for how the inner sensation of consciousness is lost. |
The rapid chain formation of numerous non-specific IPLs, triggered by alterations in extracellular matrix (ECM) properties (e.g., markedly low serum sodium) or by factors that enhance neuronal excitability, leads to seizure generation (Vadakkan, 2016). This cascade alters the conformation of the net semblance produced in the background state, thereby disrupting consciousness. |
| 112 | Changes in consciousness are proportional to variations in the frequency of oscillating extracellular potentials that deviate beyond a narrow physiological range. | An explanation is needed regarding how the narrow range of oscillating extracellular potential frequencies is linked to the maintenance of normal consciousness. | This can be explained based on the semblance hypothesis (Vadakkan, 2010; 2015). Unconscious states are associated with significant fluctuations in the frequencies of extracellular potentials recorded from the skull surface in EEG (Rusalova, 2006). These fluctuations primarily result from either an increase or decrease in the number of normal inter-postsynaptic functional links (IPLs) in the system, whose reactivations generate the net semblance for consciousness. Conformational changes in this net semblance cause alterations in consciousness. |
| 113 | The effect of dopamine in enhancing anesthetic action. | Explain the mechanism by which dopamine enhances anesthetic action, ensuring that the explanation aligns with its role in augmenting learning. | By promoting spine enlargement, dopamine enhances IPL formation, which can augment learning. Anesthetic agents induce the formation of a large number of non-specific IPLs, leading to the creation of non-specific semblances. This alters the conformation of the net semblance resulting in an unconscious state. By enlarging the spines, dopamine increases the number of non-specific IPLs & augments anesthetic effect (Vadakkan, 2016). |
| 114 | Phantom sensation and phantom pain. | It is vital to clarify the mechanism behind the sensations or pain felt in a lost limb, leading to phantom sensations or phantom pain. | As long as the IPLs that once received input from the lost limb remain stable in the brain, their reactivation by stimuli from an alternative sensory source can evoke the sensation of a phantom limb. This may occur when the same nerve root in the proximal region of the lost limb is stimulated. Further reactivation of IPLs in the pain-processing regions of the primary somatosensory cortex and the emotion-processing anterior cingulate cortex can lead to the experience of phantom pain. |
| 115 | Innate behaviors, such as the sucking reflex, are hardwired responses present at birth that support survival. | A mechanism shaped by heritable genetic changes that explains innate behavioral responses to specific stimuli is needed. | The convergence of associative sensory stimuli at IPL sites during learning—and their subsequent reactivation—is essential for cognition, encompassing both memory and motor behaviors critical for survival. To enable cognitive function from birth, IPLs are expected to be pre-formed during prenatal development. As a result, evolutionary adaptive mechanisms likely influence the developmental organization of neural pathways that carry commonly associated stimuli, facilitating the formation of abutted spines and IPLs between them. This implies that genetic factors play a key role in guiding neuronal migration and the selective apposition of neuronal processes. Altogether, this can be understood as an evolved mechanism to support survival. |
| 116 | Neurodegeneration caused by repeated general anesthesia (Baranov et al., 2009). | An explanation is needed as to why the repeated induction of loss of consciousness through anesthetics can result in the loss of dendritic spines and, ultimately, neuronal degeneration. | See the explanation how anesthetics work in row 101 (Vadakkan, 2015). Due to changes in lipid membrane composition, or presence of viral fusion proteins or other factors some of the IPLs can get converted to inter-neuronal inter-spine fusion state, ultimately causing spine loss and neuronal degeneration (Vadakkan, 2015). |
| 117 | A higher level of education, marked by an increased number of associative learning experiences, is associated with a reduced risk of developing dementia (Maccora et al., 2020). | It should be possible to explain whether surplus learning-induced changes, such as an increased number of IPLs, allow for the loss of a certain fraction while still preserving the minimum number of IPLs necessary for memory retrieval. | Associative learning involves multiple shared components. Additionally, new neurons are continuously integrated into the granule layer of the hippocampus, modifying neural networks at higher levels beyond the hippocampus. Consequently, a greater number of learning experiences can lead to the formation of excess inter-postsynaptic functional links (IPLs) in the cortex (Vadakkan, 2013; 2019). This IPL redundancy allows individuals with more advanced education to tolerate a greater loss of IPLs before exhibiting cognitive impairments, compared to those with less education. |
| 118 | Certain brain regions seem to be linked to specific functions, as evidenced by lesion studies. | A circuit-based explanation is required. | The sensory cortices receive inputs from specific sensory stimuli, with particular locations expected to generate IPLs crucial for perception. The hippocampus, on the other hand, receives inputs from all sensory modalities. In this area, converging inputs contribute to the formation of IPLs during associative learning. Cortical regions, however, feature sparse sites where converging inputs lead to the formation of IPLs, specifically tied to learning-related changes. Consequently, distinct locations within the brain are associated with particular functions. |
| 119 | Astrocytic pedicels cover less than 50% of the peri-synaptic area in approximately 60% of the synapses within the CA1 region of the hippocampus (Ventura & Harris, 1999). | The hippocampal mechanism of learning and memory must account for the distribution pattern of astrocytic processes and its functional suitability. | Astrocytic pedocytes play a role in clearing neurotransmitter molecules that spill over from the synaptic cleft and recycling them for reuse by the neurons. Regions of spines that are free of astrocytic pedicels promote the formation of inter-neuronal, inter-spine interactions, facilitating IPL formation (Vadakkan, 2019). Since nearly all spines in the hippocampus possess regions not covered by astrocytic pedicels, each spine has the potential to form IPLs. |
| 120 | Modern nervous systems have evolved over millions of years and are also shaped by a series of accidental coincidences. | It is anticipated that the circuitry underlying these features can be explained as having evolved through incremental steps driven by variation and natural selection. | The formation and reactivation of IPLs generate first-person inner sensations corresponding to features of a learned item, triggered by the earliest or fastest sensory cue from an associatively learned stimulus. This mechanism conferred survival advantages in predator-prey environments. Consequently, the IPL formation mechanism was naturally selected, promoting the continued organization and conservation of neuronal processes throughout evolution (Vadakkan, 2020). |
| 121 | As cortical neurons migrate from the periventricular region to their final destinations, the diffusion of dye from an injected neuron to neighboring neurons suggests the presence of intercellular fusion pores (Bittman et al., 1997). This phenomenon is observed in all migrating neurons. This stage is followed by the death of approximately 70% of these cells, with only about 30% surviving. | It is anticipated that we will be able to explain how an event of intercellular fusion leads to the selection of cellular variants that acquire the ability to prevent further fusion. Given that neurons are post-mitotic and arrested in interphase, a transient fusion event is likely to activate a “fusion prevention mechanism” in the surviving cells. It is also important to investigate whether this mechanism contributes to the nervous system’s unique functional capability of generating first-person inner sensations. | As outlined by the semblance hypothesis (Vadakkan, 2020), dye diffusion between neuronal cells indicates the presence of fusion pores, pointing to episodes of inter-neuronal fusion. These early fusion events may have been introduced as a means to induce adaptive responses that prevent the progression from hemifusion to full fusion during inter-neuronal interactions. This adaptation allowed for the formation of IPLs, where interactions remain confined to the hemifusion stage. The capacity of IPLs to generate first-person inner sensations provided substantial functional and survival advantages, making it crucial to maintain IPL dynamics at the hemifusion level. Consequently, initial inter-neuronal pore formation is thought to have triggered an adaptive mechanism that restricts further fusion, playing a key role in the evolutionary success of organisms with this capability. |
| 122 | Following the stage where dye diffusion is observed, a significant loss of neurons (approximately 70%) (Blaschke et al., 1996) and spine loss (ranging from 13% to 20%) are subsequently noted. | There is a high probability that the surviving cells have acquired an adaptive mechanism. | As explained by the semblance hypothesis (Vadakkan, 2020), after the death of 70% of the cells, an adaptation likely occurs in the surviving neurons that prevents any future coupling between neurons that could lead to inter-neuronal fusion. This adaptation is crucial for maintaining IPLs, which are essential for generating functional processes. |
| 123 | Aging is considered the primary risk factor for neurodegenerative disorders, including Alzheimer’s disease (Guerreiro & Bras, 2015). | It is essential to explain the loss of a specific mechanism or structural changes that occur during aging, which are responsible for age-related dementia. Dementia refers to a decline in both memory and behavioral motor functions, including speech and motor actions. | Dye diffusion between neuronal precursor cells during a specific stage of development occurs in 100% of the cells (Bittman et al., 1997). The death of up to 70% of these cells, with the survival of the remaining 30% that mature into adult neurons, suggests that an adaptation is triggered in the surviving cells, preventing any future inter-neuronal fusion, spine loss, and neuronal death. Age-related defects in this adaptation mechanism could result in cell-cell fusion, mixing of cytoplasmic contents, and neurodegeneration. This may provide a potential explanation for age-related cognitive decline (Vadakkan, 2021). |
| 124 | Higher brain functions occur only when the frequency of oscillating extracellular potentials falls within a narrow range, as evidenced by EEG recordings (Rusalova, 2006). | For oscillating extracellular potentials to occur, there must be corresponding intracellular changes. In the cortex, neurons are organized into six layers, with synaptic connections between neurons across these layers. Therefore, synaptic transmission is expected to occur perpendicular to the cortical surface. However, it is essential to demonstrate the changes that generate the horizontal component of these oscillations. | Both mechanisms for learning and memory retrieval are expected to depend on and contribute to the vector components of oscillating extracellular potentials. Propagation of potentials across the IPLs formed between spines belonging to laterally located neurons contribute to the horizontal aspect of the oscillating potentials (Vadakkan, 2010; 2013). Notably, since neurons from all cortical layers have their apical terminals attached to the subpial region, spines from neurons in different layers also participate in IPL formation and contribute to the horizontal component of the oscillations. |
| 125 | In prematurely born infants, the oscillating extracellular potentials in the electroencephalogram (EEG) display discontinuities in the waveform (Selton et al., 2000). | It is essential to explain the formation of the horizontal component during brain development as it matures. Premature infants face survival challenges below a certain age. Enabling extracellular potentials to oscillate within a narrow frequency range is a critical requirement for brain function and survival, as this process is integral to the establishment of higher brain functions and overall neurological health. | While recurrent collaterals, as well as cortico-thalamic and thalamo-cortical pathways, are expected to contribute to the horizontal component of oscillating potentials, a robust global mechanism is necessary to effectively provide horizontal component of the oscillations. This can be achieved through the formation of IPLs, which are facilitated by the arrival of a large number of associative stimuli during development (Vadakkan, 2021). The reactivation of these IPLs subsequently provides the horizontal component to the oscillations. |
