Semblancehypothesis.org

by Kunjumon Vadakkan

Welcome!

Objective: To understand how first-person inner sensations (in the mind) of higher brain functions (such as memory & perception) occur both independently & along with third-person observed motor activities such as speech and behavior.

Dedication: To all those who suffer from diseases of the brain (& therefore mind), especially who are abandoned by their families.

How to understand something that cannot be accessed by our sensory systems? A method used in physics	How can we use a non-real intermediary to solve the nervous system? Example of a case where geometry fails
A deep principle useful for solving the nervous system - demonstrated by an example	A medication for unrelated neurological and psychiatric disorders - What does it inform us?
Insulating extracellular matrix - How thick it is? Can information get etched on it?	Has learning-mechanism got features of an evolved mechanism?
How is learning related to LTP induction? An explanation	Extreme degeneracy of input signals in firing a neuron
Does the brain carry out back propagation?	Importance of triangulation in verifying a mechanism
Perception from a first-person frame of reference	Without sleep, there is no system! An explanation
Internal sensation - A comparison with electromagnetism	Testable predictions made by the semblance hypothesis

Latest pre-print: "The basic concept of "attention heads" in Transformers matches with partial features of "islets of inter-LINKed spine heads", a model of nervous system functions". Summary. Article. If a primary school child asks, I will tell this work as a Story.

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 brain such as perception and memory are first-person inner sensations (within the "mind") to which only the owner of the nervous system has access. But we have been studying these functions by examining the nervous system from outside using third person approaches at various levels (biochemical, cellular, systems, electro-physiological, imaging, and behavioral) and we were trying to find correlations between these findings with the aim of understanding the system. Through these approaches, the first-person internal sensations of different 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 practically not possible. This means we are facing a brick wall in our current approaches to understanding its operations. This work aims to overcome this by undertaking a theoretical approach.

Since a universal operational mechanism is expected to be present 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 searching for a biological mechanism that gives rise to virtual first-person inner sensations. This should not hinder our efforts in any way. In fact, we must prepare ourselves to look for a unique mechanism that has the ability to evade our attention! Keeping this 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 showed a set of unique features for a feasible operational mechanism for generating 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 in this cellular mechanism can explain several neurological and psychiatric disorders. Predictions made by this hypothesis are testable.

Are there different ways to view this hypothesis? One, Two

Can you explain the hypothesis using a figure? The connectome is expected to make certain specific changes during learning and is expected to be used during memory retrieval. It should take place within the synaptically connected neuronal network. First, we have to arrive at the location where this is possible. Then explore its nature to understand why we have been failing to recognize it. See Figure 1 below. For more details of the problem see Figure 2 (Note: FAQ page explains the contents of this black box).

Figure 1. Black box where certain changes take place during learning. A) In the conditioned learning paradigm, two different types of stimuli that can provide both first-person inner sensations and motor outputs are used. Here, the association between the sound of a bell (Conditioned stimulus, CS) and the site of food (Unconditioned stimulus, US) is commonly used. B) After learning, the arrival of sound from the bell (CS) alone generates the output features in response to both sound and food. What type of neuronal connection can provide this ability? There is a black box between the pathways through which the CS and US stimuli propagate. What is the simplest and evolutionarily selected connection that can occur at timescales of learning (milliseconds) that can then enable the CS alone to give outputs expected of both CS and US (in milliseconds)? A summary of the solution based on the semblance hypothesis is shown in Fig.18 on the FAQ page).

Figure 2. Details of the black box are shown in figure 1. A) Five neuronal orders (N1 to N5) starting from the sensory receptor level (Sy1: area dense in sensory receptors; Sy2-Sy5: area dense with synapses; N1-N5: area with neuronal cell body). Note that each neuron is expected to fire an action potential on receiving a relatively small subset of input signals from randomly located spines/input terminals (out of thousands of spines) on its dendritic tree. B) Before learning, arrival of sensory stimulus St1 (CS in Fig.1) leads to firing of a set of 3 neurons (GN1, GN2, GN3) (in green) in neuronal order N5. C) Before learning, arrival of stimulus St2 (US in Fig.1) alone results in the firing of a set of 3 neurons (RN1, RN2 and RN3) (in red) in neuronal order N5. D) During associative learning between St1 and St2, in addition to neurons GN1, GN2, GN3, RN1, RN2 and RN3, an additional neuron YN is also fired. This indicates that learning has opened a new channel through which EPSPs from neuronal circuitry activated by stimulus St1 and St2 arrive at the neuron YN that was remaining in sub-threshold activated state before learning. This new channel formation would have taken place at the synaptic region S5 where stimuli St1 and St2 converge. E) After learning, arrival of stimulus St1 alone leads to firing of neurons GN1, GN2, GN3 , YN and RN2. This shows that both YN and RN2 receive the n^thEPSPs from stimulus St1 after learning. Inputs to RN2 that lead to its firing is associated with certain specific black box changes that leads to motor actions (& inner sensation of memory) reminiscent of St2. The channel that brings additional EPSP to the neuron RN2 can solve the black box problem. There can be only one unique solution for this. F-H: Seeks a solution for the black box problem. F) Note that mean inter-spine distance is more than mean spine diameter (Konur et al., 2003). Arrival of St1 and St2 to two adjacent spines will not satisfy the conditions in Fig.1 since the output neuron is the same. G) For the motor actions of CS to take place, St1 should reach the spine of one neuron (GN). H) For the motor actions of the US to take place, St2 should reach the spine of a second neuron (RN). The black box problem (for CS to exhibit features of both CS & US after learning) will have a solution only when a channel gets established between neurons GN and RN (to which St1 and St2 arrive respectively) in such a manner that after learning, arrival of St1 to GN alone will be able to cause firing of both GN and RN. At this point, we have to make a reasonable assumption that this channel is also associated with a unique property to generate first-person inner sensations & hunt for a logically explainable hidden mechanism. For details of the solution, see Fig.19 in the FAQ section.

What is the reality in the field? If this is the last day of your life, how will you tell this?

There are several unsolved problems in neuroscience (Adolphs, 2015) observed from different levels (Edelman 2012; Gallistel & Matzel 2013). Nervous system functions observed at different levels are being studied by different faculties of science - biochemistry, cell biology, electrophysiology, systems neuroscience, psychology, imaging, behavior, and consciousness studies. The system is similar to a puzzle lying in multiple dimensions. Solving it requires fitting the correct pieces of the puzzle at the right levels to obtain the right operational function. If we examine only one or a few levels of the system, we might arrive at certain solutions that will allow fitting together some pieces of the puzzle only for those few levels. Features of the unexamined levels will most likely remain unexplainable, and we won't reach a solution for the system. The diverse nature of findings at different levels strongly indicates that the solution is going to be a unique one. At the same time, it is also expected to be a simple one. To solve the system and find out the correct mechanism, it is necessary to examine representative functions from all the levels simultaneously.

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, evidenced by our ability to develop their replacements, such as artificial heart and dialysis. What operational mechanism do we need to understand from the brain to replicate/replace it? The brain generates an inner sense of the external world during perception, stores sensory information during associative learning and later produces the internal sensation of retrieved memories of the learned item when the associatively learned cue stimulus or its partial features arrive, induces thought to connect different items from different sets of learnt events – all of which are first-person properties that cannot be accessed by third-person observers. The only information that is available from the owner of the nervous system to a third person is 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 accessible functions.

