Generalist vs Specialist' neuroarchitectural bias.

This is an old edit, the Blogger is too difficult to bother updating. For a new edit see my knol.

This is related to “A mindset for AI discovery”, but with a dose of neuroscience.
By a "generalist" I mean someone focused on finding common patterns across different fields of knowledge, rather than a "serial specialist" who develops professional competence in each of these fields. I am not a neuroscientist & the following is very speculative.
Cognitive bias toward a certain degree of generalization, as opposed to to the level of detail in learning, appears to be partly inherited or developed prenatally /early postnatally. I did some literature search for possible mechanisms of variation in such bias, this is a result. Would appreciate informed comments.

In very general terms, a neocortex is a network of columns loosely organized in a hierarchy of generalization, from primary to association areas of both sensory & motor cortices (see "The columnar organization of the neocortex" by Vernon Montcastle, "Cortex & Mind" by Joaquin Fuster, "On intelligence" by Jeff Hawkins). Given a relatively fixed volume & resources, the neocortex must trade between the number & the range of connections in the network. In other words, this cortical hierarchy can be relatively dense or sparse.
Longer-range "sparse" connections have an exponentially greater number of possible targets, thus requiring longer time to find the best match, or to "wire" the network. Fewer total connections would reduce the amount of represented detail, but their increased range will improve match & generality of the resulting patterns. This is because learning, as distinct from passive recording, is selective: the inputs must be reinforced by matches to previous knowledge (as in coincidence detection). In a sparse hierarchy the choice of such reinforcement is greater, so the best match will be better, resulting in slower & more selective learning. So, the tradeoff is between learning speed & detail of a dense hierarchy, & the generality of patterns/concepts discoverable by a sparse hierarchy.

A functional unit of neocortex is a minicolumn: a group of ~100 neurons vertically connected across six layers of neocortex, & derived from the same group of progenitor cells during embrionic development. Although functional separation of individual minicolumns is disputed, they are ontogenetically distinctive & their vertical differentiation (algorithm) is genetically determined. I suggest that this algorithm is an atomic recognition / generalization function, iterated by vertically connecting multiple minicolumns. This is based on the assumption that main cortical function is cognition, which can be reduced to recursive generalization: comparison-projection steps (for more on that see my Intelligence knol). My half-educated guess is that lateral connections among minicolumns, from layer I to layers II & III, mostly mediate a winner-take all inhibition. On the other hand, the vertical connections, from layer V,VI of an source minicolumn to layer IV of a target, via thalamus, are across generality: the output should be a compressed generalization of the inputs.

I know of three levels of neuroarchitectural differences that seem to bias a cognitive focus: hemispheric assymmetry, differences among individuals, & cortical features that distinguish humans from other animals.

First, the evidence on the correlation between neuroarchitectural & cognitive bias in cortical hemispheric asymmetry. It seems that the left hemisphere represents higher-generality, especially semantic concepts, while the right hemisphere works mostly in the background, likely searching for contextual patterns (Cortex & Mind, p. 184, Split Brain, Michael Gazzaniga). The difference, of course, is mostly in degree. Accordingly, Jeffrey Hutsler and Ralf A.W. Galuske showed in "Hemispheric asymmetries in cerebral cortical networks" that macro-columns in the left hemisphere contain relatively fewer mini-columns than corresponding areas in the right hemisphere. The axons in the left hemisphere are better myelinated, even though the total volume & number of synapses is the same in corresponding areas of both hemispheres.This asymmetry seems to be greater in humans than in other animals. The hemispheres do not normally operate independently, they are densely interconnected by Corpus Callosum. Some of this connectivity is to provide simple fault-tolerance & sensory-motor field integration, as in animals. But because of the asymmetry ("lateralization") in humans, the transfer of data between hemispheres will likely be between different levels of generality. This mismatch means that the transfer will add another step of generalization to the hierarchy of the left hemisphere.

The best evidence for neuroarchitectural differences among individuals comes from research on autism spectrum disorder (ASD), or broader autism phenotype (BAP). Much of my info on this is via "A Shade of Gray" blog: an excellent review of relevant research, highly recommend. Among other things, BAP is known to increase a focus on specifics, at the expense of higher level generalization ability.
This bias seems to be partially caused by the fact that BAP individuals have greater number of smaller & more densely packed minicolumns per macrocolumn. Their minicolumns contain the same number of smaller-size neurons, which probably drive signals over shorter range between the macrocolumns, producing local vs global connectivity bias in BAP ( from Casanova - "Abnormalities Of Cortical Circuitry In The Brains Of Autistic Individuals", via A Shade of Gray). Weaker inter-macrocolumn signals likely result in inhibited transfer of information between the levels of generalization. This would leave higher levels (associative areas) under-utilized, & my personal guess is that they will re-specialize into more "primary" areas by re-orienting toward less mediated (attenuated) specific thalamocortical inputs. Suggestive research: Partially enhanced thalamocortical functional connectivity in autism. In other words, instead of differentiating by the generality of data, the areas will differentiate by its spatio-temporal & modality-specific origin.Very interesting study "Comparison of the Minicolumnar Morphometry of Three Distinguished Neuroscientists and Controls" by Dr. Casanova is reported in "Minicolumns, Genius, and Autism". The neural connectivity of the neuroscientists appears to be similar to autistics in the density & size of minicolumns, but differ in better inhibitory isolation between adjacent minicolumns. This should focus the output of minicolumns toward vertical vs lateral connections, increasing the vertical range even for smaller minicolumns. The other likely difference is in their corpus callosi, the structure that connects the left and right cerebral hemispheres, which have consistently shown to be smaller in autistics.