| 126 | A study found that infants are capable of forming memories, but difficulties with memory retrieval likely explain infantile amnesia (Yates et al., 2025) | The retrieval mechanism likely exhibits a developmental immaturity that accounts for the observed retrieval deficits. | The brain operates within a narrow range of oscillatory frequencies. IPLs are thought to contribute to the horizontal component of these oscillations. Learning events increase the number of IPLs. During infancy, however, the relatively low number of IPLs may be insufficient to support the horizontal component of oscillatory activity, potentially compromising the robustness of the system property necessary for the generation and integration of semblions essential for memory formation. |
| 127 | Humans take a comparatively longer time to develop motor functions after birth than most animals. | It is essential to provide at least a conceptual framework to explain this developmental delay, which may be linked to the superior cognitive abilities of humans compared to other animals. A mechanistic explanation is warranted to account for this feature. | The human nervous system has the capacity to form a vast number of inter-postsynaptic functional links (IPLs) as associative learning events accumulate. Reactivation of these IPLs gives rise to first-person experiential phenomena in tandem with motor actions. To improve the system’s efficiency by associating a greater number of IPLs with a single motor response, motor neurons can initially be maintained at a low subthreshold activation level for a period of time. At a later developmental stage, these neurons can be held at a relatively higher subthreshold level, enabling the execution of motor actions in response to the reactivation of individual IPLs (Vadakkan, 2021). |
| 128 | Artificially triggering spikes in a single cortical neuron induces spiking activity in a group of neighboring neurons within the same cortical layer, located at a distance between 25 and 70 µm from the stimulated neuron (Chettih & Harvey, 2019). | It should be possible to explain a mechanism that facilitates the lateral spread of firing between neurons of the same neuronal order, through a path other than the trans-synaptic route. | One explanation is the propagation of depolarization across the IPLs between spines belonging to different neurons (Vadakkan, 2013. This also accounts for why only sparsely distributed neurons fire in a time-correlated manner. |
| 129 | The protein complexin inhibits SNARE-mediated fusion by preventing the intermediate stage of hemifusion. Complexin is present in the spines, but docked vesicles are not found within the postsynaptic terminals (spines), in contrast to the presence of docked vesicles in presynaptic terminals. | Which inter-membrane fusion process is being arrested by complexin?' It is essential to explain an inter-membrane fusion mechanism that can be mediated by SNARE proteins and blocked by complexin, specifically by halting fusion at or before the intermediate stage of hemifusion in the spines. | SNARE proteins provide the energy required to bring membranes together, overcoming repulsive charges and the energy barrier between apposed membranes (Oelkers et al., 2016). They also generate the force needed to pull the membranes as tightly together as possible (Hernandez et al., 2012). By initiating the fusion process through energy supply (Jahn & Scheller, 2006), SNARE proteins can facilitate the formation of characteristic hemifusion intermediates (Lu et al., 2005; Giraudo et al., 2005; Liu et al., 2008). The protein complexin, present within postsynaptic terminals (Ahmad et al., 2012), is known to interact with the neuronal SNARE core complex, arresting fusion at the hemifusion stage (Schaub et al., 2006). These findings suggest the possibility of inter-spine interactions mediated by SNARE proteins and regulated by complexin. |
| 130 | The cortex contains hundreds of distinct types of neurons (Huntley et al., 2020; Mao & Staiger, 2024). | It is essential to explain how these diverse types of neurons collaborate to orchestrate specific cortical functions. | What is crucial is the inter-neuronal, inter-spine interaction that forms IPLs during learning, with their reactivation generating both semblances and motor effects. IPLs can form between the spines of various types of neurons, including inhibitory neurons. The net polarity of the clusters of interlinked spines determines the conformation of the net semblance, which in turn defines the qualia of inner sensations (Vadakkan, 2021). |
| 131 | Transcriptomic analyses reveal considerable heterogeneity even among adjacent neurons of the same type within the cortex (Kamme et al., 2003; Cembrowski et al., 2016). | This suggests that any mixing of contents between these neurons would be detrimental to their function. Therefore, a robust mechanism must exist to prevent intercellular fusion. | The distinct mRNA profiles of adjacent neurons, even of the same type, suggest that any mixing of cytoplasmic contents would trigger homeostatic mechanisms, such as spine or neuronal loss, to prevent further damage (Vadakkan, 2016). This aligns with the structural limitation of IPLs, restricting them to the stage of inter-membrane hemifusion. |
| 132 | Heterogeneity in clinical features and pathological changes is observed in Alzheimer's disease and other neurodegenerative disorders. | First, a universal mechanism likely involves various types of neurons. Second, multiple factors are probably at play within this operational mechanism. The pathological changes resulting from these factors should help explain the observed heterogeneity. | A common mechanism involves the pathological conversion of the normal maximum limit of inter-spine hemifusion into pathological fusion. Clinical features are determined by: a) the formation of non-specific IPLs at different locations, and b) the locations of IPL fusion, which can lead to spine loss and even neuronal death (Vadakkan, 2016). This explains the observed heterogeneity. |
| 133 | In excitatory neurons, spine depolarization can occur without subsequent dendritic depolarization. Moreover, distal dendrites in humans contribute only limited excitation to the soma, even during dendritic spikes (Beaulieu- Laroche et al., 2018a; Beaulieu-Laroche et al., 2018b). | Why was such a mechanism selected? What is the functional significance of spine head depolarization? Is there a connection between spine head depolarization, oscillating extracellular potentials, and various brain functions? Are the spine heads involved in specific computations? | The IPL mechanism requires only the depolarization of spine heads to generate units of inner sensations. While the absence of dendritic depolarization and the lack of postsynaptic neuron firing can prevent motor outputs, they do not interfere with the generation of semblance at the inter-linked spines. This aligns with the ability to produce inner sensations without corresponding motor actions. |
| 134 | The histological features of amyloid (senile) plaques and neurofibrillary tangles, typically associated with Alzheimer's disease and a range of neurodegenerative disorders, are also observed in normal aging (Anderton, 1997). | A mechanistic explanation is needed to understand how and why intracellular neurofibrillary tangles and extracellular plaques—key pathological features of neurodegenerative disorders—are observed in normal aging, albeit without accompanying symptoms. | Individuals with a surplus of specific IPLs can afford to lose a subset of them. However, the formation of extracellular plaques can reduce the number of specific IPLs formed during learning. As a result, individuals with only a borderline number of IPLs—just enough to generate specific memories—will be more vulnerable to the effects of amyloid plaque accumulation in the extracellular matrix (ECM). |
| 135 | Valproic acid, which is used to treat a range of seemingly unrelated neurological conditions—such as seizure disorders, hyperkinetic movement disorders, spasticity, and hallucinations—can also provide relief from various types of headache pain. | Mechanistic explanations of various disorders, along with the system's operational framework, should offer interconnected insights into why valproic acid is effective across different types of headaches | By inhibiting voltage-gated sodium channels, valproic acid can reduce neuronal excitability and prevents the rapid formation of IPLs, thereby suppressing seizures. This action also prevents IPL formation between the spines of spiny neurons in the basal ganglia, helping to alleviate hyperkinetic movement disorders. Additionally, this reduces the number of IPLs & their inputs to upper motor neurons, thereby decreasing spasticity. Furthermore, this can diminish or block the inner sensation associated with headache pain. |
| 136 | Since learning is expected to generate new circuit connections, the individual circuit elements—much like components on a printed circuit board (PCB)—must remain physically separate from one another | The properties of both neuronal membranes and the extracellular matrix must align with the formation of new circuit connections, the functional characteristics they impart, and their potential for reversal. | Although the extracellular matrix space between membranes appears minimal, studies in artificial systems show that the hydration layer between lipid membranes presents a significant energy barrier (Rand & Parsegian, 1984; Martens & McMahon 2008; Harrison, 2015). Moreover, the movement of protons is responsible for electrical currents that propagate at the speed of light. In contrast, conduction in neurons occurs through the propagation of depolarization, which travels at a much slower velocity—approximately 2 m/s in non-myelinated neuronal processes. |
| 137 | Representational drift" refers to the phenomenon in which the specific set of neurons activated during a repeated brain function gradually changes over time (Schoonover et al., 2021; Marks & Goard, 2021; Deitch et al., 2021). | In the case of memory, it is essential to demonstrate either (a) redundancy in its underlying mechanisms or (b) an excess of functional units, a subset of which work together to support memory formation. | Repetition of associations involving overlapping features in future learning events, which propagate through neural circuits that incorporate new neurons in granule neuronal layer, will lead to the formation of new sets of IPLs. As a result, when a brain function is repeated, it activates a new set of neurons. Moreover, the formation of new IPLs in unrelated learning events alters the inputs received by higher-order neurons, influencing their firing patterns (Vadakkan, 2019). |
| 138 | The ability to induce robust long-term depression (LTD) in the spiny region of medium spiny neurons (MSNs) within the nucleus accumbens (NAc) of naïve animals. | It is important to explain long-term depression (LTD) as an active process, rather than merely the reversal of mechanisms involved in long-term potentiation (LTP) (Dong et al., 2015). Given that LTD takes minutes to induce, it must be described as a time-dependent mechanism (Thomas et al., 2001; Brebner et al., 2005). Additionally, it is essential to demonstrate that energy applied to the spiny region results in a depression of potentials recorded at the postsynaptic region or on the soma of medium spiny neurons (MSNs). | The formation of IPLs between a spine of a medium spiny neuron (MSN) that receives excitatory input and another spine of a second MSN that receives inhibitory input leads to the generation of a depression in net potentials. The cumulative effect of such IPLs can result in a depression of the net potentials recorded by the electrode. This mechanism can help explain the occurrence of long-term depression (LTD) (Vadakkan, 2021). |
| 139 | Following stimulation, there is a time delay before LTD can be observed (Thomas et al., 2001; Brebner et al., 2005), similar to the delay seen in the induction of LTP (Gustafsson & Wigström, 1990; Escobar & Derrick et al., 2007). | A time-dependent cellular change occurs during the delay period following LTD stimulation. | Similar to LTP, the induction of LTD also results from the formation of IPLs. Since energy is required for spine expansion, which facilitates IPL formation between spines receiving excitatory and inhibitory inputs, spine expansion itself also requires time to occur. |
| 140 | Similar to LTP, LTD in the nucleus accumbens (NAc) is also dependent on NMDA receptors (Lüscher & Malenka, 2012). | LTD induction occurs through the activation of NMDA receptors at glutamatergic synapses. It is important to explain how the activation of NMDA receptors can lead to both LTP and LTD. | Excitatory synaptic activity is crucial for spine expansion and the formation of IPLs between spines belonging to different MSNs in the nucleus accumbens (NAc) region. Since dopaminergic terminals synapse onto spines that receive excitatory inputs (with dopamine facilitating spine expansion), it is reasonable to infer that spines of excitatory synapses act as the primary partners in IPL formation (Vadakkan, 2021). |