A third view of the problem becomes evident when examined from the viewpoint of a builder. Here, the job is to replicate the brain in an engineered system. 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 by third-person observers, they cannot be studied directly using biological systems. Hence, 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. As a builder, we feel the pressure to know its operational mechanism. We are forced to speculate about all the possible ways and figure out the correct one. We will be concerned mostly with explaining the formation of inner sensations in physiological timescales. Before building the system, we need to draw a sketch of the system's operations.

A fourth view becomes possible by observing the “loss of function” states of the system occurring at various levels. This can help us understand the nature of the pieces of the puzzle. Early genetics research has gained valuable information from "inborn errors" of metabolism that provided guidance to understand the allelic organization of genes. Using various combinations of findings from both neurological and psychiatric disorders it is likely to deduce the operational mechanism.

What are the main reasons why it is difficult 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. A typical example is the difficulties in sensing the rotation of Earth (note that the speed of rotation of Earth on its axis is 1670 km per hour). Our sensory systems cannot sense the rotation of Earth towards the East, since we are in the same reference frame as that of the Earth. The fact that third-person observers cannot sense first-person inner sensations in a subject can be viewed as another frame of reference problem. In physics, constraints from several findings are used to reach a non-accessible solution. For example, see how Galileo conjectured (see below) that Sun is at the center of the universe (then).

2) Difficulty studying the “virtual” nature of first-person inner sensations: We have dealt with several virtual items in the past. For example, 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? 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 step further, we have invented complex numbers (using an imaginary number). This solved our difficulties in finding square roots of negative integers, which helped to further advance mathematics. Similarly, 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 position them and navigate that space to understand their different conformations.

3) Access problem: How to understand something that cannot be accessed by our sensory systems? We are routinely studying several things that our sensory systems cannot access directly. E.g. we cannot see DNA inside the cells or in a gel. But we stain it with ethidium bromide, which will allow us to see the stain through our eyes. This means that our access problem can be overcome by adding one or more steps of actions that will allow our sensory systems to get access towards them indirectly. Understanding inner sensations will need indirect or indirectly indirect methods that we will eventually become familiar with.

How did Galileo show us to put together observations to make an inference even when our sensory systems cannot agree with such an inference?

When there are many observations in a system, putting them together can provide a totally new inference that our sensory systems may not be able to directly sense. An example is that of the inference made by Galileo Galilei using observations that he made. While observing Jupiter in 1610, Galileo found four moons that are orbiting Jupiter. He immediately made the conclusion that if these moons are revolving around Jupiter, then it is unlikely for the Earth to be at the center of the Universe. This video explains further. While watching Venus, he found phases similar to that of Moon - New Moon and Full Moon. Galileo observed both the New and Full faces of Jupiter. When it is New, it is very big. When it is Full, it is very small. He concluded that this could happen only if Venus revolves around the Sun and therefore, he made the inference that the Sun must be at the center of the system. A suitable fit with this observation is that Earth and other planets are also revolving around the Sun. What we now know is that Venus is New when it comes close to the Earth, blocking the light from the Sun. When Venus is on the other side of the Sun during its revolution around the Sun, it is farthest from the Earth. Here, Venus is seen as small, and its face is Full. This video explains it.

The above observations made Galileo conclude that Earth is not at the center of the solar system. Galileo saw the simplicity if all planets revolved around the Sun. He was making logical arguments that allowed him to fit all the findings together. Galileo knew that it was difficult for him to convince others that the Earth is revolving around the Sun. We have such a rich tradition in science of gathering information from different observations and then putting them together to make an inference, even though we cannot appreciate it directly with our sensory systems.

Footnotes:
It was Copernicus, who, based on observations, first proposed that the Sun is stationary and that the Earth and other planets revolve around it. So, the credit must go to him as the first person who reported that Earth is revolving around the Sun. Even though Galileo thought that planets were moving in circles, Kepler found out about the elliptic path of motion of planets.

How can we solve the nervous system?

There are three crucial questions that we must ask. 1) How can we understand the operation of the nervous system even without replicating the mechanism in engineered systems? 2) What solution for the first-person inner sensations can hold all other findings from different levels in an inter-connected manner? 3) How to reach such a solution that can provide testable predictions? The challenge in this approach is to include all the observations to find the solution. Hence, it is necessary to examine findings from different levels of the system simultaneously. Since there is only one unique solution, if we can arrive at a solution that can inter-connect all the findings from different levels, then it is likely to be correct. We must use this solution to make testable predictions and verify them.

As we face situations that have more steps away from reality, we have to rely on our logical reasoning capabilities (see an excerpt from Krakauer et al., 2017 that appeared in the journal Neuron). The unique structure-function mechanism must provide inter-connected explanations. The virtual, first-person non-accessible nature of inner sensations warrant certain approaches that are similar to the core principles behind approaches used in physics (see Table 1). 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) requires an effort in the opposite direction. Anticipating this is the most important step.

	Physics	Neuroscience
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.	There are many disparate findings in neuroscience (see Table 2) that need inter-connectable explanations. E.g. How does the operation of the system relate to sleep and the electrophysiological finding of LTP?
2	The above indicates the presence of a deep underlying principle that should interconnect these disparate observations.	There should be a deep underlying principle that interconnects all the observations listed in Table 2.
3	The features of some of the elements associated with the above principle (e.g. particles and fields) cannot be directly sensed by our sensory systems.	There is a principle, the products of which (inner sensations) cannot be sensed by our (third persons') sensory systems. Yet, the principle of the mechanism should be able to explain and interconnect all the observed findings.
4	Constraints provided by disparate observations should be able to guide us towards the solution. This is done either by initial deduction followed by mathematical approximations (e.g. special and general Relativity, Higgs Bosons).	A structure-function mechanism must be sought by logical deduction & trial and error methods. The constraints offered by a large number of findings can be used to derive the solution. Success depends on moving along a path as guided by all the constraints. Only when we reach the correct solution, will we be able to explain all the findings in an inter-connectable manner.
5	The solution is then confirmed by verifying the testable predictions.	Testable predictions made by the derived mechanism can be verified.

Table 1. Comparison between the steps taken by physics and neuroscience when it becomes necessary to unify disparate findings. This is important especially when dealing with properties that are non-accessible to our sensory systems such as particles, fields, and first-person internal sensations etc.

The deep underlying principle of many studies in physics has similarities to 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 such a system, one can find that the relationships between the variables in each equation provide hints that can guide us towards the solution. If there are numerous variables, there should be at least an equal number of equations to find the unique solution. Since there are many findings at different levels of the nervous system, we can (and we must) use even minor interconnected features between them to find the solution. It is a gigantic exercise, since there are no easy methods in biology like those that are used in linear algebra. But understanding the logic behind the linear algebraic methods will help in solving the system.

In linear algebra, the Gauss-Jordan elimination method is used to find the solution for a system of linear equations. 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 making it simple for others by developing easy methods. We can examine how the relationships between variables in each equation define the unique solution for a system of linear equations and how the 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 will take some extra time - more time when more variables are involved. In other words, in mathematics, easy methods are developed for convenience. Whichever method is used, the deep underlying principle is the same - A system exhibiting numerous disparate findings (equations) most likely has a unique solution that binds (interconnects) all 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 underlying solution, which is the correct solution.

