Semblance Hypothesis

  (towards a theory since 2017)

by Kunjumon Vadakkan 

Objective: To understand how first-person inner sensations of higher brain functions occur both independently and along with third-person observed behavioral motor actions.


Dedication: This website is dedicated to all those who suffer from diseases of the nervous system.

How to understand something that cannot be accessed by our sensory systems? A method used in physics

Has learning-mechanism got features of an evolved mechanism?

There is no need for a separate mechanism for working memory

How is learning related to LTP induction? An explanation

Extreme degeneracy of inputs in firing a neuron

Does the brain do retrograde extrapolation?

Importance of triangulation in verifying a mechanism 

Testable predictions made by semblance hypothesis

Perception from a first-person frame of reference

Without sleep, there is no system! An explanation

Why do we need a first-person neuroscience?

Internal sensation - A comparison with electromagnetism


In simple words, what is semblance hypothesis? Systems in the body are being studied by observing them from outside (e.g. pumping of the heart, filtering by the kidneys, structure of DNA and synthesis of proteins). Third-person approaches are suitable for their studies. In contrast, functions of the nervous system such as perception, memory and consciousness are first-person inner sensations (within our "mind") to which only the owner of the nervous system has access. However, we have been studying these functions by examining the nervous system from outside by third-person approaches at various levels (biochemical, cellular, systems, electrophysiological, imaging, and behavioral) and trying to find correlations between these findings with an aim to understand the system. By these approaches, the first-person internal sensations of all the higher brain functions remain unexplored. The reality is that the examiner should become an insider in a subject's nervous system (and become part of the system) to sense the first-person internal sensations! This is not practically possible. This means we are facing a “frame of reference” problem in our current approaches to understand its operations. This can be overcome by undertaking a theoretical approach. Since it is expected to be a universal operational mechanism in the nervous systems of different animal species, we should be able to find it without much difficulty if we are on the right path. We had no previous experience of examining for a biological mechanism that gives rise to virtual first-person inner sensations. This should not hinder our examination in any way. In fact, we must prepare ourselves to look for a unique mechanism that has the ability to evade our attention! By keeping these in mind, a theoretical examination was carried out to arrive at a specific location where such a unique mechanism can be expected to take place. Further examination of this location has enabled identification of a set of unique features necessary for a feasible operational mechanism whereby the system can generate units of inner sensations at specific conditions (that are physiologically present). This mechanism is expected to interconnect all the findings made by third-person approaches at different levels. Until now, results using this observation are able to explain and interconnect a large number of findings from different levels. Pathological changes of the expected cellular mechanism can explain several neurological and psychiatric disorders. Predictions made by this hypothesis are testable.

Is there an alternate way to view semblance hypothesis? In order to understand the brain, we must understand how its unique function – generation of first-person internal sensations of perception, memory, and thought processes is taking place. Associative learning between two stimuli is expected to induce certain changes (in a few milliseconds) that allow one of the associatively learned stimuli (cue stimulus) to induce the internal sensation of memory of the second stimulus (in a few milliseconds). For this to occur, changes during associative learning are expected to take place at the locations of convergence of sensory stimuli within the brain. Here, we need to ask the following questions, “Is there a possible cellular location of convergence between the processes of neurons through which associatively learned sensory inputs arrive?" "Can associative learning induce certain changes at this location (in a few milliseconds), which can be used by one of the stimuli (the cue stimulus) to induce internal sensation of memory of the second stimulus (in a few milliseconds)?” “At what structural location and by what mechanism does the cue stimulus spark internal sensation as a first-person property?” “What is necessary to spark internal sensation?” “What is the basis for sensory features or qualia of internal sensation?” “What holds the system together that allows the cue stimulus to induce first-person internal sensation of the second stimulus?” "How can the mechanism that holds the system together relate to the narrow range of frequency of extracellular potentials at which both learning and memory retrieval take place?" "Is there a mechanism that can integrate internal sensations induced at different points of convergence to provide memory?" "How does the mechanism of generation of internal sensations relate to behavioral motor activity?" “Can the derived mechanism be extended to explain different brain functions in an inter-connectable manner?” If we look hard enough, we are expected to find a mechanism that can explain all the above features at the location of convergence of sensory inputs. When an inquiry was made to solve this puzzle, it was possible to derive a solution. This testable hypothesis was named semblance hypothesis.