| 141 | When rewards or conditioned stimuli predicting reward are presented, dopamine neurons in the ventral tegmental area (VTA) increase their firing (Schultz, 1998; Roitman et al., 2004) , releasing dopamine at their terminals that synapse onto the spines of MSNs in the nucleus accumbens (NAc). | Dopamine induces specific changes in the spines of MSNs that receive excitatory inputs. | Dopamine is known to induce spine expansion (Yagishita et al., 2014). Expanding spines can enhance IPL formation and maintain these formed IPLs for an extended period. Since some of the spines involved in IPL formation receive excitatory inputs while others receive inhibitory inputs, the net effect of dopamine is the augmentation of depression (Vadakkan, 2021). |
| 142 | Drugs of abuse, such as cocaine, elevate dopamine levels in the nucleus accumbens (NAc) (Lüscher & Malenka, 2011). | Dopamine exerts specific effects in the nucleus accumbens (NAc) that contribute to addiction, which can ultimately lead to substance abuse. | Dopamine promotes spine expansion and the formation of IPLs, contributing to the internal sensation of pleasure. Prolonged exposure can lead to spine loss and result in dependency on cocaine to maintain a normal comfort level (Vadakkan, 2021). |
| 143 | Exposure to cocaine results in the attenuation of postsynaptic potentials in the MSN spines of the nucleus accumbens (NAc) (Beurrier & Malenka, 2002). | It is important to demonstrate how dopamine, released as a result of cocaine's action, affects the spines of MSNs that receive excitatory inputs, leading to the attenuation of postsynaptic potentials. | Dopamine is known to induce expansion of spine that receive excitatory inputs (Yagishita et al., 2014). This expansion accelerates the above spine's ability to form IPLs with spines that receive inhibitory inputs, altering the conformation of the semblance generating the internal sensation of pleasure (Vadakkan, 2021). |
| 144 | Dopamine attenuates postsynaptic potentials induced by the stimulation of various excitatory inputs to the nucleus accumbens (NAc) shell region (Park et al., 2008). | It is necessary to explain how dopamine, released onto spines that receive excitatory inputs, leads to the attenuation of postsynaptic potentials. | Dopamine induces the expansion of the spine head that also receives excitatory input. This expanded spine forms an IPL with another spine that receives inhibitory input (Vadakkan, 2021). |
| 145 | In response to natural rewards and cocaine exposure, a significant subset of MSNs in the nucleus accumbens (NAc) exhibit a depression in firing rate (Carelli, 2002; Ishikawa et al., 2009; Kourrich & Thomas, 2009). | Rewards and drugs of abuse trigger the release of dopamine from the VTA. It is essential to demonstrate how dopamine's action on the spines of MSNs that receive excitatory inputs leads to a reduced firing rate of these MSNs. | As a result of the factors mentioned above, the reduction in postsynaptic potentials leads to a decrease in firing rate (Vadakkan, 2021). |
| 146 | Dopamine reduces the excitability of MSNs in the nucleus accumbens (NAc) in vitro (O'Donnell & Grace, 1996). | It is important to demonstrate how dopamine's action on the spines of MSNs that receive excitatory inputs leads to the inhibition of these MSNs. | Dopamine enhances IPL formation between two spines—one receiving excitatory input and the other receiving inhibitory input. As a result, the net effect leads to the inhibition of the excitatory input to the MSN (Vadakkan, 2021). |
| 147 | Synchronization of membrane potential states across a population of neurons in the nucleus accumbens (NAc) (Goto & O'Donnell, 2001). | It is important to demonstrate how membrane potential states become synchronized across a population of neurons in the nucleus accumbens (NAc). Specifically, an explanation is needed for how the spines of MSNs that receive excitatory inputs, together with those receiving inhibitory inputs, can collectively contribute to the synchronization of membrane potentials. | Inhibitory interneurons, which are electrically coupled through gap junctions, are known to generate oscillatory activity. Similarly, islets of inter-LINKed spines are also expected to contribute vector components that support the generation of oscillating extracellular potentials. According to the semblance hypothesis, these oscillations play a critical role in binding the units of inner sensations (Vadakkan, 2021). |
| 148 | Similar to LTP, LTD in hippocampal synaptic regions is implicated in various forms of learning (Kemp & Manahan-Vaughan, 2004; Dong et al., 2013; Dong et al., 2015). | It is important to explain the similarity between the correlation of LTP induction with learning and that of LTD induction with learning. | According to the semblance hypothesis, the association of two sensory stimuli during learning requires the formation of IPLs. Given that spines receiving inhibitory inputs are present on MSNs, IPLs formed between spines receiving excitatory and inhibitory inputs can give rise to LTD. Since IPL formation underlies learning, the inner sensation of memory—i.e., semblance—is generated at the inter-LINKed spines regardless of the strength of the net postsynaptic potentials (Vadakkan, 2021). |
| 149 | In the “addicted” state, there is an impaired ability to induce LTD at the input synaptic regions of MSNs in the nucleus accumbens (NAc) (Kasanetz et al., 2010). | It is important to explain how initial drug use leads to the induction of LTD. Subsequently, it is necessary to demonstrate how the transition to the “addicted” state results in a diminished capacity to induce LTD. | Initially, IPL formation between spines receiving excitatory and inhibitory inputs leads to a depression of postsynaptic potentials, manifesting as LTD. However, as addiction progresses and more spines are lost, increasingly higher amounts of the drug are required to reestablish the normal conformation of semblance at these locations, merely to maintain the internal sensation of baseline comfort (Vadakkan, 2021). |
| 150 | The inner sensation of pleasure is associated with specific properties of the nucleus accumbens (NAc), as reflected by the ability to induce LTD at the input synapses of its medium spiny neurons (MSNs). | It is essential to provide a cohesive explanation for the following: (1) the ability to induce robust LTD in the nucleus accumbens (NAc) of naïve animals; (2) the impaired ability to induce LTD in the “addicted” state; (3) the attenuation of postsynaptic potentials by cocaine; and (4) the reduced firing of MSNs in response to cocaine or dopamine. | The inner sensation is explained through the conformation of semblances generated at the inter-LINKed spines. At the IPLs formed between a spine receiving excitatory input and another receiving inhibitory input, the resulting inner sensation is expected to be that of pleasure (Vadakkan, 2021). |
| 151 | Camillo Golgi developed the Golgi staining method, which enabled the visualization of a network-like reticulum of neuronal cells in brain tissue. Ramón y Cajal later refined this technique, allowing for the visualization of individual neurons. Golgi expressed controversial views (PDF), disputing Cajal’s interpretation that the modified staining revealed discrete, individual neurons. | The chemical basis of the modifications to the original Golgi staining protocol may hold the key to resolving the roots of this controversy. It is essential to determine which aspects of the original staining method produced a reticulated view of neurons, and how the subsequent chemical modifications disrupted these connections, leading to the visualization of individual neurons instead. A complete explanation will likely become possible only when the operational mechanisms of the brain are more fully understood. |
Golgi used a single oxidizing agent to pre-treat brain tissue prior to staining, while Cajal introduced an additional oxidizing agent during the same preparatory step. This suggests that a higher oxidation state may limit the spread of the Golgi staining reaction across neurons, likely by blocking certain inter-neuronal channels. Notably, blood oxygenation level-dependent (BOLD) signals have been observed to peak in specific brain regions approximately four seconds after learning (Monti et al., 2010; Murayama et al., 2010), and most working memories tend to fade over time. These observations suggest that oxygen may play a role in reversing learning-induced channels. Given that such channels should not permit cytoplasmic mixing between neurons, their characteristics align with the properties of inter-postsynaptic functional links (IPLs), whose structural upper limit may involve inter-membrane hemifusion (Vadakkan, 2022). |
| 152 | The formation of new granule neurons in the hippocampus, known as adult hippocampal neurogenesis has a critical role in cognitive functions. | The operational mechanism of the brain should be capable of explaining the functional advantages conferred by the integration of newly formed neurons. | The integration of new granule neurons into the hippocampal circuitry results in continuous alterations to both input and output connections to those neurons, thereby reshaping existing neural networks. Repeated instances of the same associative learning process lead to the formation of new inter-postsynaptic functional links (IPLs) at higher neuronal levels, thereby expanding the repertoire of sparse storage mechanisms (Vadakkan, 2011). Since each associative learning event shares a subset of common components, subsequent learning episodes continue to generate additional IPLs for a given association, reinforcing and diversifying the representation of that information. |
| 153 | Learning entails a dynamic interplay between the loss of existing dendritic spines and the formation of new ones, reflecting the neural changes required to accommodate additional learning-associated modifications (Frank et al., 2018). | There must be a mechanism that drives the loss of dendritic spines during learning. The formation of new spines likely serves a specific purpose, facilitating the incorporation of novel information and enabling further learning processes. | The structural upper limit for inter-membrane interactions during IPL formation is inter-membrane hemifusion, an intermediate stage of membrane fusion. Various factors may circumvent the checkpoint that typically prevents hemifusion from progressing further, eventually leading to full membrane fusion. In response, neuronal cells may remove the fused spines, which could explain the observed spine loss during learning. Spine loss can also be triggered by specific computational demands, while the formation of new spines likely increases the number of IPLs to accommodate the need for enhanced units of inner sensations. |
| 154 | Permanent changes in the motor response to a single stimulus, resulting from repeated exposure to that stimulus, are known as non-associative forms of learning. | It is essential to provide a mechanism explaining how permanent changes in motor responses occur as a result of repeated exposures. | Any environmental stimulus is a high-dimensional sensory input, composed of multiple newly associated components that can lead to the formation of IPLs. Hence, repeated exposures to a single stimulus repeatedly reactivate same set of IPLs and stabilize them. Furthermore, the stimulus must propagate through newly incorporated granule neurons in the circuit. This process results in the formation of new IPLs at higher neuronal levels in response to the same stimulus. As the learning experience is repeated, the number of IPLs increases and they become stabilized, ultimately leading to permanent changes in the motor response to a single stimulus. |
| 155 | The prevalence of dendritic spikes on the dendrites of place cells (CA1 neurons) in behaving mice is predictive of spatial precision (Sheffield & Dombeck, 2015). | It is crucial to explain how spatial inputs contribute to the generation of dendritic spikes. | Large excitatory postsynaptic potentials (EPSPs) in a dendritic spike signify the summation of multiple EPSPs on the dendrite. The arrival of several EPSPs via IPLs to an islet of inter-linked spines (IILPs) provides a plausible mechanism for this process. Spatial stimuli reaching these IILPs lead to the summation of EPSPs, ultimately generating a dendritic spike. |