One can start attempting to solve the (nervous) system by using subsets of disparate findings. The optimism of this approach is that there is only one unique solution for the nervous system, and it is easy to rule out many wrong solutions quickly. Using the above principle, subsets of constraints provided by findings from various levels (Table 2) were used to derive a mechanism that can explain, and interconnect findings made by different faculties of brain research. The non-sensible component will remain non-sensible to our sensory systems even after its discovery (Fig.3). However, it is expected to show testable learning-generated change that gets reactivated at the time of memory retrieval to induce basic units of internal sensation who's integral provides qualia of memory.

Figure 3. Method to find a solution for the system from third person observed findings. (A) Features of the system are sensed either directly (represented by capital letter K) by our sensory systems or indirectly (represented by capital letters D, E, G, H) through findings such as staining of proteins, observing behavior, etc. (represented by small letters (u, w, v, x) connecting the features through straight lines (for example, observation of u enables sensing D). (B) Using both commonly used direct and indirect methods, three clusters of interconnected (represented by dotted lines) findings are found at separate levels (observations from different fields of brain science). In most cases, it was not possible to interconnect these clusters. For example, it was not possible to find interconnected explanations between 1) learning changes and inner sensation of memory both occurring in millisecond timescales, and 2) sleep and LTP. Using constraints from findings within each cluster, it is possible to examine whether they can be interconnected through a common operational mechanism. In the case of the nervous system, a very large number of findings and constraints offered by them can be examined. (C) Using constraints available from some of the features of each cluster of unrelated findings (e.g. A, B and C), it is necessary to try to derive a deep underlying principle (a structure-function solution m) that allows interconnection between them and therefore all the findings within each cluster. This solution is expected to provide a mechanism for generation of internal sensations in millisecond timescales. (D) The solution m enables explaining how various findings within each cluster are interrelated with each other and with the findings from other clusters shown in B). While remaining non-sensible to our senses by any known methods used in current biological investigations, the ability of the solution m to hold different findings from all the clusters together makes it a further verifiable solution (Figure from Vadakkan KI (2019) From cells to sensations: A Window to the Physics of Mind. Physics of Life Reviews. 31:44-78).

There are a very large number of observations from different levels of the nervous system's functions (Table 2). An example of store receipts (this is also the deep principle behind some of the approaches carried out in physical sciences to understand nature) provides us with confirmatory evidence that we can reach a final correct solution, if it becomes possible to obtain a large number of findings so that we include all variables of the system.

It is possible to draw constraints from numerous findings in multiple levels of the nervous system. Only when when we reach the correct solution that we will be able to explain all these findings. Even if we are unable to directly sense the formation of first-person inner sensations, interconnected explanations suggest their location & mechanism of formation. Several of the following explanations provide retrodictive evidence.

Findings from multiple levels

Constraints offered by the findings (on the left) that direct the inquiry towards a correct solution.

Interconnected explanations by the semblance hypothesis (Please read this row after reading the hypothesis)

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.

Memories are virtual first-person inner sensations.

It is necessary to provide a location & mechanism for its generation.

Operation of the IPLs provides a mechanistic explanation.

Learning-induced changes occur in physiological timescales (of milliseconds). ^{Foot note1}

A learning-induced mechanism that occurs (& completed) in physiological timescales.

IPL formation in milliseconds occurs between abutted spines at locations of convergence of pathways along which associated stimuli propagate.

Memory retrieval takes place in millisecond timescales.

Since memory of this can be retrieved immediately following learning, a mechanism for memory retrieval must occur.

Propagation of potentials along the IPLs to the inter-LINKed spines takes place in physiological timescales of milliseconds (Vadakkan 2007; 2013).

After associative learning between two items, arrival of one of the items generates memory of the other item.

The learning mechanism should have features to explain how either one of the associatively learned items can act as a cue stimulus to generate memory of the other item. Hence, the mechanism should have the ability to show bidirectionality in it.

Semblance can be generated from either one of the inter-LINKed spines on the two sides of an IPL (Vadakkan, 2010a; 2013).

Even partial features of one of the associatively learned item is capable of retrieving memory of the second item.

The mechanism should have features to explain how stimuli from partial features of one stimulus can retrieve memory of the second item.

Partial stimuli propagate to generate the inner sensation of a framework of an item or event. Due to the property of generalization (by virtue of the spread of depolarization across the entire islet of inter-LINKed spines), it is expected to provide more features to the memory (Vadakkan, 2010a; 2013; 2019a).

Memories that can be retrieved long period after learning are also capable of being retrieved immediately following learning (working memory).

Learning generated changes can be used for memory retrieval immediately (working memory). These changes must have a provision for remaining in a stable form for long period, responsible for long-term memory (LTM).

IPL formation takes place at the time of learning. When IPL reverses back, then its short duration can only generate working memory. Long-term stabilization of IPLs enables them to be used for retrieving memory (by a cue stimulus) for a long period (LTM) (Vadakkan, 2010a; 2013).

When exposed to a cue stimulus, the inner sensation of memory occurs in physiological timescales (in milliseconds).

A learning-induced change should be capable of inducing inner sensations of memory in physiological timescales (completed within this time).

Propagation of potentials along the IPL generates semblance over the inter-LINKed spine instantly as a system property (Vadakkan 2013).

Gradual changes in qualia of inner sensation of memory in response to gradual changes in cue stimulus.

Mechanism is expected to have unitary elements that can be integrated to provide inner sensation of retrieved memory.

Units of inner sensations generated on a specific set of inter-LINKed spines, in response to a specific cue stimulus, get integrated to provide qualia (Vadakkan 2010a).

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.

Any specific cue stimulus is capable of re-activating a specific set of IPLs & generating units of inner sensations on a specific set of inter-LINKed spines (Vadakkan, 2010a).

Absence of cellular changes during memory retrieval.

A passive reactivation of the changes that occur during learning should be used to induce units of internal sensations at the time of memory retrieval.

Since inter-LINKed spines persist from the time of learning, propagation of depolarization along the IPL does not require any new cellular changes (Vadakkan, 2010a).

The ability to store large sets of learning-induced changes is responsible for retrieving a large number of memories.

Neurons and their processes are finite in number. Therefore, an efficient operation for storing large numbers of learning-induced changes becomes possible if common elements in each learning mechanism can be shared. Hence, each memory is expected to be induced from a combination of unitary mechanisms.

Inter-LINKed spines within the islets of inter-LINKed spines can be depolarized by any specific stimulus reaching it. Since items/events consist of combinations of sensory stimuli, different combinations of inter-LINKed spines can be used by different cue stimuli to generate corresponding memories (Vadakkan, 2010a).

Transfer of learning (Dahlin et al., 2008)

Transfer can occur if the criterion and transfer tasks engage specific overlapping processing components and brain regions (Dahlin et al., 2008)

The unitary operational mechanism provided by semblance hypothesis is able to explain this (Vadakkan, 2013).

During memory retrieval, there is firing of a subset of neurons that were not firing before learning in response to the same cue stimulus.

Learning has opened certain new channels & the cue stimulus leads to propagation of depolarization through these channels to provide additional potentials to a subset of neurons that are otherwise being held at sub-threshold activation state (without firing).

Formation of IPLs during learning will lead to propagation of depolarization across them to the inter-LINKed spines. This will provide additional potentials to the inter-LINKed spines' neurons and may fire those neurons if they cross the threshold (Vadakkan, 2013).

The brain operates in a narrow range of frequencies of extracellularly recorded oscillating potentials.

Operational mechanism is expected to provide vector components of the oscillating extracellular potentials. There should be corresponding intracellular changes of ionic concentrations within the neuronal processes of involved neurons.

