SIUC Cognitive Science Colloquium

October 5, 2001

Evolution of Neural Circuits

David G. King, Ph.D., Associate Professor
Department of Anatomy and Department of Zoology
Southern Illinois University at Carbondale

ABSTRACT  Only one known process has produced material devices with sophisticated cognitive abilities, from visual perception and locomotor coordination to language and advance planning.  That process is evolution.  How our brains now work depends on how our ancestor's brains were organized, eons ago.  Investigating how mutations can cause adaptive changes in genetic and neural information systems may help us understand the biological basis for cognition.  



My title is a bit ironic.  Unfortunately, nobody knows much of anything about the evolution of neural circuits.  Nevertheless, I believe that if we only understood how nervous systems have evolved, we would be much closer to understanding how they work.  So I have spent much of my career wondering what kinds of questions we should be asking, if we want to understand how nervous systems have evolved.

I would like you to go home today believing that an evolutionary perspective might have something to offer to cognitive science.  Even if I don't convince you, at the very least you should know that I am not alone in believing that there is some interdisciplinary relevance.  

Daniel Dennett, author of Consciousness Explained, and the director of the Center for Cognitive Studies at Tufts University, was featured on last week's (Oct. 2001) public television series on evolution:

"If I were to give a prize for the single best idea anybody ever had, I'd give it to Darwin for the idea of natural selection.  Ahead of Newton, ahead of Einstein, because his idea unites the two most disparate features of our universe:  the world of purposeless, meaningless matter in motion on the one side, and the world of meaning and purpose and design on the other.  He [Darwin] understood that what he was proposing was a truly revolutionary idea."  

In a recent book, Darwin's Dangerous Idea, Dennett makes plain his belief that evolution provides the necessary and sufficient conceptual basis for understanding the human mind.  We just need to work out the details.  

On the surface, evolution may be among simplest of the many profound ideas in modern science.  As T.H. Huxley famously said (after Darwin had explained the idea to him), "How stupid of me not to have thought of that."  But (and here comes the first of several outrageous claims I shall make today), evolution is also profoundly misunderstood, even by many (possibly most) biologists.  What you think you know about evolution may well be mistaken -- unfortunately, common misconceptions are so numerous and so various, I can't afford a preemptive strike.  I must wait for questions and then try to cope.  If, at any point, I seem to be speaking patent nonsense, or if I slip into incomprehensible biological jargon, please do not hesitate to ask for clarification [e-mail].  

 


With that preamble, I'd like to introduce my perspective on neural circuits.  [What are "neural circuits"?]  

Behavior is controlled by the nervous system.  The nervous system consists of large numbers of individual cells, which are electrically active and which communicate with one another by secreting chemicals at sites of contact called synapses.  Somehow, the properties of the cells and their connections determine behavior.  [What?!  Yes, I know that these assertions are simplistic.  For a more honest and complete formulation, click here.]

Let me give you just a couple examples, to illustrate neural organization at the cellular level.  These examples aren't coming from the human brain, not even from cats or rats or monkeys, but from invertebrates.  Now, when you think of cognition, you may not think first of bugs.  But even with their pin-head brains, insects and spiders and crustaceans are capable of some pretty fancy feats of perception and motor performance [ref20].  Compared to the best robots we have yet constructed, bugs are rather impressive pieces of work.  

For my doctoral dissertation [ref1,2], I worked on a small piece of the nervous system of the spiny lobster. The adjacent diagram [ref3] shows the front end of the lobster, facing toward the left.  The nervous system is distributed in several cell clusters, with the largest located up front, and with additional ganglia in each segment of the body.  The big gray lump is the stomach.  The lobster's stomach has teeth, mounted on skeletal levers.  The muscles that work these levers and teeth express a moderately elaborate rhythm -- grab, grind, release, repeat, squeeze, filter, etc.  

The rhythm of lobster stomach movements is controlled by neural circuitry concentrated on a tiny ganglion (red arrow) on top of the stomach.  In Allen Selverston's lab at UC San Diego, we studied the cells comprising this ganglion.  Lobsters are especially handy for cellular neurobiology because their nerve cells are conveniently large and accessible.  By placing electrodes into each cell, it is possible to determine each cell's identity.   By carefully recording and experimentally manipulating the activity of these nerve cells, it is possible to map the "circuit" of connections among these cells.

