#44. The Denervation-supersensitivity Theory of Mental Illness [neuroscience, evolution, genetics]

NE  EV  GE    

Red, theory; black, fact

Midplane section of human brain annotated with the Brodmann areas, which are related to different functions

People contract mental illness but animals seemingly do not, or at least not outside of artificial laboratory models such as the unpredictable, mild-stress rodent model of depression. A simple theory to account for this cites the paleontological fact that the human brain has been expanding at breakneck speed over recent evolutionary time and postulates that this expansion is ongoing at the present time, and that mental illness is the price we are paying for all this brain progress.

The Evolution of the Human Brain

In other words, the mentally ill may carry the unfavorable mutations that have to be selected out during this progress. The mutation rate in certain categories of mutation affecting human brain development may be elevated in modern humans by some sort of "adaptive" hot-spot system. "Adaptive" is in scare quotes to indicate that the adaptation inheres in changes in the standard deviation of traits, not the average, and is therefore not Lamarkian.

In brain evolution, the growth changes in the various parts very probably have to be coordinated somehow. There may not be any master program doing this coordination. Rather, the human brain would comprise scores of tissue "parcels," each with its own gene to control the final size that parcel reaches in development. This is consistent with the finding of about 400 genes in humans that participate in establishing body size. All harmonious symmetry, even left-right symmetry, would have to be painstakingly created by brute-force selection, involving the early deaths of millions of asymmetrical individuals. 

Assuming that left and right sides must functionally cooperate to produce a fitness improvement, mutations affecting parcel growth must occur in linked, left-right pairs to avoid irreducible-complexity paradoxes. The crossing-over phenomenon in egg and sperm maturation may create these linked pairs of mutations, where the two mutations are identified with the two ends of the DNA segment that translocates. Since the two linked mutations are individually random, linkage per se does not eliminate asymmetry. That must be done by natural selection, as previously stated, so there is a subtlety here. Natural selection could equally well create adaptive asymmetry. The human heart and the claws of the fiddler crab are examples.

Functional Human Brain Anatomy 

Most of the evolutionary expansion of the human brain appears to be focused on association cortex, which would implement if-then rules like those making up the knowledge bases familiar from the field of artificial intelligence. The "if" part of the rule would be evaluated in post-Rolandic cortex, i.e., in temporal and parietal association cortices, and the "then" part of the rule would be created by the pre-Rolandic association cortex, i.e., the prefrontal cortex. The white matter tracts running forward in the brain would connect the "if" part with the "then" part, and the backward running white-matter tracts would carry priming signals to get other rules ready to "fire" if they are commonly used after the rule in question.

Possible Disorders of Brain Growth

Due to such tight coordination, the ideal brain will have a fixed ratio of prefrontal cortex to post-Rolandic association cortex. However, the random nature of the growth-gene bi-mutations, perhaps at mutational hot-spots, permitting human brain evolution will routinely violate this ideal ratio, leading to the creation of individuals having either too much prefrontal cortex or too much temporal/parietal cortex. In the former case, prefrontal cortex will be starved of sensory input. In the latter case, sensory association cortex will be starved of priming signals feeding back from motoric areas.

Denervation supersensitivity occurs when the normal nerve supply to a muscle is interrupted, resulting in a rapid overexpression of acetylcholine receptors on the muscle. This is an adaptation to compensate for weak nerve transmission with a re-amplification of the signal by the muscle. Analogous effects have been found in areas of the cerebral cortex deprived of their normal supply of sensory signals, so the effect seems to be general.

In cases of genetically-determined frontal-parietal/temporal imbalance, the input-starved side would develop denervation supersensitivity, making it prone to autonomous, noise-driven nervous activity.

Differential Growth-Related Brain Disorders 

If the growth excess is in sensory association cortex, this autonomous activity will manifest as hallucinations, resulting in schizophrenia. If the growth excess is in the prefrontal cortex, however, the result of the autonomous activity will be mania or a phobia.