Synaptic transmission & near perpendicular propagation of depolarization across the IPL provide vector components (Vadakkan, 2010a).

Motivation promotes learning. Motivation is associated with release of dopamine & activation of dopamine receptors at different locations of the brain (lino et al., 2020).

Motivation must be associated with specific factors & their specific actions are expected to promote the learning-induced change and possibly to retain this change for a longer period than those occur in their absence.

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, which may trigger some stabilization steps.

Most excitatory glutamatergic synapses are on dendritic spines that enlarge during learning. Glutamate causes spine enlargement in both hippocampal slices (95%) (Matsuzaki et al., 2004) and the neocortex in vivo (22%) (Noguchi et al.,2019).

Spine enlargement is expected to offer certain functional uses, especially in locations where the extracellular matrix (ECM) is very thin.

Enlarging spines in locations where neuronal processes are densely packed can promote IPL formation if two abutted spines where associatively learned stimuli arrive & converge.

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

The same learning-induced change is retained for different duration. Long-term memory loses its clarity both due to loss of some unitary mechanisms & dilution of specificity by combining with newly formed units of inner sensations.

Memories of all duration take place by reactivation of inter-LINKed spines by depolarization propagating along the IPLs and generating units of inner sensations (Vadakkan 2010a; 2013).

Most learning events lead to a working memory that lasts only for a short period of time and does not continue to become long-term memory.

Learning-induced change must have a quickly reversible mechanism.

IPL formation is a high energy requiring process as can be inferred from experiments using artificial membranes (Rand and Parsegian, 1984; Martens and McMahon, 2008; Harrison, 2015). Hence, the majority of IPLs are expected to reverse back quickly.

Some of the memories that can be retrieved as working memories can be retrieved after a long period of time after learning (long-term memories).

Learning-induced change must be able to undergo certain changes that will enable it to get maintained for a long period.

Stabilization of IPLs for long periods can induce the same units of inner sensation for a long period. If the number of IPLs that can be reactivated by a cue stimulus decreases with time, then the qualia of memory will deteriorate with time (Vadakkan 2010a; 2013).

Simultaneous existences of the previous two conditions (above two rows) within the system.

Learning-induced mechanism should have an initial, quickly reversible change. But under certain circumstances some of them can get stabilized for long periods of time.

When memory of a beneficial or deleterious item/event becomes advantageous or deleterious for survival, then IPLs responsible for those memories get stabilized for a long period (Vadakkan, 2010a; 2013).

The ability to store new memories without needing to overwrite the old ones.

Sharing of unitary mechanisms for common features, and provision for formation of new units with new associations are expected to be present in the system.

Inter-LINKed spines within islets of inter-LINKed spines can be shared by any stimuli reaching them. Hence, there is no need to overwrite old memories. New associations lead to additional spines inter-LINKing to the existing inter-LINKed spines (Vadakkan, 2010a; 2013).

Consolidation of memory (apparent transfer of storage locations of memory from the hippocampus to the cortex) over a span of 5 to 8 years.

Addition of specific learning-induced changes in the cortex over time using similar unitary sensory associations in the hippocampus. The ability to generate memory by a global integrating mechanism. Must go through a stage of having surplus unitary mechanisms.

Convergence of all sensory stimuli in the hippocampus leads to dense islets where inter-LINKed spines can be formed. Sparse sets of IPLs are expected in the cortex. Repetition of associative elements within each learning event along with new neuron insertion in the granule layer will lead to formation of surplus new IPLs in the cortex over time (Vadakkan, 2011a).

Mechanism uses pre-existing schemas (Tse et al., 2007). Schemas are expected to get used interchangeably.

Changes induced by one learning event are shared by another learning event. For this to occur, there must be shared unitary mechanisms that can be used for retrieval of different memories.

Inter-LINKed spines can be used by any cue stimulus that can reach them, allowing the unitary structural operations to get shared. Thus, pre-existing inter-LINKed spines get shared by similar elements in different stimuli (Vadakkan, 2010a; 2013).

A constantly adapting dynamic circuit mechanism.

Provisions should be present to accommodate a large number of new learning events.

Since extracellular matrix space is minimal in the cortex, a large number of spines from different neurons are expected to remain abutted to each other. They can be readily inter-LINKed if stimuli from associative learning events converge (Vadakkan, 2010a; 2013).

Framework of a mechanism that can generate a hypothesis by the system.

When one of the elementary mechanisms of one associative learning event undergoes association with a third elementary mechanism during a third associative learning session, it will lead to an interconnected chain of associations (ICAs). When there are common elements in different ICAs, then the system will be able to generate a hypothesis of relationships between events/items.

When one spine of each two islets of inter-LINKed spines is inter-LINKed, one spine from one islet establishes a relationship with any one spine in the second islet of inter-LINKed spines. When more than one islet of inter-LINKed spines is inter-LINKed in this manner, it leads to generation of hypotheses about something that will not occur ordinarily (Vadakkan, 2010a; 2013).

A system needs a state of sleep for nearly one third of its operational time.

It is necessary to explain why the system won't be able to exist without sleep. i.e. Explain the substantive nature of sleep in the operation of the system.

A state of sleep is needed to keep postsynaptic depolarization by presynaptic terminal as a dominant state of the system. Only when this dominant state is maintained, then only a lateral activation of the postsynaptic terminal (spine) will induce units of inner sensation of a stimulus arriving from the environment through the presynaptic terminal (Vadakkan, 2016b). Since nothing comes from the environment, it is a hallucination (Minsky, 1980).

While living in space, the requirement for sleep reduces by more than one hour.

Provide a mechanistic explanation why reduced sensory stimuli in space reduces the need for sleep.

Since sensory stimuli are less in space, the number of reactivations of inter-LINKed spines is reduced. This reduces the time to set the system to its baseline dominant state of postsynaptic depolarization by its presynaptic terminal (Vadakkan, 2016b).

During memory retrieval, the inner sensation of memory can occur with or without motor actions such as speech or behavioral motor actions.

The mechanism that generates the inner sensation of memory should have a connection with the mechanism that generates motor action. There should be a provision for disabling this connection at will.

The IPL mechanism can generate both units of first-person inner sensations and motor action reminiscent of the arrival of the item whose memory is retrieved. The motor outputs can be inhibited while inner sensation is being generated (Vadakkan, 2010a; 2013).

It is difficult to inhibit a memory which is being retrieved.

A structural mechanistic explanation is needed.

IPL is an inter-membrane connection. Once IPL is present and functions, it is not possible to inhibit its function voluntarily. Additional inter-spine LINK with an inhibitory spine may become possible through future associative learning events (Vadakkan, 2007; 2010a).

The mean inter-spine distance on the dendrite of a pyramidal neuron is more than the mean spine diameter (Konur et al., 2003).

This opens the possibility for neuronal processes that belong to other neurons to occupy the inter-spine space. It is reasonable to expect some functional importance for such a scheme of inter-spine spacing. Since spines of different neurons occupy this space and ECM is often negligible (see Fig.13 in FAQ), some of the spines that belong to different neurons can remain abutted to each other.

Abutted spines that belong to different neurons increase the probability of inter-neuronal inter-spine interactions. These interactions are the basis of IPL proposed by the semblance hypothesis (Vadakkan, 2010a; 2013).

Both learning and retrieval of memory are associated with the firing of a set of neurons.

