From Science


This page examines how methods used in other fields of science can be utilized to understand the operational mechanism of the nervous system. Specific instances from the fields of molecular biology, immunology, physics and mathematics that can be used to overcome the current difficulties in understanding the nervous system are explained.
How to understand the operational mechanism of the nervous system functions?
What lessons can be used from other fields of research?
NEUROSCIENCE
It is generally considered that it is very difficult to understand the operational mechanism of the nervous system. This is primarily because brain functions are being studied by a large number of levels and there are a large number of important findings at all those levels. Bringing all those findings together is very difficult in the current circumstances. But if we look positively, all those findings are providing us with constraints that can be used to derive the operational mechanism of the system. But a huge systematic approach is necessary towards this. Unlike the situation before the discovery of the structure of DNA where Watson and Crick were anxiously waiting for obtaining constraints from a different level, in neuroscience we are overwhelmed with too many constraints that can be used to solve the system. A list of constraints from findings from different levels is given in Table 2 in the home page of this website. The mechanism should be able to fulfill all those constraints. Only the correct solution can explain disparate constraints. A sample list includes the following - explain all the observed correlations between learning and LTP induction,  explain the learning-induced change that can remain for different duration for generating working, short and long-term memories and explain why the system needs sleep. In summary, we should be taking advantage of this situation. 
MOLECULAR BIOLOGY
Model of DNA put forward by Watson and Crick was a hypothesis (see the last paragraph of their article). (Watson & Crick (1953) Article).  Nearly a dozen hypotheses were put forward at the same time. Why did Watson & Crick  get it right? The composition of DNA was known by 1950. While configuring the structure, one is expected to make sure that it matches with features necessary for all of its functions.  For example, since DNA molecule is tightly packed within the chromosomes (even though DNA in interphase chromosome is not as tightly packed as in metaphase), DNA  structure should provide sufficient unwinding for allowing both replication and transcription. This will make one to back off from a helical structure since huge amount of energy will be necessary to unwind supercoiled DNA and then to separate the strands in  a helix. But this didn't dissuade Watson and Crick from putting forward their hypothesis, since they knew that the constraints provided by a large number of observations must be leading them to the correct solution. It is to be noted that the enzymes that are involved in replication and transcription were discovered later! For e.g. DNA polymerase was discovered only in 1956 and RNA polymerase (- DNA dependent)  only in 1960. Primarily Watson and Crick relied on constraints from observations to find the solution. Compared to others they had constraints from one additional level - X ray crystallographic picture of DNA, which is a finding different from the level of biochemical findings. Including one additional constraint from a different level was very powerful that it led them to the correct model. This indicates that a solution arrived using more constraints provide confidence, even though some observations may make us think otherwise initially. Crick was a physicist and that made a difference. 
NEUROSCIENCE
Difficulty to undertake hypothesis building that can encompass the findings from different levels and at the same time conduct experiments to verify the predictions resulting from such work is conceivable. Previous hypotheses could not provide a solution with inter-connectable explanations for different features of the nervous system from different levels and make testable predictions. However, we have carried out a very large number of experiments at different levels and collected a huge amount of data. Even after these achievements we are confident that we do not understand the operational mechanism of the nervous system. Why is the situation not changing? How can we break this impasse? When we say that we do not understand the system, what it clearly says is that we do not understand its most important function of generation of first-person internal sensations within it. This is because third-person experimenters do not have access to the first-person internal sensations generated within it. This provides us an implicit confidence about the difficulties in discovering its operational mechanism. Since we already know the problem, we must make it explicit and seek for a solution immediately. If we want to continue the conservative approach that we have been following in science, this is the next step that we must embrace.
PHYSICS
When a branch of science accumulates a large number of information, then it is necessary to have separate areas for both theory and experiments. This is because, the theorists often have to spend huge amount of time to synthesize a hypothesis for a basic governing mechanism/principle of the system using constraints from a large number of findings and verify their theoretical fitness. Physics is an example. When a system exhibits disparate features, it is necessary to derive a theoretical solution first to make further progress. This is because, the results of a theoretical inquiry is often cannot be imagined or appreciated. When a system exhibits disparate features, constraints from them often leads to a unique solution that otherwise will not be available to us. A solution (hypothesis) is expected to make predictions, which is a basic requirement. The idea here is that rejecting a hypothesis quickly is cost-effective than trying to prove it correct. Hypotheses that cannot explain all the properties of the system in an inter-connectable manner can be rejected prima facie. Those that do not provide predictions will remain untestable.  
NEUROSCIENCE
Many scientists do not even discuss about the first-person internal sensation due to the implicit difficulties in studying this property. This prevents further progress in solving the system. Since solution for the system is expected to provide nothing less than the gold standard test of its replication in engineered system, it is necessary to understand the operational mechanism that generates internal sensations. The mechanism for this function within this evolved system is expected to occur from a simple operation capable of evading our attention. Is there a way forward? Let us take the case of memory and examine the problem. Memories are virtual first-person inner sensations that can be viewed as hallucinations (a sensory experience of something in its absence) (Minsky (1980) Article). Therefore, we need to find out a learning-induced changes that can be used by one of the associatively learned stimuli to induce memories as hallucinations. Now we have a challenge. Hallucination is a first-person property towards which our (third-person) sensory systems do not have access. Where can we get help from? Are there any basic science field that has dealt with items towards which our sensory systems do not have access?
PHYSICS
The first-person internal sensation can be compared to different fundamental properties of physics that cannot be further split into its components. For example, electromagnetism (EM). EM field is generated when a current carrying conductor cuts a magnetic field. We accept it as a basic property. We then try to derive an equation that can explain this property using all the variables that determine this property. For example, formulation of an equation for the EM radiation by James Clark Maxwell.

