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 independently and in conjunction with third-person observable motor actions like speech and behavior.
Dedication: To all those who suffer from disorders of the brain—and therefore the mind—especially those who have been abandoned by their families.
Latest pre-print: Fear conditioning experiments have provided large number of disparate findings. Specific features from them are used to synthesize a testable mechanism for the memory engram. Findings from several recent modified classical fear conditioning experiments have constrained the operational mechanism further to understand more about the engram. PrePrint
What are the present challenges in brain sciences?
There are still many questions in neuroscience that scientists haven’t figured out yet (Adolphs, 2015), and these questions come from different parts of the brain’s activity (Edelman 2012; Gallistel & Matzel 2013). Since information only makes sense when it’s connected to a system and its situation (Brette 2018; Deacon 2021), and because it is always changing, scientists believe the “engram” — the brain’s memory trace — should also have these qualities. It’s also expected that engrams are made up of physical parts in the brain that carry information (Galllistel, 2021). That means we need to understand how these parts change when we learn something. Researchers are now working to understand how changes in brain cell activity and connections during learning and memory could explain how the brain stores information (O’Sullivan & Ryan, 2024). A good theory about memory should help interconnect all the different research from different parts of the brain (Frégnac, 2017). Finally, scientists think the engram should work like something that has evolved naturally over time to help us survive.
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.
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.
It is possible to derive constraints from numerous findings across various levels of the nervous system. Only by reaching the correct solution will we be able to explain all of these findings. Even if we cannot directly perceive the formation of first-person inner sensations, interconnected explanations offer insights into their location and the mechanism behind their formation. Several of the following explanations provide retrodictive evidence. (Here is a demonstration of how constraints can be used to find a solution: pdf) | |||
| Findings from multiple levels | Constraints provided by the findings (on the left) that guide the inquiry toward the correct solution. | Explanations: It is important to note that all explanations must be interconnected in order to claim we have found a solution (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 inter-postsynaptic functional LINK (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 sof tructural remodeling was proposed to be a cellular basis of learning and memory (Yuste & Bonhoeffer, 2001). | Certain specific mechanical changes are expected to explain the cellular basis of learning and memory. | Simultaneous activation of two synapses whose spines (postsynaptic terminals) are abutted to each other can lead to IPL formation spontaneously. Even though high energy is needed to displace the hydration layer between abutted spines, certain molecular events are expected to overcome this energy barrier while maintaining specificity (Vadakkan, 2019). |
| 52 | Several seizures spread laterally to the adjacent cortices. Focal seizures manifest Jacksonian march (both sensory and motor). | The cellular mechanism responsible for seizures should be capable of explaining the lateral spread. | Seizures are explained as rapid chain generation of IPLs in the cortex (Vadakkan, 2016). This explains how sensory, and motor features propagate from one sensory area to the next in the order in which they are represented in the homunculus (sensory & motor). |
| 53 | Several seizures are associated with different hallucinations. | It should be possible to explain how seizure activity reaches different sensory cortices and triggers inner sensations of sensory stimuli in their absence. | Lateral spread of seizures through rapid formation of IPL mechanism explains inner sensation of perception of various sensations (Vadakkan, 2016). |
| 54 | Pathological changes of amyotrophic lateral sclerosis (ALS) spreads laterally. | It is necessary to provide an explanation how certain alterations from the normal operational mechanism aid in the lateral spread of neurodegenerative changes in ALS. | IPL formation is a spectrum of inter-membrane changes. IPL structural stability remains only till the stage of inter-spine membrane hemifusion. Any alterations of membrane structure, or viral fusion proteins can lead to membrane fusion leading to laterally spreading pathological changes of spine loss and eventual neuronal loss as observed in ALS (Vadakkan, 2016). |
| 55 | Transfer of injected dye from one CA1 neuron to the neighboring CA1 neurons is observed in animal models of seizures (Colling et al., 1996). | CA1 neurons are located lateral to each other in the CA1 region of hippocampus. Hence, it is necessary to explain a physical path between laterally located CA1 neurons through which dye can spread. | Increased excitability and lateral spread of potentials across the IPLs can lead to the pathological conversion of IPLs (maximum allowed interactive state is inter-membrane hemifusion) to membrane fusion between spines that belong to to different neurons (Vadakkan, 2016). This explains dye spread between neurons. |
| 56 | Loss of dendritic spines after kindling, during seizures and following LTP induction. | It must be possible to explain a mechanism that causes loss of spines after kindling, during seizures and LTP induction in an interconnected manner. It is also necessary to find certain benefits that the neurons obtain by loss of spines. | Inter-neuronal inter-spine fusion can lead to mixing of cytoplasmic contents between 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. This is to protect their neurons from further damage (Vadakkan, 2016). |
| 57 | CA2 area of hippocampus is resistant to seizures. | It is necessary to explain a mechanism for seizures using constraints from the findings offered by the disorder & then provide a specific property of CA2 area that enables to resist seizures in that region. | Based on the semblance hypothesis, anything that prevents formation of IPLs blocks induction of LTP (see inter-connected explanation why CA2 region is also resistant to LTP induction). Perineural net proteins around the spine head region (Dansie & Ethell, 2011) can resist IPL formation between spines of different neurons, which provides an explanation (Vadakkan, 2016; Vadakkan, 2019). |
| 58 | 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). |
| 59 | Anesthetic agents alleviate seizures. | Mechanism of action of anesthetic agents should be able to explain how seizure generation and propagation are stopped by anesthetic agents. | Anesthetic molecules increase the number of IPLs that will inter-LINK several islets of already inter-LINKed spines. This increases the magnitude of the horizontal component of oscillating potentials severely reducing the frequency of oscillating extracellular potentials. This prevents both inner sensations and motor actions (Vadakkan, 2016). |
| 60 | Memory impairment in patients with seizure disorders (Mazarati, 2008). | It is necessary to explain how the mechanism of learning, memory retrieval and behavioral motor actions are impaired by the mechanism of seizures. | Seizure pathology involves rapid formation of several non-specific IPLs, and IPL fusion between spines leading to spine loss and even loss of neurons. Formation of non-specific IPLs, spine & neuronal loss contribute to reduction in the number of specific IPLs needed from cognitive functions (Vadakkan, 2016). |
| 61 | Intracellular electro-physiological correlate of epileptiform activity is paroxysmal depolarizing shift (PDS), which is a giant excitatory postsynaptic potential (EPSP) (Johnson & Brown, 1981). | A mechanistic explanation is needed for generation of a giant EPSP at the dendritic spine area during a seizure. It has a propensity to propagate laterally to other cortical regions. Need a mechanistic explanation. | Results strongly indicate that a large EPSP is formed through a postsynaptic mechanism (Johnson & Brown, 1981). Since PDS has a maximum voltage of 50 mV & since distal dendrites normally produce EPSP with an amplitude over 10 mV (Spruston, 2008), spatial summation of several of these EPSPs is a feasible mechanism to explain the PDS. IPL formation between spines of different neurons can provide an explanation for PDS in seizures (Vadakkan, 2016). |
| 62 | Though simultaneous reduction in Ca2+ & elevation in K+ in the ECM space during seizure can prevent action potential propagation along the axon (Seignuer & Timofeev, 2011), seizures continue in status epilepticus. | It should be possible to provide an alternate route through which spread of seizure activity takes place. Since PDS is a giant EPSP, it is necessary to explain how such giant EPSPs continue to get generated and spread. | Formation of large number of non-specific IPLs between abutted spines of different neurons provides an alternate route that can favor summation of EPSPs & also provide a route through which PDS-like activity can propagate throughout the cortex (Vadakkan, 2016). |
| 63 | Cell swelling is observed during "spreading depression" phase of seizures (Kempski et al., 2000; Olsson et al., 2006; Colbourn et al., 2021). | It is necessary to explain cell swelling as a cause or effect of seizure associated changes (either prior to seizures or as a result of it). | Enlargement of dendritic spines is expected to compress and even displace the hydration layer of ECM between the spines. This can favor formation of non-specific IPLs, especially when additional factors that favor seizure generation are present. |
| 64 | Ketogenic diet is used to prevent seizures (Martin-McGill et al., 2020; Kossoff et al., 2021). Ketogenic diet increases serum concentration of long chain polyunsaturated fatty acids (LC-PUFA) (Anderson et al., 2001; Fraser et al., 2002). | It is necessary to provide an inter-connected explanation how LC-PUFA can alter the key cellular structures and prevent seizures. | Membrane lipid composition remain optimal when the dietary n-3 PUFA is more than 10% of total PUFA (Abbott et al., 2012). One possible explanation is that LC-PUFAs in the ketogenic diet or their modified forms gets incorporated as side chains on the lipid membrane triglyceride backbone, blocking formation of non-specific IPLs between spine membranes and prevent seizures (Vadakkan, 2016). |
| 65 | Seizure disorders are associated with neurodegenerative changes (Farrell et al., 2017). | It is necessary to provide an explanation how seizures lead to neurodegeneration. | Seizure disorder can be explained as rapid chain formation of IPLs in the cortex. Even though IPL changes are limited only up to the hemifusion stage, changes in cell membrane composition & frequency of repetition of seizures can lead to IPL fusion. When cytoplasms of different neurons mix, it can lead to spine loss & neuronal loss (Vadakkan, 2016). |
| 66 | Loss of consciousness during complex seizures. | It is necessary to provide a framework that generates first-person inner sensation of consciousness & explain how seizure activity leads to loss of consciousness. | Reactivation of a large number of IPLs in response to both internal & external cue stimuli generate background semblance responsible for the inner state of conscious state. Rapid chain generation of a large number of IPLs leads to induction of a large number of non-specific semblances that cause loss of conformation of semblance for consciousness (Vadakkan, 2016). |
| 67 | Multiple vertical sub-pial resections are found to alleviate seizures (Morrell et al, 1989). | Some structural connections are severed when vertical resections are carried out. Neurons are organized in six layers from the cortical surface to the interior aspect near the ventricles. So, it is necessary to explain what lateral connections are sectioned in this procedure. | Both recurrent collaterals and IPLs form horizontal connections. Cutting though the IPLs is expected to prevent IPL-mediated rapid chain lateral propagation of seizure activity (Vadakkan, 2016). |
| 68 | In status epilepticus (continuous seizures) anesthetics are used to obtain a state of "burst suppression" in the EEG. This is a state of lack of electrical activity for several seconds in between periods of high-voltage bursts of activity (Meierkord et al., 2010). | It is necessary to find a feasible explanation of how introduction of a state of "burst suppression" is achieved with anesthetics & this may aid in controlling seizures and preventing cortical damage due to status epilepticus. | Anesthetic agents are expected to induce rapid generation of large number of non-specific IPLs (reversible). Formation of very large number of IPLs is expected to form a very large horizontal component that will lead the oscillating extracellular potentials to flatten out to a straight line. This can explain a reversible state of “burst suppression”. This will reduce firing of downstream neurons and muscle contractions of seizures (Vadakkan, 2016). |
| 69 | Ictal (during seizure) & postictal characteristics in electroconvulsive therapy (ECT) & patients with generalized tonic-clonic seizures are essentially similar (Pottkämper et al., 2021). | Need an explanation how high energy used in old ECT procedures caused generalized convulsions. | High energy used in ECT will generate large number of non-specific IPLs. It was previously shown that seizures are generated by rapid chain formation of IPLs along the cortical synaptic regions (Vadakkan, 2016). |