There is an important point here which may need some emphasis.  This ganglion is not just a collection of several interchangeable, general-purpose nerve cells.  This is an organized set of uniquely identifiable individual cells and cell sets, each of which can be recognized individually in any particular specimen.

The cells are interconnected in a very specific way [enlarged diagram] [ref4], and each cell has specific electrical parameters upon which the circuit behavior depends.  From the interaction between the properties of the individual cells AND from their effects upon one another, a rhythmic motor pattern emerges, a pattern which can be switched or tuned by input from other cells outside the ganglion.  There are, in fact, dozens of quantitative parameters which are relevant for proper neural functioning, and these parameters vary in consistent ways among the various unique individual cells.  And this sort of circuit-diagram doesn't begin to do justice to actual biology.  Each cell has elaborately branching processes [enlarged image].  The synaptic connections among the cells occur in a complex tangle, and the number of individual points of contact number on the order of one million [enlarged image].  

Okay so far?  Biological systems, even ones as relatively simple as this 30-cell ganglion, can be impressively complex and intricately organized.  There is no empirical evidence that larger systems, with more cells and more impressive behavioral capacities, are any less precisely organized.  

Just how precise can this organization be?  I'll give just one more example, this time from the famous fruit fly, Drosophila melanogaster [enlarged image].  Fruit flies are not convenient for cellular neurobiology.  Although a fly's nervous system contains thousands of cells, the whole animal is is only a couple millimeters long, not much bigger than the 30-cell ganglion we just looked at.  Nevertheless, its nerve cells can be studied.  Here's a slice across the nervous system in the thorax [enlarged image].  This portion of the nervous system contains the circuitry for establishing the basic coordination of muscles needed for most activities -- flying, walking, singing, mating.  (The brain, in the head, handles sensory perception -- sight and hearing and smell -- and modulates motor patterns accordingly.)  Notice that this is not just squishy mush.  There is an obvious symmetry, which reflects the fact that particular, identifiable individual cells have unique and precisely determined features.  

Certain gifted individuals, such as my colleague Mark Tanouye, can successfully record electrical activity from particular individual nerve cells, even in this small animal.  The circuit which is best known involves a pair of very large nerve fibers which pass from the head into the thorax and synapse with a thoracic interneuron, which in turn synapse with motor neurons which go out to muscles [ref5].  This circuit mediates the rapid escape reflex that enables the fly to dodge the fly swatter (more on giant axons and escape reflexes).  Within this circuit, particular synapses between particular parts of identified nerve cells can be reliably located in the same place in each individual fly [enlarged image].  Once one learns where to look, one can even locate the homologous synaptic sites in various different species, even in species from different families of flies [ref6].

What of evolution?  Here is a slice across the neck of a fly, showing the thousands of fibers which connect the head and the thorax [enlarged image].  Note the giant axons of the escape reflex circuit.  Each of the other fibers also has some particular function.  We don't know how many of them are unique, but it is apparent that several are exceptionally large.  Symmetry is not obvious here, because of incidental distortion.  Here is a different species [enlarged image], in which symmetry is more evident, demonstrating that quite a few individual fibers can be readily recognized just by size and position.  Now, fiber diameter matters for nerve cell function -- it determines speed, power, and reliability of signalling (more on nerve cell function).  Fiber diameter is only one of dozens of quantitative parameters which differentiate nerve cells from one another and which significant for proper function.  Fiber diameter is adjustable by evolution, as evident by differences among species (more on axons in fly necks).

Okay.  Now let's think about this a bit.  I call your attention to several points.  

First point: Brains have evolved.  Biological brains are the only examples we have of material objects capable of cognition.  Even at the "simple" level of perception, problem solving, decision making, and motor coordination represented by the behavior of a fly, which you may or may not wish to denominate as cognition, biological systems far exceed our best inventions.  Biological brains, of course, have been invented by evolution.  If we can discover how evolution did the inventing, that result might be useful for understanding cognition itself.  

Second point: Biological systems display evolvability.  Brains not only have evolved, they have the intrinsic ability to evolve.  This attribute, although often taken for granted, is utterly alien to the computers and software we often use to model or mimic cognition.  Evolvability is fundamental to all existing cognitive systems.

