click for enlargement of
this Mark Meyer painting
Thinking a Thought in
the Mosaics of the Mind
copyright ©1996 by
William H. Calvin
The Cerebral Code proposes a bold new theory for how Darwins
evolutionary process could operate in the brain, improving ideas on the
time scale of thought and action. Jung said that dreaming goes on
continuously but you cant see it when youre awake, just as you cant
see the stars in the daylight because it is too bright. Calvins is a
theory for what goes on, hidden from view by the glare of waking mental
operations, that produces our peculiarly human consciousness and
Shuffled memories, no better than the jumble of our nighttime dreams, can evolve subconsciously into something of quality, such as a sentence to speak aloud. The interoffice mail circuits of the cerebral cortex are nicely suited for this job because theyre good copying machines, able to clone the firing pattern within a hundred-element hexagonal column. That pattern, Calvin says, is the cerebral code representing an object or idea, the cortical-level equivalent of a gene or meme. Transposed to a hundred-key piano, this pattern would be a melody a characteristic tune for each word of your vocabulary and each face you remember.
Newly-cloned patterns are tacked onto a temporary mosaic, much like a choir recruiting additional singers during the Hallelujah Chorus. But cloning may blunder slightly or overlap several
and that variation makes us creative. Like dueling choirs, variant
hexagonal mosaics compete with one another for territory in the
association cortex, their success biased by memorized environments and
Unlike selectionist theories of mind, Calvins mosaics can fully implement all six essential ingredients of Darwins evolutionary algorithm, repeatedly turning the quality crank as we figure out what to say next. Even the optional ingredients known to speed up evolution (sex, island settings, climate change) have cortical equivalents that help us think up a quick come-back during conversation.
Mosaics also supply audit trail structures needed for Universal Grammar, helping you understand nested phrases such as I think I saw him leave to go home. And, as a chapter title proclaims, mosaics are A Machine for Metaphor. Even analogies can compete to generate a strata of concepts that are inexpressible except by roundabout, inadequate means as when we know things of which we cannot speak.
William H. Calvin is a theoretical neurophysiologist at the University of Washington in Seattle, and author of nine books.
A Bradford Book
My other 1996 book is HOW BRAINS THINK in the Science Masters series (BasicBooks in the US, 12 translation editions). THE CEREBRAL CODE is primarily for scientists and only secondarily for intrepid general readers (though Ive used an extensive glossary and cartoons to help the nonscientist).
Cartoons by Malcolm Wells
All rights reserved. Except for brief excerpts and personal photocopying of a single chapter, no part of this book may be reproduced in any form (including information storage and retrieval, photocopying, and recording) without permission from the publisher.
Softcover, US$14.00; ISBN 0-262-53154-2.
The German translation, Die Sprache des Gehirns: Wie in unserem Bewußtsein Gedanken entstehen, is at amazon.de.
2 Cloning in Cerebral Cortex
3 A Compressed Code Emerges
4 Managing the Cerebral Commons
5 Resonating with your Chaotic Memories
6 Partitioning the Playfield
8 Convergence Zones with a Hint of Sex
9 Chimes on the Quarter Hour
10 The Making of Metaphor
11 Thinking a Thought in the Mosaics of the Mind
About the Author
About the Artists
INSTRUCTORS: If you need glossary links from your own web page "handouts," you can make use of the glossary items in THE CEREBRAL CODE, e.g., to gloss postsynaptic, use
The German translation, Die Sprache des Gehirns: Wie in unserem Bewußtsein Gedanken entstehen, is at amazon.de.
Here is the card catalog listing (consider clipping and sending to your librarian):
Author: Calvin, William H., 1939-
The back cover of THE CEREBRAL CODE includes:
This book is indeed of importance to specialists in the field, and is likely to be used as a source book for students to read in courses on the neural basis of cognition. Calvin proposes a model of a major part of cerebral cortical function and shows how it could apply to or explain a number of examples of operations and cognitive achievements at various higher levels. The Cerebral Code is certainly original, readable, and of sound scholarship. It should appeal to an audience of professionals, students, and general readers.
Bill Calvin writes with elegance, economy, and authority. In The Cerebral Code, he has solidly embedded his ideas in experimental neurophysiology and neuropharmacology, deriving from his decades in the laboratory. He explores the ramifications of his insights into a wide range of cerebral functions, such as sleep, dreaming, awareness, problem solving, creative thinking, and the dynamics of nerve cell assemblies that make consciousness possible. Calvin has written primarily for his colleagues in neuroscience, as well as for lay readers. I believe he will achieve his aim, by recounting in adequate detail the basic concepts from which he is reasoning, and thereafter exploring ideas and issues that his reductionstically minded colleagues have largely ignored.