| 70 | Electroconvulsive therapy (ECT) alleviates endogenous depression (Subramanian et al., 2022). This has been a standard of care for the last 70 years. | A mechanistic explanation for its effectiveness is needed. | Depression is a state of inner sensation of a depressed mood. It is reasonable to infer that net qualia of semblances from one or more brain regions are responsible for this. Very large energy provided to the cortical regions can lead to the generation of a large number of non-specific IPLs between abutted spines. This changes net semblance that leads to the inner sensation of depression. |
| 71 | There is short term memory loss following ECT using methods used before early 1980s (Duncan, 1949; Squire, 1977; Frith et al., 1983). Since the start of low energy ECT after 1990s, memory impairment reduced (Meeter et al., 2011). | A mechanistic explanation for this effect is needed. | Very large energy provided to the cortical regions can lead to the generation of a large number of non-specific IPLs between abutted spines. Hence, when a specific cue stimulus arrives, it will reactivate very large number of non-specific IPLs in addition to specific IPLs. This will lead to dilution of specific semblance needed to get generated for a specific memory. |
| 72 | Neurodegenerative disorders show loss of spines and neuronal death. | An explanation is needed for contiguous spread of pathology leading to spine loss and neuronal death. Causative factors should be acting at specific locations to explain all its features. | Changes in lipid membrane composition, viral fusion proteins, and other factors can lead to pathological progression of IPLs to a fusion state. This causes mixing of cytoplasms of two different cells that leads to removal of one or both spines. If at least one of the fused spines cannot be removed, it can progress to neuronal death (Vadakkan, 2016). |
| 73 | Dementia in neurodegenerative disorders. | Need an explanation for the role of spines in both generation of inner sensation of memory along with concurrent behavioral motor activity. | Loss of spines and neurons will lead to reduction in the number of specific IPLs that are necessary to generate specific units of inner sensations for a specific memory (Vadakkan, 2016). |
| 74 | Perception as a first-person inner sensation. | A variant or a modification of the mechanism of induction of inner sensation for memory should be able to explain first-person inner sensation of perception. | Explained by the special property of the IPL that it can be stimulated from its both sides by stimuli from two adjacent locations of an item to generate units of inner sensation of perception (Vadakkan, 2015). |
| 75 | Apparent location of the percept different from its actual location. | Matching explanations using the mechanism of induction of units of inner sensation are needed. | The inner sensation of percept is generated by the integral of all the units of perception (perceptons). Hence, the actual location of an object need not necessarily match the percept. This becomes clear when there is a medium that can shift the path of light towards the eye (Vadakkan, 2015). |
| 76 | Homogeneity in the percept of a stimulus arriving above the flicker fusion frequency. | A mechanism for fusion of separate inner sensations to generate uninterrupted continuous perception of a source of light arriving above the flicker fusion frequency. | Since units of perceptions (perceptons) from IPLs located at different regions in response to a single flicker are generated in a temporal pattern, perceptons from consecutive flickers overlap & generate a continuous percept (Vadakkan, 2015). |
| 77 | Perception of object borders. | A mechanistic explanation for the formation of first-person percept for object borders is needed. | The percept of a stimulus has to be generated from a stimulus at the borders of an object that reaches the brain. When perceptons formed from these stimuli integrate, they generate inner sensation of percept to generate boarder. Similarly, stimuli from outside the borders also do the same to generate a contrasting border of the background (Vadakkan, 2015). |
| 78 | First-person inner sensation of pressure phosphenes. | Mechanism of generation of first-person inner sensations is expected to provide an explanation for phosphenes triggered by pressure over the eyeball. | Stimulation of sensory paths anywhere along it before the locations of their convergence c (such as retina) an lead to reactivation of IPLs for generation of perceptons (Vadakkan, 2015). |
| 79 | Continued perceptions of moving objects without any interruptions. | It is necessary to explain how the percept is maintained the same while the object is moving. | The perception of a moving object depends on its speed & its distance from the eyes. Smooth pursuit of the eyeballs allows the stimuli to fall on either side of the same set of IPLs. Arrival of stimuli beyond this limit can be perceived as continuous when the perceptons are overlapped. When the object moves faster than certain limits, then it will trigger saccadic eyeball movements that will allow for continuity of the percept. |
| 80 | There are different types of perceptions such as vision and olfaction. | It is necessary to show evidence for the presence of a comparable neuronal circuity for two different sensations (if possible, in two different nervous systems). | Circuitry for perception was conjectured initially for vision in mammalian brains. It was possible to show the presence of a comparable circuitry for olfactory perception in the nervous system of the fly Drosophila (Vadakkan, 2015). |
| 81 | It is possible to discriminate two odorants sniffed at 60 milliseconds interval (Wu et al., 2024) | The mechanism of perception should be able to provide explanatory evidence to support this finding. | Perception occurs by rapid reversible formation of IPLs. After perception, IPLs reverse back immediately. This facilitates formation of different sets of IPLs with the arrival of the second odorant that will generate different perceptons to form inner sensation of perception of the second odor (Vadakkan, 2015). |
| 82 | Orientation tuning of a population of neurons in V1 before and after training on a visuo-motor task showed different sets of neurons responding (Failor et al., 2021). | Neurons that fire during associative learning change in the primary visual cortex varies with time. | Based on the semblance hypothesis, the primary mechanism of perception is not through the firing of a specific set of visual cortical neurons. Instead, perceptons are generated when two sides of an inter-LINKed spine is activated (Vadakkan, 2015). |
| 83 | Flash-lag effect (FLE) - When a flash is briefly presented in a specific location adjacent to the path of a uniformly moving object, the former is perceived to lag the latter. | Matching explanation using the mechanism of induction of units of inner sensation is needed. Needs to explain how perception is affected by relative time of arrival of a stimulus. | Explained based on the semblance hypothesis (Vadakkan, 2022). There is a delay of nearly 70ms from retina to perception (Lamme & Roelfesma, 2000). Of this, nearly 12ms can be attributed to synaptic delays in 5 synapses & conduction delay through neurons. The rest is attributed by IPL formation, reactivation, semblance formation & latter's integration. Continuous perception can use the already formed IPLs for perception, compensating for the delay. |
| 84 | A moving object that abruptly appears & starts to move is initially invisible for some distance, a phenomenon known as the Frohlich effect (Frohlich, 1929). There is a delay of at least 100 ms following retinal photo-receptor cell stimulation & conscious perception (De Valois & De Valois, 1991; Nijhawan 2008). | Five synapses are present from the rods & cones to visual cortical neurons. So, synaptic delay (1-2ms) accounts for 5-10 ms delay. 10 cm myelinated optic nerve - 1ms delay. Total delay: 6-11 ms. Need an explanation for rest of the delay (nearly 90 ms, which is 90% of the delay). | Additional delays due to IPL formation, IPL reactivation, formation of perceptons & latter’s integration can account for the rest of the delay. Note: Synaptic & conduction delays constitute only a minor fraction (10%) of the total delay. |
| 85 | A moving object is perceived slightly beyond the end of its trajectory (Hubbard, 2005) and decays within a few hundred milliseconds after the object disappears (Hubbard, 2018). | It is necessary to make sure that the operational mechanism can provide an explanation for this finding. | At the last moment of arrival of a stimulus from a moving object, in addition to synaptic & conduction delays, percept formation suffers delay due to reactivation of continuously maintained IPLs, and formation & integration of perceptons. The latter three steps that contribute to the majority of the delay (90%) will be responsible for perception beyond the end of the trajectory of a moving object. |
| 86 | Observers do not perceive an object beyond a point at which the object changes direction (Eagleman & Sejnowski, 2000). | It should be possible to explain why the object will not be perceived beyond a point at which the object changes direction (if refractive indices of media through which visual stimuli arrive do not change). | When there is no stimulus beyond a point, there is no further IPL formation & percept generation. So, perception stops instantaneously (after normal perception delay) for reversal of already-formed IPLs by moving object. So, there is no perception beyond the location of the object; there can only be delay in perception. |
| 87 | No FLE is perceived when both moving object & flash disappear simultaneously (Eagleman & Sejnowski, 2000). | Need an explanation based on what happens to the last stimuli from both (see row 77). | IPLs formed by a continuously moving object will take more time when compared to reversal of freshly formed IPLs by a flash. Whereas flash needs time for IPL formation & only less time for reversal of these comparatively newly formed IPLs. When these two conditions are examined, it can be seen that formation of last percepton by the moving object takes place almost at the same time as that of the formation of last percepton by the flash. |
| 88 | FLE is not perceived if the moving object stops moving at the time when a flash is presented as a stationary object (Kanai et al., 2004; Hubbard 2014). | When a moving object is stopped, perception will continue for some more time. A flash (that is going to remain stationary) will have a delay in getting perceived. Need an explanation why there is no FLE. | When a moving object is stopped, perception will continue for some more time due to synaptic, conduction and percepton integration delays. A flash (that is going to remain stationary) will have perception delay due to synaptic, conduction, IPL formation & percepton integration delays. When these two delays match, there will not be any FLE. |
| 89 | In the “high-ϕ illusion”, when a rotating texture is suddenly replaced by a random texture, an82 observer perceives the texture to jerk backwards (Wexler et al., 2013). | It is necessary to show that the sudden appearance of a random texture requires additional time for its perception. | IPLs that are formed by rotation texture are expected to be maintained continuously during its rotation. However, newly arriving random texture need time for the formation of new IPLs, their reactivations & percept formation. Hence, an observer perceives the texture to jerk backward. |
| 90 | FLE increases when the distance between the moving object & flash increases (Hubbard, 2014). | It should be possible to provide a mechanistic explanation for the effect of distance on the time interval between perception of the moving object the flash. | Stimuli from a moving object lead to activation of neurons of 5 neuronal orders involved in visual perception. It will maintain more neurons at sub-threshold activation states such that they can be fired by signals arriving from the flash. Hence, a nearby flash will be able to reach up to more abutted spines in the visual cortex & form sufficient number of IPLs faster & generate more perceptons to get integrated to generate a percept faster compared to a flash located far from the moving object. |
| 91 | 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. |
| 92 | When successive stimuli arrive at frequencies above the critical flicker frequency then stimuli will be perceived as a continuous one (Jensen, 2006). | It is necessary to explain how fusion between the percepts occur. | Perceptons for the first stimulus will be overlapped by 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. |
| 93 | When a stationary object is presented for 2.5 s, then removed for very short interval such as 30 ms & presented again in immediate motion, the object may get continuously perceived (Whitney & Cavanagh, 2000). | A mechanistic explanation is needed how fusion between the percepts occur. | Some of the perceptons for the first stimulus are likely overlapped by perceptons by the second stimulus, thus generating a percept of a continuous stimuli. |
| 94 | When a flash stimulus is more eccentric by reaching retinal periphery, compared to a stimulus reaching fovea, it causes poor performance on a visual task (Staugaard et al., 2016). FLE is more when eccentricity is more (Hubbard, 2014). | It is necessary to explain why the image of a flash falling on the periphery of retina, leads to an increased FLE. | Fovea is a location on the retina where photoreceptors are present in high density (Kolb et al., 2020). Since photoreceptor density is comparatively lower at the periphery, the IPLs are expected to be sparingly distributed in the corresponding areas in the visual cortex. Hence, it will take more time for integrating perceptons to generate a percept of an eccentric flash. |