The non-overgrown association cortex might secondarily develop the opposite of denervation supersensitivity as the result of continual bombardment with autonomous activity from the other side of the Rolandic fissure. This could account for the common observation of hypoprefrontality in cases of schizophrenia.

Picture credit: Wiki Commons

#16. The Intermind, Engine of History? [evolutionary psychology]

EP

Red, theory; black, fact

Statue of Samuel de Champlain, explorer

A Mechanism of Rapid Evolution 

A plausible reason for having a mechanism of rapid evolution is that it permits evolutionary enlargement of body size without loss of evolvability; larger size leads to more internal degrees of freedom and therefore access to previously impossible adaptations. For example, eukaryotes can phagocytose their food; prokaryotes cannot. However, larger body size comes at the expense of longer generation time, which reduces evolvability. A band of high frequencies in the spectrum of environmental fluctuations therefore develops where the large organism has relinquished evolvability, opening it to being out competed by its smaller rivals. 

What I call the intermind would be a proxy for classical evolution that fills the gap, but it needs an objective function to provide it with its ultimate gold standard of goodness of adaptations. Species-replacement group selection could ensure that the objective function is close to optimal. This group selection process takes place at enormously lower frequencies than those the intermind is tracking, because if the timescales were  too similar, chaos would result. For example, in model predictive control, the model is updated on a much longer cycle than are the predictions derived from it.

This genetic intelligence may construct our sociobiology in an ad hoc fashion, by rearranging a knowledge base, or construction kit, of rules of conduct into algorithm-like assemblages. This rearrangement would be blindingly fast by the standards of classical Darwinian evolution, which only provides the construction kit itself, and presumably some further, special rules equivalent to a definition of an objective function to be optimized. The ordinary rules translate experiences into the priming of certain emotions, not the emotions themselves, 

Its Properties 

The set of ordinary rules or intermind would be intermediate in speed between classical evolution and learning by operant conditioning. (All three depend on trial-and error.) The name is also appropriate in that the intermind would be a distributed intelligence, acting over continental, or a least national, areas. Its objective function, which is simply whatever produces survival, will be explicitly encoded into the genes specifying the intermind. (For more on multi-tier, biological control systems with division of labor according to time scale, see "Sociobiology: the New Synthesis," E. O. Wilson, 1975 & 2000, chapter 7.)

Evil Explained

The intermind may account for evil because it is only concerned with survival of the entire species and not with the welfare of individuals.

Evolutionary Mechanisms 

The intermind will have been created by group selection of species. Higher taxonomic units such as genus or family will scarcely evolve because the units that must die out to permit this are unlikely to do so, because they comprise relatively great genetic and geographical diversity. However, we can expect intermind-related adaptations that facilitate the creation of new species, the units of selection. Imprinted genes may be one such adaptation, which might enforce species barriers by a lock-and-key mechanism that kills the embryo if any imprinted gene is present in either two or zero active copies. Species-replacement group selection need act only on the objective function used by trial-and-error processes.

What Are Its Objectives?

In these times, we have come to know that species survival is imperiled by loss of range and by loss of genetic diversity. Thus, the objective function will tend to produce range expansion (exploration in humans) and optimization of genetic diversity. 

However, all this is insufficient to explain the creativity of humans, starting at the end of the last ice age with cave paintings, followed shortly thereafter by the momentous invention of agriculture. The hardships of the ice age must have selected genes for a third, novel component, or pillar, of the species objective function, namely optimization of memetic diversity. Controlled diversification of the species memeplex may have been the starting point for cultural creativity and the invention of all kinds of aids to survival. Art forms may represent the sensor of a feedback servomechanism by which a society measures its own memeplex diversity, measurement being necessary to control.