Is it possible to explain semblance hypothesis by yet another way? Currently, studies of the nervous system face three major issues. 1) It was not possible to view memories in their true sense as first-person internal sensations and understand their operational mechanism. Due to this reason, memories are being studied using their surrogate markers such as speech or behavioural motor activities. 2)  Current investigations are primarily based on the following postulate made in 1949 by Professor Donald Hebb. "When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency as one of the cells firing B is increased" (Hebb D. O. The organization of behavior. New York: Wiley & Sons). Modification of this postulate is generally known as synaptic plasticity thesis. This thesis has not been able to provide a mechanistic explanation how learning-induced changes are used for the generation of internal sensation of memory. 3) Behavioral markers of memory retrieval are being correlated with the firing of a set of neurons with the hope to understand the mechanism. The very fact that only a minor fraction of inputs (nearly  randomly arriving 140 inputs) can fire a cortical neuron having thousands of dendritic spines shows extreme degeneracy of inputs in firing a neuron. Postsynaptic potentials attenuate as they propagate towards the neuronal soma. Since many neurons are being held at sub-threshold activation states at rest, it is possible that even fraction of one postsynaptic potential can fire a neuron from its resting state. In these contexts, to avoid loss, information storage must be taking place using a mechanism occurring at the location of origin of postsynaptic potentials. This storage mechanism is also expected to provide an explanation how first-person internal sensation of memory is generated. Dendritic spikes that have similarities to the neuronal spikes (neuronal firing) prompts us to re-examine the system. In the past, we started with certain notions that operating mechanism is occurring at the synapses or that a neuron is the operational unit of the system in the absence of supporting scientific basis. These were necessary to initiate experimentations. Since we have already spent enough time to test these ideas and since we are not approaching towards any foreseeable solution to understand the first-person internal sensations of various higher brain functions, we should try to develop a scientific approach to solve the system. During the last several decades, we have made very large number of observations at different levels of the nervous system. Now, we are in a position to use constraints available from all these observations to try to derive a theoretically-fitting testable mechanism that can explain how first-person internal sensations are being generated. If successful, this will provide a solid scientific basis for the mechanism that we are seeking. The mechanism is expected to operate in synchrony with the synaptically-operating nervous system and takes place at physiological time-scales of milliseconds. It is also expected to operate in agreement with the observation that there is a huge redundancy in inputs that can fire a neuron. If a hypothesis can explain all the features of the system in principle, then we can start verifying both its structural features and predictions. Semblance hypothesis resulted from this approach.

Can we explain semblance hypothesis by a fourth method using some pictures? The unknown mechanism is shown as a blackbox in Figure 1 below. The content of this black box is shown at the bottom of the FAQ page.

Black Box of the Nervou System

Figure 1. How to solve the black box of the nervous system? A) Let us imagine that we are associating two sensory stimuli in a learning event. Stimulus 1 and Stimulus 2 activate their sensory receptors and the stimulus-induced depolarization propagates through their synaptically-connected neuronal paths (Neurons along their pathways are numbered from N1 to N4). We want to know where and what type of a change occur during learning, so that at a later time when Stimulus 1 arrives as a cue stimulus, it can generate an internal sensation of features of Stimulus 2, which we call as a memory of Stimulus 2. It should also explain how this can produce behavioral motor actions reminiscent of Stimulus 2. If we can provide an explanation for this, we are moving in the right direction for solving the nervous system. B) A synaptic junction between two neurons (marked Pre 1 and Post 1) along the path through which Stimulus 1 propagates is shown. Current studies examine changes occurring presumably at all the synapses along the pathways through which both Stimulus 1 and Stimulus 2 propagate during learning. During memory retrieval, it tries to correlate the learning changes at the synapses with behavioral motor actions indicative of memory retrieval. To understand causation, our task is to use all the available information and examine the exact location where and how the learning-change is occurring that allows one of the stimulus (cue stimulus) to spark memory of the associatively learned second stimulus at physiological time-scales of milliseconds along with provisions for generating behavioral motor actions. C) The still unknown mechanism is shown as a large black box next to the synapse. To decipher the secret, it is necessary to view memories as first-person inner sensations generated within milliseconds. Since learning can occur in milliseconds, it is also necessary to search for a learning mechanism that occur in milliseconds from which memories can be generated. Semblance hypothesis has provided 1) a solution for the contents in this black box that can explain how the association between Stimulus 1 and Stimulus 2 is stored during learning, and 2) at a later time when the Stimulus 1 arrives (as a cue stimulus) how it generates the internal sensation of memory of Stimulus 2 as a first-person property that can only be accessed by the (owner of the) system. It also explains how the Stimulus 1 (cue stimulus) can generate motor actions reminiscent of the arrival of Stimulus 2 as expected of a conditioning paradigm. In addition, it explains a large number of features of the nervous system observed at different levels. Please read this page and go through the FAQ section on the next page. If you have already done this before, a summary figure showing the contents of this black box is posted at the bottom of the FAQ section on the next page.