| 95 | FLE is more when flash is less predictable (Hubbard, 2014). | Need to explain the reason for small FLE when flashes occur at fixed intervals that are predictable. | More predictable flashes will generate certain reverberating circuit that provides potentials to many neurons to keep them in a sub-threshold state. When the next flash arrives, it can depolarize more abutted spines & form more IPLs for the generation of a fast percept. |
| 96 | Predictable moving dots at the leading edge are correlated with suppressed blood oxygenation level dependent (BOLD) responses (Schellekens et al., 2016). | Need to explain a favorable mechanistic change during anticipation & how it is associated with low BOLD signals. | An explanation for Golgi staining reaction led to an inference that oxygen is involved in reversing the IPLs (Vadakkan, 2021). This indicates that suppressed BOLD signals are an indication that decreased oxygen release facilitates continued maintenance of IPLs while observing a moving object. |
| 97 | 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 & the individual fixates to a single point in the visual field. In the above conditions, blind spot is a location in the visual field at which a visual stimulus cannot be perceived. | Percept formation occurs at a spatial location of integrated perceptons (Vadakkan, 2015a). There are no locations found in the visual cortex equivalent to a blind spot at which visual stimuli do not reach. Blind spot is a conformationally empty space in the net perceptons. During monocular vision when eye fixates to a point, then stimuli arriving at the margins of the blind spot are not capable of forming a percept in this region. In contrast, a visual stimulus arriving at the margin of a blind spot generate perceptons & are expected to reach IPLs in the visual cortex, the integral of which can reach towards the periphery of the blind spot. This is due to the branching of dendritic arbor & their overwhelming overlap that prevents having a cortical equivalent of a blind spot. |
| 98 | It is necessary to provide a mechanistic explanation for changes in brain inflammation & how it can lead to perception of stimuli in their absence. | Inflammation leads to swelling of cells & their processes. This predisposes abutted dendritic spines to form non-specific IPLs & trigger inner sensations in the absence of any sensory stimuli (hallucinations). Specific hallucinations can occur when inflammation occurs in specific brain regions. | |
| 99 | Inner sensations of consciousness. | The presence of a continuous operational mechanism for the generation of inner sensations that depends on/contributes to maintaining the frequency of oscillating extracellular potentials in a narrow range is expected. The combined inner sensation is expected to generate inner sense of being conscious. | There is a continuous baseline oscillating extracellular potentials as recorded by EEG. Both internal & external stimuli continuously reactive numerous IPLs & the resulting units of inner sensations get integrated to generate inner sensation of consciousness (Vadakkan, 2010). A framework for consciousness was explained as the net semblance from non-deleterious & non-beneficial stimuli from environment & body (Vadakkan, 2010; Vadakkan, 2015). |
| 100 | Loss of consciousness by anesthetic agents. | It is necessary to first provide a framework of a mechanism that generates first-person properties of consciousness. Then, explain how anesthetic agents block the above mechanism. | A framework for consciousness was explained (see above row) (Vadakkan, 2010; Vadakkan, 2015). Spontaneous curvature induced by anesthetics arriving from the ECM space initially to the outer lipid membrane leads to asymmetry between the outer & inner leaflets of the lipid bilayer (Lipowsky, 2014). In addition, lipophilic anesthetics get partitioned inside the hydrophobic lipid phase in the regions of membrane reorganization on the spines (lateral aspect). The net result is dehydration of the inter-membrane ECM space leading to physical contact between the abutted spine membranes. This leads to the formation of a large number of non-specific IPLs altering inner sensation of consciousness. |
| 101 | Potency of an inhaled anesthetic agent is proportion to its partition coefficient (concentration ratio) between olive oil & water (hydrophobic solubility). This has a correlation coefficient of 0.997 (Firestone et al., 1986), one of the most powerful correlations in biological systems (Halsey, 1992). | It is necessary to show that the mechanism of anesthetic action is dependent proportional to the lipid solubility. | Based on the semblance hypothesis, lipid solubility affects the membrane properties and proportionately leads to formation of non-specific IPLs. Non-specific semblances generated on the inter-LINKed spines of non-specific IPLs lead to proportional loss of consciousness (Vadakkan, 2015). |
| 102 | Anesthetics are known to have different actions - GABA-A receptor agonists, alpha adrenergic receptor agonists, NMDA receptor antagonists, dopamine receptor antagonists and opioid receptor agonists (Kopp et al., 2009). | It is necessary to show either that all these receptor actions lead to a common path responsible for consciousness or that there is a common mechanism of action for these agents other than on those receptors. | A framework for consciousness was explained (see above row) (Vadakkan, 2010; Vadakkan, 2015). Anesthetic actions of general anesthetics are proportional to their lipid solubility - with a very high correlation coefficient of 0.997. Spontaneous curvature induced by anesthetics arriving from the ECM space initially to the outer lipid membrane leads to asymmetry between the outer & inner leaflets of the lipid bilayer (Lipowsky, 2014). This can lead to formation of large number of non-specific IPLs by the anesthetic agents (Vadakkan, 2015). |
| 103 | General anesthesia induced by anesthetics is reversed by the application of pressure outside the animal placed within a closed container. i. e. by application of pressure over an aquatic or terrestrial animal by increasing the pressure of water or air respectively (Lever et al., 1971; Halsey et al., 1986). | It should become possible to show a mechanism that can lead to reversal of actions of anesthetic agents in response to external pressure. | External pressure propagates through middle ear, perilymph, CSF & paravascular space to reach the neuronal processes (Iliff et al., 2012). Based on the Le Chatelier’s principle, when the pressure on a system at equilibrium is disturbed, the equilibrium position will shift in the direction necessary to reduce the pressure. This will lead to removal of anesthetic molecules from the lipid membranes to the ECM volume that will escape through the paravenular space into the venous system (Iliff et al., 2012). This in turn will reverse the non-specific IPLs generated by the anesthetics (Vadakkan, 2015). |
| 104 | Only reduced amounts of anesthetic agents are required for anesthesia in the presence of levodopa (Segal et al., 1990). | It is necessary to explain a specific mechanism of action of dopamine that will augment anesthetic action. | It is known that dopamine can lead to enlargement of spines (Yagishita et al., 2014). This can augment IPL formation and reduce the required concentration of anesthetic agents for generating a certain level of anesthesia compared to that in the absence of dopamine. |
| 105 | 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 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). |
| 106 | General anesthetics generally do not impair existing long-term memory (Bramham & Srebro, 1989). | It is necessary to explain how the mechanism that retains long-term memory remains unaffected by general anesthetics. | IPLs responsible for maintaining long-term memory are well stabilized by maintaining stable inter-membrane interactions at the IPL locations as explained by the semblance hypothesis (see Fig.12D in the FAQ section) (Vadakkan, 2015). Hence, these stable regions will not be affected by anesthetics. |
| 107 | There are several reports of cognitive decline after surgery that uses general anesthetic agents. | It is necessary to provide a plausible explanation of how the normal mechanism responsible for memory is likely getting affected by a common factor in all these surgical cases. | Since IPLs are responsible for generating memories & anesthesia leads to the formation of large number of non-specific IPLs, it is possible that any extension of the IPL structure to form IPL fusion (see Fig.12F in FAQ section) can lead to spine and neuronal loss as a consequence (Vadakkan, 2015; Vadakkan, 2016). |
| 108 | As the anesthetic dose is increased, patients enter a state of excitation characterized by euphoria or dysphoria, defensive or purposeless movements, & incoherent speech. This state is termed "paradoxical" since the anesthetic, intended to induce unconsciousness, cause excitation (Brown et al., 2010). | It is necessary to provide an explanation for the generation of new inner sensations & motor actions during the early stages. | Motor neurons in layer 5 of the motor cortex is being held at a sub-threshold level of activation that will enable them to fire when additional potentials arrive. In the initial stages of anesthesia, when the anesthetics induce more IPLs, it will lead to both generations of certain inner sensations & firing of several sub-threshold activated neurons in the motor cortex. |
| 109 | Loss of consciousness during a generalized seizure and its reversal after seizure. | Mechanism of seizure generation should be able to explain how inner sensation of consciousness is lost. | Rapid chain formation of large number of non-specific IPLs due to changes in ECM properties (e.g. very low serum Na+) or increased excitability of neurons generates seizures (Vadakkan, 2016). This will change the conformation of net semblance generated in the background state altering consciousness. |
| 110 | Changes in consciousness proportional to variations in the frequency of oscillating extracellular potentials beyond a narrow range. | Need an explanation how a narrow range of frequency of oscillating extracellular potentials is associated with normal consciousness. | Explained based on the semblance hypothesis (Vadakkan, 2010; 2015). Unconscious states are associated with large variations in the frequencies of extracellular potentials recorded from the skull surface in EEG (Rusalova, 2006). Conformational changes in the net semblance for consciousness is affected. |
| 111 | Effect of dopamine in augmenting anesthetic action. | Explain a mechanism how dopamine augments anesthetic action. This explanation must match with the explanation for the action of dopamine in augmenting learning (see row 15). | Anesthetic agents generate large number of non-specific IPLs leading to the formation of non-specific semblances, altering conformation of net semblance for conscious state to generate an unconscious state. Spine enlargement by dopamine augments IPL formation. Hence, dopamine augments anesthetic action (Vadakkan, 2016). |
| 112 | Phantom sensation and phantom pain. | Explain a mechanism for the inner sensation of pain from a lost limb at the time of phantom sensation or phantom pain. | As long as the IPLs that have received inputs from a limb remains stable in the brain, any reactivation of this by stimuli arriving to this set of IPLs through a different sensory input can evoke semblance of phantom limb or pain. This can possibly occur when the same nerve root in the proximal regions of the lost limb is stimulated. |
| 113 | Innate behavior (e.g. sucking reflex) that enables survival. | A mechanism evolving from heritable changes to explain innate behavior in response to a stimulus. | Associative sensory stimuli of different velocities propagate through pathways that converge at certain locations. IPL mechanisms at these locations generate inner sensations such as memory & also fire motor neurons for survival. When these associations from environment is important for survival, then adaptational changes will generate IPLs at the locations of convergence of sensory inputs. This can be viewed as an evolved mechanism. |
| 114 | Neurodegeneration resulting from repeated general anesthesia (Baranov et al., 2009). | Need an explanation why the repeated induction of a mechanism of loss of consciousness by anesthetics can lead to loss of spines and eventual loss of neurons. | Anesthetics arriving from ECM space first to the outer lipid membrane leads to asymmetry between the outer & inner leaflets of the lipid bilayer causing curving of membranes (Lipowsky, 2014). Lipophilic anesthetics get partitioned inside the hydrophobic lipid phase in the regions of membrane reorganization on the spines (lateral aspect). This results in dehydration of the inter-spine ECM space leading to large number of non-specific IPLs altering inner sensation of consciousness (Vadakkan, 2015). Conversion of IPLs to inter-neuronal inter-spine fusion leads to spine loss & neuronal death. |
| 115 | More years of education (increased number of associative learning events) reduces dementia risk (Maccora et al., 2020). | Should be able to explain whether surplus learning-induced changes are generated by prolonged learning events. | Associative learning events have several shared associative elements in them. This leads to formation of surplus number of IPLs by different learning events since new neurons get inserted into the circuitry and alters it at higher orders above the granule neuron layer of the hippocampus. Hence, surplus IPLs are formed in the cortex (Vadakkan, 2013; 2019), which can explain reduced dementia risk with more education. |