| 156 | Both consolidation of long-term memory (Flexner et al., 1967; Davis & Squire, 1984) and late-phase long-term potentiation (LTP) in in vitro slices (Krug et al., 1984; Huang et al., 1996) are dependent on protein synthesis. However, after exposure to a protein synthesis inhibitor in consolidated memory engram cells, direct optogenetic activation of these cells still retained the ability to retrieve specific memories (Ryan et al., 2015). | It is essential to demonstrate the presence of a protein synthesis-independent, functional engram cell-specific connectivity mechanism to explain how memories are retained. Moreover, it is crucial to show that a non-protein-dependent mechanism is responsible for the long-term maintenance of memories. | According to the semblance hypothesis, during learning, an IPL is formed between the spines of different output engram neurons. The results of the experiment by Ryan et al., (2015) suggest that IPLs are not protein-based. In line with the semblance hypothesis, learning generates IPLs through inter-spine membrane interactions, progressing to the stage of inter-membrane hemifusion. |
| 157 | Compared to the set of neurons that fire in response to an associatively learned stimulus before learning, additional neurons are activated when the animal is exposed to the same stimulus after learning. This phenomenon has been documented in the lateral amygdala in fear conditioning experiments. (Schoenbaum et al., 1998; Tye et al., 2008). | New neural pathways are formed during learning, propagating potentials to additional sub-threshold activated neurons, thereby facilitating their firing. Identifying the location and mechanisms responsible for the creation of these pathways is crucial. | According to the semblance hypothesis, IPLs are formed during learning. After learning, exposure to one of the associatively learned stimuli propagates through these IPLs, providing additional potentials to specific neurons, enabling them to reach the threshold for firing. This mechanism explains why additional neurons fire when the animal is exposed to the same stimulus after learning. Exposure to the same stimulus long after learning will activate an additional set of neurons, due to the influence of IPLs formed from subsequent learning events and the presence of newly incorporated granule neurons in its propagation path. |
| 158 | Fear learning generates local connectivity between lateral amygdala (LA) neurons (Abatis et al., 2024). Electrophysiological studies have shown that stimulation of a single LA neuron induces depolarization in a small subset of neighboring LA neurons. | After cued fear conditioning (CFC), many LA neurons establish functional connectivity between them. It is essential to explain the pathway through which depolarization propagates from one LA neuron to the next. This connectivity mechanism must be learning-induced, occur between neurons of the same neuronal order, and occur on millisecond timescales, suggesting that it is likely a non-synaptic mechanism. | According to the semblance hypothesis, IPLs represent the engram changes that occur during associative learning. Artificial stimulation of a single LA neuron induces backpropagation of potentials along its dendritic branches towards spines, which can then propagate to the inter-LINKed spines. This, in turn, spreads towards the postsynaptic LA neuronal soma of the inter-LINKed spines. If this allows these postsynaptic LA neurons to cross the threshold, they fire. |
| 159 | Fear conditioning is associated with enlarged synapses on the dendritic spines of LA neurons (Ostroff et al., 2010; Choi et al., 2021). | Synapse enlargement can result from the expansion of either pre- and/or postsynaptic terminals. A mechanistic explanation linking this enlargement to the fear learning process is needed. | Enlargement of spines can enhance IPL formation by displacing the hydration layer between the membranes of the spines. |
| 160 | Synapses on the dendritic spines of LA neurons exhibit a higher ratio of postsynaptic density (PSD) area relative to that of presynaptic structures (Ostroff et al., 2012). | This finding suggests that a higher postsynaptic density is likely associated with the enlargement of postsynaptic terminals (spines) relative to presynaptic terminals. The resulting lateral expansion of spines during learning may confer a structural advantage that supports the formation of fear memories. | IPLs are expected to form between the lateral regions of dendritic spines, aligning with findings that vesicle exocytosis involved in AMPA receptor insertion also occurs at these lateral spine regions (Rácz et al., 2004). |
| 161 | Synapses devoid of astrocytic coverage emerge in the amygdala during the consolidation of Pavlovian threat conditioning (Ostroff et al., 2014). | Astrocytic pedicels cover less than 50% of the perisynaptic area in approximately 60% of synapses within the CA1 region of the hippocampus (Ventura & Harris, 1999). The reduction or disappearance of astrocytic pedicels in the amygdala during the consolidation of Pavlovian threat conditioning may provide a spatial basis for the underlying mechanism of memory consolidation. | The disappearance of astrocytic pedicels increases the abutted surface area between neighboring spines, which in turn may enhance the number of inter-postsynaptic functional links (IPLs) that a single spine can form. This phenomenon is therefore associated with increased efficiency in fear learning and provides indirect support for the role of IPLs in both learning and their maintenance during memory consolidation (R´acz et al., 2004; Makino and Malinow, 2009; Jacob and Weinberg, 2015). |
| 162 | A disconnect between dendritic depolarization and neuronal firing has been observed during fear conditioning (d’Aquin | An operational mechanism, most likely related to the first-person property, is expected to emerge at the dendritic level, independent of neuronal firing. | The IPL mechanism, occurring between abutted spines primarily belonging to different neurons, explains the dichotomy between the operational mechanisms at the dendritic level and action potential generation (neuronal firing) at the axon hillock, near the neuronal soma. |
| 163 | Contextual fear conditioning recruits newly synthesized GluA1-containing AMPA receptors into the spines of hippocampal memory-ensemble cells in a learning-specific manner. (Matsuo et al., 2008). | A mechanistic explanation of how the insertion of the GluA1 subunit into the spines facilitates learning is required. | GluA1-containing AMPA receptors (AMPARs) are located approximately 25 nm from the synaptic margins (Jacob & Weinberg, 2015). This aligns with the lateral spine head region, where inter-postsynaptic functional links (IPLs) are expected to form. The transport of these subunits in vesicles to the spine membrane would result in the insertion of some vesicle membrane segments into the lateral spine head region, thereby facilitating IPL formation. |
| 164 | Autophagy leads to memory destabilization and the erasure of auditory fear memories, a process associated with AMPAR endocytosis (Shehata et al., 2018). | A mechanistic explanation is required to elucidate how autophagy leads to memory loss. | GluA2-dependent AMPAR endocytosis is a prerequisite for autophagy to induce memory destabilization (Shehata et al., 2018). Endocytosis removes membrane segments from the spine head region, leading to a decrease in spine size and the reversal of existing IPLs. This process can explain memory loss. |
| 165 | Circuits with identical synaptic connectivity can function differently (Mardar, 2012). | There are missing connections within neuronal circuits that exhibit the same synaptic connectivity patterns. | IPLs between the dendritic spines of different neurons, and occasionally between branches of the same neuron, as proposed by the semblance hypothesis, are well-suited to fulfill this requirement. |
| 166 | Neither the synaptic connectivity of the neuronal circuit nor the computational task performed by the synaptically connected neurons alone can uniquely determine the mechanism of circuit function. (Biswas & Fitzgerald, 2022). | It is essential to incorporate supplementary circuit rules through a yet-to-be-discovered mechanism. | The function of IPLs, which can operate in unison with the synaptically connected neuronal circuitry, explains how the system generates both the first-person property by computing unitary mechanisms that generates inner sensations alongside the option to produce motor outputs, as well as how motor actions can occur in the absence of first-person properties. |
| 167 | The firing of the same individual neurons in the prefrontal cortex prior to speaking identical phonetic words, such as 'sea' and 'see.' (Khanna et al., 2024). | A mechanism that generates first-person meaning and assigns specific words to form a meaningful sentence, followed by motor neuronal firing that produces the phoneme, is expected to be present in the system. | The IPL mechanism can support both the generation of first-person experience and motor output. An operational hub composed of islets of inter-linked postsynaptic terminals (IILPs) serves as a suitable candidate mechanism to explain how a query navigates prior relational patterns within a given context to generate first-person meaning, followed by motor output using appropriate phonemes to effectively convey the message to others (Vadakkan, 2024). |
| 168 | When mice were injected with a histone acetyltransferase (HAT) enzyme to enhance transcription, the strength of their fear memory increased (Santoni et al., 2024). The study also found that a) neurons in which HAT is overexpressed are the neurons that fire during memory retrieval, & b) optogenetic silencing of these specific set of neurons prevents fear memory recall. | Fear memory is associated with transcription & the subsequent translation of specific polypeptides. It is necessary to show the source of additional potentials that allow the HAT overexpressed neurons to fire. | One possible explanation is that at the time of associative learning, when membrane segments are utilized for IPL formation, exposure to HAT is expected to trigger synthesis of more phospholipid molecules to replace membrane segments used for endocytosis. Synthesis of additional phospholipid molecules is triggered, promoting exocytosis and thereby increasing the number of IPLs, while maintaining all the remaining essential endocytotic processes of the cell. Presence of additional IPLs generated by the HAT forms channels through which additional potentials arrive towards those HAT overexpressed neurons. |
| 169 | Firing of lateral amygdala (LA) neurons becomes more synchronized through modulation of theta frequency within the LA (Pare´ and Collins, 2000). Synchronous oscillations in the theta and gamma bands are observed between the basolateral amygdala (BLA) and interconnected brain regions during the retrieval and consolidation of fear memories (Bauer et al., 2004; Seidenbecher et al., 2003). | The operational mechanism that produces the first-person experience of fear is linked to oscillations in extracellular potentials. | These phenomena can be explained by the reactivation of interlinked spines—distributed across multiple inter-internally linked pathways (IILPs)—on the dendrites of lateral amygdala (LA) neurons. The integration of semblances associated with fear, originating from different brain regions, is mediated by the system-level dynamics of oscillating potentials. Moreover, if an inhibitory neuron within a network of oscillating inhibitory neurons forms a synapse with a spine of a principal neuron (PN) that is part of an IILP, it is expected to influence the synchronization of membrane potentials among the postsynaptic PNs. |
| 170 | Memory retrieval induces synchronized rhythmic activity between the basolateral amygdala (BLA) and interconnected brain structures, accompanied by the reactivation of certain sets of neurons that are called fear engram neurons (Bocchio et al., 2017). | Oscillations in potential difference recorded from two locations using differential electrodes require contributions from different vector components. When this is coupled with the reactivation of engram neurons, it is reasonable to infer that some of these vector components also contribute to the firing of these neurons. | The IPL mechanism, wherein synaptic transmission and the propagation of potentials along the IPLs act as candidate mechanisms, operates in near-perpendicular directions to provide vector components to the oscillating potential differences. |
| 171 | Artificial stimulation of neurons within the nervous system can evoke various types of hallucinations (Selimbeyoglu & Parvizi, 2010). Electrical stimulation of the medial temporal lobe has been shown to elicit vivid autobiographical memories (Vignal et al., 2007). | It is essential to explain how neuronal stimulation activates an upstream operational mechanism responsible for generating inner sensations. This implies that the stimulated neurons serve as an intermediate pathway between sensory input and the mechanism underlying perception. | According to the semblance hypothesis, stimulation of an intermediate pathway is sufficient to reactivate both sides of an IPL in the sensory cortices for perception (Vadakkan, 2015). |