There are several unsolved problems in neuroscience (Adolphs, 2015) and they have been observed from different levels (Edelman 2012; Gallistel & Matzel 2013). The challenges in understanding the nervous system can be viewed in different ways as follows. Nervous system functions observed at different levels are being studied by different faculties of science - biochemistry, cell biology, electrophysiology, systems neuroscience, psychology and consciousness studies. The system is similar to a puzzle lying in multiple dimensions. Solving it requires finding the correct pieces of the puzzle at the right level with the right operational function so that it can be used to build the system from which formation of all the functions can be explained. Solving the system is also necessary to troubleshoot its disorders, for example to treat psychiatric disorders. If we examine only one or a few levels of the system, we might find some solutions that will allow fitting together pieces of the puzzle, but only for those few levels. Features of the unexamined levels will remain unexplainable and we won't find the solution for the system. The diverse nature of different functions strongly indicates that the solution is going to be a very unique one. At the same time, it is also expected to be a simple one. In order to solve the system and find out the correct operational units, it is necessary to simultaneously examine representative functions from all the levels.

    A second view of the problem can be described as follows. It begins by examining the following situation: The heart pumps the blood and the kidneys filter the waste materials from the blood; these functions are observed by us from a third-person perspective. We understood their functions quite well, as evidenced by our ability to develop methods to replace their functions - using artificial heart and dialysis. What functions does the nervous system carry out? Knowledge of the function of the brain that is essential for replicating/replacing it? Brain creates an inner sense of the external world during perception, stores sensory information by associative learning and later produces the internal sensation of retrieved memories of the learned item when the associatively learned cue stimulus arrives at the system, induces thought process to connect different items from different sets of learning for solving problems – all of which are first-person properties that cannot be accessed by others, the third-persons. The only sensory stimuli from the owner of the nervous system that are available to a third-person are from the surrogate markers consisting of motor activity - specifically, speech and behavior. Therefore, the pieces of the puzzle mentioned in the above paragraph should be capable of explaining both first- and third-person detectable functions.


    A third view of the problem become evident when examined from the viewpoint of a builder. Here, the job is to replicate the nervous system in an engineered system. The real problems in solving the system will become very clear by taking this approach. Since intentionality to feed and carry out all the actions for survival and reproduction are present even among the members of lower level animal species, a robust evolutionarily conserved circuit mechanism for generating internal sensations is expected to be present in all the nervous systems. Since the first-person properties cannot be accessed from a third-person approach, they cannot be studied using biological systems. Therefore, we should keep replication of the mechanism in engineered systems as the gold standard proof. These systems need to be built to provide readouts for the first-person internal sensations that can be accessed by the third-persons. As a builder, we will feel the pressure to know how the system can operate all the different functions. We are forced to speculate all the possible mechanisms and figure out the correct one. We will be concerned mostly to explain the formation of internal sensations at physiological time-scales. Before building the system, we need to make sure that we can draw a sketch of the systems operations.


A fourth view becomes possible when we observe the “loss of function” states of the system occurring at various levels. Mother Nature has provided us with this excellent  tool set of “loss of function” states that can help understanding the nature of the pieces of the puzzle. Early years of genetics research have gained valuable information from "inborn errors" of metabolism that provided guidance to understand the alleles of genes. In this context, examining the neurological and psychiatric disorders can help understanding the nature of the operating mechanism. Since the exact pathological features of many of these diseases are not yet known, it is expected that the loss of function of the operational units that induce both the first- and third-person features should be able to provide information about the nature of their pathologies from which the function can be deduced.


Based on the above challenges, a conclusion can be arrived that for arriving at an operational mechanism that can explain both third- and first-person properties, a theoretical approach is the most efficient method. This led to the development of the semblance hypothesis. Of the different higher brain functions, memory has a special advantage in that it can be tested at various levels (induction, storage, maintenance, and retrieval at the structural and functional levels). Studies were carried out by examining how the first-person internal sensation of memory is formed at physiological time-scales using electro-physiological properties compatible with cell biological features. Further examinations were carried out to test whether the same mechanism or its derived operations can explain findings from different fields of neuroscience research. These included findings that are unsolvable when examined by third-person observations. A hypothesis was published first as a book in 2007 (a copy is uploaded in Publications section). Revised editions were published in 2008 and 2010.