| 116 | Specific brain regions appear to be associated with specific functions based on the lesions/ lesion studies. | Need to provide a circuit-based explanation. | Sensory cortices receive inputs from specific sensory stimuli. These locations are expected to have IPLs necessary for perception. Hippocampus receives inputs from all the sensations. Converging inputs here form IPLs during associative learning. Cortical regions have sparse converging locations where IPLs form for specific learning associated changes. Thus, specific locations have specific functions. |
| 117 | Astrocytic pedocytes cover less than 50% of peri-synaptic area in nearly 60% of the synapses in the CA1 region of hippocampus (Ventura & Harris, 1999). | Hippocampal mechanism of learning & memory must explain the suitability of distribution of astrocytic processes. | Area of spines free of astrocytic pedocytes favor generation of inter-neuronal inter-spine interactions for IPL formation (Vadakkan, 2019). Astrocytic pedocytes can mop up neurotransmitter molecules spilled over from the synaptic cleft and recycle them to provide back to the neurons. |
| 118 | Present nervous systems have evolved over millions of years & are also the results of certain accidental coincidences. | It is expected to be possible to explain how the circuitry that provides all the features can be evolved through simple steps of variations and selection. | IPL formation & reactivation lead to sparking of the first-person inner sensations of features of a learned item in response to the arrival of fastest or first sensory cue stimulus (associatively learned). This started providing survival advantages to animals in a predator-prey environment. These beneficial features were selected such that organization of the neuronal processes continued to get maintained and conserved over time (Vadakkan, 2020). |
| 119 | Dye diffuses from one neuronal cell to another as the cortical neurons move from periventricular region towards their destination indicating formation of an inter-cellular fusion pore (Bittman et al., 1997). This occurred in all the cells. This is followed by death of nearly 70% of these cells and survival of the remaining 30% cells. | It is expected to become possible to explain how an event of inter-cellular fusion leads to selection of variants that acquire an ability to prevent further inter-cellular fusion. Since neurons cannot divide further (arrested in interphase), a transient stage of fusion is expected to trigger a "fusion prevention mechanism" in the surviving neuronal cells. It is also necessary to explain whether this mechanism has any role in the unique functional property of generation of first-person inner sensations in the nervous system. | Explained based on the semblance hypothesis (Vadakkan, 2020). Dye diffusion indicates formation of fusion pores between neuronal cells. The initial occurrence of inter-neuronal fusion could have taken place due to changes in membrane composition or lack of checkpoint mechanisms to arrest hemifusion from progressing to fusion. But the neuronal adaptations that it brought to arrest IPL changes beyond IPL hemifusion enabled the neuronal processes to generate IPLs. The functional advantages of generating first-person inner sensations provided exceptional survival advantages to the organisms. |
| 120 | Following the above stage where dye diffusion is observed, significant neuronal death (70%) (Blaschke et al., 1996) & spine loss (13 to 20%) are observed. | There is a high probability that the surviving cells have acquires an adaptation. | Explained based on the semblance hypothesis (Vadakkan, 2020). Following death of 70% cells, an adaptation occurring in the surviving cells most likely prevents any future coupling between neurons that may result in inter-neuronal fusion. This adaptation is suitable for maintaining IPLs for generating useful functions. |
| 121 | Aging is the most important risk factor for neurodegenerative disorders such as Alzheimer’s disease (Guerreiro & Bras, 2015). | It is necessary to explain loss of a specific mechanism or structural change occurring during aging responsible for age-related dementia. Dementia means both decline in memory & behavioral motor activity such as speech & motor actions. | Dye diffusion between neuronal precursor cells during one stage of development occurs in 100% of cells (Bittman et al., 1997). Death of up to 70% of these cells & survival of rest 30% of cells that become adult neurons indicates that an adaptation is triggered in the surviving cells that prevents any future inter-neuronal fusion events, spine loss & neuronal deaths. Age-related defects in this adaptation mechanism can lead to cell-cell fusion, cytoplasmic content mixing & neurodegeneration. This a possible explanation for age-related cognitive decline (Vadakkan, 2021). |
| 122 | Higher brain functions take place in a narrow range of frequency of oscillating extracellular potentials as evidenced by EEG (Rusalova, 2006). | To have oscillating extracellular potentials, there should be corresponding intracellular changes. In the cortex, neurons are arranged in six neuronal orders (layers). Neurons between these orders are connected by synapses. So, synaptic transmission is expected to take place perpendicular to the cortical surface. It is necessary to show changes that generate horizontal component of those oscillations. | Both the mechanisms for learning & memory retrieval are expected to contribute/depend on vector components to the oscillating extracellular potentials. What provides the horizontal component? Propagation of potentials across the IPLs that are formed between spines that belong to laterally located neurons have the ability provide the horizontal component for oscillating potentials. (Vadakkan, 2010; 2013). Note: Since neurons of all the orders have their apical terminal attached to the subpial region, spines that belong to neurons of different neurons also participate in IPL formation & contribute to the horizontal component of oscillations. |
| 123 | In prematurely born infants, the oscillating extracellular potentials in electroencephalogram (EEG) show discontinuity in the waveform (Selton et al., 2000). | It is necessary to explain a horizontal component formed during development as the brain matures. Since premature infants will not survive below certain age & since "brain death" is considered as "death", enabling extracellular potentials to oscillate in a narrow range of frequency is a vital requirement. | This can be explained in terms of formation of additional IPLs, by the arrival of large number of associative stimuli that provides lateral spread of potentials through them. Formation of recurrent collaterals, cortico-thalamic & thalamo-cortical pathways are also expected to contribute to the horizontal component (Vadakkan, 2021). |
| 124 | A study found that infants are capable of encoding memories during infancy. However, deficits in retrieval mechanisms are likely responsible for infantile amnesia in humans (Yates et al., 2025) | The retrieval mechanism should have some maturity related deficiency that can explain retrieval deficits. | Brain operates only in a narrow range of frequency of oscillating potentials. IPLs are expected to contribute to the horizontal component of these oscillating potentials. Learning events increases the number of IPLs. During infancy, it is likely that the relatively a smaller number of IPLs won't be sufficient to contribute to the horizontal component of oscillations to keep this system property robust for the generation and integration of semblions for memory formation. |
| 125 | A comparatively longer duration for humans to achieve motor functions, after birth, compared to animals. | It is necessary to provide at least a framework of an explanation for this delay. This may also likely relate to the higher cognitive abilities of humans compared to animals. A mechanistic explanation is needed. | In humans, sufficient number of motor units (one motor neuron & the muscle fibers supplied by it) receive input signals through a more time-consuming process. One of the routes through which motor neurons receive potentials is through the IPLs. Large number of associative learning events can lead to the formation of more IPLs, which in turn enable generation of first-person inner sensations of more higher brain functions in humans compared to animals. Since more time will be needed for the formation of sufficient number of IPLs for potentials to reach motor units, it takes more time for humans to achieve full-fledged motor functions (Vadakkan, 2021). |
| 126 | Artificial triggering of spikes in one neuron in the cortex causes spikes in a group of neighboring neurons in the same neuronal order located at short distance (25–70µm) from the stimulated neuron (Chettih & Harvey, 2019). | It should be possible to explain a mechanism that can lead to lateral spread of firing between neurons of the same neuronal order within a short radius. Need an explanation for a mechanism through a path other than trans-synaptic route. | One explanation is propagation of depolarization across the IPLs between spines that belong to different neurons (Vadakkan, 2013). This also explains why only sparsely located neurons get fired, correlated in time. |
| 127 | The protein complexin blocks SNARE-mediated fusion by arresting the intermediate stage of hemifusion. Complexin is present in the spines. But docked vesicles are not found inside the postsynaptic terminals (spine) (in contrast to what is observed in the presynaptic terminals). | This leaves the question, "Which inter-membrane fusion is getting arrested by complexin?" It is necessary to explain an inter-membrane fusion process that can be mediated by SNARE proteins and blocked by complexin by arresting fusion at or before the intermediate stage of hemifusion in the spines. | SNARE proteins provide energy for bringing together membranes against repulsive charges and overcoming energy barrier between abutted membranes (Oelkers et al., 2016). They also generate force to pull together abutted membranes as tightly as possible (Hernandez et al., 2012). By initiating the fusion process by supplying energy (Jahn & Scheller, 2006), SNARE proteins can lead to the formation of characteristic hemifusion intermediates (Lu et al., 2005; Giraudo et al., 2005; Liu et al., 2008). Protein complexin present within the postsynaptic terminals (Ahmad et al., 2012) is known to interact with the neuronal SNARE core complex to arrest fusion at the stage of hemifusion (Schaub et al., 2006). These indicate possibility for inter-spine interactions mediated by SNARE and regulated by complexin. |
| 128 | There are hundreds of types of neurons in the cortex (Huntley et al., 2020; Mao & Staiger, 2024). | It is necessary to explain how these many different types of neurons can orchestrate a specific cortical function. | What is important is the inter-neuronal inter-spine interaction forming IPLs during learning & their reactivation generating both semblances & motor effects. IPLs can be formed between spines of different types of neurons, including that of the inhibitory neurons. It is the net polarity of the islets of inter-LINKed spines that determine the conformation of net semblance that determine the qualia of inner sensations (Vadakkan, 2021). |
| 129 | Transcriptomic analyses show heterogeneity of even adjacent neurons of the same type in the cortex (Kamme et al., 2003; Cembrowski et al., 2016). | This indicates that any mixing of the contents between these neurons is fatal to them. Hence, there will be a robust mechanism to prevent intercellular fusion. | Different mRNA profiles of adjacent neurons of even the same type indicate that any cytoplasmic content mixing will lead to homeostatic mechanisms such as spine or neuronal loss to prevent it from further progress (Vadakkan, 2016). This matches with the structural limitation of IPLs to only the stage of inter-membrane hemifusion. |
| 130 | Heterogeneity in clinical features & pathological changes in Alzheimer's disease (& other neurodegenerative disorders). | First, there will be a universal mechanism that involves different neuronal types. Secondly, many factors are likely involved in the operational mechanism. Pathological changes due to these factors should be able to explain heterogeneity. | A common mechanism is pathological conversion of normal maximum limit of hemifusion to pathological fusion. Clinical features depend on a) formation of non-specific IPLs at different locations, & b) locations of IPL fusion that can lead to spine loss & even neuronal death (Vadakkan, 2016). Hence the heterogeneity. |
| 131 | In excitatory neurons, spine depolarization can occur without any dendritic depolarization. Also, distal human dendrites contribute limited excitation to the soma even during the occurrence of dendritic spikes (Beaulieu- Laroche et al., 2018a; Beaulieu-Laroche et al., 2018b). | Why did such a mechanism get selected? What is the functional significance of depolarization of the spine head? Is there any link between depolarization of the spine heads, oscillating extracellular potentials & different brain functions? Are the spine heads involved in certain computations? | The IPL mechanism needs only depolarization of the spine heads for generating units of inner sensations. Even though lack of depolarization of the dendrites & lack of firing of the postsynaptic neurons can prevent motor outputs, it does not affect generation of semblance at the inter-LINKed spines. This matches with the ability to generate inner sensations without generating any corresponding motor actions.