Learning is expected to make certain new channels. Passage of potentials across these channels (both during learning & memory retrieval) is expected to allow certain neurons held at sub-threshold level to cross the threshold to fire a new set of neurons.

This can be a cause or effect. During learning & memory retrieval, stimuli propagating as action potentials can fire neurons. The outputs from these neurons allow potentials to propagate through new IPLs formed at the time of learning. This allows neurons that are being held at sub-threshold activation states to fire action potentials.(Vadakkan, 2010a; 2013).

Place cells fire in response to specific spatial stimuli.

A mechanism that generates the inner sensation of memory for a location is expected to have a mechanistic connection with the firing of a set of CA1 neurons.

Place cells are CA1 pyramidal cells. When islets of inter-LINKed spines of overlapping dendrites of CA1 neurons receive spatial inputs, they provide potentials to their postsynaptic CA1 neurons. If these CA1 neurons are being held at subthreshold activation states, then they fire. This explains place cell firing (Vadakkan, 2013; 2016a).

Firing of an ensemble of neurons during a higher brain function.

Inner sensation generated during a higher brain function is associated with firing of an ensemble of neurons.

Reactivation of IPLs during a higher brain function will add potentials from the inter-LINKed spines to their postsynaptic neurons. If these potentials add up to allow these neurons to cross the threshold, they will fire (Vadakkan, 2010a; 2016a).

Firing of separate sets of neurons during learning and memory retrieval.

Associative learning between two stimuli is expected to cause firing of a set of neurons. Only one of the associatively learned items is needed to be present to retrieve the memory of the second item. Hence, only a subset of neurons that fire at the time of learning is expected to fire at the time of memory retrieval.

During learning, two associating stimuli will propagate depolarization along their paths and lead to firing of a set of neurons. At the time of memory retrieval, only one/ partial feature of one of the associatively learned stimuli is present. In addition, potentials propagating across the learning generated IPLs will lead to firing of a new set of neurons that are being held at sub-threshold activation states along their paths (Vadakkan, 2010a; 2016a).

Fast changes in both the magnitude and correlational structure of cortical network activity (Benisty et al., 2024).

Rapidly time-varying functional connectivity is responsible for such changes.

Changes in environmental stimuli, self-triggered thought processes, inner sensations of fear, anticipation, hunger, and comfort levels fluctuate moment to moment indicating the formation and reactivation of a new set of IPLs. This will change network activity (Vadakkan, 2019a).

A cortical pyramidal neuron in one neuronal order is receiving input from several neurons of the lower order (Ecker et al., 2010).

To cause firing of a cortical pyramidal neuron, it is most likely that these neurons are being held at a sub-threshold state in the background state. If a cue-induced memory retrieval mechanism causes firing of a specific set of neurons that were not firing before learning (in response to the cue stimulus alone), then it is necessary to show that the change generated by learning is acting as a channel during memory retrieval to provide potentials to postsynaptic neurons to cross the threshold for firing.

Recent modeling studies have shown that a pyramidal neuron can fire an action potential by spatial summation (summation at the same time) of nearly 140 EPSPs at the axonal hillock that arrives from randomly located dendritic spines (Palmer et al. 2014; Eyal et al., 2018). However, based on calculations of energy per bit of information, 2000 synaptic inputs are needed for neuronal firing (Levy and Calvert, 2021). IPL mechanism is able to explain how learning generated change is capable of generating cue-induced inner sensations as well as motor responses. In addition, it also leads to the firing of a new set of neurons.

Any set of 140 input signals arriving from random locations on the dendritic tree can fire a neuron. Hence, there is extreme degeneracy of input signals in firing a neuron. A system operating by such a scheme was selected from a large number of variations since this offered functional advantages to the system.

Since such a scheme is expected to be used specifically, then a possible situation must be there. If a neuron is being held at sub-threshold level by receiving nearly 130 inputs, then it needs 10 more input signals for its firing. If only a specific cue stimulus in a specific context can provide a specific set of input signals for 10 additional input signals, then this possibility can be tested.

Islets of inter-LINKed spines can provide an opportunity to pool all the potentials at one location from where it can be delivered in a summated manner. Dendritic spikes can be viewed resulting from it. These can reach the axonal hillock efficiently to cause neuronal firing for motor effect. Inter-LINKing with spines that receive different neurotransmitters in the islets can regulate these islets (Vadakkan, 2016a).

Many neurons are being held at sub-threshold activation state.

By holding a neuron at a certain potential below the threshold, it is possible to regulate the neuronal output, conditional upon arrival of a certain number of inputs. This can be very important to generate certain motor outputs such as speech & behavioral actions.

Several neurons are being held at sub-threshold activation states (Seong et al., 2014). At the islets of inter-LINKed spines, summation of potentials generated by a set of input signals can generate summated potentials to cross the threshold to fire the output neurons.

An operational mechanism is expected to take place in an energy efficient location.

Input signals (postsynaptic potentials) have maximum strength at the location of their origin, which is the spine head. As the potentials propagate further, they get attenuated in the spine neck region. Further attenuation occurs as they propagate towards the neuronal cell body. Signals from different spines mix within the dendrite. Also, they attenuate as they propagate towards the neuronal soma. Hence, the most likely location for a learning mechanism that can maintain specificity until the time of its retrieval is expected to occur in the spine head region.

IPLs are formed between the head regions of abutted spines that belong to different neurons (Vadakkan, 2010a; 2016a). Hence, information arriving at the input regions are preserved most. Note that any set of nearly 140 input signals cause the same neuronal firing. Hence, neuronal firing is non-specific with respect to specific input signals. This leads to loss of specificity of information. Hence, it is reasonable to anticipate a mechanism to recover/compensate for the lost information during memory retrieval.

A dendritic spike occurs by the summation of nearly 10 to 50 postsynaptic potentials (on the spines) at the dendritic region (Antic et al., 2010).

It is necessary to explain which spines contribute to the potentials and explain their significance.

Semblance hypothesis explained that the potentials that contribute to a dendritic spike belong to spines (of different neurons) that form an islet of inter-LINKed spines (Vadakkan, 2016a).

When current is injected into the dendrites of human layer 2/3 neurons they generated repetitive trains of fast dendritic calcium spikes, which can be independent of somatic action potentials (Gidon et al., 2020).

It is necessary to explain the routes through which the high potential of a dendritic spike propagate without reaching the cell body to generate a somatic action potential (neuronal firing).

An islet of inter-LINKed spines can lead to generation of dendritic spikes. The net potential of dendritic spike can drain through a few of the inter-LINKed spines depending on the several regulatory factors - for e.g. inter-LINKing with spines that synapse inhibitory or other regulatory inputs (Vadakkan, 2016a).

Certain dendritic spikes are not followed by somatic action potentials (Golding & Spruston, 1998).

Conventionally it is thought that dendritic spikes are efficient detectors of specific input patterns ensuring a neuronal output (action potential) (Gasparini et al., 2004). So, a source for leakage of potentials from the dendritic area other than its propagation towards the soma needs to be explained.

The islet of inter-LINKed spines (IILSs) provides routes for a dendritic spike to propagate. A dendritic spike can propagate to inter-LINKed spines within an IILSs (that offer fewer resistant routes) towards the dendritic trees of those IILSs' neurons. Recordings carried out from those neurons can provide a proof for the presence of IILSs.

Inner sensation of certain higher brain functions occurs without any motor actions.