Among different brain functions, memory has the advantage that experiments can be carried out both to associatively teach the system and then verify how learning-induced changes are used during memory retrieval. Very large amount of experimental data is available in the field of memory research. Retrieved memories are assessed using behavioral motor changes such as speech or motor activity occurring at the time of memory retrieval. Since no cellular changes are observed during memory retrieval, the memory retrieval is likely taking place by a passive reactivation of a learning-induced change. Since molecular or electro-physiological changes are not observed during memory retrieval, current studies are limited to examining changes taking place at the time of associative learning. Memories were classified into working, short-term and long-term memories based on the differences in the period of time, following learning, during which they can be retrieved. Studies have been carried out with the assumption that the cellular mechanisms during learning that leads to memories classified in this manner are different. Since qualia (virtual first-person internal sensations) of these retrieved memories are almost same, it prompts one to ask, "What if a) a common cellular mechanism is taking place during learning, and b) the retrieval of different types memories (currently classified) can be explained by reactivations of learning-induced changes that are retained for different durations?" One may also ask, "Can we directly examine the memories themselves instead of examining the motor activity such as behavior and speech at the time of memory retrieval?" This will also eliminate our dependence on correlating memories with slow molecular changes occurring after learning. In this context, it is necessary to re-examine the question: "What are memories?" Memories are first-person virtual internal sensations of an item (in the absence of that item) induced within the nervous system (in response to a cue stimulus or occurring spontaneously). Sensation of a stimulus in its absence is hallucination. Therefore, memories can be viewed as cue-induced hallucinations. Can we search for a mechanism that can induce virtual first-person internal sensations of memory? What can spark hallucinations in a cue-specific manner?

Large number of features observed by different branches of neuroscience and psychology are required to be explained by a solution for the system. Since these features are very diverse, only a unique cellular mechanism will be able to explain all of them. This unique mechanism is expected to be a unique structure-function mechanism occurring at the intersection between the third-person observed features and first-person properties. In other words, it is a dynamic, but stabilizable structural feature that can provide basic units of first-person internal sensations of different higher brain functions. It is necessary to verify whether the derived solution can explain findings from different specialized faculties within the large fields of neuroscience and psychology and test whether the explanations are inter-connectable. Since our current research efforts in each field are moving towards more specialized and super-specialized areas, finding and verifying the unique solution (to put the pieces of the puzzle together) require an effort in the opposite direction. Anticipating this is the most important requirement for solving the system. It is necessary to explain how the nervous system functions occurring at different levels, such as - a mechanism that directs potentials to induce the internal sensation concurrent with the activation of motor neurons at physiological time-scales (interconnecting central mechanism), dendritic spine changes, long-term potentiation, place cell firing, consolidation of memory, and association of memory with a feasible framework for consciousness - are interconnected.

In summary, there are three main reasons why we were not able to solve the nervous system.
1) Frame of reference problem: Every time we had a frame of reference problem in the past, we needed to pause for some time to make further progress. Examples include a) Difficulties in sensing the rotation of Earth (note that the speed of rotation of Earth on its axis is 1670km per hour). Our sensory systems cannot sense rotation of Earth since we are located in the same frame of reference as that of the Earth. b) Special and General relativity - while moving at the highest possible velocities by humans, our sensory systems cannot sense any changes in time or length. But calculations show that at velocities close to that of light, time slows down. The predictions made by relativity theory were found true. It is currently being used to make corrections in instruments that are used to locate positions on Earth using satellite transmission.

Even after finding the correct solution, our sensory systems continue to face the original frame of reference problems! This is inevitable. For example, we can only sense the movement of the Sun and not the rotation of Earth. But, what is important is that we can recognize the truth behind it. It is obvious that the major function of the nervous system is generation of internal sensations within it (which we call as "mind"). These are first-person internal sensations to which third-person observers do not have any access. So, here we have a frame of reference problem. Until now, only physics has developed methods to solve frame of reference problems mentioned in the above paragraph. In the case of the nervous system, we need to use the principles of methods used in physics to cross the frame of reference to become successful in solving it. Since this is new for neuroscience, there will be some difficulties in thinking about it in the beginning. But eventually, we will appreciate the problem and will move towards the correct solution.  

2) Difficulty to study the “virtual”: An associated feature is the virtual nature of first-person inner sensations. We have the history of becoming comfortable with several areas that are virtual in nature. Some of them are so frequently used that we don’t even think about it as virtual any more. Mathematics provides good examples with different flavors of virtual nature. Numbers do not exist. We made them. In fact, they are virtual in nature. We can say that they represent real counts of items. What about negative numbers (integers?). They can exist only in our imagination. Yet, we use them routinely in mathematics. On a graph, we don’t feel their virtual nature at all. Going one more step further, we have invented complex numbers (imaginary number). This solved our difficulties to find square roots of negative integers, which helped to further advance mathematics. In a similar manner, once we understand where and how units of inner sensations are sparked within the system, we will be able to perceive a virtual space where we can locate them and navigate that space to understand their different conformations.