Calvins single, simple purpose for The Cerebral Code is to propose a substantial hypothesis for how the human cerebral cortex might work. He suggests that the brain uses a selection algorithm, what he calls a Darwin Machine, based upon small anatomical and physiological units, local spatiotemporal patterns of neuronal activity that should tile regions of cortex with a hexagonal mosaic. Until this book, the concept of selection in the brain has not been so plausibly linked with real, empirically observable cellular structures and functions.
William Calvin writes with clarity and elegance about the brain. In an age when brain science is becoming increasingly fragmented and specialised Calvin is a rara avis... he provides a broad overview on the functions of the brain and a bold and novel conjecture about the most highly evolved yet enigmatic of all biological organs the human cerebral cortex.
Book reviews so far:
|SUPPLEMENTARY MATERIAL: There are now animated illustrations for the spatiotemporal patterns.|
R. A. W. Galuske, H. Bratzke, W. Schlote (1998), "Patterns of long range connectivity in different language related areas of human cerebral cortex," Society for Neuroscience Abstracts 24:15.1. Brocas(45) interpatch separations 1.150mm. Wernickes(22) was 1.400 on left side, R was 1.200).
Corrections and Supplements to the are already incorporated into the web pages and softcover editions; they are also posted here in case owners of the hardcover printing wish to update their copies. Almost none of these are publisher's errors (I did the formatting for the press myself), they're mostly little improvements for the paperback edition.
Dust jacket author photo credit was left off: Doug vanderHoof, Modern Media.|
p.82: "When chaos theory came along (which, for me, is dated to Otto Rösslers famous paper of 1983), it started to become evident how basins of attraction lived in the connectionists' networks. When complexity theory and artificial life came along on their heels,..."
p.84: "to implement a shaping-up process, "
p.92: "boomtime survivals that would otherwise have been lost to juvenile mortality."
p.100: "that can be standardized in a crystalline manner (it's Dawkins' minimum replicable unit). "
p.102: "lingering after the active spatiotemporal patterns had died out. "
p.125: "sang a fifth (a 3:2 ratio of frequencies, seven semi-tones apart) or an octave (2:1, twelve semi-tones apart) higher"
p.126: " only certain semi-tones (7 of the 12 in an octave) are thought to go well enough together to make chords."
p.137: Addendum. As I was attempting to explain to John Maynard Smith (author of The Evolution of Sex, etc.) the Cerebral Code's analogies of corticocortical convergence to gamete dimorphism and the resulting numerical disproportion, he said, "You know, Calvin, the real reason why it takes so many sperm to fertilize a single egg? It's because none of the sperm will ask for directions."
p.161: "the little words of grammar"
p.171: "Its meeting a high quality criterion that"
p.186: "An expert (someone who knows"
p.191: "meet some nonstandard criterion that itself evolves"
Protolanguage is a simple form of language lacking the fancier structure provided by syntax. Its the language of the trained animals, children less than two years of age, speakers of pidgins, agrammatic aphasics, and American professors trying to communicate with Greek shopkeepers. With structureless protolanguage, it takes a lot of time to relate who did what to whom, even when supplemented by gestures.p.193: "develop a mechanistic outline for some"
p.197: "Corticocortical coherence that became good enough to convey even novel spatiotemporal"
p.205: "chunking Collapsing multiple-word phrases into a single word, in the manner of acronyms."
p.213: "stellate neurons The nonpyramidal neurons in the neocortex, on the basis of anatomy. Physiologically, most of them have inhibitory actions, an exception being the spiny stellate neurons."
p.215: correct title to Derek Bickerton, Language and Human Behavior (University of Washington Press 1995). Add: Daniel C. Dennett, Kinds of Minds (BasicBooks 1996). Add: John Maynard Smith and Eörs Szathmáry, The Major Transitions of Evolution (Freeman 1995).
p.217: 4 William James's development of his darwinian theory of mind, see pp. 433ff of Robert J. Richards, Darwin and the Emergence of Evolutionary Theories of Mind and Behavior (University of Chicago Press 1987). The modern chapter of mental darwinism starts in 1965 with Dan Dennett's D. Phil. thesis, published as Content and Consciousness (Routledge and Kegan Paul 1969).
p.225: Add editor:
61 Donald T. Campbell, "Epistemological roles for selection theory," in Evolution, Cognition, and Realism: Studies in Evolutionary Epistemology, edited by N. Rescher (Lanham, MD: University Press of America 1990), pp. 1-19 at p. 9.p.225(?) change "night star" to "night sky."
p.227, append: An important predecessor, pointed out to me by Richard Dawkins in 1998, is the paper by J. W. S. Pringle, "On the parallel between learning and evolution," Behaviour 3:174-215 (1951).
p.229: Add "100 Richard Dawkins, The Extended Phenotype (Oxford 1982)."
p.232: at 134, "p.105"
p.233: at 137, add title Origins of Sex
There may be nothing new under the sun, but permutation of the old within complex systems can do wonders.