| 172 | Auditory hallucinations are a common symptom of schizophrenia. | It is necessary to elucidate the nature of the pathology that gives rise to first-person inner sensations of meaningful sound in the absence of corresponding external auditory stimuli. | According to the semblance hypothesis, perception occurs either when an intermediate pathway from the sensory receptors to the sensory cortex is stimulated, or when inter-postsynaptic functional links (IPLs) in the sensory cortices are activated on either side. The latter can occur when natural stimuli travel through typical sensory pathways reactivating non-specific IPLs, potentially resulting in pathological hallucinations (Vadakkan, 2010). |
| 173 | Spontaneous activity of dopaminergic neurons in the ventral tegmental area (VTA) has been linked to the emergence of psychotic symptoms (Liddle et al., 2000; Lodge et al., 2007). Also, hyperactivity of the striatal dopamine system is associated with schizophrenia (Brunelin et al., 2013). | A mechanistic explanation is required to clarify how excess dopamine contributes to the generation of psychotic symptoms. | Dopamine is known to cause spine expansion (Yagishita et al., 2014). Hence, hyperdopaminergic conditions can promote the formation of non-specific inter-postsynaptic functional links (IPLs), potentially resulting in hallucinations and cognitive impairments. |
| 174 | Neuronal oscillations undergo alterations in schizophrenia (Uhlhaas & Singer, 2010). | It is essential to provide an explanation of how the pathological changes in schizophrenia can alter neuronal oscillations. | The non-specific inter-postsynaptic links (IPLs) present in the penultimate neuronal order, arising from oscillating neuronal circuits, can induce changes in oscillatory neuronal activity (Vadakkan, 2010). |
| 175 | Dopamine antagonists are a primary class of medications used to treat schizophrenia. | Dopamine is known to induce spine expansion (Yagishita et al., 2014). Dopamine plays a role in both motivation-driven learning (Wang et al., 2004) and the persistence of long-term memory storage (Rossato et al., 2009). It is important to explain how inhibiting spine expansion could potentially reduce the symptoms of hallucinations. | The pathology in schizophrenia that generate hallucinations is expected to occur due to the formation of non-specific IPLs. In this context, dopamine facilitates the formation of these non-specific IPLs, thereby exacerbating symptoms. Dopamine antagonists, in contrast, counteract this effect, helping to alleviate the symptoms. |
| 176 | Schizophrenia is characterized by impaired working memory performance (Goldman-Rakic, 1994). | It is necessary explain how memory retrieval is affected in schizophrenia. | Formation non-specific IPL will reduce the specificity of retrieved memories. |
| 177 | Abnormally low gamma power during working memory is seen in schizophrenia (Woo et al., 2010; Uhlhaas and Singer, 2013). | It is necessary to provide an interconnected explanation how memory retrieval is affected in schizophrenia and what component of this mechanism is involved in oscillating extracellular potentials that can reflect in low gamma power during working memory. | While non-specific IPL will reduce the specificity of retrieved memories, it will also increase the horizontal components of extracellular oscillations, which will reduce the amplitude of gamma frequency (typically 30–100 Hz) of oscillations. |
| 178 | In patients with schizophrenia, cognitive deficits related to attention and working memory are often resistant to treatment (Insel, 2010). | It is important to clarify that reducing the formation of non-specific IPLs through dopamine antagonists will not address the deficits in attention and working memory. | Although dopamine antagonists prevent the formation of non-specific IPLs to alleviate hallucinations, their action is not selective. As a result, they also inhibit the formation of specific IPLs, which can impair cognitive abilities. |
| 179 | Hallucinations and cognitive deficits are associated with hippocampal pathologies (Vignal et al., 2007). | It is essential to explain how both cognitive deficits and hallucinations arise in the context of hippocampal pathologies. | Pathological lesions of the hippocampus can lead to a) the loss of specific IPLs and b) inability to form specific IPLs that can result in cognitive deficits. Irritation of the hippocampal regions can lead to non-specific stimulation of higher neuronal orders leading to formation of non-specific IPLs, which can lead to the development of hallucinations. |
| 180 | Deficiency in polyunsaturated fatty acids (PUFAs) has been linked to psychotic symptoms and cognitive deficits. Studies have shown that omega-3 PUFAs can prevent the development of psychotic disorders in adolescents exhibiting the known prodrome for the disease (Amminger et al., 2007; Amminger et al., 2015). | The effect of PUFAs in preventing the progression of the disease requires further explanation. According to the semblance hypothesis, the formation of non-specific IPLs linking non-specific spines is the underlying cause. | It is possible that omega-3 PUFAs incorporate into the Sn-2 position of phospholipids (Murray et al., 2006). This compositional change may prevent the formation of non-specific inter-postsynaptic functional LINKs (IPLs), thereby inhibiting the further progression of the disease. |
| 181 | Schizophrenia is characterized by a profound alteration in aspects of consciousness, such as self-relatedness and the ability to relate to the external world (Urfer-Parnas et al., 2010). | It is essential to provide a mechanistic explanation of how the pathological changes in schizophrenia are linked to the mechanisms that generate normal conscious features. | Formation of large number of non-specific inter-postsynaptic functional links (IPLs) distort the frequency and amplitude of oscillatory waveforms, thereby altering the conformation of C-semblance (Vadakkan, 2010) and modifying the conscious state. |
| 182 | Parkinson's disease is due to damage of the substantia nigra pars compacta neurons that release dopamine at their axonal terminals that synapse with medium spiny neurons (MSNs) of the basal ganglia. | It is necessary to explain how lack of dopamine at these synaptic region leads to tremor, rigidity bradykinesia and postural instability. | Dopamine activates both the direct and indirect pathways in the basal ganglia, regulating thalamic output to the upper motor neurons of the motor cortex, thereby facilitating smooth motor actions. Dopaminergic axons synapse onto the necks of dendritic spines in medium spiny neurons (MSNs) (Bouyer et al., 1984, Freund et al., 1984). Dopamine is known to promote spine expansion (Yagishita et al., 2014). In the absence of dopamine, the formation and reactivation of inter-postsynaptic functional links (IPLs) essential for smooth motor output are diminished. |
| 183 | L-DOPA treatment remains effective for only a few years after the diagnosis of Parkinson's disease. Over time, patients often require progressively higher doses of L-DOPA to achieve the same therapeutic effects. | An explanation is needed for why higher doses of L-DOPA are required over time and why, eventually, L-DOPA becomes ineffective. | Increasing doses of L-DOPA elevate dopamine levels, facilitating the formation of inter-postsynaptic functional links (IPLs). It is likely that additional factors contribute to the conversion of IPL hemifusion—typically the normal upper limit of IPL formation—into full IPL fusion between the spines of different medium spiny neurons (MSNs). This process ultimately leads to the loss of spines or the eventual death of MSNs. Fusion between MSNs has been observed through dye diffusion in MSNs treated with dopamine agonists (Onn and Grace, 1994)." |
| 184 | In advanced cases of Parkinson’s disease, when patients become refractory to high doses of L-DOPA, symptoms such as cognitive impairment and even hallucinations begin to manifest." | It is essential to explain how these symptoms emerge when patients become refractory to L-DOPA treatment. | Firstly, elevated dopamine levels can result in the formation of non-specific inter-postsynaptic functional links (IPLs) elsewhere in the nervous system. These non-specific IPLs can create generalized semblances in response to specific stimuli, contributing to cognitive impairments. Additionally, the presence of non-specific IPLs may also lead to hallucinations." |
| 185 | Chorea, a hyperkinetic movement disorder, can be observed in Parkinson's disease patients who are treated with neuroleptic medications, which act as dopamine receptor D2 blockers. | This presents a constraint that requires a comprehensive explanation, one that integrates with the explanations for the preceding conditions. | When D2 receptors are blocked, the dopamine available from the substantia nigra pars compacta binds to D1 receptors, leading to unopposed activation of the direct pathway and resulting in the hyperkinetic movements characteristic of chorea. |
| 186 | A hallmark of Huntington’s disease is chorea—a type of hyperkinetic movement characterized by involuntary, graceful, and excessive limb motions | Excessive dopamine contributes to the pathology of the disease and is managed using tetrabenazine, a drug that depletes dopamine from the synaptic vesicles of dopaminergic neurons. A detailed mechanistic explanation of this process is essential for a deeper understanding | Enlargement of dendritic spines due to excessive dopamine can result in the formation of a large number of inter-postsynaptic functional links (IPLs). This, in turn, may cause excessive and unbalanced activity in the direct pathway, leading to the characteristic graceful, involuntary movements seen in chorea. |
| 187 | Subcortical dementia and hallucinations are additional features observed in Huntington’s disease. | It is essential to provide explanations for these symptoms. | Non-specific inter-postsynaptic functional links (IPLs) give rise to non-specific semblances, which dilute the overall semblance and result in memory lapses. Additionally, the formation of such non-specific IPLs may contribute to hallucinations |
| 188 | Parkinsonian features typically appear in the later stages of Huntington’s disease | It is important to explain how an excess of dopamine can ultimately lead to symptoms that resemble those caused by a dopamine deficiency. | Since a large number of medium spiny neuron (MSN) spines undergo fusion in Huntington’s disease, this leads to the loss of both the spines and the associated neurons. As a result, symptoms resembling the hypokinetic movements seen in Parkinson’s disease may emerge. |
| 189 | Botulinum toxin, local anesthetic agents, and plastic surgery are used for treating different types of headache pains (Becker, 2020; Robbins et al., 2014; Kung et al., 2011). | It is essential to provide a unified explanation of how these three seemingly unrelated skin applications alleviate headache pain. | All three procedures alter sensory input from the skin surface of the scalp. This can lead to the formation of new inter-postsynaptic functional links (IPLs) or the removal of existing ones, both in the cortical regions responsible for localization and pain perception. These changes modify the conformation of semblance associated with pain, thereby alleviating headache symptoms. |
| 190 | Magnesium is used for preventing headaches (Luckner et al., 2018; Saldanha et al., 2021). Intravenous magnesium is used to control certain seizure disorders such as eclampsia. | It is important to establish a unified mechanism that explains both headaches and seizures. Note: Although magnesium is not particularly effective for either condition, it is less toxic and therefore preferred during pregnancy. | Magnesium inhibits the activation of NMDA receptors at excitatory glutamatergic synapses, thereby reducing the reactivation of inter-postsynaptic functional links (IPLs) responsible for generating semblances and the perception of pain. This same mechanism, by maintaining NMDA receptor closure, also hinders the rapid formation of IPL chains, thereby helping to control seizures. |
| 191 | Both dopamine agonists, such as dihydroergotamine, and dopamine antagonists, such as chlorpromazine and metoclopramide are used to relieve certain refractory headaches. | When therapeutic interventions with opposing mechanisms of action are effective in alleviating certain headache pains, it may indicate the presence of unique and complex underlying features specific to those headache types. | Dopamine is known to increase the size of dendritic spines (Yagishita, 2014). Both dopamine agonists and antagonists can alter spine size, which subsequently leads to the formation or reversal of IPLs. These will alter the conformation of net semblance for headache pain in different ways and alleviate headache pains. |
| 192 | Oxygen is used as a treatment for cluster headaches (Cohen et al., 2009). | It is important to explain a specific aspect of the operational mechanism of IPL formation that is influenced by high oxygen concentrations. | The original Golgi staining technique revealed a network of interconnected cells. Cajal modified this method by introducing an additional oxidizing agent, which reduced the visible interconnections between cells. This observation is interpreted as evidence for the oxygen state–dependent nature of IPLs that connect neurons (Vadakkan, 2022). Consequently, a high concentration of oxygen is expected to reverse several IPLs, thereby altering the conformation of pain semblance. |