#8. What is Intelligence? Part II. Human Brain as Knowledge Base [neuroscience, engineering]

EN   NE 

Red, theory; black, fact

The Human Brain Through an AI Lens

The cis control element-structural-gene realization of the if-then rule described in the previous post appears to have three realizations in neuroscience. These are: a single neuron (dendrites, sensors; axon, effectors) the basal ganglia (striatum, sensors; globus pallidus, effectors) and the corticothalamic system (post-Rolandic cortex, sensors; pre-Rolandic cortex, effectors).

Cerebral Rules

Taking the last system first, the specific association of a pattern recognizer to an output to form a rule of conduct would be implemented by white-matter axons running forward in the brain. The brain's sensory parts lie at the back, and its motor, or output, parts lie at the front.

The association of one rule to the next within a block of instructions would be by the white-matter axons running front-to-back in the brain. Since the brain has no clock, unlike a computer, the instructions must all be of the if-then type even in a highly automatic block, so each rule fires when it sees evidence that the purpose of the previous rule was accomplished. This leads to a pleasing uniformity, where all instructions have the same form. 

This also illustrates how a slow knowledge base can be morphed into a fast algorithm by keeping track of the conditional firing probabilities of the rules, and rearranging the rules in their physical storage medium so that high conditional probabilities correspond to small distances, and vice-versa.

However, in a synaptic intelligence, the "small distances" would be measured on the voltage axis relative to firing threshold, and would indicate a high readiness to fire on the part of some neuron playing the role of decision element for an if-then rule, if the usual previous rule has fired recently. An external priming signal having the form of a steady excitation or disinhibition could produce this readiness. Inhibitory inputs to thalamus or excitatory inputs to cortical layer one could be such priming inputs.

Basal Ganglia Rules

The low-to-medium conditional firing probabilities would characterize if-then rules that act as jump instructions between blocks, and the basal ganglia appear to have the connections necessary to implement these. 

In Parkinson disease, the basal ganglia are disabled, and the symptoms are as follows: difficulty in getting a voluntary movement started, slowness of movements, undershoot of movements, few movements, and tremor. Except for the tremor, all these symptoms could be due to an inability to jump to the next instruction block. Patients are capable of some routine movements once they get started, and these may represent the output of a single-block program fragment.

Unproven, trial-basis rules of the "jump" type that are found to be useful could be consolidated by a burst of dopamine secretion into the striatum. Unproven, trial-basis rules of the "block" type found useful could be consolidated by dopamine secretion into prefrontal cortex. 

A Sophistication 

If-then rules may influence behaviour with great indirection, by changing the firing thresholds of other rules, that themselves only operate on the thresholds of still other rules, and so on in a chain eventually reaching the rules that actually produce overt behaviour. The chain of indirection probably passes medial to lateral over the cortex, beginning with the limbic system. Each level of indirection may correspond to a level of indentation seen in a modern computer language such as C. 

If the priming signals are delivered to pairs of cortical regions in order to establish communication between them, analogously to connecting specific pairs of digital devices to a data bus, the result would be an intelligent instruction decoder. This will result in an expansion of the number of instructions that can be executed until the environment itself becomes the code.

The Brain Through a Coding Lens

You can take a professionally written, high-level computer program and parse it into a number of conventions. Such features already dealt with are the common use of if-then rules, block structuring, and levels of indentation. Each such convention may correspond to a structural feature in each of the natural intelligences, the genetic and the synaptic. Extending this concept, we would predict that features of object-oriented programming will be useful in assigning function to form in the two natural intelligences. 

For example, the concept of class may correspond to the Brodmann areas of the human brain, and the grouping of local variables with functions that operate on them may be the explanation of the cerebellum, a brain structure not yet dealt with. In the cerebellum, the local variables would be physically separate from their corresponding functions, but informationally bound to them by an addressing procedure that uses the massive mossy-fiber/parallel-fiber array.