3) Access problem: Characteristic feature of the nervous system is that inner sensations of various higher brain functions such as memory and perception occurring within a person's brain cannot be accessed by our (third-person's) sensory systems. So this leads to the most difficult question that we are facing, "How to understand something that cannot be accessed by our sensory systems?" There are several examples where we are comfortable with solving this access problem. For example, we cannot see DNA inside cells or in a gel. But we stain it with ethidium bromide that will allow us to see the stain through our eyes. This means that our access problem is only one step away from what we can sense using our sensory system (here, our eyes). We sometimes go two steps. For example, we use a primary antibody to an antigen, followed by a secondary antibody with a color that can then be visualized through our eyes. Even though our sensory systems do not have direct access, we believe in the presence of the antigen based on the logic and reason that we apply (stringent washing in between the steps is one criterion). We also verify its related features. After using this method few times, we get used to it and become comfortable in using this method to discover properties of Nature that cannot be directly sensed by our sensory systems. 

How can we solve the nervous system?

By continuing the process explained in the last paragraph, we can approach more difficult situations. As we face situations that have more steps away from reality, we have to rely on our logic and reasoning capabilities. We also have to use more stringent criteria. Unlike examples of staining explained above, the case of the nervous system is different. Here, we have a very large number of findings from different levels and we have to discover the solution. First, we have to make sure that the system operation is taking place through the generation of unitary mechanisms that get integrated at physiological time-scales. Evidence shows that this is the suitable operational mechanism when a finite system has to generate internal sensations of an infinite number of items and events from the environment (see the FAQ and Publication sections). Therefore, the solution that is expected to generate units of first-person inner sensations of memory from a learning-induced change is expected to occur at the deepest level and interconnect all the findings of the system. The following may serve as an example. When we used to visit a new city before the internet was available, we sometimes walk from our hotel in one direction for 1 kilometer to reach an intersection. Then, from that intersection we may walk towards the right side for another 1 kilometer. On our way back to our hotel, we might wonder whether we can make a short cut through the hypotenuse of the right angled triangle that we already travelled. We arrive at such solutions from our day to day experience. What if we turned many times to reach a destination? In this case if we need a short cut towards our original location, we should have made a drawing of the angles and distances that we traveled. Missing one angle or distance will not help us to reach back towards our original location through the shortest possible route.

Finding a solution for the nervous system requires to use methods applied in all the above examples to overcome a) the frame of reference problem, b) the access problem, and c) to deal with the virtual nature of internal sensations. But, what if we cannot sense one part of the solution directly by our sensory systems while trying to find the solution? In this case, it is possible to seek examples of approaches that are used by other fields of sciences. For example, physics study particles and fields that are not accessible to our sensory systems. What is the deep underlying principle behind their success? A summary is given in Table 1 below. The deep underlying principle of their studies is taken from the method used in linear algebra for solving a system of large set of linear equations that has a unique solution. If one tries to solve a system of linear equations having a unique solution, one can find that the relationships between the variables in the equations guide us towards the solution. If there are a large number of variables, there should be an equal number of equations to find the unique solution. Since there is a large number of findings that show their relationship with each other at different levels of the nervous system, we can (and we must) use all the non-redundant relationships to find the solution. It is a gigantic exercise since there are no easy methods in biology like that are used in linear algebra; for example, Gauss-Jordan elimination method. (If we look carefully, we can see that easy methods in linear algebra were designed by someone who understood the deep underlying principle and worked on to make it simple for others. We can examine how the relationships between variables in each equation defines the unique solution for a system of linear equations and how Gauss-Jordan elimination method was invented). It is to be noted that we can also solve linear algebra problems using trial and error methods. But it may take some extra time. In other words, mathematical methods are used for convenience. Whichever method is used, the deep underlying principle is the same - A system exhibiting a large number of disparate findings (equations) most likely has a unique solution that binds (interconnects) the findings (equations) within that system. By finding a solution that can interconnect a subset of findings and by repeating this approach using different subsets of findings, one can hope to reach a common overlapping solution, which is the correct solution. One can start attempting to solve the (nervous) system by using subsets of disparate findings from the list in Table 2. The optimism with this approach is that there is only one unique solution and it is easy to verify whether the derived solution is correct or not.



1) First, a large number of observations are made that appear to be disparate in nature. This means that these findings cannot be explained in terms of each other. 1) There are a large number of disparate findings in neuroscience (see Table 2) that need inter-connectable explanations. Example: How does the operation of the system related to sleep and also to the electrophysiological finding of LTP?
2) The above indicates the presence of a deep underlying principle that should interconnect these disparate observations. 2) There should be a deep underlying principle behind all those observations in Table 2.
3) The effects of the above principle are the ones (e.g. particles and fields) that cannot be directly sensed by our sensory systems. 3) There is a principle, the products of which (inner sensations) cannot be sensed by our (third-person's) sensory systems. Yet, the principle of the mechanism should be able to explain and interconnect all the observed findings.
4) The next step is to search for any possible solution that can interconnect all the findings. Constraints provided by disparate observations are what guide towards the solution. This is done either by initial deduction followed by mathematical approximations (Special and General Relativity) or by pure mathematical derivation (Higgs Bosons). 4) A structure-function mechanism has to be sought by logical deduction & trial and error methods. All the constraints offered by a large number of findings can be used to derive the solution. Success depends on moving through the path by taking guidance from all the constraints. Only when we reach the correct solution, we will be able to explain all the findings in an interconnectable manner.
5) The solution is then confirmed by verifying the predictions that can be made by the solution. 5) Testable predictions made by the derived mechanism can be verified.