| 193 | Some anti-seizure medications (e.g. topiramate) is an effective in alleviating migraine headaches (Paungarttner et al., 2023; Pearl et al., 2023) | It is necessary to provide an explanation that similar pathological changes are responsible for both these disorders (or two different mechanisms of action of the same medication) to substantiate why same medications are effective in both disorders. | It was possible to explain that seizure disorders are due to rapid chain formation of IPLs (Vadakkan, 2016). Similarly, headache pains can also be explained in terms of IPL formation. Jacksonian march in seizures and cortical spreading depression in headaches (Eikermann-Haerter et al., 2010; Vitale et al., 2023) can be explained in terms of spread of IPL formation. |
| 194 | Post-ictal headache (Caprara et al., 2020). | An interconnected explanation is needed to explain headache following a generalized seizure. | A large number of non-specific IPLs are generated during a generalized seizure (Vadakkan, 2016), explaining loss of consciousness. Once the patient regains consciousness, there will be large number of non-specific IPLs that can explain headache pain. This headache pain decreases over time matching with the anticipated reversal of non-specific IPLs with time. |
| 195 | Hemiplegic migraine: | It is necessary to explain how migraine headache can be associated with upper motor neuron (UMN) lesion-like changes. | Increased number of IPLs changes conformation of background semblances to generate pain semblance for headache. Excessive IPLs can divert potentials from reaching the UMNs (layer V cortical neurons called Betz cells). This leads to transient UMN type of weakness in the limbs. |
Long-term potentiation (LTP) is an experimentally observed phenomenon. The capacity to induce LTP at various locations where sensory inputs converge has shown correlations with different learning abilities. LTP remains the most significant discovery, offering the greatest number of constraints for testing the semblance hypothesis. However, it is crucial to emphasize that obtaining interconnected explanations required reinterpreting findings from LTP experiments conducted by various laboratories and presenting alternative explanations that differ from those proposed by the original authors. I recognize that, while often uncomfortable, this process is an essential step. The following are findings of LTP, and their interconnected explanations based on the semblance hypothesis. | |||
| 196 | The experimental phenomenon of long-term potentiation (LTP) has shown multiple correlations with behavioral motor actions that serve as surrogate markers of memory retrieval. | It should be possible to explain how the cellular changes occurring during LTP induction and learning are correlated, and how these changes relate to the ability to retrieve memories. | High-energy stimulation during LTP induces the formation of a large number of non-specific inter-postsynaptic functional links (IPLs), which contribute to LTP. 1) High-energy stimulation promotes the formation of non-specific inter-postsynaptic functional links (IPLs), responsible in mediating long-term potentiation (LTP). 2) A higher density of closely apposed dendritic spines at sites of sensory convergence enhances both learning capacity and the strength of LTP that can be induced (Vadakkan, 2019). |
197 | Learning occurs within milliseconds, whereas the induction of long-term potentiation (LTP) requires at least 20 to 30 seconds (Gustafsson & Wigström), and in some cases, over a minute (Escobar et al., 2007). | The cellular changes that occur during learning are likely amplified during LTP induction in a time-dependent manner. To account for the extended time required for LTP induction, it is necessary to identify a cellular mechanism that is inherently time-consuming. | The high energy delivered during LTP stimulation protocols induces dendritic spine expansion and promotes the formation of numerous non-specific inter-postsynaptic functional links (IPLs). These IPLs establish multiple pathways through which synaptic potentials can reach the recording electrode, resulting in a potentiated response. The prolonged persistence of these IPLs accounts for the sustained, long-term nature of LTP (Vadakkan, 2019). |
198 | Agents that inhibit membrane fusion have been shown to block the induction of long-term potentiation (LTP) (Lledo et al., 1998). | It is important to clarify the cellular location at which these agents exert their effects and to explain the mechanism by which they block LTP. | The substantial energy applied during LTP stimulation is expected to induce inter-neuronal and inter-spine fusion. However, when membrane fusion blockers are introduced, this fusion is inhibited, preventing the induction of LTP (Vadakkan, 2019). |
199 | There is loss of dendritic spines during LTP induction (Yuste & Bonhoeffer, 2001). | A mechanistic explanation is required to understand the loss of dendritic spines when high energy is applied during LTP stimulation. | High-energy stimulation during LTP induction results in the formation of numerous non-specific inter-postsynaptic functional links (IPLs). Additionally, high energy can lead to IPL fusion, which triggers mechanisms to prevent the mixing of cytoplasmic contents. If the fusion pores cannot be reversed, the neuron will remove dendritic spines as a protective response, thereby preventing further cellular damage. |
200 | The CA2 region of the hippocampus is resistant to LTP induction; however, the removal of perineuronal net proteins from this area facilitates the induction of LTP (Carstens et al., 2016). | The cellular mechanism underlying LTP induction must account for how perineuronal net proteins inhibit LTP, as this may offer insights into a structural explanation of LTP. | According to the semblance hypothesis, any factor that prevents the formation of inter-postsynaptic functional links (IPLs) will block the induction of LTP. Perineuronal net proteins surround the spine head region (Dansie & Ethell, 2011). Removal of these proteins can facilitate IPL formation, which offer a potential explanation for this mechanism (Vadakkan, 2019). |
201 | Varying strengths of LTP can be induced at different brain regions where inputs converge with differing densities. The hippocampus, which integrates inputs from multiple sensory modalities, exhibits the highest levels of long-term potentiation (LTP). | It should be possible to explain why the strength of LTP is greater at sites where a higher number of inputs converge. | According to the semblance hypothesis, a higher number of inter-postsynaptic functional links (IPLs) are expected to form at sites where multiple inputs converge (Vadakkan, 2010; 2013). At these locations, the increased density of abutting dendritic spines from different input pathways facilitates the formation of a proportionally greater number of non-specific IPLs, which are implicated in the induction of long-term potentiation (LTP)(Vadakkan, 2019). |
202 | LTP is associated with the enlargement of dendritic spine heads (Lang et al., 2004). Experiments inducing LTP at individual spines have demonstrated corresponding spine enlargement (Matsuzaki et al., 2004). | It is essential to provide an explanation for how spine enlargement leads to long-term potentiation (LTP)—one that accounts for all key features of LTP and its correlation with learning, particularly in an interconnected and associative manner. | Spine enlargement facilitates the formation of inter-postsynaptic functional links (IPLs). Under high-energy stimulation conditions used to induce LTP, a large number of non-specific IPLs are generated. These IPLs enable a regular stimulus to propagate through multiple alternate pathways, allowing signals to summate and reach the recording electrode with enhanced strength (Vadakkan, 2019). |
| 203 | LTP, kindling, and seizures are closely interrelated phenomena. | A relationship between structure, function, and pathology exists, requiring interconnected explanations to account for these interactions. | The IPL mechanism, as proposed by the semblance hypothesis, provides an interconnected framework for understanding these processes. The formation of non-specific IPLs is expected in response to high-energy stimuli during LTP, kindling, and seizures. Pathological conditions that lead to membrane instability, increased neuronal excitability, and ionic imbalances further amplify these changes (Vadakkan, 2019). |
204 | LTP induction is associated with the redistribution of AMPA receptor subunits from the cytoplasm to the membrane of the spine head region (Shi et al., 1999; Passafaro et al., 2001). | It is essential to demonstrate the functional significance of movement of vesicles containing AMPA receptors to the spine membranes, in a way that aligns with other findings in an interconnected manner. | It has been shown that the exocytosis of vesicles containing AMPA receptor subunits is linked to their lateral movement during LTP (Park et al., 2006). |
| 205 | LTP induction requires high-energy stimulation, which can be delivered either through high-frequency or high-intensity protocols. | An explanation is needed for how this high-energy stimulation triggers cellular changes that lead to the generation of LTP. The correlation between the ability to learn and the strength of LTP induction calls for an understanding of LTP as a scaled-up change that occurs during learning. | LTP can be explained as a scaled-up change that occurs during learning through the formation of a large number of non-specific IPLs between the stimulating and recording electrodes (Vadakkan, 2019). This process requires high energy, as the removal of the hydration layer between spine membranes—necessary for IPL formation—demands significant energy. This inference is supported by experiments using artificial membranes (Rand & Parsegian, 1984; Martens & McMahon, 2008; Harrison, 2015). |
| 206 | LTP requires the specific postsynaptic fusion protein SNARE (Jurado et al., 2013). | It is essential to describe the specific properties of this protein that enable it to elicit LTP. | The SNARE protein has the ability to bring together repulsive membranes and overcome the energy barriers associated with curvature deformations during hemifusion (Martens & McMahon, 2008; Olkers et al., 2016). It generates the force necessary to pull abutted membranes together as tightly as possible (Hernandez et al., 2012). The t-SNARE protein syntaxin plays a crucial role in generating local membrane trafficking within spines and directing membrane fusion (Kennedy et al., 2010). |
207 | LTP induction is possible, even after blocking NMDA receptors, by increasing postsynaptic Ca²⁺ levels through voltage-sensitive calcium channels (Grover and Tayler, 1990; Cavuş and Teyler, 1996). | A mechanistic explanation is needed to provide an interconnected framework for understanding how LTP can be induced by stimulating postsynaptic terminals (spines) alone. | The formation of IPLs can occur by stimulating the abutted postsynaptic terminals (spines) alone. Therefore, even after blocking NMDA receptors, an increase in postsynaptic Ca²⁺ levels is sufficient to induce LTP (Vadakkan, 2019). |
208 | Blockade of the exocytosis of vesicles containing AMPA receptors results in a significant reduction in LTP (Kennedy et al., 2010; Ahmad et al., 2012). | A logical explanation is necessary to clarify how the exocytosis of vesicles containing AMPA receptors is mechanistically linked to the induction of LTP. | Tetanic stimuli that induce LTP lead to both AMPA receptor insertion & generalized recycling of membrane segments from endosomes that contain GluR1 AMPA receptor sub-units (Park et al., 2006). It was shown that majority of AMPARs incorporated into synapses during LTP is from lateral diffusion of spine surface receptors containing GluR1 (Makino and Malinow, 2009). Vesicle membrane segments arriving at the lateral spine margins reorganize the membrane at this region and can facilitate the formation of IPLs. |
209 | The only conditions under which LTP was impaired were those with markedly decreased AMPA receptor surface expression (Granger et al., 2013). | A logical explanation is necessary to clarify how the surface expression of AMPA receptor subunits is linked to the formation of inter-postsynaptic functional links (IPLs). | LTP induction leads to both AMPA receptor insertion & generalized recycling of membrane segments from endosomes that contain GluR1 AMPA receptor sub-units (Park et al., 2006). It was shown that majority of AMPARs incorporated into synapses during LTP is from lateral diffusion of spine surface receptors containing GluR1 (Makino and Malinow, 2009). Vesicle membrane segments arriving at the lateral spine margins can reorganize the membrane at this region and facilitate the formation of IPLs. |