Third point: Behavior evolves readily.  That is, however the brain works, the behavior it produces is readily "reprogrammed" by evolution. For all the attention given to learning, fundamentally the brain is reprogrammed by changing the hardware.   [Yes, this wording is simplistic.  Click for more.]  In spite of the learning capacities of most animals, and the much vaunted plasticity of the human brain, specific parts of the brain are dedicated -- "hard-wired" in some squishy sort of way -- to perform specific functions.  For that matter, the basic ability to learn, to adapt to particular and changing conditions within the span of a single lifetime, is part of the hardware.  The ability that brains have to learn in particular ways at particular times is itself a built-in, evolved function.   [In the words of Bernd Heinrich and Thomas Bugnyar (Scientific American, April 2007), "By some process that still remains one of the great unsolved mysteries of biology, exquisitely precise behaviors can be genetically programmed in animals with brains no larger than a pinhead."]

Fourth point: We already understand, at least in basic outline, how evolution works.   Darwin's basic theory has several components.  Evolution emerges from the interaction of these component processes.  

  1. Variation.  Organisms vary.  
  2. Heredity.  Some variation (in morphology and behavior) is causally linked to differences in genes.  
  3. Fitness differences.  Some hereditary variants work better than others (at least statistically).  
  4. Reproduction.  Organisms reproduce in excess, typically producing many more offspring than can the environment can support.  
  5. Selection.  The conditions of existence determine that those organisms whose particular variations better suit them for surviving and reproducing will, on statistical average, be the ones which do survive and reproduce.  To the extent that their advantageous qualities were hereditary, these qualities will be preserved and perpetuated in subsequent generations.  
  6. Mutation.  As less-fit variation is eliminated by selection, new variation continually arises by mutation.  
     
  7. Recursiveness.  This process repeats indefinitely.  The output from preceding evolutionary processes is the input for subsequent evolution.

In modern terms, a gene is a particular DNA sequence which is causally associated with some aspect of an organism's form and function.  Mutations are changes in DNA sequence.  Variations in DNA sequences lead to variations in form and function.  Natural selection on the various forms and functions leads, within a population, to replacement of one particular sequence by another.

This is standard textbook evolution.  Every part of the process is empirically observable.  In many ways, we understand the process quite well.  The piece that is least understood is mutation -- over a century after Darwin we still don't know much about the nature of the specific mutations which have led to any particular adaptation -- and most especially nothing about those leading to behavioral adaptations.  

Behavior evolves as one mutation arises, is associated with a small incremental advantage, and thereby spreads through a population.  But we don't know what kind of mutations can produce adaptive advantages in behavior.  

If we want to know how any particular aspect of cognition emerges, we need to discover the nature of the evolutionary transitions between pre-cognitive material systems and those capable of cognition.  Within cognitive systems, we can ask the same question about particular aspects -- face recognition, language acquisition, even walking upright without falling over.  This, I believe, is a key question for understanding the biological basis for cognition:  What manner of mutations led us from there to here?

You have probably been taught that all the heavy lifting in evolution is done by selection.  That is, although mutation provides raw material, all the creative shaping is done by selection.  In the quote at the start of this presentation, you might have noticed that Daniel Dennett gave Darwin credit NOT for the whole package of evolution, but for the specific idea of natural selection.  Happily, we do have a pretty good idea how selection works in relation to cognition.  Basically, smarter is better -- at least for animals with active life-styles.  (I add the "active" qualifier because there are many life styles, notably those of parasites and of sessile filter-feeders like clams, for which being smart offers little benefit and the organisms in question have notably low cognitive capacities.)

Anyway, conventional pedagogy presents natural selection as the principle designer in evolution.  Mutation is usually treated rather dismissively.  Although mutations are necessary as a source of variation, mutations are nothing but random accidents, the inevitable result of imperfect reproduction.  Does that last sentence sound familiar?   Mutations are nothing but random accidents, the inevitable result of imperfect reproduction.  It should, because it is a commonplace textbook assertion.  However, it is also false -- or, at the very least, a grave oversimplification.  Even Darwin understood the deep significance of variation -- In his Origin of Species, Darwin wrote,

"I have hitherto sometimes spoken as if the variations . . . had been due to chance.  This, of course, is a wholly incorrect expression, but it serves to acknowledge plainly our ignorance of the cause of each particular variation.  Some authors believe it to be as much the function of the reproductive system to produce individual differences, or very slight deviations of structure, as to make the child like its parents."  
Origin of Species, Chapter 5

And then,

"When the views entertained in this volume on the origin of species, or when analogous views are generally admitted, we can dimly foresee that there will be a considerable revolution in natural history. . . A grand and almost untrodden field of inquiry will be opened, on the causes and laws of variation."  Origin of Species, Conclusion

Unfortunately, that field remains largely untrodden.  We still do not know much about "the causes and laws of variation" [but see ref22].