The mechanism that generates inner sensations must be able to demonstrate that either no behavioral motor actions are generated along with a particular inner sensation or that the motor action can be voluntarily suppressed.

It is shown that the apical dendrites in human layer 5 neurons are electrically isolated from that of the somatic compartment (Beaulieu-Laroche et al., 2018). This indicates possible occurrence of independent operations of islets of inter-LINKed spines at those remote dendritic regions.

When two differential electrodes are placed at 2 extracellular locations, extracellular potentials can be recorded. They show oscillations. Brain operates only when the frequency of these oscillations remains within a narrow range.

It is necessary to demonstrate that 1) the vector components contributing to these oscillations are likely involved in generating both inner sensations and associated behavioral motor actions, and 2) they have reciprocal ionic changes in the cytoplasm of the processes of cells (mostly neurons).

While synaptic transmission provides one vector component, something else constitutes the other vector component/s that is/are expected to take place nearly perpendicular to the direction of synaptic transmission. Propagation of depolarization along the IPL matches with the latter (Vadakkan, 2010a; 2013).

Apical tuft regions of neurons of all the cortical neuronal orders are anchored to the inner pial surface resulting in overlapping of the dendritic arbors of neurons from different orders. This resulted from a sequence of movement of neuronal precursors during development.

Dendritic spines of neurons that belong to both the same (mainly) and different neuronal orders overlap with each other to serve certain functions.

Overlapping of dendrites that belong to different neurons facilitate formation of inter-neuronal inter-spine LINKs (Vadakkan, 2016a, 2019a). Anchoring of apical tuft regions of all the cortical neuronal orders facilitates inter-order neuronal inter-spine LINKs.

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

The process by which repeated retrievals of a memory in response to a cue stimulus lead to its sub-conscious nature must be able to explain a framework of a mechanism of consciousness.

Explained by the semblance hypothesis (Vadakkan, 2010b; 2019a). A routinely arriving cue stimulus becomes either unessential or deleterious for survival. Hence, the units of inner sensations evoked by its IPL reactivations merge with the net semblance of consciousness. Hence, those cue stimuli or memories evoked by them will reach a subconscious state.

Activity-dependent structural 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.

High energy applied during LTP stimulation on single spines has shown to cause spine enlargement (Matsuzaki et al., 2004). LTP can be explained in terms of formation of large number of IPLs in response to the application of high energy. Hence, it is possible to expect a scaled down effect of IPL formation between already abutting spines during associative learning (Vadakkan, 2019b).

Several seizures spread laterally to the adjacent cortices.

The cellular mechanism responsible for seizures should be capable of explaining the lateral spread.

Explained by the semblance hypothesis (Vadakkan, 2016d).

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 IPLs mechanism explains inner sensation of perception and trigger motor neurons from layer V of the cortex at those regions (Vadakkan, 2016d).

Pathological changes of amyotrophic lateral sclerosis (ALS) spreads laterally.

It is necessary to find an explanation how certain structural alterations from the normal operational mechanism aid in the lateral spread of neurodegenerative changes in ALS.

IPL structural stability remained only till the stage of inter-spine membrane hemifusion stage. Any alterations of membrane structure can lead to membrane fusion leading to laterally spreading pathological changes of spine loss and eventual neuronal loss as observed in ALS (Vadakkan, 2016c).

Transfer of injected dye from one CA1 neuron to the neighboring CA1 neurons is observed in animal models of seizures (Colling et al., Brain Res. 1996).

CA1 neurons are located lateral to each one. 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, 2016d).

Loss of dendritic spines after kindling.

It must be possible to explain loss of spines after kindling in an interconnected manner with similar changes during seizures and LTP. What advantage does this action provide to their neurons?

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, homeostatic mechanisms are expected to cause loss of spines involved in fusion. This is to protect their neurons from further damage (Vadakkan, 2016d).

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 and then provide a specific property of CA2 area that helps to resist seizuers in that region.

Based on 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 and Ethell, 2011) provides an explanation (Vadakkan, 2016d; Vadakkan, 2019b).

Seizures and memory loss are caused 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.

HSV fusion proteins can lead to conversion of IPL hemifusion state to fusion state. This will lead to mixing of cytoplasms of different neurons leading to memory loss & seizures (Vadakkan, 2016d).

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 severly reducing the frequency of oscillating extracellular potentials. This prevents both inner sensations and motor actions (Vadakkan, 2016d).

Memory impairment in patients with seizure disorders (Mazarati, 2008).

Mechanism of learning, memory retrieval and behavioral motor actions are expected to be affected by the mechanism of seizures.

Seizure pathology involves formation of several non-specific IPLs, and IPL fusion between spines leading to spine loss and even loss of neurons. These can explain memory defects in seizures (Vadakkan, 2016d).

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 (S pruston,2008), spatial summation of several of these EPSPs is a feasible mechanism to explain the PDS. Hence, IPL formation can explain PDS in seizures (Vadakkan, 2016d).

Even though simultaneous reduction in Ca²⁺ and an elevation in K⁺in the extracellular matrix 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 a 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 provides an alterate route that can favor summation of EPSPs and also cause propagation of PDS-like activity throughout the cortex (Vadakkan, 2016d).

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 the ECM between the spines. This can favor formation of non-specific IPLs, especially when additional factors leading to seizures are present.

Ketogenic diet is used to prevent seizure (Martin-McGill et al., 2020; Kossoff et al., 2021). Ketogenic diet serum concentrations 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, preventing nonspecific membrane hemifusion and fusion, preventing rapid formation of IPLs to prevent seizures (Vadakkan, 2016d).

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 throughout the cortical regions. Even though IPLs are limited only up to IPL hemifusion stage, changes in cell membrane composition and 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, 2016d).

Loss of consciousness during complex seizures.

It is necesary to explain a framework that generates first-person inner sensation of consciouness & explain how seizure activity lead to loss of consciousness.

Rapid chain generation of a large number of IPLs leads to induction of a large number of non-specific semblances that cause loss of C-semblance for consciousness (Vadakkan, 2016d).

Multiple vertical sub-pial resections have been found to alleviate seizures (Morrell et al, 1989)

Some structural connection are getting lost when vertical resection are carried out. Neurons are organized from top to bottom in the cortical layers. So, it is necessary to explain what lateral connection are getting sectioned in this procedure.

The horizontal connections that are severed are the recurrent collaterals and IPLs. Removal of IPLs will prevent IPL-mediated rapid chain lateral
propagation of seizure activity (Vadakkan, 2016d).

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 how introduction of a state of "burst supression" is achieved with anesthetics & this may aid in controlling siezures 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 horizointal 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 IPL formations at those levels.

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.

Explained by the semblance hypothesis (Vadakkan, 2016c).

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.

Explained by the semblance hypothesis (Vadakkan, 2016c).

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 either side by two ajacent stimuli to generate units of inner sensation of perception (Vadakkan, 2015b).

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 integral of all the perceptons. Hence, the actual location of an object need not necessarily match the percept. This becomes clear when there is a medium that shift the patch of light towards the eye (Vadakkan, 2015b).

Homogeneity in the percept for stimuli arriving above the flicker fusion frequency.

A mechanism for fusion of inner sensation of continuous perception of a source of light that is affected by frequency of flickers is needed.

Since perceptons from IPLs located at different regions in response to one flicker has a temporal pattern of generation, overlapping formation of perceptons from consecutive flickers overlap and generate a continuous percept (Vadakkan, 2015b).

Perception of object borders.