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| 132 | The histological features of amyloid (senile) plaques & neurofibrillary tangles observed in Alzheimer's disease & in a spectrum of neurodegenerative disorders are also observed in normal aging (Anderton, 1997). | A mechanistic explanation for how & why intracellular neurofibrillary tangles & extracellular plaques that are key pathological features in neurodegenerative disorders are observed in normal aging (but without symptoms). | The formation of extracellular plaques can reduce the number of specific IPLs formed during learning, which are necessary for generating specific memories. People with large number of surplus specific IPLs will be able to afford to lose a subset of those IPLs. However, those with only borderline number of IPLs (just enough to generate specific memories) will be affected by the accumulation of amyloid plaques in the ECM space. |
| 133 | Therapeutic agents developed for treating seemingly unrelated neurological diseases such as seizure disorders, Parkinson's disease, spasticity, & hallucinations can alleviate different headache pains. | Explanations for mechanisms of different disorders & the operational mechanism of the system should provide interconnected explanations for the effectiveness of therapeutic agents in different headaches. | By inhibiting voltage-gated sodium channels, it reduces neuronal excitability & prevent rapid IPL formation preventing seizures, prevents IPL formation between spines of spiny neurons of basal ganglia, reduce inputs via IPLs to upper motor neurons reducing spasticity, reverse/inhibit IPLs inhibiting/reducing inner sensation of headache pains. |
| 134 | Since learning is expected to generate certain new circuit connections, the circuit elements (like on a printed circuit board (PCB)) must remain separate from each other. | Properties of both neuronal membranes and extracellular matrix should match with the new circuit connections, functional properties imparted by them and their reversal. | Even though extracellular matrix space seems negligible between the membranes, hydration layer between the lipid membranes shows high energy barrier in artificial systems (Rand & Parsegian, 1984; Martens & McMahon 2008; Harrison, 2015). |
| 135 | "Representational drift" - meaning that when a brain function is repeated, set of neurons that fire changes with time (Schoonover et al., 2021; Marks & Goard, 2021; Deitch et al., 2021). | In the case of memory, it is necessary to show either a) redundancy in its operational mechanism, or 2) surplus operational units, subset of which integrate to provide memory. | Correlation between a brain function & neuronal firing will be true for those neurons that are being held at sub-threshold activation state & receive additional potentials through learning generated IPLs. Repetition of associations of overlapping features in future learning events propagating through a circuitry that inserts new neurons along its path will generate new set of IPLs. Hence, when a brain function is repeated, it fires new set of neurons (Vadakkan, 2019). |
| 136 | Ability to induce robust long-term depression (LTD) in the spinous region of medium spiny neurons (MSNs) of nucleus accumbens (NAc) of naïve animals. | It is necessary to explain LTD as an active process & not merely reversal of a mechanism for LTP (Dong et al., 2015). Since it takes minutes to induce LTD, it is necessary to explain it as a time-dependent mechanism (Thomas et al., 2001; Brebner et al., 2005). It is also necessary to show that energy applied at the spinous region leads to depression of potentials at the recording electrode placed at the postsynaptic region or on MSN soma. | IPL formation between a spine of a MSN that synapse with excitatory inputs and another spine of a second MSN that synapses with inhibitory inputs leads to the generation of depression of net potentials. The net result of many of such IPLs can cause depression of the net potentials recorded by the recording electrode. This can explain LTD (Vadakkan, 2021). |
| 137 | Following stimulation, there is a time delay to observe LTD (Thomas et al., 2001; Brebner et al., 2005) comparable to the time delay observed in the induction of LTP (Gustafsson & Wigström, 1990; Escobar & Derrick et al., 2007). | A time-dependent cellular change is taking place during the delay period following LTD stimulation. | Like LTP, LTD induction also results from the formation of IPLs. Since energy is needed for spine expansion that can facilitate IPL formation between spines that synapse with excitatory and inhibitory inputs, spine expansion also needs time to take place. |
| 138 | Similar to LTP, LTD in NAc is also NMDA receptor-dependent (Lüscher & Malenka, 2012). | LTD induction takes place through activation of NMDA receptors of glutamatergic synapses. It is necessary to explain how NMDA receptor activation leads to both LTP & LTD. | Excitatory synaptic function is necessary for spine expansion and IPL formation between spines that belong to different MSNs in the NAc region. Since dopaminergic terminals that synapse on to the spines that receive excitatory inputs, it is reasonable to infer that spines of excitatory synapses are the major partner of the IPLs (Vadakkan, 2021). |
| 139 | When rewards or conditioned stimuli that predict reward are presented, dopamine neurons in the VTA increase their firing (Schultz, 1998; Roitman et al., 2004) releasing dopamine in their terminals that synapse with spines of MSNs in NAc. | Dopamine produces certain changes at the spines of MSNs that synapse with excitatory inputs. | Dopamine is known to cause spine expansion (Yagishita et al., 2014). Expanding spines can augment IPL formation and retain the formed IPLs for a long period. Since some of the spines involved in IPL formation synapse with excitatory inputs and some with inhibitory inputs, the net effect in the presence of dopamine is augmentation of depression (Vadakkan, 2021). |
| 140 | Drugs of abuse such as cocaine increase dopamine levels in the NAc (Lüscher & Malenka, 2011). | Dopamine has certain actions in the NAc to cause addiction that leads to its abuse. | Dopamine leads to spine expansion, formation of IPLs that leads to inner sensation of pleasure. Continued exposure can lead to spine loss & dependency on cocaine to maintain normal comfort level (Vadakkan, 2021). |
| 141 | Exposure to cocaine leads to attenuation of postsynaptic potentials in MSN spines of NAc (Beurrier & Malenka, 2002). | It is necessary to show how dopamine released due to the action of cocaine acts on spines of MSNs that synapse with excitatory inputs & results in attenuation of postsynaptic potentials. | Dopamine is known to cause spine expansion (Yagishita et al., 2014). Spine expansion speeds up IPL formation with a spine that receive inhibitory input, altering the conformation of semblance at this location to generate inner sensation of pleasure (Vadakkan, 2021). |
| 142 | Dopamine attenuates postsynaptic potentials elicited by stimulation of different excitatory inputs to NAc shell region (Park et al., 2008). | Action of dopamine on spines of MSNs that synapse with excitatory inputs attenuates postsynaptic potentials when these excitatory inputs are stimulated through a mechanism. | Attenuation of postsynaptic potentials by dopamine can be explained in terms of expansion of the spine head to which the dopaminergic terminal synapses to & that spine in turn form an IPL with another spine that is synapsing with an inhibitory input (Vadakkan, 2021). |
| 143 | In response to natural rewards & cocaine exposure, a major set of MSNs in NAc show depression of firing rate (Carelli, 2002; Ishikawa et al., 2009; Kourrich & Thomas, 2009). | Rewards and drugs cause release of dopamine from VTA. It is necessary to show how dopamine’s action on spines of MSNs that synapse with excitatory inputs result in reduced firing rate of MSNs. | Due to the reasons mentioned in the above row, as postsynaptic potentials reduce firing rate also reduces (Vadakkan, 2021). |
| 144 | Dopamine reduces excitability of MSNs in NAc in vitro (O'Donnell & Grace, 1996). | It is necessary to show how the action of dopamine on the spines of MSNs that synapse with excitatory inputs results in inhibition of MSNs. | Dopamine augments IPL formation between two spines - one synapsing with an excitatory input & another synapsing with an inhibitory input. Hence, the net effect results in inhibition of the excitatory output (Vadakkan, 2021). |
| 145 | Synchronization of membrane potential states in a population of NAc neurons (Goto & O'Donnell, 2001). | It is necessary to show how membrane potential states in a population of NAc neurons get synchronized. It is necessary to provide an explanation how spines of the MSNs in NAc that receive excitatory input & spines that receive inhibitory inputs together exhibit synchronization of membrane potentials. | Inhibitory inter-neurons that are electrically connected with each other through gap junctions are known to make oscillations. The islets of inter-LINKed spines are also expected to contribute vector components towards generating oscillating extracellular potentials. Based on the semblance hypothesis, these oscillations are responsible for binding units of inner sensations. |
| 146 | Similar to LTP, LTD in the hippocampal synaptic areas is implicated in different types of learning (Kemp & Manahan-Vaughan, 2004; Dong et al., 2013; Dong et al., 2015). | It is necessary to explain the similarity between correlation between LTP induction & learning with that of the LTD induction & learning. | Based on the semblance hypothesis, associating two sensory stimuli in learning requires formation of IPLs. Since spines that receive inhibitory inputs are present on the MSNs, IPLs formed between spines receiving excitatory & inhibitory inputs can exhibit LTD. Since IPL formation is the basis of learning, irrespective of the strength of net postsynaptic potentials, semblance formed on the inter-LINKed spines generates inner sensation of memory (Vadakkan, 2021). |
| 147 | Impaired abilities to induce LTD at the input synaptic region of MSNs of NAc in “addicted” state (Kasanetz et al., 2010). | It is necessary to explain how the initial use of drugs leads to LTD. Then it is necessary to show how "addicted" state leads to an impaired ability to induce LTD. | Initially, IPL formation between spines synapsing to excitatory and inhibitory inputs leads to depression of postsynaptic potentials showing LTD. Later, when more spines are lost in the "addicted state", more amount of drug will become necessary even to generate normal conformation of semblance at those location to maintain internal sensation of normal comfort (Vadakkan, 2021). |
| 148 | Inner sensation of pleasure is correlated with specific NAc properties, which is reflected by the ability to induce LTD at the input regions of MSNs of NAc. | It is necessary to provide interconnected explanations for 1) ability to induce robust LTD in NAc from naïve animals, 2) impaired ability to induce LTD in “addicted” state, 3) attenuation of postsynaptic potentials by cocaine, & 4) reduced firing of MSNs in response to cocaine/dopamine. | Inner sensation is explained in terms of the conformation of semblances generated at the inter-LINKed spines. At the IPLs between a spine that receive excitatory input & another receiving inhibitory input, the inner sensation is expected to be that of pleasure (Vadakkan, 2021). |
| 149 | Controversial views (pdf) expressed by Camillo Golgi against Ramón y Cajal's interpretations of results obtained from modified Golgi staining protocols. | The chemistry behind the modification of original Golgi staining protocol must be able to provide reasons for this controversy. Such an explanation is expected to become possible when we understand the operational mechanism of the brain. | Golgi used one oxidizing agent to pre-treat brain tissue before the staining reaction, whereas Cajal used an additional oxidizing agent for the same step. It shows that increasing oxidation state restricts the spread of Golgi chemical reaction between neurons by blocking certain channels between them. Since blood oxygenation level dependent (BOLD) signals occur in specific brain regions peaking around 4 seconds after learning (Monti et al., 2010; Murayama et al., 2010) & since most working memories are lost with time, it is possible to infer that oxygen reverses learning-induced channels. Since this gate should not allow mixing of cytoplasmic contents between neurons, it matches with the properties of IPLs with inter-membrane hemifusion as their structural upper bound (Vadakkan, 2022). |
| 150 | Formation of new neurons in the hippocampus | The operational mechanism should be able to explain functional advantage provided by insertion of new neurons. | Both input and output connections of new neurons will continuously alter the existing circuitry. Repetition of same associative learning will create new IPLs at higher neuronal orders increasing number of sparse storage mechanisms (Vadakkan, 2011). Since every associative learning event has a certain subset of commoon components, each learning continues to generate more IPLs for a given association. |
| 151 | A combination of both loss of spines and formation of new spines during learning (Frank et al., 2018). | There must be a mechanism that leads to loss of spines during learning. Formation of new spines should accomplish something new that can facilitate further learning. | The structural upper bound of permitted inter-membrane interaction for IPL formation is inter-membrane hemifusion, which is an intermediate stage of membrane fusion. Several factors can overcome the checkpoint needed to arrest the changes at the stage of hemifusion, leading to fusion. Neuronal cells will respond to this by removing those fused spines, which can explain spine loss during learning. |