If this talk has one central message, it is this:  The mutations which sustain the evolutionary process are neither random nor accidental.  Mutations do have, in Darwin's words, "causes and laws".  But science has barely begun to understand the signficance of that fact.  Mutations are produced by mechanisms which are themselves the product of the evolutionary process.  Direct Darwinian selection acts on bodily form and function, to produce adaptation.  But selection also operates indirectly, shaping mechanisms which, recursively, make the evolutionary process more efficient.  Indirect selection favors genetic systems which increase the probability that some variation will be beneficial (or, equivalently, which decrease the probability that variation will be deleterious) [ref14].  Because many mutations are the product of active biological organization, the domain in which those mutations are generated can itself be shaped, and indeed has been shaped, by evolution.  

This assertion remains deeply heretical.  Nothing like it has been incorporated into mainstream evolutionary biology.  But it is also a matter of established fact.  There is abundant evidence that mutations arise from complex chemical reactions which are precisely managed by enzymes.  DNA does not sponaneously self-replicate, textbook cartoons notwithstanding.  Furthermore, DNA is not left alone once it forms.  It is proof-read, edited, cut, spliced, rearranged, you name it.  There are highly evolved enzymes for these functions.  Mutations don't "just happen", they are the specific product of enzyme activity, and those enzymes are themselves the product of evolution.  

Here is a paraphrase, in modern terminology, of the quote I just read from Darwin:  "It is as much the function of DNA metabolism to produce individual differences, or very slight genetic variations, as it is to replicate genes accurately."  Here is how David Thaler put it, in a1994 article in Science titled The Evolution of Genetic Intelligence:  "The generation of genetic variation is in large part controlled by the genes and physiology of DNA metabolism... Natural selection acts beyond particular alleles.  It also favors genetic metabolism that generates alleles with a high probability of passing the tests of environmental selection" [ref7]

Of course, mutations can be accidental.  You can feed mutagenic chemicals to animals, or expose them to x-rays or ultraviolet light, and damage their DNA.  Such unnatural mutations, induced experimentally in order to break genes and study the consequences, have been very important for the science of genetics.  But such experimental mutagenesis has warped our perception of how complex and evolved (that is, how biological) the natural process of mutation really is.

So, what is the significance for cognitive science, of thinking about mutation?  Simply this:  In order for complex patterns of organization to evolve, the appropriate variation must have arisen before it could be selected.  Evolutionary biology has largely ignored this simple requirement.  Because evolution has occurred, variation has been presumed to have been adequate for the job.  If a selective advantage for a step-by-step transformation can be identified, then we act as if that step-by-step transformation has been explained.  We take for granted the process of mutation, the process which generates appropriate variation.  Because the evolutionary process has occurred, because we know the result, therefore the necessary and appropriate variation must have arisen.  QED?  

But this conventional approach is really missing a big opportunity.  Evolvability is NOT a simple, self-evident attribute, not for bacteria and certainly not for complex, highly integrated systems like the human nervous system.  It is far from obvious that random accidental mutation should be sufficient for evolution of cognitive functions, or even for the instinctive behaviors produced by the nervous system of a fly.  

It is not good enough just to presume that random accidental mutations have explored all possibilities and that selection has done the rest, especially when we already know of so many elaborate enzymatic mechanisms for tinkering with DNA.  We should be asking, What manner of mutation, and what manner of encoding between mutation and end product, are most likely to yield adaptive results?  How can it be, that the nervous system can accommodate changes in its genetic instruction set, such that plausible fiddles with those instructions can make the system work in better and more elaborate ways?  Can you imagine typographical errors in Shakespeare leading to a more deeply meaningful play?  Or typographical errors in a computer operating system leading to a more powerful and reliable work station?  Remember, selection cannot work magic.  Selection can only choose among available variations.

Let me elaborate.  Another of the talking heads in last week's (Oct. 2001) PBS series on evolution was Steven Pinker, author of How the Mind Works, in the Department of Psychology at Harvard.  Pinker emphasized how wonderfully the parts of our brains have been fine-tuned by evolution.  According to Pinker, higher cognitive functions, particularly language, have evolved not just by making more brain-stuff, but by wiring it in precise ways.  We've just seen what precise wiring entails, in systems that are simple enough for us to investigate at the level of specific cell-to-cell connections (above).  And then Pinker noted that our brains contain hundreds of billions of nerve cells, with hundreds of trillions of connections.  