NEUROSCIENCE
Using constraints from all the findings from different levels of the nervous system, a solution-point can be derived. If successful, this location is expected to have all the required features of the system that can generate first-person inner sensations as hallucinations.

When a method similar to solving a system of linear equations is applied in solving the nervous system, the following requirements have to be taken into account - a) incorporate all the variables, including those containing first-person internal sensations into the equations, and b) do not add any redundant equations. These indicate that we have to try to solve the system using only the non-redundant equations and should be seeking new experiments only if we cannot solve the system. In the latter instance, we may be able to predict the nature of the new equation/s (experiments and their results) to be selected towards reaching the solution.

Is there another feature available to identify this location of major function within a system?
MATHEMATICS
When deriving a new, unknown principle, in many instances physics uses the basic principle of solving a system of linear equations having a unique solution. This necessitates incorporating all the non-redundant equations within the system and then use all the variables to formulate the solution. The solution point (for e.g. in a graph) binds all the equations within the system of linear equations. Before starting the procedure to solve the system, it is better to remove all the non-redundant equations since they do not add any value in solving the system. 
NEUROSCIENCE
In the nervous system, it is known that only a minute fraction of inputs to a cortical neuron with tens of thousands of inputs can fire that neuron. This extreme degeneracy of inputs that can fire a neuron (Vadakkan (2018) Article), indicates that the operational mechanism of the system is associated with these inputs. Since these inputs weaken as they propagate towards the neuronal cell body, the operational mechanism most likely be occurring at the origin of these inputs.

Usually, we find initial difficulties in identifying the location of redundancy/ combinatorial elements/ redundancy in a system as evident from the cases of codons and variable regions of immunoglobulins. In the case of the nervous system, we know where the redundancy is. We were not utilizing this finding since we could not derive a potential mechanism for generating internal sensations (hallucinations). Furthermore, we have been examining behavior in lieu of internal sensations.

Using different constraints from the findings of the nervous system, it was possible to derive a solution-point at the location of origin of inputs (dendritic spine head region). More specifically, an interaction between the abutted spines during learning called inter-postsynaptic functional LINK (IPL) was derived. The properties of the IPL junction allow reactivation of the IPL from a lateral direction by a cue stimulus to induce a hallucination that the inter-LINKed spine is receiving a sensory input from the environment (Vadakkan (2013) Article).

How do we know that the hypothesis is correct? What is the most important deciding factor that determines the derivation of a correct hypothesis? How does basic science view such properties like generation of internal sensations that third-person examiners cannot sense using their sensory systems?
IMMUNOLOGY
In situations where limited resources must be used for an infinite number of conditions, then nature often makes use of the power of combinatorial mechanisms by using unitary mechanisms. A typical example is the combinatorial mechanism for generating immunoglobulin gene variations for generating nearly 1011 (close to the number of humans that have ever lived!) different antibodies with specificity to respond to that many different antigens arriving from the environment (Tonegawa (1983) Article; (2001) Review).
NEUROSCIENCE
The solution was examined for its ability to explain a very large number of findings and satisfy the constraints offered by them (Table 2 on the Home page). It was possible to provide explanations for all of them. For example, both associative learning and induction of first-person inner sensations take place only when the system operates at a narrow range of frequency of oscillating potentials (Vaz et al. (2019) Article). Induction of internal sensations is a function of frequency of oscillating potentials.
MOLECULAR BIOLOGY
One big question in middle of last century was to find how DNA codes for amino acids to synthesize a polypeptide. From 4 bases, it is necessary to make 20 amino acids. Logic alone led to the discovery here. If 1 base code for one amino acid - only 4 amino acids can be coded. If 2 bases code for one amino acid, then 42 = 16 amino acids can only be coded. If 3 bases are used 43 = 64 amino acids can be coded. But there are only 20 amino acids. This stretch of logical thinking came from the lab of Francis Crick (Article). It also led to the thinking that some amino acids may be coded by more than one code - degeneracy of the codons at the 3rd base of the codon (mainly).