This is a book about thought, memory, creativity, consciousness, narrative, talking to oneself, and even dreaming. In a book that parallels this one, How Brains Think, I explored those subjects in a general way but here I treat them as some of the predicted outcomes of a detailed darwinian theory for how our cerebral cortex represents mental images and occasionally recombines them, to create something new and different.
This book proposes how darwinian processes could operate in the brain to shape up mental images. Starting with shuffled memories no better than the jumble of our nighttime dreams, a mental image can evolve into something of quality, such as a sentence to speak aloud. Jung said that dreaming goes on continuously but you cant see it when you are awake, just as you cant see the stars in the daylight because the sky is too bright. Mine is a theory for what goes on, hidden from view by the glare of waking mental operations, that produces our peculiarly human type of consciousness with its versatile intelligence. As Piaget emphasized, intelligence is what we use when we dont know what to do, when we have to grope rather than using a standard response. In this book, I tackle a mechanism for doing this exploration and improvement offline, how we think before we act and how we practice the art of good guessing.
Surprisingly, the subtitles mosaics of the mind is not just a literary metaphor. It is a description of mechanism at what appears to be an appropriate level of explanation for many mental phenomena that of hexagonal mosaics of electrical activity, competing for territory in the association cortex of the brain. This two-dimensional mosaic is predicted to grow and dissolve, much as the sugar crystals do in the bottom of a supersaturated glass of iced tea. Looking down on the cortical surface, with the right kind of imaging, ought to reveal a constantly changing patchwork quilt.
A closer look at each patch ought to reveal a hexagonal pattern that repeats every 0.5 mm. The pattern within each hexagon of this mosaic may be the representation of an item of our vocabulary: objects and actions such as the cat that sat on the mat, tunes such as Beethovens dit-dit-dit-dah, images such as the profile of your grandmother, a high-order concept such as a Turing Machine even something for which you have no word, such as the face of someone whose name you havent learned. If I am right, the spatiotemporal firing pattern within that hexagon is your cerebral code for a word or mental image.
The other phrase in the books title that is sure to be mistaken for literary license is, of course,
the cerebral code. The word code is often only a short way of saying unlocking the secrets of
and newspaper headline writers love such short words. Neurobiologists also speak loosely
about codes, as when we talk of frequency codes and place codes, when we really mean
only a simple mapping.|
Real codes are phrase-based translation tables, such as those of bank wires and diplomatic telegrams. A code is a translation table whereby short abstract phrases are elaborated into the real thing. Its similar to looking up ambivalence in a dictionary and getting an explanatory sentence back. In the genetic code, the RNA nucleotide sequence CUU is translated into leucine, the triplet GGA into glycine, and so on. The cerebral code, strictly speaking, would be what we use to convert thought into action, a translation table between the short-form cerebral pattern and its muscular implementation.
Informally, code is also used for the short-form pattern itself, for instance, a nucleotide chain such as GCACUUCUUGCACUU. In this book, cerebral code refers to the spatiotemporal firing pattern of neocortical neurons that is essential to represent a concept, word, or image, even a metaphor. One of my theoretical results is that a unique code could be contained within a unit hexagon about 0.5 mm across (though it is often redundantly repeated in many neighboring hexagons).
It was once thought that the genetic code was universal, that all organisms from bacteria to people used the same translation table. Now it turns out that mitochondria use a somewhat different translation table. Although the cerebral code is a true code, it surely isnt going to be universal; I doubt that the spatiotemporal firing pattern I use for dog (transposed to a musical scale, it would be a short melody, perhaps with some chords) is the same one that you use. Each persons cerebral codes are probably an accident of development and childhood experience. If we find some commonality, for example, that most peoples brains innately use a particular subset of codes for animate objects (say, C minor chords) and another subset (like the D major chords) for inanimate objects, I will be pleasantly surprised.