Table 1. Steps that are taken by physics when it tries to unify different findings, which usually result in the discovery of particles and fields that are not accessible to our sensory systems. These steps are numbered from 1 to 5. A parallel approach is necessary to understand the non-accessible first-person internal sensations formed in the brain (given in the right column). The key in this approach is to undertake a theoretical approach that will allow us to derive a solution that can be verified by testing for its predictions. 

Using the above principle, constraints provided by findings from various levels (Table 2) were used during the derivation of a testable mechanism that can explain and interconnect findings made by different faculties of brain research. It is a testable mechanism occurring during learning that can be reactivated at the time of memory retrieval to induce basic units of internal sensation whose computational product can provide sensory qualia for the retrieved memory. Structural and electrophysiological changes that are expected to occur from these changes are explained using experimental results from different laboratories.  


Constraints offered by findings (on the left side) that direct the enquiry towards a correct solution/ What needs to be explained?

Nervous system is made of synaptically-connected neuronal circuitry Mechanism should operate synchronous with the synaptically-connected neuronal circuitry
Learning-induced changes occur at physiological time-scales (in milliseconds) A learning-inducible change that can occur (and completed) at physiological time-scales (to explain the ability to retrieve memory instantly following learning)
Memories that can be retrieved long time after learning are also capable of getting retrieved immediately after learning (working memory) Learning should generate retrieval-efficient changes within milliseconds at the time of learning. These changes should have a provision for remaining in a stable form for long period of time, responsible for long-term memory
When exposed to a cue stimulus, internal sensation of memory takes place at physiological time-scales (in milliseconds) A learning-induced change should be capable of inducing internal sensation of memory at physiological time-scales (should be able to complete within this time)
Memory is an internal sensation with certain specific sensory features (qualia) Mechanism is expected to have elements that can provide sensory features to the retrieved memory
Ability to store large set of learning-induced mechanisms responsible for retrieving very large number of memories Neurons and their processes are finite in number. Therefore, an efficient operation for storing very large number of learning-induced changes becomes possible if common elements in each learning can be shared. This becomes possible if each memory gets induced from a combination of unitary mechanisms 

Instant access to very large memory stores

A specific cue stimulus should be able to induce a specific memory by combinatorial reactivation of a specific set of learning-induced unitary changes

Absence of cellular changes during memory retrieval

A passive reactivation of the changes that occurred during learning should be getting used at the time of memory retrieval to induce units of internal sensations. This should take place at physiological time-scales   

Operates at a certain range of frequency of extracellularly recorded oscillating potentials

Expected mechanism provides vector components of the oscillating potentials

Motivation promotes learning

Motivation is associated with a specific factor and its specific action to augment the learning-induced change and possibly to retain this change for longer period of time than that occur in its absence

Internal sensations of working, short and long-term memories have similar qualia

Same learning-induced change is retained for different durations. Long-term memory might lose some unitary mechanisms and it might affect clarity

Working memory lasts only for a very short period of time Learning-induced change must have a quickly reversible mechanism

Retrieval of memories very long period of time after the learning

A feasible mechanism for long-term maintenance of learning-induced change

Simultaneous existence of previous two conditions (above two rows) within the system Learning-induced mechanism should have an initial quickly reversible change that if prompted can progress towards a stage where it can get stabilized for long period of time

Ability to induce internal sensation of memory in a cue specific manner

Specific sensory features from the cue stimulus induce a combination of internal sensory units to generate internal sensory features of the item whose memory is being retrieved

Ability to store new memories without needing to overwrite the old ones

Sharing of unitary mechanism for common features, reversal of learning changes by forgetting and provision for formation of new units with new associations are expected to be present in the system

Consolidation of memory

Mechanism for gradual transfer of locations of learning-induced changes and ability to generate memories by a global computational mechanism

Mechanism to use schemas inter-changeably

How changes induced by one learning are shared by another learning event and how  these shared changes are used at the time of memory retrieval?

A constantly adapting dynamic circuit mechanism is expected Provisions should be present to accommodate large number of new learning events

Framework of a mechanism that can generate hypothesis by the system

When there is a common element in two pairs of associative learning events, how can the operational mechanism generate a hypothesis of relationship between associated pairs?     