| 152 | Permanent changes in the motor response to a single stimulus occur due to repeated exposure to that stimulus & are called non-associative form of learning. | It is necessary to provide a mechanism how permanent changes in the motor responses occur due to repeated exposures. | Any stimulus from the environment is a high-dimensional sensory input consisting of many newly associated components in it that can lead to formation of IPLs. During the time in between repeated exposures to this stimulus, it has to propagate through newly incorporated new neurons in the circuit. This leads to the formation of new IPLs in response to the same stimulus at the higher neuronal orders. Repetition of learning stabilizes these IPLs resulting in permanent changes in motor response to a single stimulus. |
| 153 | Prevalence of dendritic spikes on the dendrites of place cells (CA1 neurons) in behaving mice predicts spatial precision (Sheffield & Dombeck, 2015). | It is necessary to explain how spatial inputs lead to dendritic spikes. | Large EPSPs in a dendritic spike indicate arrival of addition of several EPSPs on the dendrite. Arrival of several EPSPs via IPLs to reach an islet of inter-LINKed spine is feasible. Spatial stimuli reaching an islet of inter-LINKed spines leading to summation of EPSPs in the islet & generates a dendritic spike. |
| 154 | Both consolidation for long-term memory (Flexner et al., 1967; Davis & Squire, 1984) and late-phase LTP in in vitro slices (Krug et al., 1984; Huang et al., 1996) are protein synthesis dependent. However, after protein synthesis inhibitor exposure to the consolidated memory engram cells, direct optogenetic activation of these cells retained the ability to retrieve specific memory (Ryan et al., 2015). | It is necessary to show the presence of a protein synthesis independent functional engram cell-specific connectivity mechanism to explain how memories are retained. It is necessary to show that a non-protein mechanism is responsible for long-term maintenance of memories. | Based on the semblance hypothesis, during learning, an IPL is generated between the spines of different output engram neurons. The results of the experiment (Ryan et al.,2015) show that IPLs are not made of proteins. Based on the semblance hypothesis, learning generates IPLs by inter-spine membrane interactions leading up to the stage of inter-membrane hemifusion. |
| 155 | Compared to the set of neurons that fire when exposed to one of the associatively learned stimuli before learning, additional neurons are fired when an animal is exposed to the same stimulus after learning. This is documented in the lateral amygdala in fear conditioning experiments (Schoenbaum et al., 1998; Tye et al., 2008). | New paths originate during learning. It is necessary to provide a location and mechanism for these paths. | Based on the semblance hypothesis, IPLs are formed during learning. After learning, one of the associatively learned stimuli will propagate through the IPLs and provide additional potentials to some of the neurons that will allow them to cross the threshold for firing. This explains how additional neurons fire when the animal is exposed to the same stimulus after learning. |
| 156 | Fear learning generates local connectivity between LA neurons (Abatis et al., 2024). Electrophysiological studies show that stimulation of one LA neuron causes arrival of depolarization to a minor fraction of LA neurons in the immediate neighborhood. | After cued fear conditioning (CFC), many LA neurons achieve functional connectivity between them. It is necessary to explain the route through which depolarization can occur from one LA neuron to the next. It should be a learning induced connectivity mechanism that occurs in millisecond timescales. Hence, it must be a non-synaptic mechanism. | Based on the semblance hypothesis, inter-neuronal and intra-neuronal inter-branch inter-spine interactions (called IPLs) constitute the engram changes during associative learning. When more than two spines are LINKed in this manner, it leads to the formation of islets of inter-LINKed spines (IILSs). Artificial stimulation one LA neuron will cause back propagation of potentials along its dendritic tree branches towards the spines that can propagate to the rest of the inter-LINKed spines within different IILSs & propagate towards the latter's postsynaptic LA neuronal soma causing some of these LA neurons to fire. |
| 157 | Fear conditioning is associated with enlarged synapses on the LA dendritic spines (Ostroff et al., 2010; Choi et al., 2021). | Synapse enlargement can be due to enlargement by pre and/or postsynaptic terminals. a mechanistic explanation linking this and fear learning mechanism is needed. | Enlargement of spines can augment IPL formation by displacement of the hydration layer between the membranes of the spines. |
| 158 | Synapses on the spines of LA dendrites show a greater ratio of the area of postsynaptic density (PSD) compared to that of the presynaptic structures (Ostroff et al., 2012). | This finding indicating that the spines that enlarge laterally during learning must have a structural advantage in fear leaning. | IPLs are expected to form between the lateral spine regions. Moreover, this matches with the findings that vesicle exocytosis (for AMPA insertion) takes place at the lateral spine regions https://pubmed.ncbi.nlm.nih.gov/15322548/ |
| 159 | Synapses lacking astrocyte appear in the amygdala during consolidation of Pavlovian threat conditioning (Ostroff et al., 2014). | Nearly 50% of the space around the perisynaptic region is occupied astrocytic pedocytes. Disappearance of astrocytic pedocyte must explain a spatial explanation. | This increases the number of IPLs that one spine can form. Hence, this event is related to the efficiency of fear learning and supports the formation of IPLs during fear learning (R´acz et al., 2004; Makino and Malinow, 2009; Jacob and Weinberg, 2015). |
| 160 | Disconnection between dendritic depolarization and neuronal firing is found in fear conditioning (d’Aquin | An operational mechanism independent of neuronal firing (most likely that of the first-person property) is expected to form at the level of the dendrites. | IPL mechanism taking place within the islets of inter-LINKed postsynaptic terminals (IILPs) explains the dichotomy between the operational mechanisms at the dendritic and neuronal soma levels. |
| 161 | Contextual fear conditioning recruits newly synthesized GluA1-containing AMPAR into the spines of the hippocampal memory-ensemble cells in a learning-specific manner (Matsuo et al., 2008). | A mechanistic explanation of how GluA1 subunit insertion into the spines facilitates learning. | GluA1- AMPARs are located nearly 25nm from the synaptic margins (Jacob & Weinberg, 2015). This matches with the lateral spine head region at which IPLs are expected to form. Bringing these subunits in vesicles to the membranes will lead to insertion of some of the vesicle membrane segments to the lateral spine head region facilitating IPL formation. |
| 162 | Autophagy results in memory destabilization and erasure of auditory fear memory associated with AMPAR endocytosis (Shehata et al., 2018). | It is necessary to provide a mechanistic explanation how autophagy leads to loss of memory. | GluA2-dependent AMPAR endocytosis is a prerequisite for autophagy to affect memory destabilization (Shehata et al., 2018). Endocytosis removes membrane segments from the spine head region causing decrease in spine size and reversal of existing IPLs. This can explain loss of memory. |
| 163 | Circuits with same connectivity can function differently (Mardar, 2012). | There are some missing connections within the neuronal circuits that have same synaptic connectivity patterns. | IPLs between the dendritic spines of different branches of different neurons (rarely of the same neuron) proposed by the semblance hypothesis are suitable to fulfill this requirement. |
| 164 | Neither the synaptic connectivity of the neuronal circuit alone nor the computational task carried out by the synaptically-connected neuronal circuitry alone can uniquely determine the mechanism of circuit function (Biswas & Fitzgerald, 2022). | It is necessary to include supplementary circuit rules by a not yet discovered mechanism. | IPL function that can operate in unison with the synaptically-connected neuronal circuitry explains how the system can operate to generate both first-person property concurrent with the option of generating motor outputs & also how motor actions can take place in the absence of first-person properties. |
| 165 | Firing of same single neurons in prefrontal cortex prior to speaking same phonetic words. For e.g. sea & see. (Khanna et al., 2024). | The mechanism that assigns specific words for generating a meaningful sentence must occur prior to neuronal firing that generates the phoneme. A mechanism for first-person meaning + motor output should be present prior to the firing motor output driving neuron. | An operational hub consisting of islets of inter-LINKed spines (IILSs) or postsynaptic terminals (IILPs) is a suitable candidate mechanism to explain how a query makes search among previous relationships in a given context & provide meaningful output (Vadakkan, 2024). |
| 166 | When mice were injected with histone acetyl transferase (HAT) enzyme to increase transcription, strength of fear memory is increased (Santoni et al., 2024) | Fear memory is associated transcription (and possibly eventual translation) to polypeptides. | One possible is explanation is the triggering of the synthesis of more phospholipid molecules that is expected to promote exocytosis, which in turn will increase the number of IPLs. |
| 167 | Firing of LA neurons becomes more synchronized through modulating theta frequency in the LA (Pare´ and Collins, 2000). Synchronous oscillations in the theta and gamma bands occur between the BLA and interconnected structures during retrieval of fear memories and fear memory consolidation (Bauer et al., 2004; Seidenbecher et al., 2003). | Operational mechanism that generates first-person property of fear is associated with oscillations of extracellular potentials. | These can be explained in terms of reactivation of inter-LINKed spines (within several IILPs) on the dendrites of LA neurons. Furthermore, if one of the inhibitory neurons among a set of oscillating inhibitory neurons synapse with a spine of one of the PN neurons that is part of an IILPs, it is expected to modulate synchronization of membrane potentials among those postsynaptic PNs. |
| 168 | Memory retrieval triggers synchronization of rhythmic activity between the BLA & interconnected structures along with reactivation of engram neurons (Bocchio et al., 2017). | Oscillations of potential difference recorded from two locations using differential electrodes need contributions from different vector components. When this is associated with reactivation of engram neurons, it is reasonable to infer that some of the vector components also contributes to the firing of these neurons. | IPL mechanism where the synaptic transmission and propagation of potentials along the IPLs are candidate mechanisms that operates in near perpendicular directions to provide vector components to the oscillating potential differences. |
The following are findings related to long-term potentiation (LTP), an electro-physiological finding that shows numerous correlations with the ability to learn. But a few of its features (e.g. high intensity stimulation, time scales of seconds instead of milliseconds, & sudden drop in peak-potentiated effect (short-term potentiation)) needed explanations to substantiate causation for the ability to learn & memorize. Amongst all, LTP remains the single most finding that provided maximum number of constraints to test the semblance hypothesis. Note: To reach interconnected explanations, sometimes it was necessary to re-interpret the findings from different laboratories and provide alternate explanations different from those of the authors (Please note: I regard this inevitability as an unpleasant, but crucial step in this process). | |||
169 | Experimental finding of long-term potentiation (LTP) has shown several correlations with behavioral motor actions that are surrogate markers of memory retrieval. | It must be possible to explain how cellular changes during LTP induction and learning are correlated & how this is related to the ability to retrieve memory. | High energy applied during LTP stimulation leads to the formation of large number of non-specific IPLs responsible for LTP. 1) More the abutted spines at locations of convergence of sensory stimuli, more the ability to learn, and 2) Application of high energy leads to increased formation of non-specific IPLs responsible for LTP (Vadakkan, 2019). |
170 | Learning takes place in milliseconds, whereas LTP induction takes at least 20 to 30 seconds (Gustafsson & Wigström), 1990), and even more than a minute (Escobar et al., 2007). | Cellular changes during learning are expected to get scaled-up during LTP induction in a time-dependent manner. Need to explain a time-consuming cellular change for this. | High energy delivered by LTP stimulation protocols leads to spine expansion & formation of large number of non-specific IPLs. This opens several channels through which potentials arrive at the recording electrode, showing a potentiated effect. Long duration of persistence of IPLs explains the long-term nature of LTP (Vadakkan, 2019). |