From above examples, one can make a reasonable assumption that if degeneracy or combinatorial mechanism is present at a lower level, then it is most likely that unitary elements for a candidate mechanism for the operation of that system is residing at this level. In other words, the elements of a system at the level that exhibits degeneracy are most likely associated with the generation of the unitary operational mechanism of that system. At this level, one may also expect to find features for integrating these operational units. 
NEUROSCIENCE
In the nervous system, triangulation can be applied as follows. It will become possible to explain memory, sleep, and long-term potentiation (LTP) using the solution only if the solution is accurate. Otherwise, it will not become possible for us to provide an interconnected explanation. Similarly, the solution enables triangulating large number of findings from both normal and pathological conditions. Since the solution derived by using constraints from all the findings have reached at inter-postsynaptic LINKs (IPLs) between spines that belong to different neurons, we have to examine its presence within the system while conducting electron microscopic and other advanced microscopic studies. Otherwise, we will be wasting our precious time.
PHYSICS
To arrive at a correct hypothesis, the most crucial point is that it is necessary to take into account the constraints offered by all the findings of the system while formulating the hypothesis. It is for this reason that those who are engaged in theoretical work spend a lot of time understanding different fields within physics so that they will be able to arrive at the correct solution especially when trying to unify two major disparate findings within a system.
NEUROSCIENCE
It is necessary to replicate the mechanism in an engineered system as a gold standard test.
PHYSICS
In addition, the method of triangulation can be applied to determine the accuracy of the solution. These provide proof for the mechanism.
NEUROSCIENCE
The induction of first-person inner sensations as hallucinations within the nervous system started occurring by an accidental coincidence at some stage of evolution. It started providing a survival advantage to those nervous systems having this property. This evolved property is expected to occur through a simple mechanism that we are not yet familiar with. It should have a unique property capable of evading our attention easily. It should be present universally within the nervous systems of all the animals.

Since the solution derived by using constraints from all the findings have reached at inter-postsynaptic LINKs (IPLs) between spines that belong to different neurons, we have to examine its presence within the system while conducting electron microscopic and other advanced microscopic studies. Knowledge of the IPLs also cautions us not to disrupt the IPLs while undertaking techniques for advanced imaging. For example, any artificial expansion of extracellular matrix space will break the IPLs. This will prevent viewing its presence. 
PHYSICS
Replication is the gold standard test for understanding any property of a given system. Keeping this as the final aim allows maintaining rigorous criteria during each and every stage of the derivation.
NEUROSCIENCE
Physics had gone through several unification stages during its history. For e.g. development of standard model of physics. Since large number of disparate findings have accumulated in the broad field of brain sciences, it is necessary that this field of science should make attempts to unify its findings. Semblance hypothesis has carried out such a unification around a verifiable mechanism that can generate first-person inner sensations. It has provided large number of postdictive evidence to support the mechanism. Its testable predictions can be verified. 
PHILOSOPHY
In principle, there should be no obstacle to duplicate the causal structure of the human brain (Watch how philosopher John Searle is stressing this between 36.40 to 38.40 min). https://www.youtube.com/watch?v=ikUqoBQJk3U
NEUROSCIENCE
We should give priority to test the predictions made by any new hypothesis that can provide inter-connectable explanations for findings from different levels and that can make testable predictions. This is a cost-effective approach that can make rapid progress in the field. It should be possible to explain the mechanism of generation of first-person inner sensations compatible with the explanations of the mechanisms of at least some of the physical properties. In this regard, generation of internal sensations occurring at physiological timescales can be viewed as an engineering problem. Therefore, to fully explore this property involvement of physical and engineering sciences is inevitable.
PHYSICS
If a new mechanism can be derived that agrees with all the observations made at different levels (in an inter-connectable manner), then the newly derived mechanism should be correct. But verifiable predictions are a must for testing any new hypothesis. See how rigorous the argument is made by physicist Nima Arkani-Hamad (Watch from 44.38 to 46.20).

PHYSICS
Any progress in neuroscience will benefit physics. This is because understanding the mechanisms of perception will influence how measurements are made in physics. Physicists are constantly watching how progress is being made in neuroscience. Here is a good read https://www.nature.com/news/physics-qbism-puts-the-scientist-back-into-science-1.14912