An important consequence of my cerebral code candidate, falling out of the way in which cortical pattern-copying mechanisms seem capable of generating new categories, is that ascending levels of abstraction become possible even analogies can compete, to help you answer those multiple-choice questions such as A is to B as C is to D,E,F. With a darwinian process operating in cerebral cortex, you can imagine using stratified stability to generate those strata of concepts that are inexpressible except by roundabout, inadequate means as when we know things of which we cannot speak. Thats the topic of the books penultimate chapter, The Making of Metaphor.
As a neurophysiologist with long experience doing single neuron recordings in
locales ranging from sea slug ganglia in vitro to human cerebral cortex in situ, I
undertook this theoretical venture about a decade ago. I didnt set out to explain
representations, or even the nature of working memory. Like most people in neurobiology, I considered such questions too big to be approached directly. One had to
work on their foundations instead.|
Back then, I had a much more modest goal: to seek brain analogies to the darwinian mechanisms that create higher-order complex systems in nature, something that could handle Kenneth Craiks 1943 notion of simulating a possible course of action before actually acting. We know, after all, that the darwinian ratchet can create advanced capabilities in stages, that its an algorithmic process that gradually creates quality and gets around the usual presumption that fancy things require an even fancier designer. We even know a lot of the ins-and-outs of the process, such as how evolution speeds up in island settings and why it slows down in continental ones.
However attractive a top-down cognitive design process might be, we know that a bottom-up darwinian process can achieve sophisticated results, given enough time. Perhaps the brain has invented something even fancier than darwinism, but we first ought (so I reasoned) to try the darwinian algorithm out for size, as a foundation and then look for shortcuts. In 1987, I wrote a commentary in Nature, The brain as a Darwin Machine, proposing a term for any full-fledged darwinian process, in analogy to the Turing Machine.
Indeed, since William James first discussed the matter in the 1870s during Charles Darwins lifetime, darwinian processes have been thought to be a possible basis for mental processes, a way to shape up a grammatically correct sentence or a more efficient plan for visiting the essential aisles of the grocery store. Theyre a way to explore the Piagetian maze, where you dont initially know what to do; standard neural decision trees for overlearned items may suffice for answering questions, but something creative is often needed when deciding what to do next as when you pose a question.
When first discovered by Darwin and Wallace and used to explain the shaping up of new species over many millennia, the darwinian ratchet was naturally thought to operate slowly. Then it was discovered that a darwinian shaping up of antibodies also occurs, during the days-to-weeks time course of the immune response to a novel antigen. You end up with a new type of antibody that is a hundred times more effective than the ones available at the time of infection and is, of course, far more numerous as well. What would it take, one asks, for the brain to mimic this creative mechanism using still faster neural mechanisms to run essentially the same process? Might some milliseconds-to-minutes darwinian ratchet form the foundation, atop which our sophisticated mental life is built?
As Wittgenstein once observed, you gain insights mostly through new arrangements of things you already know, not by acquiring new data. This is certainly true at the level of biological variation: despite the constant talk of mutations, its really the random shuffle of grandparent chromosomes during meiosis as sperm and ova are made, and the subsequent sexual recombination during fertilization, that generates the substantial new variations, such as all the differences between siblings. Novel mental images have also been thought to arise from recombinations during brain activity. In our waking hours, most of these surely remain at subconscious levels but many are probably the same sorts of juxtapositions that we experience in dreams every night. As the neurophysiologist J. Allan Hobson has noted:
The mechanistic requirements for this kind of darwinian process are now better known than
they were in the 1870s; they go well beyond the selective-survival summary of darwinism that
so often trivializes the issue. Charles Darwin, alas, named his theory natural selection, thus
leading many of his followers to focus on only one of what are really a half-dozen essential
aspects of the darwinian process. Thus far, most darwinian discussions of the brains
ontogeny, when examined, turn out to involve only several of the darwinian essentials and
not the whole creative loop that I discuss in later chapters.|
I attempted to apply these six darwinian attributes to our mental processes in The Cerebral Symphony and in Islands in the mind, published in Seminars in the Neurosciences in 1991, but at that time I hadnt yet found a specific neural mechanism that could turn the crank. Later in 1991, I realized that two recent developments in neuroscience emergent synchrony and standard-length intracortical axons provided the essential elements needed for a darwinian process to operate in the superficial layers of our cerebral cortex. This neocortical Darwin Machine opens up a broad neurophysiological-level consideration of cortical operation. With it, you can address a range of cognitive issues, from recognition memory to higher intellectual function including language and plan-ahead mechanisms even figuring out what goes with the leftovers in the refrigerator.