| 210 | Potentials recorded following LTP stimulation do not exhibit a ramp-like increase before reaching their peak. | The sudden rise to a peak-potentiated effect following a delay requires a suitable mechanistic explanation. | The high energy delivered during LTP induction causes the enlargement of dendritic spines, which facilitates the time-dependent formation of inter-postsynaptic functional links (IPLs). Initially, small islets of interlinked spines form within the field but do not yet establish a direct connection to the recording electrode. These islets are most likely to form initially near the stimulating electrode, where the highest energy is delivered. During this intermediate stage, the recording electrode is unlikely to detect summated inputs, which would result in ramp-like changes. Over time, these small islets of interlinked spines coalesce into larger islets, leading to mega-summation of potentials that are transmitted through multiple pathways to the recording electrode. This can explain the sudden, amplified responses, after a delay, observed during LTP (both field & patch clamping) (Vadakkan, 2019). |
211 | The persistence of the potentiated effect over a long duration led to the term long-term potentiation (LTP). | A mechanistic explanation is needed to account for the prolonged duration of the potentiated effect once LTP is induced. | The high energy associated with LTP stimulation is likely to induce membrane fusion at regions where IPLs are formed. Due to the significant energy involved, it is difficult for these multiple fusion sites to reverse. This contrasts with the formation of IPLs during natural learning, where the changes occur at much smaller scales, typically on the order of a few nanometers. In these cases, most IPLs are reversible. |
212 | LTP induction is associated with the lateral movement of vesicles containing AMPA receptor subunits (Makino & Malinow, 2009). However, high-energy stimulation alone can bypass this requirement, directly inducing LTP even in the absence of such receptor trafficking (Herring & Nicoll, 2016). | It is essential to provide a coherent explanation for two key questions: (a) What is the functional role of the vesicles containing AMPA receptor subunits? and (b) How can the application of high energy stimulation overcome the apparent requirement for their trafficking? This represents a unique scenario—only by arriving at the correct mechanistic understanding can a suitable and unified explanation be achieved. | The formation of inter-postsynaptic functional links (IPLs) requires overcoming a significant energy barrier (Rand & Parsegian, 1984; Martens & McMahon, 2008; Harrison, 2015). One way this barrier can be overcome is through spine enlargement. This process is supported by the addition of membrane segments to the lateral regions of dendritic spines, a phenomenon observed following LTP induction (Park et al., 2006). Alternatively, high-energy stimulation—known as electrofusion—can also facilitate intercellular membrane fusion. This principle is employed in the fusion of B cells with myeloma cells to produce hybridomas (Zimmermann & Vienken, 1982; Greenfield, 2019). |
213 | A sudden drop in the peak-potentiated effect is referred to as short-term potentiation (STP) (STP) (Racine et al., 1983). | It is necessary to identify the mechanism responsible for the rapid reversal observed immediately after peak potentiation is reached. At least one underlying factor must be reverting quickly, leading to the phenomenon of STP. | Exclusion of hydration from the space between membranes is a high-energy demanding process, and the hemifusion state is known to be highly reversible (Chernomordik & Kozlov, 2008). Therefore, immediately following LTP induction, many IPLs are likely to revert due to the instability of the hemifused state, contributing to the sudden drop in the potentiated effect observed as short-term potentiation (Vadakkan, 2019). |
214 | Synapses and synaptic transmission are essential for the induction of LTP when stimulation is applied from the presynaptic side. | An operational mechanism that functions concurrently with synaptic transmission is necessary to fully explain the induction and expression of LTP. | When LTP stimulation is applied to the presynaptic side and recorded from the postsynaptic side, normal synaptic function is essential for inducing LTP. Additionally, the enlargement of postsynaptic terminals (spines) leads to the formation of IPLs, which redirect potentials generated by regular stimuli towards the recording electrode through multiple pathways following LTP induction. Therefore, synapses are critical for LTP induction when stimulated from the presynaptic side and recorded from the postsynaptic side. Similarly, the formation of IPLs during learning also requires synaptic function to operate normally (Vadakkan, 2019). |
215 | Non-Hebbian plasticity changes are observed during the induction of LTP (Schuman & Madison, 1994; Bonhoeffer et al., 1989; Kossel et al., 1990; Engert & Bonhoefferet, 1997). | It is necessary to explain why synapses that are not directly stimulated also become involved during LTP induction. | When a group of spines expands, it compresses the extracellular matrix around them and the abutted spines that were not directly stimulated by LTP. This compression can lead to the formation of IPLs with those neighboring spines, providing an explanation for the occurrence of non-Hebbian plasticity during LTP induction (Vadakkan, 2019). |
216 | Following LTP induction, the field EPSP amplitude increases by 200%, which is significantly greater than the 60% increase observed in the EPSP amplitude recorded from a single CA1 neuron (Abbas et al., 2015; Holmes & Grover, 2006). | The difference in EPSP amplitudes between these two cases requires an explanation. | In field recordings, since the electrode is placed in the extracellular matrix (ECM), it captures the summation of potentials from a large number of overlapping input pathways (IPLs) in the surrounding region. In contrast, when recording from a single CA1 neuron, the detected potentials primarily reflect inputs from the IPLs generated by its own dendritic spines (Vadakkan, 2019). |
217 | During LTP induction, only a fixed fraction of stimulated presynaptic terminals directly synapse onto the recorded CA1 neuron. LTP induction requires cooperative interactions between the directly stimulated presynaptic terminals and the spines of the recorded CA1 neuron; without such synergy, LTP fails to occur. | The cooperative mechanism enabling detection of potentiation at the recording electrode likely involves complementary pathways beyond NMDA receptor activation. While Mg²⁺ blockade of NMDA receptors (Kauer et al., 1988) was insufficient to prevent this effect, alternative routes may mediate the cooperative integration necessary for observable potentiated effect. | The semblance hypothesis posits that LTP-induced IPLs create a cooperative network that distributes synaptic signals, enabling detection at recording electrode even when traditional synaptic plasticity mechanisms are blocked. Formation of large number of IPLs connects between the directly stimulated presynaptic terminals and the spines of CA1 neuron from which recording is carried out through thee IPLs (Vadakkan, 2019). |
218 | A characteristic of LTP induction is its associative nature, whereby a weak synaptic input can be potentiated when activated in conjunction with a strong tetanic stimulus applied to a separate but convergent input pathway (Levy & steward, 1979). | It is necessary to explain what new connection occur during this procedure that will later allow the weak input to bring potentiated effect at the recording electrode. | The convergent nature of the inputs enables distinct clusters of interlinked spines—activated by both weak and strong stimuli—to become connected through the formation of inter-postsynaptic links (IPLs). This connectivity allows both clusters to interface with the recording CA1 neuron. As a result, the weak input can propagate through multiple pathways and reach the recording electrode in a summated form (Vadakkan, 2019). |
| 219 | Input specificity in LTP induction (Andersen et al., 1977): A strong stimulus is capable of inducing long-term potentiation (LTP), whereas a weak stimulus alone cannot. However, weak inputs that are active concurrently with the strong stimulus can share in the potentiation induced by the stronger input. | A mechanistic explanation is needed for the process by which simultaneous activation of both weak and strong stimuli enables the weak stimulus to exhibit a potentiated effect later. | The simultaneous application of strong and weak stimuli at optimal spatial distances is essential to induce IPLs between distinct islets of interlinked spines and the individual spines targeted by the weak stimulus. This occurs because the strong stimulus leads to the enlargement of a large number of spines, thereby increasing the likelihood that some of them will form IPLs with the spines activated by the weak stimulus. As a result, the weak stimulus can propagate through the IPL network established by the strong stimulus and ultimately reach the recording electrode, producing a potentiated effect later (Vadakkan, 2019). |
220 | Learning can be occluded following LTP induction, and conversely, LTP can be occluded after learning (Moser et al., 1998; Whitlock et al., 2006). | A mechanistic explanation is needed to account for the shared mechanisms underlying both LTP induction and learning. | LTP induction results in the formation of a large number of IPLs within a localized region. As a result, learning that follows LTP induction will be unable to generate new IPLs at that site. During memory retrieval, as the cue stimulus propagates through the extensive network of non-specific IPLs formed by LTP, it gives rise to a large number of non-specific semblances. This accounts for the significantly reduced memory observed in these experiments (Vadakkan, 2019). |
221 | Dopamine enhances both motivation-driven learning (Bromberg-Martin et al., 2010) and LTP (Otmakhova & Lisman, 1996). | It is essential to demonstrate that both learning and LTP share a common underlying mechanism, with dopamine enhancing both processes through this same mechanism. | The augmentation of both motivation-enhanced learning and LTP can be explained by the enlargement of spines induced by dopamine (Yagishita et al., 2014), which in turn facilitates the formation of IPLs (Vadakkan, 2019). |
222 | Most learning-related changes are short-lived, typically giving rise to only working memories, whereas LTP is long-lasting, enduring for hours. | A mechanistic explanation is needed to understand why learning changes are rapidly reversible, while the larger-scale changes associated with LTP are resistant to reversal. | Most IPLs are reversible because their formation during learning, which involves the exclusion of the hydration layer between spine membranes, is an energy-intensive process. In contrast, LTP stimulation consumes a significantly higher amount of energy, during which physiological changes in IPLs are expected to progress to membrane fusion, thereby conferring resistance to reversal (Vadakkan, 2019). |
223 | NMDA receptor inhibitors do not reverse the maintenance of late-phase LTP (Day et al., 2003). | A change that is maintained during the late stage of LTP cannot be reversed by inhibiting NMDA receptors, suggesting that mechanisms beyond NMDA receptor activation are involved in the long-term maintenance of LTP during this phase. | High-intensity stimulation during LTP induction leads to IPL fusion changes in most of the non-specific IPLs formed. The stably maintained fused IPLs are likely responsible for the late phase of LTP and are resistant to reversal. As a result, NMDA receptor inhibition has no role in the maintenance of LTP (Vadakkan, 2019). |
224 | Both LTP decay and memory loss are mediated by the endocytosis of AMPA receptors (Dong et al., 2015). | It is essential to explain how AMPA receptor endocytosis can reverse the changes induced by LTP. | The endocytosis of AMPA receptor subunits, which utilizes membrane segments from the lateral regions of spines, is expected to reduce spine size and consequently lead to the reversal of IPLs. This process provides a plausible explanation for LTP decay (Vadakkan, 2019). |
225 | GluA1 subunits play a key role in trafficking AMPA receptors to the cell surface, a process that is closely associated with both LTP and fear memory (Rumpel et al., 2005). | A mechanistic explanation is needed for how the insertion of GluA1 subunits into dendritic spines facilitates both LTP and learning. | GluA1-containing AMPA receptors are positioned approximately 25 nm from the synaptic margins, in the lateral regions of the spine head where IPLs are expected to form (Jacob & Weinberg, 2015). As these subunits are delivered to the surface via vesicular trafficking, they contribute membrane segments to this region, thereby facilitating IPL formation. According to the semblance hypothesis, IPL formation underlies both learning and LTP induction. |