#7. What is Intelligence? Part I. DNA as Knowledge Base [genetics, engineering]

EN   GE

Red: theory; black, fact

The Known Intelligences 

There may be three intelligences: the genetic, the synaptic, and the artificial. The first includes genetic phenomena and may be the scientifically accessible reality behind the concept of God. The synaptic is the intelligence in your head, and seems to be the hardest to study and the one most in need of elucidation. The artificial is the computer, and because we built it ourselves, we understand it. Thus, it can provide a wealth of insights into the nature of the other two intelligences and a vocabulary for discussing them.

The Artificial Intelligence 

Artificial intelligence systems are classically large knowledge bases (KBs), each animated by a relatively small, general-purpose program, the "inference engine." The knowledge bases are lists of if-then rules. The “if” keyword introduces a logical expression (the condition) that must be true to prevent control from immediately passing to the next rule, and the “then” keyword introduces a block of actions the computer is to take if the condition is true. Classical AI suffers from the problem that as the number of if-then rules increases, operation speed decreases dramatically due to an effect called the combinatorial explosion.

DNA Through an AI Lens

A genome can be compared to a KB in that it contains structural genes and cis-acting control elements. The latter trigger the transcription of the structural genes into messenger RNAs in response to environmental factors and these are then translated into proteins that have some effect on cell behavior. The analogy to a list of if-then rules is obvious. A control element evaluates the “if” condition and the conditionally translated protein enables the “action” taken by the cell if the condition is true.

Avoiding Slowdowns at Scale

Note that the structural gene of one rule precedes the control element of the next rule along the DNA strand. Would this circumstance not also represent information? However, what could it be used for?

It could be used to order the rules along the DNA strand in the same sequence as the temporal sequence in which the rules are normally applied, given the current state of the organism’s world. This seems to be a possible solution to the combinatorial explosion problem, leading to much shorter delays on average for the transcriptase complex to arrive where it is needed. I suspect that someday, it will be to this specific arrangement that the word “intelligence” will refer.

A Rule-ordering Mechanism 

The process of putting the rules into an efficient sequence may involve trial-and-error, with transposon jumping providing the random variation on which selection operates. 

A variant on this process would involve the enhancement by de-methylation of recombination sites that have recently produced successful results. These results would initially be encoded in the organism's emotions, as a proxy to reproductive success. In this form, the signal can be rapidly amplified by inter-individual positive feedback effects such as competition. It would then be converted into patterns of DNA de-methylation in the germ line. DNA methylation is known to be able to cool recombination hot spots, so de-methylation should do the opposite.

Rule Creation 

A longer-timescale process involving meiotic crossing-over may create novel rules of conduct by breaking DNA between promoter and structural gene of the same rule, a process analogous to the random-move generation discussed in my post on dreaming. Presumably, the longest-timescale process would be creating individual promoters and structural genes with new capabilities of recognition and effects produced, respectively. This would happen by point mutation and classical selection.

Implementing Jump Instructions In DNA 

How would the genetic intelligence handle conditional rule firing probabilities in the medium to low range, which would call for jump instructions as opposed to merely incrementing the instruction pointer?

This could be done by cross linking nucleosomes via the histone side chains in such a way as to cluster the cis control elements of likely-to-fire-next rules near the end of the relevant structural gene, by drawing together points on different loops of DNA. The analogy here would be to a science-fictional “wormhole” from one part of space to another via a higher-dimensional embedding space. In this case, “space” is the one-dimensional DNA sequence with distances measured in kilobases, and the higher-dimensional embedding space is the three-dimensional physical space of the cell nucleus.

A Possible Mechanism of Jump Instructions 

The cross linking is presumably created and/or stabilized by the diverse epigenetic marks known to be deposited in chromatin. Most of these marks will certainly change the electric charge and/or the hydrophobicity of amino acid residues on the histone side chains. Charge and hydrophobicity are crucial factors in ionic bonding between proteins. A variety of such changes are possible.

Another way of accounting for the diversity of epigenetic marks, mostly due to the diversity of histone marks, is to suppose that they can be paired up into negative-positive, lock-key partnerships, each serving to stabilize by ionic bonding all the wormholes in a subset of the chromatin that deals with a particular function of life. The number of such pairs would equal the number of functions. Their lock-key specificity would prevent wormholes, or jumps, from forming between different functions, which would cause chaos.