171 | Blockers of membrane fusion blocks LTP (Lledo et al., 1998). | Need to explain the cellular location where they act & explain how they block LTP. | Huge energy applied during LTP stimulation is expected to cause inter-neuronal inter-spine fusion. When blockers of membrane fusion are used, this will not take place, preventing LTP induction (Vadakkan, 2019). |
172 | Loss of spines during LTP induction (Yuste & Bonhoeffer, 2001). | A mechanistic explanation is needed for loss of spines when high energy is applied during LTP stimulation. | High energy applied during LTP induction leads to formation of large number of non-specific IPLs and IPL fusion. IPL fusion leads to triggering mechanisms to stop cytoplasmic content mixing. Removing spines by the neuron will prevent further damage to that neuron. |
173 | CA2 region of hippocampus is resistant to LTP induction. Removal of peri-neural net proteins from this region allows LTP induction. | The cellular mechanism responsible for LTP induction must be able to explain how peri-neural net proteins block LTP. This can provide hints for a structural explanation of LTP. | Based on semblance hypothesis, anything that prevents formation of IPLs blocks induction of LTP. Perineural net proteins around the spine head region (Dansie & Ethell, 2011) provides an explanation (Vadakkan, 2019). |
174 | Hippocampus having convergence of all the sensory inputs has shown maximum strength of LTP. It is possible to induce LTP of different strengths at different locations where inputs converge. | It should be possible to provide an explanation why LTP strength is high at locations where more inputs converge. | Based on the semblance hypothesis, more IPLs are expected to form at locations where more inputs converge (Vadakkan, 2010; 2013). At locations where more IPLs are present, it is possible to generate proportionately more non-specific IPLs responsible for LTP induction (Vadakkan, 2019). |
175 | LTP is associated with enlargement of spine heads (Lang et al., 2004). LTP on single spines show spine enlargement (Matsuzaki et al., 2004). | It is necessary to an explanation how enlargement of spines leads to LTP that can explain all the features of LTP and its correlation with the ability to learn in an interconnected manner. | Spine enlargement favors IPL formation. In the presence of high energy of LTP stimulation, large number of non-specific IPLs are formed, which will allow a regular stimulus to propagate through multiple channels to summate and arrive at the recording electrode (Vadakkan, 2019). |
176 | LTP, kindling, and seizures are strongly interrelated. | A structure-function-pathology relationship exists that must provide interconnecting explanations. | Explained as formation of non-specific IPLs in response to high energy stimuli and pathological conditions causing membrane instability, increased neuronal excitability and ionic changes in terms of alterations of IPLs proposed by the semblance hypothesis (Vadakkan, 2019). |
177 | LTP induction is associated with AMPA receptor sub-unit redistribution into the cytoplasm of the spine head region (Shi et al., 1999; Passafaro et al., 2001). | To provide a mechanistic explanation for inter-neuronal inter-spine interaction during IPL formation, it is necessary to show that vesicles containing AMPA receptors move laterally within the spines. | It was shown that exocytosis of vesicles containing AMPA receptor sub-units is associated with their lateral movement during LTP (Park et al., 2006). |
178 | LTP stimulation needs high energy (either in the form of high frequency or high intensity stimulation). | Need an explanation how this high energy is used to make cellular changes to generate LTP. Correlation between the ability to learn and the strength of LTP that can be induced necessitates an explanation for LTP as a scaled-up change that occurs during learning. | It was possible to explain LTP as a scaled-up change occurring during learning by the formation of large number of non-specific IPLs between the stimulating and recording electrodes (Vadakkan, 2019). This requires high energy since hydration layer between the spine membranes is expected to need high energy for its removal for the formation of an IPL. This can be inferred from experiments using artificial membranes (Rand & Parsegian, 1984; Martens & McMahon, 2008; Harrison, 2015). |
179 | LTP requires a specific postsynaptic fusion protein SNARE (Jurado et al., 2013). | It is necessary to provide a suitable property of this protein in terms of its ability to elicit LTP. | SNARE protein has the ability to bring together repulsive membranes & overcome energy barriers related to curvature deformations during hemifusion (Martens & McMahon, 2008; Olkers et al., 2016). SNARE protein generates force for pulling the abutted membranes together as tightly as possible (Hernandez et al., 2012). t-SNARE protein syntaxin generates local membrane traffic in spines and directs membrane fusion (Kennedy et al., 2010). |
180 | It was possible to induce LTP after blocking NMDA receptors by increasing postsynaptic Ca2+ via voltage-sensitive calcium channels. | A mechanistic explanation is necessary to provide an inter-connected explanation how it was possible to induce LTP by stimulating postsynaptic terminals (spines) alone. | Formation of large number of inter-spine LINKs during LTP induction derived by the semblance hypothesis provides a suitable explanation (Vadakkan, 2019). |
181 | Blockade of exocytosis of AMPA receptor containing vesicle cause severe reduction in LTP (Kennedy et al., 2010; Ahmad et al., 2012). | To provide an inter-connected explanation, it is necessary to have a logical explanation how exocytosis of AMPA receptor containing vesicles is associated with IPL formation. | 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). Vesicle membrane segments contribute to reorganize the lateral spine membrane that can lead to the formation of IPLs. |
182 | Surface expression of any AMPA receptor subunit is sufficient for inducing LTP (Granger et al., 2013). | To provide an inter-connected explanation, it is necessary to have a logical explanation how surface expression of AMPA receptors subunits is associated with IPL formation. | 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). Vesicle membrane segments contribute to reorganize the lateral spine membranes that can lead to the formation of IPLs. |
183 | Potentials from the recording electrode following LTP stimulation does not show a ramp-like increase before reaching its peak. | Sudden rise to peak-potentiated effect following a delay needs a suitable explanation. | Initial formation of small islets of inter-LINKed spines that finally coalesce to form a large islet will lead to a sudden occurrence of a mega-summation of several small, summated potentials (Vadakkan, 2019). |
184 | Persistence of potentiated effect for long duration, which led to the name LTP. | Need a matching mechanistic explanation for the long duration of potentiated effect once LTP is induced. | High energy of LTP stimulation is likely to cause membrane fusion at regions of IPLs. It is difficult for these multiple regions to reverse back. This contrasts with the few nanometers at which IPLs are expected to form during natural learning. Hence, in the latter case, most of them reverse back. |
185 | LTP induction is associated with lateral movement of vesicles containing AMPA receptor sub-units (Makino & Malinow, 2009). However, high energy stimulation alone can surpass the above requirement (Herring & Nicoll, 2016). | It is necessary to provide a suitable explanation for a) what is the function of the vesicles? b) how can application of high energy overcome this requirement? (Note: This is a unique condition. Only when we reach the correct solution, it will become possible to arrive at a suitable explanation.) | Lateral movement of vesicles can contribute membrane segments at the lateral regions of spines (Park et al., 2006) and facilitate IPL formation. IPL formation requires overcoming a high energy barrier (Rand & Parsegian,1984; Martens & McMahon, 2008; Harrison, 2015). High energy stimulation alone can achieve inter-cellular fusion (for e.g. in hybridoma production (Zimmermann & Vienken, 1982). |
186 | Sudden drop in peak-potentiated effect, called short-term potentiation (STP) (Racine et al., 1983). | It is necessary to explain what reverses back immediately after a peak potentiation is reached. At least one factor is getting reversed back very quickly. | Hydration exclusion from the space between the membranes is a high energy requiring process and hemifusion state is highly reversible (Chernomordik & Kozlov, 2008). Hence, immediately following LTP induction, several IPLs tend to reverse back responsible for sudden drop in potentiated effect (Vadakkan, 2019). |
187 | Synapses and synaptic transmission are necessary for LTP induction when stimulating from the pre-synaptic side. | An operational mechanism that can operate concurrent with synaptic transmission is necessary to explain LTP. | Formation of large number of non-specific IPLs is associated with normal operation of the synapses and are necessary for IPL formation during learning (Vadakkan, 2019). |
188 | Non-Hebbian plasticity changes are observed during LTP induction (Schuman & Madison, 1994; Bonhoeffer et al., 1989; Kossel et al., 1990; Engert & Bonhoefferet, 1997). | It is necessary to explain why synapses that are not stimulated also get involved during LTP induction. | When a group of spines expands, it will compress the extracellular matrix around them and the abutted spines across them that are not stimulated by LTP. This can lead to formation of IPLs with those spines and explain the finding of non-Hebbian plasticity (Vadakkan, 2019). |
189 | Field EPSP amplitude is increased (200%) more than EPSP amplitude (60%) recorded from a single CA1 neuron after LTP induction (Abbas et al., 2015; Holmes & Grover, 2006). | An explanation is necessary for the difference in the amplitudes of EPSPs in these two cases. | Since the recording electrode is in the ECM in field recording, it reflects arrival of large number of potentials through a large number of IPLs around it. when one CA1 neuron is recorded, potentials can arrive through the IPLs generated by its spines (Vadakkan, 2019). |
190 | Property of cooperativity in LTP induction. Only a fixed fraction of stimulated presynaptic terminals directly synapses with the CA1 neuron from which recording is carried out. Unless certain cooperative property is present, this will not occur. | Need an explanation for a cooperative function that allows potentiated effect to be recorded from the recording electrode. Since blocking NMDA receptors using Mg2+ alone could not prevent this (Kauer et al., 1988) other routes are involved. | Based on the semblance hypothesis, formation of large number of non-specific IPLs between the lateral portions of abutted spines provide routes through which a regular stimulus can reach the recording electrode after LTP induction. This can be viewed as a cooperative function (Vadakkan, 2019). |
191 | Property of associativity in LTP induction. It is potentiation of a weak input if it is activated along with a strong tetanus at a separate location, but as a converging input (Levy & steward, 1979). | It is necessary to explain what is connected during this procedure that will later allow the weak input to bring potentiated effect at the recording electrode. | The convergent nature of the inputs allows separate islets of inter-LINKed spines from the weak and strong stimuli to become connected through the formation of IPLs between them. This will allow both islets to get connected with that of the recording CA1 neuron. Hence, a weak input will be able to propagate through multiple channels and arrive at the recording electrode in a summated form (Vadakkan, 2019). |
192 | Property of input specificity in LTP induction (Andersen et al., 1977). A strong stimulus can induce LTP, whereas a weak stimulus will not. Weak inputs that are active only at the arrival of strong stimulus share the potentiation induced by the strong stimulus. | A mechanistic explanation for a process that requires simultaneity of stimulation of both the weak and strong stimuli is needed. | Simultaneous application of the strong and weak stimuli at optimal distances will be necessary to generate IPLs between the separate islets of inter-LINKed spines that these stimuli generate if they are stimulated independently. Note that IPL formation requires removal of hydration layer between abutted spines, which is a high energy requiring process (Rand and Parsegian, 1984; Martens and McMahon, 2008; Harrison, 2015). |
193 | Learning can be occluded after LTP induction and vice versa (Moser et al., 1998; Whitlock et al., 2006). | It is necessary to provide a mechanistic explanation for a shared mechanism following LTP induction and learning. | LTP induction leads to the formation of a large number of IPLs in a localized area. Hence, learning following LTP induction will not to be able to generate new IPLs at that location. As the cue stimulus propagates (during memory retrieval) through the large number of non-specific IPLs formed by LTP induction, it generates a large number of non-specific semblances. This explains reduced memory observed in those experiments. |
194 | Dopamine augments both (motivation-promoted) learning (Bromberg-Martin et al., 2010) and LTP (Otmakhova & Lisman, 1996). | It is necessary to show that both learning and LTP have a shared common mechanism, and dopamine operates to augment both learning and LTP by the same mechanism. | Augmentation of both motivation-enhanced learning and LTP can be explained in terms of enlargement of spines caused by dopamine (Yagishita et al., 2014) that can augment IPL formation. |