System needs an unconscious state of sleep for nearly one third of its operational time

Substantive nature of sleep in the operation of the system. In other words, it is necessary to explain why the system won't be able to exist without sleep

Internal sensation of memory can lead to behavior Mechanism should show how internal sensation of memory is related with motor action for behaviour
Activation of a single dendritic spine can fire a neuron (when that neuron is at sub-threshold activated state). Retrieval of memory is associated with firing of certain neurons.  Need explanation for a mechanism that can cause both firing of a neuron and at the same retrieve information as units of first-person internal sensation of memory with specificity just by activating one dendritic spine

Place cell firing in response to specific spatial stimulus

How internal sensation of memory for a location is linked with firing of a set of CA1 neurons?

Firing of an ensemble of neurons during a higher brain function

How internal sensation generated during a higher brain function is related with firing of an ensemble of neurons?

Firing of a set of neurons during a specific higher brain function (for example, during both learning and memory retrieval)

How both learning and induction of internal sensation of memory are associated with firing of separate sets of neurons?

Firing of a cortical neuron (axonal spike) is possible by summation of nearly 140 postsynaptic potentials (inputs) arriving from random locations. These cortical neurons have tens of thousands of dendritic spines where postsynaptic potentials can get generated These neurons have to be maintained at a sub-threshold state at the background state and the mechanism of induction of internal sensation has to be associated with providing additional postsynaptic potentials for crossing the threshold for firing of these neurons
Dendritic spikes occur by the summation of nearly 10 to 50 postsynaptic potentials at the dendritic region It is necessary to explain which spines contribute to the potentials and explain their significance
Oscillating extracellular potentials While synaptic transmission provides one vector component, what constitutes the other vector component/s that is/are expected to take place nearly perpendicular to the direction of synaptic transmission?
Apical tuft regions of all the cortical neuronal orders are anchored to the inner pial surface resulting in crowding of the dendritic arbors of neurons from different orders What purpose does it serve by having dendritic spines of neurons that belong to both the same order and that belong to different neuronal orders overlap with each other?
On an average, inter-spine distance is more than the spine head diameter What is occupying the inter-spine region and what possible functional contribution can they make? Based on the above row, what are the possible implications?

Following learning, initially there is conscious retrieval of memory and eventually this becomes sub-conscious after repeated retrievals

What change is taking place when there is repetition of learning? How does this affect consciousness? Does this contribute to subjective aspect of consciousness? Must be able to explain at least as a framework of a mechanism

Experimental finding of long-term potentiation (LTP) has several correlations with behavior associated with memory

It must be possible to explain how cellular changes during LTP induction and learning are correlated

Learning takes place in milliseconds, whereas LTP induction takes at least 20 to 30 seconds and even more time What cellular change during learning can get scaled up during LTP induction in a time-dependent manner? Explain the mechanism behind this?

Blockers of membrane fusion blocks LTP

Need to explain the cellular location where they act and explain how it blocks LTP         

Induction of LTP at the CA2 area of the hippocampus becomes possible by the removal of the peri-neural net proteins chemically

Why should the extracellular volume be devoid of such proteins? How does it affect LTP induction and natural learning?

Relationship between LTP, kindling and seizures

Need an interconnecting explanation

Loss of dendritic spines after kindling

Specific reason to explain the loss of spines

CA2 area of the hippocampus is resistant to seizures

How peri-neural net proteins can block the mechanism of seizures, which is related with kindling and HSV infection?

Seizures and memory loss by herpes simplex viral (HSV) encephalitis

Mechanistic explanation for both these features is expected to provide some information about the relationship between these findings in HSV encephalitis

Mechanism of neurodegenerative disorders

How contiguous spread of pathology cause spine loss and neuronal death? Is there an explanation for the sporadic occurrence of these changes?

Dementia in neurodegenerative disorders

How can loss of spines lead to dementia? How does it cause loss of internal sensation of various higher brain functions along with concurrent behavior?                

Perception as a first-person internal sensation

How a variant or a modification of the mechanism of induction of internal sensation for memory can explain perception?

Flash lag delay, apparent location of the percept different from the actual location, homogeneity in the percept for stimuli above the flicker fusion frequency, mechanism for object borders and generation of pressure phosphenes

Matching explanations using the mechanism of induction of units of internal sensation for all these features

Inner sensation of consciousness

A testable mechanism for the generation of inner sensations that depends on/contributes to the frequency of oscillating extracellular potentials. Explain what contributes latter's vector components and their role. What determines qualia during perception?

Loss of consciousness by anesthetic agents

Using all the known properties of anesthetic agents and how they alter the framework of consciousness

Loss of consciousness during a generalized seizure and its reversal

How the explanation for seizure generation is linked with alteration of the framework for consciousness?