A mechanistic explanation for the formation of first-person percept for object borders is needed.

Percept of a stimulus has to be generated from stimuli within the border region 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, 2015b).

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 reaching the locations of their convergence can lead to reactivation of IPLs for generation of perceptons (Vadakkan, 2015b).

Continued perception of moving objects without any interruptions.

It is necessary to explain how the percept is maintained 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 sides of the same set of IPLs. If the object moves faster than the formation of perceptons that can be overlapped, then it will lead to saccadic eyeball movements that will allow for continuity of the percept.

Both vision and olfaction are perceptions.

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).

It was possible to show the presence of a comparable circuitry for olfactory perception in the nervous system of the fly Drosophila (Vadakkan, 2015b).

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 changes 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 at the inter-LINKed spines on either side of an IPL (Vadakkan, 2015b).

Flash-lag effect - 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). Visual pathway has synapses that cause synaptic delay. Overlapping reactivation of IPLs by continuous arrival of stimuli maintains perception; whereas a fresh stimulus undergo delay to initiate perception.

Inner sensation 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 baseline oscillating extracellular potentials as recorded by EEG. This shows testable propagation of potentials along many IPLs contributing to its horizontal component. Net inner sensation generated by reactivation of inter-LINKed spines during background state can contribute to inner sensation of consciousness (Vadakkan, 2010b).

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 as the net semblance from non-deleterious & non-beneficial stimuli from environment & body. (Vadakkan, 2010; Vadakkan, 2015a ). 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 formation of large number of non-specific IPLs altering inner sensation of consciousness.

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 explain how actions on different receptors cause loss of consciousness. 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.

Based on the semblance hypothesis, large number of non-specific IPLs are generated by the anesthetic agents by virtue of their common property of lipid solubility (Vadakkan, 2015a).

Potency of an inhaled anesthetic agent is proportion to its partition coefficient (concentration ratio) between olive oil and water (hydrophobic solubility). This has a correlation coefficient of 0.997 (Firestone et al. 1986), which is 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, 2015a).

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, 2015a).

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 promote increased IPL formation and reduce the required amount of anesthetics for generating a certain level of anesthesia compared to that in the absence of dopamine.

Low doses of anesthetics leave very short-term memory intact, such
that patients can carry on a conversation and appear to
be lucid (Wang and 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; whereas increasing doses start affecting it.

Since IPLs are highly reversible, newly formed IPLs by anesthetic

agents reverse back. But formation of more non-specific IPLs will start affecting the short-term memory. Since most IPLs generated by anesthetic agents are non-specific, at higher concentrations of anesthetic agents, learning-induced IPLs will get diluted in the presence of increasing number of non-specific IPLs generated proportional to that of the concentration of anesthetic agent (Vadakkan, 2015a).

General anesthetics generally do not impair existing long-term memory (Bramham and 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, 2015a).

There are several reports of cognitive decline after surgery that uses general anesthetic agents

It is necessary to provide a plausible explanation 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, 2015a; Vadakkan, 2016).

As the anesthetic dose is increased, patients enter a state of excitation characterized by euphoria or dysphoria, defensive or purposeless movements, and
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 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. As anesthetics induce more IPLs, it will lead to both generation of certain inner sensations & firing of several sub-threshold activated neurons in the motor cortex.

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.

Explained based on the semblance hypothesis (Vadakkan, 2016d). Rapid chain formation of large number of non-specific IPLs due to changes in ECM properties (e.g. very low serum Na⁺) or due to increased excitability of neurons.

Changes in consciousness with 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 state of normal state of consciousness.

Explained based on the semblance hypothesis (Vadakkan 2010b; 2015a). Unconscious states show large variations in the frequencies of extracellular potentials recorded from skull surface in EEG (Rusalova, 2006).

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 11).

Inputs two different locations converge into one IPL at a higher neuronal order region can lead to semblance of sensory input towards those regions (Vadakkan, 2010a, 2013).

Phantom sensation or 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 IPL through a different sensory input can evoke semblance of phantom limb or pain.

Mechanism for innate behavior that enables survival.

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

Explained based on the semblance hypothesis (Vadakkan, 2020). Convergence of sensory stimuli having different velocities is programmed in the genetic code and executed during development that favor the formation of IPLs.

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.

Explained based on the semblance hypothesis (Vadakkan,2015a). Conversion of IPLs to inter-neuronal inter-spine fusion leading to degeneration is a testable mechanism.

More years of education (increased number of associative learning events) reduces dementia risk (Maccora et al., 2020).

Should be able to explain whether redundant learning-induced changes get induced by prolonged learning events.

Explained based on the semblance hypothesis (Vadakkan 2013; 2019a). Redundant IPLs form during different learning events as new neurons get inserted into the circuit.

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. Hence, these are most likely locations of converging fiber tracts or converging locations of specific input signals responsible for those functions.

Astrocytic pedocytes cover less than 50% of peri-synaptic area in nearly 60% of the synapses in the CA1 region of hippocampus (Ventura and Harris, 1999).

Hippocampal mechanism of learning & memory must explain the suitability of distribution of astrocytic processes.

Explained based on the semblance hypothesis (Vadakkan 2019a). Remaining free area of the spines favor inter-neuronal inter-spine interactions that form IPLs.

Present nervous systems have evolved over millions of years and are also the results of certain accidental coincidences.

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.

Explained based on the semblance hypothesis (Vadakkan 2020). Sparking of the first-person inner sensations of all the features of an item in the environment on arrival of the fastest or first sensory stimulus from that item started providing survival advantage to animals in a predator-prey environment.

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 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 prevent further inter-cellular fusion. Since neurons cannot divide further, a transient stage of fusion is expected to trigger 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 first occurrence of inter-neuronal fusion is likely due to changes in membrane composition or lack of checkpoint mechanisms to arrest hemifusion from progressing to fusion.

Following the above stage where dye diffusion is observed, significant neuronal death (70%) (Blaschke et al., 1996) and 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.

Higher brain functions take place in a narrow range of frequency of oscillating extracellular potentials as evidenced by EEG (Rusalova, 2006).

Both the mechanism for learning and memory retrieval is expected to contribute/depend on vector components to the oscillating extracellular potentials.

Explained based on the semblance hypothesis (Vadakkan, 2010a; 2013).

100

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.

101

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 spines (in contrast to what is observed in the presynaptic terminal).

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 the process 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).

102

Transcriptomic analyses show heterogeneity of even adjacent neurons of the same type in the cortex (Kamme et al., 2003).

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 (Vadakkan, 2016c). This matches with the final purpose of it to restrict structural aspect of IPLs to the stage of inter-membrane hemifusion.

103

Heterogeneity in clinical features and pathological changes in Alzheimer's disease (& other neurodegenerative disorders).

1. Many factors are likely involved in the operational mechanism. 2. There will be a universal mechanism that involves different neuronal types. Pathology of such an operational mechanism can explain heterogeneity.

A common mechanism is pathological conversion of normal maximum limit of hemifusion to pathological fusion. Clinical features depend on a) locations of IPL fusion that can damage spines & neurons, and b) formation of non-specific IPLs at different locations (Vadakkan 2016c).

104

In excitatory neurons, spine depolarization can occur even without dendritic depolarization (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?

IPL mechanism that generates units of inner sensation needs only depolarization of spines. Lack of firing of the postsynaptic neuron will lead to lack of motor output while units of inner sensation occur at an inter-LINKed spine (Vadakkan, 2013; 2019a).