This should raise an intriguing question.  How do you accomplish the "precise wiring" of hundreds of trillions of connections, by a process in which one mutant gene gradually replaces another over many generations?  How many genes must be involved?  How many gene replacements would it take?  According to the latest results from the Human Genome Project, the human genome contains only a few tens of thousands of genes.  And presumably we need at least a few thousand of those genes for making and running all the other parts of the body.  Am I the only one who sees a problem here?  

It's not too big a trick to use a small set of instructions to construct a system consisting of many individual parts.  Consider a checkerboard.  64 squares, each with a particular position and color.  That checkerboard can be specified with about four instructions:  make an array of squares, 8 this way, 8 that way, with alternating colors.  But what if you wanted to make one particular square green?  And another particular square orange?  It's one thing to make a complex pattern.  It's quite another thing to make it in such a way that particular elements can be precisely tuned for particular functions, and do so with a seemingly restricted instruction set.  The genome is not a limitless reservoir of information.  It is quite finite, and and it appears to be relatively small compared to the system which it specifies.  (And, given the slowness of the evolutionary process, the amount of time available for the genome to evolve is also quite finite.)

One might intuitively expect the evolutionary process to slow down asymptotically over time.  The more elaborate and functionally sophisticated a nervous system becomes, the harder it should be to make further improvements by random trial and error.  In fact, the evolution of instinctive behavior, which must involve genetically-based reorganization of complex neural connections, apparently occurs faster and with greater ease than the evolution of morphology.  

Why should there be a gene -- how could there be a gene --such that by mutating it we make a more appealing courtship song, or a more effective spider web, or a more versatile innate grammar?  What kind of prior organization, whether of DNA sequences or nerve cells, will permit such a process to work?  These are the sort of questions that should be asked, but very seldom are.  

While thinking about such questions (back in the early 80's, when I first became impressed with the problem of evolvability), I tried to imagine some evolvable patterns of organization which would in turn facilitate the evolutionary process.  The metaphor of "tuning knobs" presented itself.  Evolution might work more efficiently if adaptively (cognitively) interesting features were adjustable.

At the time, I was enjoying books by Douglas Hofstadter (Cognitive Science at Indiana University).  In Metamagical Themas, Hofstadter writes, "Variations on a theme is the crux of creativity."  And he then introduced the metaphor of "twiddling a knob on a concept" [ref8].  Variations on a theme are obvious in biology.  How, I wondered, might the genome implement the idea of twiddling a knob on a concept, given that protein-coding genes (the standard "genes" of textbook definition) are rather brittle and conservative?  

The genome includes a lot of stuff which is called "junk DNA".  The idea of junk DNA is sometimes understood, metaphorically, as a resource for tinkering.  But rather more commonly, it is understood as useless trash.  Among the various categories of junk DNA are repetitive sequences -- stretches of DNA in which a pattern of bases repeats itself over and over dozens or hundreds of times.  Not only is the information content apparently minimal, but mutations in such sequences are extremely frequent.  Repetitive sequences are notoriously unstable, most notably by increasing or decreasing the number of repetitions.  Surely, these sequences are just useless trash.  Surely such uninformative, unstable sequences could not play a role in precise adaptation?  

However, what if information was represented in the length -- the number of repetitions -- of such DNA sequences, such that changes in length would exert a quantitative effect on the expression of some hereditary trait?  Then frequent mutations in length would amount to twiddling a knob on the trait, allowing for rapid and precise evolutionary tuning.

I tried to publish this idea in 1985, but didn't succeed.  Then in the early 90's, things became quite exciting.  In the journal Science, under the headline, "The Puzzle of the Triplet Repeats", came news of some peculiar human neurological diseases associated with repetitive DNA triplets [ref9].  The severity of the disease was associated with the number of repetitions, and mutations affecting repeat number were quite frequent.  This was exciting.  The pull-quote, "No one expected that DNA sequences could be so unstable or behave as these do," was especially provocative.  After all, this is exactly the behavior I had speculated, a decade earlier.  Here we had repetitive DNA "twiddling a knob" on a disease.  I wrote to Science.  My letter was published on February 4, 1994 [ref10].  The very next week, Science published an article with the title "Transcriptional Activation Modulated by Homopolymeric Glutamine and Proline Stretches" [ref11].  This is dense jargon; I almost missed the article altogether.  "Transcriptional activation" means control of gene activity.  "Homopolymeric" means "a polymer of like units"; glutamine and proline are amino acids, each encoded by a triplet of DNA bases.  So, homopolymeric glutamine and proline stretches translates to DNA triplet repeats.  What the title says, then, is that genes can be regulated by triplet repeats.  And the data showed not only that the number of repetitions had a quantitative effect on gene expression but that such sequences turned up in all sorts of regulatory genes.  