Changes in consciousness with the alteration in the frequency of oscillating extracellular potentials How a specific range of frequency contributes to the state of normal consciousness? What are the vector components?

Effect of dopamine in augmenting anesthetic action

Explain a mechanism how dopamine augments anesthetic action. Now verify if this explanation matches with the explanation for the action of dopamine in augmenting learning

Phantom sensation or pain Explain a mechanism for the internal sensation of pain from a lost limb at the time of phantom sensation or pain
Referred pain Explain a mechanism for the internal sensation of pain from a location different from the location where the cause of pain is present

Mechanism for innate behavior that enables survival

A mechanism evolving from heritable changes to explain innate behavior in response to a stimulus

Comparative circuitry in a remote animal species

Comparable features that show relationship of a mechanism that induces units of internal sensation using synaptically-connected neuronal circuitry among different species of animals  

Neurodegeneration resulting from repeated general anesthesia

How mechanism of loss of consciousness by anesthetics, if induced repeatedly, cause loss of spines and other features of neurodegeneration?
More education reduces dementia risk Should be able to explain how learning-induced changes can contribute to reducing dementia risk
Certain functions appear to be located at specific brain regions based on the findings of lesions/lesion studies These minimum locations that cause loss of function are most likely locations of convergence of specific inputs responsible for those functions (they can also be locations of converging fiber tracts)
Astrocytic pedocytes cover less than 50% of peri-synaptic area in nearly 60% of the synapses in the CA1 region of hippocampus Suitability of the distribution of astrocytic processes in the operational mechanism
Present nervous systems have evolved over millions of years and are also the results of certain accidental coincidences. They have different survival features It is expected to become possible to explain how the circuitry that provides all the features can be evolved through simple steps of variations and selection
Significant neuronal death (70%) and spine loss (13 to 20%) are observed during development It is necessary to explain the cause for these observations and provide an explanation how new variants were selected to prevent such events in the future
Dye diffusion is observed from one neuronal cell to another as the cortical neurons move from periventricular region towards their final destination, which indicates formation of inter-cellular fusion It is expected to become possible to explain how an event of inter-cellular fusion leads to selection of variants that prevents further inter-cellular fusion. Since neurons cannot divide further, a transient stage of fusion is expected to trigger fusion preventing mechanism in the surviving neuronal cells. It is also necessary to explain whether this last stage has any role in the unique functional property of generation of first-person internal sensations within the nervous system
Both learning and retrieval of memory take place at a narrow range of frequency of oscillating extracellular potentials a) Both the mechanism for learning and memory retrival contribute vector components of the oscillating extracellular potentials. b) The specific mechanism for both learning and memory retrieval depends on the frequency of oscillating extracellular potentials
Artificial triggering of spikes in one neuron in the cortex causes spikes in a group of sparsely distributed neighbouring neurons in the same neuronal order located at short distance (25–70µm) from the stimulated neuron It should be possible to explain a mechanism that can lead to lateral spread of activity between neurons of the same neuronal order. Its temporal relationship suggests occurrence of a mechanism through a path other than trans-synaptic route
Protein complexin blocks SNARE-mediated fusion by arresting the intermediate stage of hemifusion. Since complexin is present in the spines and since no docking of vesicles is seen within the spines, what inter-membrane fusion is getting arrested by complexin? It is necessary explain an inter-membrane fusion that can be mediated by SNARE proteins and blocked by complexin by arresting the process at the intermediate stage of hemifusion in the spines

Table 2. Features of the system from different levels that need to be explained independently and in an inter-connectable manner using a derived  solution. Even though several possibilities can be excluded (for example, biochemical reactions that occur slower than the physiological time-scales at which learning takes place (from which memory needs to be retrieved), which can help exclude candidacy of several biochemical intermediates 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 few mathematical equations. Once we have a unitary solution, we need to understand the principle of their computations where mathematics is expected to have a major 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 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 and third-person perspectives qualifies it as a testable hypothesis. Research findings from different laboratories have been examined in terms of the semblance 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 many years. Even though the present hypothesis is compatible with the experimental data, it must be considered unproven until verified.


Video presentations

1. A testable hypothesis of brain functions

2. How to study inner sensations? Examples from mathematics

3. Neurons and Synapses

4. List of third-person findings and the derivation of the solution for the nervous system

5. Constraints to work with

6. Induction of units of inner sensation

7. Why do we need to sleep?

8. A potential mechanism for neurodegeneration

9. LTP: An explanation by semblance hypothesis

10. A framework for consciousness

11. A potential mechanism of anaesthetic agents


The challenge: "What I cannot create (replicate), I do not understand" Richard Feynman

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 that occur concurrently 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 verifications by triangulation methods and examining comparable circuitries 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!