105

The histological features of amyloid (senile) plaques and neurofibrillary tangles observed in normal aging (Anderton, 1997) are also the pathological features in Alzheimer's disease & several other disorders in the spectrum of neurodegenerative disorders.

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 last stage of IPL formation is hemifusion, which is an intermediate stage of fusion. Various factors such as viral fusion proteins and membrane compositional changes can overcome the check point mechanisms converging IPLs to inter-neuronal inter-spine fusion. This will cause cytoplasmic content mixing. Since expression profiles of even adjacent neurons of same type are different, it leads to neuronal damage (Vadakkan, 2016c).

106

Therapeutic agents developed for treating seemingly unrelated neurological diseases such as seizure disorders, Parkinson's disease, spasticity, and 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.

107

Since learning is expected to generate certain new circuit connections, the circuit elements (like on a printed circuit board) 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 and Parsegian, 1984; Martens and McMahon 2008; Harrison, 2015).

108

"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 redundancy in its operational mechanism, presence of a common integration mechanism and shift in the locations from where function occurs.

Correlation between a brain function and neuronal firing will be true for those neurons that are being held at sub-threshold activation state and receive additional potentials through the same IPLs. Subthreshold activation state of a neuron can be affected by several factors. Additional learning events can lead to the formation of new IPLs. These can change the set of neurons that fire (Vadakkan, 2019a).

109

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.

Spines within the islets of inter-LINKed spines are connected via an oxidation state dependent manner (Vadakkan, 2022).

110

Formation of new neurons in the hippocampus, especially in non-stationary environments.

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 make new IPLs at higher neuronal orders increasing number of sparse storage mechanisms (Vadakkan, 2011a).

111

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 last stage of permitted inter-membrane interaction leading to 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.

112

Generalization is seen in the Transformers of the large language models (LLMs) that use neural networks organized using a hidden layer.

A mechanistic explanation is needed to explain where and how the hidden layer operates. This must explain how the system generates an appropriate output in response to a new prompt that the system never got exposed in the past.

Basic concept of “islet of inter-LINKed spine heads” in the semblance hypothesis matches with that of the “attention heads” in the Transformers of LLMs (Vadakkan, 2024).

The following are findings related to long-term potentiation (LTP), an electro-physiological finding that has shown several correlations with the ability to learn. Constraints from several findings associated with LTP matches with scaled up formation of non-specific IPLs derived by the semblance hypothesis. Note: To reach interconnected explanations, sometimes it was necessary to re-interpret the findings and provide alternate explanations different from that by the authors of research work.

113

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 formation of large number of non-specific IPLs responsible for LTP. More abutted spines at locations of convergence of sensory stimuli leads to a) increased ability to learn, and b) when high energy is applied it leads to increased formation of non-specific IPLs responsible for LTP (Vadakkan, 2019b).

114

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, 2019b).

115

Blockers of membrane fusion blocks LTP (Lledo et al., 1998).

Need to explain the cellular location where they act and 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, 2019b).

116

Loss of spines during LTP induction (Yuste and Bonhoeffer, 2001).

A mechanistic explanation is needed for loss 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.

117

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 and Ethell, 2011) provides an explanation (Vadakkan, 2019b).

118

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, 2010a; 2013). At locations where more IPLs are present, it is possible to generate proportionately more non-specific IPLs responsible for LTP induction (Vadakkan, 2019b).

119

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, 2019b).

120

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, 2019b).

121

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).

122

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, 2019b). 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 and Parsegian, 1984; Martens and McMahon, 2008; Harrison, 2015).

123

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 brings together repulsive membranes and overcome energy barriers related to curvature deformations during hemifusion (Martens & McMahon, 2008; Olkers et al., 2016). SNARE proteins generate force for pulling the abutted membranes together as tightly as possible (Hernandez et al., 2012). t-SNARE protein syntaxin cause local membrane traffic in spines and directs membrane fusion (Kennedy et al., 2010).

124

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, 2019b).

125

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 membranes that can lead to the formation of IPLs.

126

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.

127

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, 2019b).

128

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 a few nanometers at which IPLs are expected to form during natural learning. Hence, in the latter case, most of them reverse back.

129

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 and Parsegian,1984; Martens and McMahon, 2008; Harrison, 2015). High energy stimulation alone can achieve inter-cellular fusion (for.e.g. in hybridoma production (Zimmermann & Vienken, 1982).

130

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, 2019b).

131

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, 2019b).

132

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, 2019b).

133

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, 2019b).

134

Property of cooperativity in LTP induction. Only a fixed fraction of stimulated presynaptic terminals directly synapse 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, 2019b).

135

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, 2019b).

136

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).

137

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 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.

138

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.

139

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 uses very high energy during which physiological IPL changes are expected to progress to membrane fusion that offer resistance to reversal.

140

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.

IPL fusion changes produced by LTP induction are highly resistant to get reversed back. Since IPL fusion changes occur between lateral margins of spines that belong to different neurons, they will not have any influence by NMDA receptor inhibition.

141

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.

Reversal of the IPLs is expected to be associated with both endocytosis of AMPAR subunits and reduction in the size of enlarged spines that can explain LTP decay.

142

Increase in size of mEPSP (miniature EPSP) after LTP induction (Manabe et al., 1992).

mEPSP is thought to be influenced by an increase in the number or function of AMPA receptors. 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 that mostly belong to different neurons showing increase in the size of mEPSP.

143

Several delayed changes that occur following LTP induction that have shown correlations with learning and memory (e.g CaMKII phosphorylating AMPA receptor subunits (Lisman et al., 2012).

It is necessary to explain how delayed changes following LTP is 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 generate new IPLs during subsequent learning events.

144

LTP induction is known to modify specific sets of place cells. Specifically, LTP hippocampal pathways abolished existing place fields and created new place fields (Dragoi et al., 2003).

It is necessary to provide a mechanistic explanation how changes brought about by LTP induction affect firing of place cells (CA1 neurons in 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).

145

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.

146

Potentiated effect was observed by patch-recording 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 generate them.

This can be explained in terms of the formation of several IPLs by the spines of new granule neurons (compared to the old ones) with the pre-existing islets of inter-LINKed spines of existing granule neurons.

147

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 through which potentials arrive to generate large EPSPs.

Simultaneous arrival of input signals to two or more synapses that have inter-LINKed spines (postsynaptic terminals) will lead to summation of EPSPs leading to large EPSPs recorded from any single postsynaptic terminal.

148

Prevalence of dendritic spikes in the dendrites of place cells (CA1 neurons) in behaving
mice predict 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 additional potentials to a dendritic spine. Arrival via IPLs is feasible. Spatial stimuli reaching an islet of inter-LINKed spines can lead to summation of EPSPs in the islet and generate a dendritic spike.

149

Permanent changes in the motor response to a single stimulus occur due to repeated exposure to that stimulus and 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 single stimulus consists of many components. Hence, it can lead to generation of IPLs. Furthermore, incorporation of new neurons in the circuit in between the repetition of stimuli can alter the circuit and lead to formation of new IPLs.

IPL: Inter-postsynaptic functional LINK; ECM: Extracellular matrix

Foot note 1: If we provide a set of colors and picture against each color and ask people to learn the association in one second, most people will be able to learn two or more associations during this period. This means that associative learning can take place in milliseconds. What type of a change can occur in less than one second?

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, it must be considered unproven until further verification of its testable predictions are made.

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!

‌Semblance hypothesis