226 | An increase in the amplitude of miniature EPSPs (mEPSPs) following LTP induction (Manabe et al., 1992). | The amplitude of mEPSPs is believed to be influenced by an increase in the number or functional efficacy of AMPA receptors (Malenka & Nicoll, 1999). Therefore, it is essential to identify the source of the enhanced AMPA-mediated current. | The recording electrode is electrically connected to abutted spines through inter-postsynaptic links (IPLs), allowing current from interlinked spines—primarily originating from different neurons—to contribute to the recorded signal. The additional current arriving from interlinked spines across the IPLs is responsible for the observed increase in mEPSP amplitude (Vadakkan, 2019). |
227 | Several delayed changes following LTP induction have been correlated with learning and memory—for example, the phosphorylation of AMPA receptor subunits by CaMKII (e.g. CaMKII phosphorylating AMPA receptor subunits (Lisman et al., 2012). | Clarifying how delayed changes following LTP contribute to an animal's learning ability is crucial for understanding the cellular basis of memory formation. | The downstream cascade of biochemical changes within neurons can be interpreted as preparatory steps that enable spines to both stabilize existing inter-postsynaptic links (IPLs) and form new IPLs during future learning events. |
228 | LTP induction is known to modify specific sets of place cells; in particular, LTP in hippocampal pathways can abolish existing place fields and establish new ones (Dragoi et al., 2003). | A mechanistic explanation is needed to clarify how the changes induced by LTP affect the firing patterns of place cells, specifically CA1 neurons in the hippocampus. | The formation of a large number of new IPLs induced by LTP can facilitate the propagation of potentials through these links, leading to the activation of additional postsynaptic CA1 neurons (Vadakkan, 2016). |
229 | Small spines have been identified as preferential sites for the cellular changes associated with LTP induction (Matsuzaki et al., 2004). | It is important to explain which specific characteristics of small spines, as compared to large spines, contribute to their role in LTP induction. | Large spines are likely to have already formed IPLs with adjacent spines, making them less likely to form additional IPLs during LTP induction. In contrast, small spines have the capacity to expand in response to LTP stimulation, enabling the formation of several new IPLs, which contribute to the potentiated effect. |
230 | Associative LTP can be more readily induced in newly formed granule neurons (Schmidt-Hieberet al., 2004). | This phenomenon has been attributed to a reduction in the threshold for inducing LTP, suggesting that new neurons lack certain ion channels. It is crucial to demonstrate that LTP induction can lead to the expression of these channels in newly formed neurons. | This can be explained by the formation of multiple IPLs between the spines of new granule neurons—compared to older neurons—and the spines on pre-existing islets of inter-LINKed spines in established granule neurons (Vadakkan, 2016). |
231 | Fear conditioning induces associative LTP in the amygdala (Rogan et al., 2007; McKernan & Schinnick-Gallagher, 2007). | It is essential to explain how learning induces a potentiated effect at the synaptic region between MGN-LA neurons when recordings are made from LA neurons. In other words, it is important to demonstrate how fear conditioning alters auditory conditioned stimulus (CS)-evoked responses in the LA in a manner similar to LTP induction. | According to the semblance hypothesis, LTP can be explained by the formation of numerous IPLs between spines from different dendritic branches, primarily from different LA neurons, although occasionally from branches of the same neuron. Given that there is only one motor output (foot shock), the latter condition is likely more common in LA during fear conditioning foot shock experiments. |
232 | Dendritic spikes a) mediate a stronger form of LTP that necessitates the spatial proximity of associated synaptic inputs (Hardie & Spruston, 2009), b) serve as a mechanism for cooperative LTP (Golding et al., 2002), and c) are essential for single-burst LTP (Remy & Spruston, 2007). | One of the requirements for LTP is postsynaptic depolarization, which can result from large EPSPs that trigger dendritic spikes (Hardie & Spruston, 2009). Dendritic spikes induce a stronger form of LTP compared to alternative mechanisms (Hardie & Spruston, 2009). In this context, it is crucial to identify the source of the potentials that contribute to the generation of large EPSPs. | The simultaneous arrival of input signals to two or more synapses, whose spines (postsynaptic terminals) are inter-LINKed, leads to the summation of EPSPs, resulting in large EPSPs recorded from any single postsynaptic terminal (Vadakkan, 2016). When large number of spines are inter-LINKed to form an islet of inter-LINKed postsynaptic terminals (IILPs), it can mediate stronger LTP. Hence, large IILPs are most likely responsible for dendritic spikes. |
233 | A modified fear conditioning study involving two associative learning events with one common stimulus demonstrated inputs synapsing onto a single type of output neuron—Lateral Amygdala (LA) neurons (Abdou et al., 2018). Stimulation of autophagy in LA neurons following one learning event erased the memory. Optical LTP enabled anisomycin-treated mice to fully recover from this amnesia. | It is essential to explain how the stimulation of autophagy within postsynaptic LA neurons leads to the erasure of memory from a specific associative learning event, with inputs arriving through axonal terminals that synapse onto these LA neurons. Since the mechanism of storage is not reversible by a protein synthesis inhibitor, a non-protein-dependent mechanism must be explained. | According to the semblance hypothesis, during learning, an IPL is generated between the spines of different LA neurons. When the motor output function is the same, IPLs can also form between spines from different branches of the same LA neuron. Stimulation of autophagy in LA neurons triggers increased endocytosis, which removes membrane segments from the lateral spine head region. This process reduces the spine size enough to reverse the newly formed IPLs generated by learning. After autophagy is induced, membrane segments are recycled back to the spine heads to some extent, allowing many spines to re-abut. Optical LTP provides a substantial energy boost to the input terminals, sufficient to generate IPLs in the abutted spines, and also promotes spine expansion, further facilitating IPL formation. |
| 234 | In the study by (Abdou et al., 2018), using modified fear conditioning experiments, optical LTD led to the loss of memory associated with a specific learning event. Optogenetic stimulation of axonal terminals from AC and MGN neurons did not induce freezing in animals subjected to LTD. | Optical LTD erases specific associative learning changes. These changes cannot be reinstated by optical stimulation of the axonal terminals of AC and MGN neurons. | Modest depolarization used in LTD induces AMPAR endocytosis (Malenka,1994), which removes membrane segments from the lateral spine head regions, leading to the reversal of formed IPLs. This process results in the loss of memory for a specific event. Following LTD induction, ordinary stimulation of input terminals cannot facilitate memory retrieval due to the lack of IPLs because: a) LTD is typically long-lasting, maintaining the reversed IPLs in a non-LINKed state, and b) ordinary optogenetic stimulation lacks sufficient energy to promote spine expansion to the level required for IPL formation. |
Abbreviations AC: Audiory cortex ECM: Extracellular matrix (matrix between brain cells) EPSP: Excitatory postsynaptic potential FLE: Flash-lag effect HAT: Histone acetyltransferase IILPs: Islets of inter-LINKed spines IPL: Inter-postsynaptic functional LINKs (Inter-spine LINKs). These do not occur between adjacent spines on a dendritic branch LA: Lateral amygdala LINKs: Written in capital letters to show their significance LTD: Long-term depression LTP: Long-term potentiation MGN: Medial geniculate nucleus MSN: Medium spiny neuron NAc: Nucleus accumbens PDS: Paroxysmal depolarization shift | |||
Foot note 1: When presented with a set of colors, each paired with a corresponding image, and given just one second to learn the associations, most individuals can successfully form two or more connections in that brief interval. This suggests that associative learning can take place within mere milliseconds. But what kind of change can occur in such a short span of time? | |||
Table 2. The system exhibits a large number of features across multiple levels, each of which must be explained in an interconnected manner through a unifying solution. Since all observations have been made in relation to behavior, the system can initially only be solved at the behavioral level. The constraints imposed by these findings prompt the central question: What fundamental mechanism can satisfy all of these requirements? It is crucial to recognize that the empirical findings are highly diverse, yet the constraints they impose are so stringent that only a single, unique solution is likely to exist—one that must be consistent with all prior experimental evidence. Each observation contributes specific constraints that narrow the range of viable explanations, guiding us toward the correct solution. A subset of these observations can be used to derive this solution, while the remaining features serve to test and validate it. Given that both learning and memory retrieval occur on the order of milliseconds, candidate mechanisms that operate too slowly—such as certain biochemical reactions or molecular storage processes—can be ruled out. Once a solution explaining behavior is identified, it can be further examined for properties that might give rise to first-person phenomena—inner sensations that precede and accompany behavior. Since the system relies on a finite number of neurons and muscles, yet must support a vast array of first-person experiences and motor actions such as speech and behavior, the underlying mechanism is expected to consist of unitary processes whose integration gives rise to both subjective experiences and observable actions. Once the fundamental mechanism is established, the next step is to uncover the principles governing the integration of these units—both of inner sensations and of motor outputs—where mathematics is expected to play a central role. | |||
A complete understanding of the operational mechanism underlying first-person properties can only be achieved by conducting the gold-standard test: replication in engineered systems. While replicating motor activities such as speech in behaviorally equivalent machines may appear sufficient, the task remains incomplete until the subjective, first-person aspects of the mind are also fully understood. One of the central engineering challenges in this endeavor lies in developing methods to translate internally accessible sensations into observable and measurable outputs. This requires both computational modeling and experimental engineering efforts to implement and test theoretically plausible mechanisms. The ability of a proposed mechanism to explain brain functions from both first-person (subjective) and third person (objective) perspectives qualifies it as a testable hypothesis. This work emerged from a deep curiosity to uncover the underlying order within the brain’s seemingly complex functions. In pursuing this goal, I have taken some liberty in proposing a novel foundational principle to help piece together the broader puzzle. This effort would not have been possible without the vast body of rigorous research produced by many scientists over the years. Although the current hypothesis aligns with experimental data across multiple levels, it must be regarded as provisional until it has been thoroughly tested and validated.
Video presentations
1. A testable hypothesis of brain functions
2. How to study inner sensations? Examples from mathematics
4. List of third-person findings and the derivation of the solution for the nervous system
6. Induction of units of inner sensation
8. Potential mechanism for neurodegeneration
9. LTP: An explanation by semblance hypothesis
10. A framework for consciousness
11. A potential mechanism of anaesthetic agents
12. Conditioned learning explained using a video
The challenge: "What I cannot create (replicate), I do not understand" – Richard Feynman. We must approach the task of understanding the nervous system with the rigor required to replicate its mechanisms in an engineered system. Everything else will follow from that foundation.
The optimism: “What are the real conditions that the solution must satisfy?” If we can get that right, then we can try and figure out what the solution is" – Murray Gell–Mann
The hope: We will give our utmost effort. Together, we will explore and uncover it!