I have since learned that this same idea emerged independently in at least four locations.  Here at SIU with me, at the University of Zürich with the researchers cited above, at the Weizmann Institute of Science with a theoretician named Ed Trifonov (a Russian emigre to Israel), and at the Hebrew University in Jerusalem with quantitative geneticists Morris Soller and Yechezkel Kashi.  

I have collaborated with the latter group, reviewing the extensive evidence that a mechanism of genetic regulation based on repetitive DNA is pervasive and interpreting this mechanism as evidence of an evolutionary-tuning-knob function [ref12,13,14].  Although the idea has still not caught on in a big way, the more general concept of evolving strategies for mutation is receiving some serious attention.  A meeting at the Rockefeller Institute in 1998, convened by Nobel prize winner Werner Arber to discuss "Molecular Strategies in Biological Evolution", received news coverage in Science [ref15] (proceedings later published by NYAS [ref19]).  Participants at this meeting expressed delight in discovering colleagues, working in various different disciplines, who shared similar vision.  The "tuning knob" metaphor was introduced by Trifonov (the Russian theoretician), who was astonished to learn that I had published the same metaphor the preceding year.  Then, in January 1999, the evolutionary tuning knob concept was picked up in an article in Scientific American, "DNA Microsatellites: Agents of Evolution?", by Richard Moxon and Chris Wills [ref16]. The basic idea of molecular strategies for mutation has been expanded to book length by Lynn Helena Caporale (one of the organizers of the Rockefeller meeting mentioned above) [ref19].

Are "tuning knob genes", based on repetitive DNA, important for cognitive science?  Nobody knows.  But consider the following.  The period gene in Drosophila contains a hexanucleotide repeat in which variation seems to affect the temperature sensitivity of the fly's circadian rhythm [ref17].  The human D4 gene, which encodes a dopamine (neurotransmitter) receptor, contains a 48-nucleotide repeat in which variation has been linked to personality differences in novelty-seeking [ref18].  Most of the genetic diseases associated with triplet repeat expansion are neurological diseases.  The inheritance pattern of bipolar disorder (manic-depression) suggests genetic anticipation, the hallmark of the triplet-repeat diseases.  It is perhaps not too far-fetched to speculate that mutational adjustment of repeat-based genetic "tuning knobs" has been involved in rapid evolution of the cognitive abilities which characterize our species -- most notably language facility, tool use, and sophisticated social structures based on substantial differences in talent and personality.  [Evidence continues to accumulate, that tandem repeats are especially important in nervous system genetics (ref21).]

The concept of tuning knobs is quite simple.  I hope that the genetic tool kit of mechanisms underlying evolvability will grow more interesting, once folks catch on that (1) evolvability may be a most significant feature of cognitive systems, and that (2) the mutations which are needed to enable the evolvability of cognitive systems are not random accidents.

 