195 | Most learning changes are short-lasting, capable of generating only working memories. But LTP is long lasting (hours). | It is necessary to find a mechanistic explanation for rapidly reversing learning changes and why the scaled-up learning change in LTP is resistant to reverse back. | Most IPLs are reversible since their formation during learning by exclusion of hydration layer between spine membranes is a high energy requiring process. In contrast, LTP stimulation uses very high energy during which physiological IPL changes are expected to progress to membrane fusion that offer resistance to reversal. |
196 | Inhibitors of NMDA receptors do not reverse late LTP maintenance (Day et al., 2003). | Need to explain a change that is maintained during late stage of LTP, which cannot be revered by inhibiting NMDA receptors. | Since IPL changes between lateral margins of spines that belong to different neurons already occurred during LTP induction, NMDA receptor inhibition will have no role in LTP maintenance. Moreover, IPL fusion changes produced by LTP induction are highly resistant to getting reversed back. |
197 | LTP decay and memory loss are mediated by AMPA receptor endocytosis (Dong et al., 2015). | It is necessary to explain how AMPA receptor endocytosis can reverse LTP induced changes. | Endocytosis of AMPAR subunits that uses membrane segments from the lateral spine region is expected to reduce spine size & lead to reversal of the IPLs. This can explain LTP decay. |
198 | GluA1 subunits have a main role in directing AMPA receptors to the surface, which is correlated with LTP and fear memory (Rumpel et al., 2005). | A mechanistic explanation how GluA1 subunit insertion into the spines facilitates both LTP & learning (& also memory). | GluA1- AMPARs are located nearly 25nm from the synaptic margins (Jacob & Weinberg, 2015) that are lateral spine head regions at which IPLs are expected to form. Since these subunits are brought to the surface by vesicles, it promotes incorporation of membrane segments to this region & facilitate IPL formation. Based on the semblance hypothesis, the latter is the basis for both learning and LTP induction. |
199 | mEPSP is thought to be influenced by an increase in the number or function of AMPA receptors (Malenka & Nicoll, 1999). It is necessary to show the source for increased AMPA current. | Recording electrode is electrically connected with neighboring spines through IPLs. This allows arrival of current from neighboring spines which mostly belonging to different neurons, which mostly belonging to different neurons, showing increase in the size of mEPSP. | |
200 | Several delayed changes that occur following LTP induction have shown correlations with learning & memory (e.g. CaMKII phosphorylating AMPA receptor subunits (Lisman et al., 2012). | It is necessary to explain how delayed changes following LTP are correlated with animals' ability to learn. | A downstream cascade of biochemical changes within the neurons can be viewed as steps to prepare the spines both to maintain the already formed IPLs and to generate new IPLs during subsequent learning events. |
201 | LTP induction is known to modify specific sets of place cells. Specifically, LTP in hippocampal pathways abolish existing place fields & create new place fields (Dragoi et al., 2003). | It is necessary to provide a mechanistic explanation of how changes brought about by LTP induction affect firing of place cells (CA1 neurons in the hippocampus). | Formation of a large number of new IPLs induced by LTP can lead to the spread of potentials through these IPLs and result in firing of additional postsynaptic CA1 neuron (Vadakkan, 2016). |
202 | Small spines were found to be preferential sites for cellular changes causing LTP induction (Matsuzaki et al., 2004). | It is necessary to explain what particular feature of small spines in contrast to large spines lead to LTP induction. | Large spines are likely to have already formed IPLs with their abutted spines. Hence, they are unlikely to form additional IPLs during LTP induction. In contrast, small spines have the ability to expand in response to LTP stimulation and form several new IPLs responsible for the potentiated effect. |
203 | Associative LTP can be induced more easily in new granule neurons (Schmidt-Hieberet al., 2004). | It was explained in terms of a reduction in the threshold for inducing LTP. It means that new neurons are devoid of certain channels. It is necessary to show that LTP is able to introduce these channels on them. | This can be explained in terms of the formation of several IPLs between the spines of new granule neurons (compared to the old ones) with the spines on the pre-existing islets of inter-LINKed spines of existing granule neurons (Vadakkan, 2016). |
204 | Fear conditioning induces associative LTP in the amygdala (Rogan et al., 2007; McKernan & Schinnick-Gallagher, 2007). | Provide an explanation how learning causes a potentiated effect at the MGN-LA synaptic area. In other words, show how fear conditioning alters auditory CS-evoked responses in LA in the same way as LTP induction. | Based on the semblance hypothesis, LTP can be explained by the formation of a large number of IPLs between a set of spines through which high energy current flows (Vadakkan, 2019). Here, spines of both different LA neurons & different branches of the same LA neuron (since the output function is the same - foot shock) undergo form IPLs. |
205 | Dendritic spikes mediate a stronger form of LTP that requires spatial proximity of associated synaptic inputs (Hardie & Spruston, 2009). Dendritic spike is a mechanism for co-operative LTP (Golding et al., 2002). Dendritic spikes are necessary for single-burst LTP (Remy & Spruston, 2007). | One of the requirements of LTP is postsynaptic depolarization that can result from large EPSPs that trigger dendritic spikes (Hardie & Spruston, 2009). Dendritic spikes generate a stronger form of LTP than alternative methods (Hardie & Spruston, 2009). In these contexts, it is necessary to show the source from which potentials arrive to generate large EPSPs. | Simultaneous arrival of input signals to two or more synapses whose spines (postsynaptic terminals) are inter-LINKed will lead to summation of EPSPs resulting in large EPSPs recorded from any single postsynaptic terminal (Vadakkan, 2016). |
206 | A modified fear conditioning study using two associative learning events with one common stimulus where inputs are synapsing on to one type of output neuron (Lateral amygdala (LA) neurons (Abdou et al., 2018). Stimulation of autophagy in LA neurons following one learning erased its memory. Optical LTP allowed anisomycin treated mice to completely recover amnesia. | It is necessary to explain how stimulation of autophagy within the postsynaptic LA neurons erases memory of a specific associative learning through inputs arriving through axonal terminals that synapse on to the LA neurons. The mechanism of storage is not reversible by protein synthesis inhibitor. Hence, a non-protein involved mechanism needs to be explained. | Based on the semblance hypothesis, during learning an IPL is generated between the spines of different LA neurons (Fig.19 in FAQ). When the motor output function is the same, then IPL can be formed between spines that belong to different branches of the same LA neuron (Fig.2 of the Home page). Stimulation of autophagy in LA neurons will cause increased endocytosis, removing membrane segments from the lateral spine head region. This will reduce the size of the spines sufficiently to reverse the learning generated new IPLs. After introduction of autophagy there will be recycling of membrane segments back to the spine heads to a certain extent to cause many spines to get abutted back. Optical LTP provides huge energy to the input terminals sufficient to generate IPLs in abutted spines. It also leads to spine expansion favoring IPL formation. |
207 | In the above study (Abdou et al., 2018) using modified fear conditioning experiments, optical LTD caused loss of a memory of a specific learning. Optogenetic stimulation of axonal terminals of AC & MGN neurons did not cause freezing in LTD induced animals. | Optical LTD does erases specific associative learning change. This should be such a change that cannot be reinstated by optical stimulation of the axonal terminals of AC & MGN neurons. | Modest depolarization used in LTD cause AMPAR endocytosis (Malenka,1994). Endocytosis removes membrane segments from the lateral spine head regions causing reversal of formed IPLs. This leads to loss of memory of a specific event. Ordinary stimulation of input terminals will not be able to cause memory retrieval due to the absence of IPLs since a) LTD is usually long lasting keeping the reversed IPLs in baseline non-LINKed states, & b) ordinary optogenetic stimulation has no sufficient energy for spine expansion to the level necessary for IPL formation. |
IPL: Inter-postsynaptic functional LINK; ECM: Extracellular matrix; NAc: Nucleus Accumbens; MSNs: Medium spiny neurons; FLE: Flash lag effect. Foot note 1: If we present a set of colors, each paired with a corresponding image, and ask individuals to learn the associations within one second, most people will successfully form two or more associations in that brief period. This indicates that associative learning can occur within milliseconds. What kind of change is capable of happening in such a short timespan? | |||
Table 2. Features of the system from different levels that need to be explained independently and by an inter-connectable manner using a derived solution. In other words, these constraints permit us to ask the question, "What should be the foundational operation that can satisfy all these constraints?" Even though several possibilities can be excluded (for example, biochemical reactions that occur slower than the physiological timescales of milliseconds during which learning takes place (using which memory needs to be retrieved) that can help exclude candidacy of several biochemical intermediates such as storage molecules), a systematic approach is necessary to find the correct solution. Please note that the listed findings are so disparate, and the constraints offered by them are so strong that there can only be one unique solution. In other words, this unique solution for the system should be compatible with all the previous experimental observations. Constraints provided by each of the observations help to narrow down the possibilities to arrive at the solution. A subset of the above list of observations can be used to derive the solution and the rest of the features can be used to verify whether the derived solution is correct or not. Please note that we cannot arrive at a solution using a few mathematical equations. Once we have a unitary solution, we need to search for the principle of their integration where mathematics is expected to have a role. | |||
A complete understanding of the operational mechanism leading to the first-person properties will only be achieved by carrying out the gold standard test of its replication in engineered systems. Even though replication of motor activities (such as speech) to produce behaviorally equivalent machines may seem adequate, the work will not be complete until first-person properties of the mind are understood. Engineering challenges with this approach include devising methods to convert the first-person accessible internal sensations to appropriate readouts. Experiments to translate theoretically feasible mechanisms of its formation both by computational and engineering methods are required. Feasibility to explain various brain functions both from first-person and third-person perspectives qualifies it as a testable hypothesis. The present work resulted from curiosity to understand the order behind the seemingly complex brain functions. In this attempt, I have used some freedom to seek a new basic principle in order to put the pieces of the puzzle together. This work wouldn't have become possible without a large amount of research work painstakingly carried out by many researchers over several years. Even though the present hypothesis is compatible with experimental data from different levels, it must be considered unproven until we complete its verification.
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. The rigor with which we should try to solve the nervous system must be with an intention to replicate its mechanism in an engineered system. Everything else will follow.
The reality: We are being challenged to find a scientific method to study the unique function of the nervous system - how different inner sensations are being generated in the brain concurrent with different third person observed findings. We cannot directly study them using biological systems. But we can use all the observations to try to solve the system theoretically, followed by verifying its predictions.
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 expectation: We are likely able to solve the mechanism of the nervous system functions in multiple steps. First, using constraints offered by all the observations, it is necessary to derive a solution (most likely a first principle) that can unify those observations. This can be followed by further verification by triangulation methods and examining comparable circuitry in different animal species. Once identified and verified, we can expect to replicate the mechanism in engineered systems.
The advice: "Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less." Marie Curie
The hope: We will give everything we can. Together, we will explore it!