Evolutionary History of Jump Instructions 

If the eukaryotic cell is descended from a spheriodal array of prokaryotes with internal division of labor and specialization, then by one simple scheme, the specialist subtypes would be defined and organized by something like mathematical array indexes. For parsimony, assume that these array indexes are the different kinds of histone marks, and that they simultaneously are used to stabilize specialist-specific wormholes. A given lock-key pair would wormhole specifically across regions of the shared genome not needed by that particular specialist.

A secondary function of the array indexes would be to implement wormholes that execute between-blocks jumps within the specialist's own program-like KB. With consolidation of most genetic material in a nucleus, the histone marks would serve only to produce these secondary kind of jumps while keeping functions separate and maintaining an informational link to the ancestral cytoplasmic compartment. The latter could be the basis of sorting processes within the modern eukaryotic cell.

#5. Why We Dream [neuroscience]

NE

Red, theory; black, fact

The Conjunction of Jupiter and Venus

We Dream Because We Learn

Operant conditioning is the learning process at the root of all voluntary behaviour. The process was discovered in lab animals such as pigeons by B.F. Skinner in the 1950s and can briefly be stated as "If the ends are achieved, the means will be repeated." (Gandhi said something similar about revolutionary governments.)

Learning in the Produce Isle

Operant conditioning is just trial-and-error, like evolution itself, only faster. Notice how it must begin: with trying moves randomly--behavioral mutations. However, the process is not really random like a DNA mutation.  Clearly, common sense plays a role in getting the self-sticky polyethylene bag open for the first time, but any STEM-educated person will want to know just what this "common sense" is and how you would program it. Ideally, you want the  creativity and genius of pure randomness, AND the assurance of not doing anything crazy or even lethal just because some random-move generator suggested it. You vet those suggestions.

How Dreams Help Learning

That, in a nutshell, is dreaming: vetting random moves against our accumulated better judgment to see if they are safe--stocking the brain with pre-vetted random moves for use the next day when we are stuck. This is why the emotions associated with dreaming are more often unpleasant than pleasant: there are more ways to go wrong than to go right. The vetting is best done in advance (e.g., while we sleep) because there's no time in the heat of the action the next day, and trial-and-error with certified-safe "random" moves is already time-consuming without having to do the vetting on the spot as well.  

A Possible Neurobiological Mechanism

Dreams are loosely associated with brain electrical events called "PGO waves," which begin with a burst of action potentials ("nerve impulses") in a few small brainstem neuron clusters, then spread to the visual thalamus, then to the primary visual cortex. I theorize that each PGO wave creates a new random move that is installed by default in memory in cerebral cortex, and is then tested in the inner theatre of dreaming to see what the consequences would be. In the event of a disaster foreseen, the move would be scrubbed from memory, or better yet, added as a "don't do" to the store of accumulated wisdom. Repeat all night.

If memory is organized like an AI knowledge base, then each random move would actually be a connection from a randomly-selected but known stimulus to a randomly-selected but known response, amounting to adding a novel if-then rule to the knowledge base.

Support For a Requirement for Vetting 

In "Evolution in Four Dimensions" [1st ed.] Jablonka and Lamb make the point that epigenetic, cultural, and symbolic processes can come up with something much better than purely random mutations: variation that has been subjected to a variety of screening processes.

An Observation and an Exegesis

Oddly, my nightmares happen just after a turn of good fortune for me. However, in our evolutionary past, my kind of good fortune may have meant bad fortune for someone else, and that someone else will now be highly motivated to kill me in my sleep. Unless I have a nightmare and thus sleep poorly or with comforting others. The dream that warned the Wise Men not to return to Herod may have been just such a nightmare, which they were wise enough to interpret correctly. The content was probably not an angelic vision, but more like Ezekiel's valley of dry bones vision in reverse.