References

  1. King, D.G. (1976)  Organization of crustacean neuropil:  I.  Patterns of synaptic connections in lobster stomatogastric ganglion.  Journal of Neurocytology 5:207-237.  [Abstract]
  2. King, D.G. (1976)  Organization of crustacean neuropil:  II.  Distribution of synaptic contacts on identified motor neurons in lobster stomatogastric ganglion.  Journal of Neurocytology 5:239-266.  [Abstract]
  3. Orlov, Jurij (1926)  Die Innervation des Darmes des Flusskrebse, Zeitschrifte für Microscopisch-Anatomische Forschung, 4:102.
  4. Selverston, A., D.R. Russell, J.P. Miller, and D.G. King, (1976)  The stomatogastric nervous system:  Structure and function of a small neural network.  Progress in Neurobiology 7:215-290.
    Updated review: The Crustacean Stomatogastric System, Springer-Verlag 1996.
  5. Wyman, R.J., J.B. Thomas, L. Salkoff, and D.G. King (1984)  The escape response of Drosophila melanogaster.  In:  Neural Mechanisms of Startle Behavior (R. Eaton, Ed.), Plenum Press, New York.
  6. King, D.G. and K.L. Valentino (1983)  On neuronal homology:  A comparison of similar axons in Musca, Sarcophaga and Drosophila (Diptera:  Schizophora).  Journal of Comparative Neurology 219:1-9.  [Abstract]
  7. Thaler, David S. (1994) The evolution of genetic intelligence.  Science 264: 224-225.
  8. Hofstadter, D. R.  (1985)  Metamagical Themas: Questing for the Essence of Mind and Pattern NY: Basic Books. [More books by Hofstadter.]  
  9. Morell, V.  (1993)  The puzzle of the triplet repeats.  Science 260:1422-1423.
  10. King, D.G. (1994)  Triplet repeat DNA as a highly mutable regulatory mechanism.  Science 263:595-596.
  11. Gerber, H.-P., K. Seipel, O. Georgiev, M. Höfferer, M. Hug, S. Rusconi, W. Schaffner (1994)  Transcriptional activation modulated by homopolymeric glutamine and proline stretches. Science 263:808-811.
  12. Kashi, Y., D.G. King,, and M. Soller (1997)  Simple sequence repeats as a source of quantitative genetic variation.  Trends in Genetics 13:74-78.
    Updated review:  Y. Kashi and D.G. King (2006)  Simple Sequence Repeats as Advantageous Mutators in Evolution.  Trends in Genetics 22:253-259.  [Abstract]
    More recent update: Gemayel, R., et al. (2010)  Variable tandem repeats accelerate evolution of coding and regulatory sequences. Annu. Rev. Genet. 44: 445-477.
  13. King, D.G., M. Soller and Y. Kashi (1997)  Evolutionary tuning knobs.  Endeavour 21:36-40.  [Abstract]
  14. King, D.G., and M. Soller (1999)  Variation and fidelity:  The evolution of simple sequence repeats as functional elements in adjustable genes.  In:  S.P. Wasser, ed., Evolutionary Theory and Processes: Modern Perspectives, pp. 65-82.  Kluwer Academic Publishers, Dordrecht, The Netherlands.
  15. Pennisi, E.  (1998)  How the Genome Readies Itself for Evolution.  Science 281:1131-1134.
  16. Moxon, E.R. and C. Wills.   (1999)  DNA Microsatellites: Agents of Evolution?
    Scientific American 280: 94-99.
  17. Sawyer, L.A., J.M. Hennessy, A.A. Peixoto, E. Rosato, H. Parkinson, R. Costa, and C.P. Kyriacou  (1997)  Natural variation in a Drosophila clock gene and temperature compensation.  Science 278:2117-2120.
  18. Epstein, R.P., O. Novick, and R. Umansky, et al.  (1996)  Nature Genetics 12:78-80; Benjamin, J., L. Li, C. Patterson, et al. (1996)  Nature Genetics 12:81-84.  (Also see Dean Hamer and Peter Copeland, Living with Our Genes, Doubleday, 1998.)
  19. Lynn Helena Caporale, Darwin in the Genome, McGraw-Hill, 2002. [Also see L.H. Caporale, Foresight in Genome Evolution, American Scientist 91(3): 234-241, May-June, 2003; L.H. Caporale, ed., Annals of the New York Academy of Sciences, Vol. 870 (Molecular Strategies in Biological Evolution), NYAS, 1999.]
  20. Ralph J. Greenspan and Bruno van Swinderen (2004)  Cognitive consonance: complex brain functions in the fruit fly and its relatives.  Trends in Neuroscience 27: 707-711.
  21. Updated review:  Fondon III, J.W., E.A.D. Hammock, A.J. Hannan, and D.G. King (2008)  Simple sequence repeats: Genetic modulators of brain function and behavior.  Trends in Neuroscience 31: 328-334.  doi: 10.1016/j.tins.2008.03.006.   [authors' prepublication MSWord document]
  22. King, D.G. (2012)  Indirect Selection of Implicit Mutation Protocols.  Annals of the New York Academy of Science 1267:45-52.  
    doi:  10.1111/j.1749-6632.2012.06615.x  [author preprint] [email for PDF: dgking@siu.edu]

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Last updated:  22 March 2013 / dgk