Yet another set of evidence is the difference in cortical architecture between humans (with obviously vastly greater generalization ability) & other animals. Beside much larger neocortex & hemispheric assymetry, the most salient such difference is the Spindle neurons , which are present only in humans &, to a far lesser extent, in other primates & whales. From Wikipedia, via "A Shade of Gray: "Spindle cells appear to play a central role in the development of intelligent behavior and adaptive response to changing conditions and cognitive dissonance. They emerge postnatally and eventually become widely connected with diverse parts of the brain, evidencing their essential contributions to the superior capacity of hominids to focus on difficult problems." Becuse they're much bigger, & their axons are longer & less branched than those of pyramidal neurons they replace, the spindle neurons should radically extend the range of vertical connections between the minicolumns. This increased range is probably not free, but comes at the expense of reduced density of connections.

The above discussion considered neuroarchitecturally determined trade-offs. Cognitive focus is also biased by the variation in temporal attention span, which probably also affects the architectural bias during cortical development. Attention span, or a stimuli "decay rate" in the neocortex, is probably determined by the speed of reuptake for excitatory neurotransmitters. Most likely candidates are dopamine & norepinephrine, "the pay attention" neurotransmitters, necessary for signal propagation from primary to higher association areas.
The evidence here is contradictory because there are many feedback loops. I suspect that during prenatal / early postnatal development high levels of cortisol / low levels of serotonin increase the levels of phasic dopamine, which in turn upregulates dopamine reuptake. This leads to greater fluctuations in the levels of tonic dopamine and increased novelty seeking as opposed to long term focus. A tantalizing hint can be found in this study: http://jcn.sagepub.com/cgi/content/abstract/9/2/18: "To advance our understanding of attention-deficit hyperactivity disorder and medication effects we draw upon the evidence for (1) a neurotransmitter imbalance between norepinephrine and dopamine in attention-deficit hyperactivity disorder and (2) an asymmetric neural control system that links the dopaminergic pathways to left hemispheric processing and links the noradrenergic pathways to right hemispheric processing. It appears that attention-deficit hyperactivity disorder may involve a bihemispheric dysfunction characterized by reduced dopaminergic and excessive noradrenergic functioning. In turn, favorable medication effects may be mediated by a restoration in neurotransmitter balance and by increased control over the allocation of attentional resources between hemispheres." (J Child Neurol 1994;9:181-189).
It's also known that ADHD sufferers have fewer dopamine autoreceptors, leading to greater variations in its levels. This probably causes lower sensitivity to to dopamine due to less efficient receptors, such as D1.
Faster dopamine reuptake should reduce "vertical" signal propagation, causing constant novelty seeking for "primary" stimulation to keep the neocortex busy. ADHD can be remedied by the use of stimulants, most efficiently by reuptake inhibitors such as Bupropion.

The generalist vs specialist trade-off is somewhat ambiguous in terms modern societal utility:
- On one hand, speed & precision was far more important for survival "in the wild", which probably explains why apes likely have a photographic memory, superior to humans: Chimps beat humans in memory test.
- On the other hand, more recent functional differentiation of modern society rewards specialization & precision, & speed, probably more so than a generalization ability on the opposite end of cognitive diversity spectrum.

IQ tests are inherently incapable of capturing high generalization ability because of their time limits. The tests are supposed to be background-neutral, which means they can only measure an ability to discover patterns within data given to a subject during relatively brief test (except for verbal & math IQ, which are not background-neutral). That means they’re biased toward the speed of learning, & "sparse & slow" subjects will be at disadvantage.
The same bias is built into an educational system: the detail-oriented "dense" subjects would be better at passive knowledge acquisition. "Sparse" architecture will excel at independent knowledge discovery & critical thinking, but this is far more difficult to evaluate. Also, modern science accumulated a very substantial body of knowledge, which must be "passively acquired" prior to being able to make a novel discovery. This is a disadvantage for a generalist, & may help to explain why we haven't had a "new Einstein" in a century.
Moreover, it's a lot easier to recognize competence of a specialist than that of a generalist: we all share lower generality levels, which is where we get the original data, but the effective generality of the top associative levels definitely differs among individuals. I would speculate that this is why the quality of work in social sciences, & especially philosophy, is so vastly inferior to that in "hard" sciences.