Despite the heritage from William James and Kenneth Craik, despite the recent interdisciplinary enthusiasm for fresh darwinian and complex adaptive systems approaches to long-standing problems, any such darwinian crank is going to seem new to those scientists who have
little detailed knowledge of darwinian principles beyond the crude survival of the fittest
For one thing, you have to think about the statistical nature of the forest, as well as the characteristic properties of each type of tree. Population thinking is not an easily acquired habit but I hope that the first chapter will briefly illustrate how to use it to make a list of six essential features of the darwinian process plus a few more features that serve as catalysts, to turn the ratchet faster. Next comes a dose of the local neural circuits of cerebral cortex, as that is where the triangular arrays of synchronized neurons are predicted, that will be needed for both the coding and creative complexity aspects. This is also where I introduce the hexagon as the smallest unit of the Hebbian cell-assembly and estimate its size as about 100 minicolumns involving 10,000 neurons (its essentially the 0.5 mm macrocolumn of association cortex, about the same size as the ocular dominance columns of primary visual cortex but perhaps not anchored as permanently). This is where compressing the code is discussed and that puts us in a position to appreciate how long-term memory might work, both for encoding and retrieval.
About halfway through the book, well be finished with the circuitry of a neocortical Darwin Machine and ready to consider, in Act II, some of its surprising products: categories, cross-modality matching, sequences, analogies, and metaphors. Its just like the familiar distinction we make between the principles of evolution and the products of evolution. The products, in this case, are some of the most interesting ways that humans differ from our ape cousins: going beyond mere category formation to shape up further levels of complexity such as metaphor, narrative, and even agendas. I think that planning ahead, language, and musical abilities also fall out of this same set of neocortical mechanisms, as Ive discussed (along with their free lunch aspects, thanks to common neural mechanisms) in my earlier books.
Some readers may have noticed by now that this book is not like my previous ones. They were
primarily for general readers and only secondarily for fellow scientists, but that order is
reversed here. To help compensate, Ive provided a glossary starting at page 203 (even the
neuroscientists will need it for the brief tutorials in chaos theory and evolutionary biology).
Consult it early and often.|
And I had the general reader firmly in mind as I did the book design (its all my fault, even the page layout). The illustrations range from the serious to the sketchy. In Three Places in New England, the composer Charles Ives had a characteristic way of playing a popular tune such as Yankee Doodle and then dissolving it into his own melody; even a quote of only four notes can be sufficient to release a flood of associations in the listener (something that I tackle mechanistically in Act II, when warming up for metaphor mechanisms). As a matter of writers technique, I have tried to use captionless thumbnail illustrations as the briefest of scene-setting digressions, to mimic Ives. I have again enlisted the underground architect, Malcolm Wells, to help me out you wont have any trouble telling which illustrations are Macs! Furthermore, a painting by the neurobiologist Mark Meyer adorns the cover. For some of my own illustrations, alas, I have had to cope with conveying spatiotemporal patterning in a spatial-only medium (further constrained by being grayscale-only and tree-based!). Although Ive relied heavily on musical analogies, the material fairly begs for animations.
I have resisted the temptation to utilize computer simulations, mostly for reasons of clarity (in my own head and perhaps also the readers). Simulations, if they are to be more than mere animations of an idea, have hard-to-appreciate critical assumptions. At this stage, simulations are simply not needed one can comprehend the more obvious consequences of a neocortical Darwin Machine without them, both the modular circuits and the territorial competitions. Plane geometry fortunately suffices, essentially that discovered by the ancient Greeks as they contemplated the hexagonal tile mosaics on the bathhouse floor.
Everyone knows that in 1859 Darwin demonstrated the occurrence of evolution with such overwhelming documentation that it was soon almost universally accepted. What not everyone knows, however, is that on that occasion Darwin introduced a number of other scientific and philosophical concepts that have been of far-reaching importance ever since. These concepts, population thinking and selection, owing to their total originality, had to overcome enormous resistance. One might think that among the many hundreds of philosophers who had developed ideas about change, beginning with the Ionians, Plato and Aristotle, the scholastics, the philosophers of the Enlightenment, Descartes, Locke, Hume, Leibniz, Kant, and the numerous philosophers of the first half of the nineteenth century, that there would have been at least one or two to have seen the enormous heuristic power of that combination of variation and selection. But the answer is no. To a modern, who sees the manifestations of variation and selection wherever he looks, this seems quite unbelievable, but it is a historical fact.
The paperback US edition |
is available from many bookstores and
The German translation,
Die Sprache des Gehirns:
Wie in unserem Bewußtsein Gedanken entstehen,
is at amazon.de.