by Kevin Walker
University of California, Berkeley
1991
Walter Freeman has shown the importance of adopting a macroscopic as well as a microscopic view of mental activity. His findings on perception raise some intriguing possibilities for the study of other brain activities. If the brain acts in such a global, integrated fashion during perception, might such "chaotic activity" play a role in consciousness in general, in forming meaning, in learning, memory, and intelligence? And what might be the adaptive significance of such integrated, chaotic activity in the evolution of human intelligence?
This involves a few assumptions. First, I am projecting Freeman's rather narrow findings on olfactory perception in rabbits to sensory perception in general, and to humans, and potentially to other, "higher" mental functions. "Mind" is held to be contingent on biological properties of the brain. This involves some speculation, but this path can be a fruitful one to follow, I believe, for some interesting hypotheses can be drawn regarding human evolution.
Freeman shows how millions of neurons spread across the cortex can, almost instantly, generate a (highly subjective) "picture" of an incoming stimulus, and place it in a certain "context". Chaos theory provides a convenient explanation of the process; and indeed, Freeman is one of the first to effectively operationalize chaos theory in human neurobiology. The theory holds that when studying systems with any degree of complexity, errors made at "lower" levels can be greatly magnified at subsequent levels, so instead of conceptualizing a linear process, an integrated, more random (though not competely random) system is viewed. "The system is deterministic, but you can't say what it's going to do next," says James Gleick, a leading chaos theorist.1 Freeman likens the system to commuters in a train station, as against a random mob. (This raises interesting possibilities of chaos in social groups, but this is beyond the scope of this paper.) It is self-generating activity, complex behavior with some hidden order.
In the brain, a very slight input can cause whole collections of neurons to shift abruptly from one complex pattern to another, and this, Freeman believes, makes perception possible. It underlies the flexibility of the brain, allowing it to generate novel patterns, including fresh ideas. This recalls Dawkins's meme theory, in which an incoming meme ("cultural replicator"), which is consciously or unconsciously selected, can physically alter a brain's structure. Memes, Dawkins argues, are in fact biological organisms, living in human brains. This touches on issues of intelligence, to which I will return later. For now it is sufficient to note that rapid "state changes" in a brain, (perhaps analagous to "punctuated equilibrium" in evolution?) occur in response to a relatively weak input, and there are distinct patterns or "chaotic attractors" for individual stimuli.
This model appears to be complex and unorganized, but on the contrary, it exhibits signs of being a structured "hierarchic system" in Herbert Simon's definition.2 There appear to be increasing levels of complexity, from individual neurons to regions of the brain, to the entire brain, each successive level having properties equal to more than the sum of its parts. But it is becoming increasingly clear that the mechanism that unifies mental functioning is not spatial but temporal; it is defined by "intensity of interaction"3. Incoming sensory signals combine with information from other senses, from experience, emotion and perhaps other factors, and through cooperative, interactive activity, produce perceptions that allow for appropriate action and/or are committed to memory. Perception itself may said to be a temporally structured hierarchical system, since an individual perceives, first, an overall "gestalt", then a successively more detailed "picture" the more time is allotted to the perceiving process.
This has all sorts of interesting consequences. For instance, one may see so many "strangers" in one's lifetime, whether in the course of walking the streets of one's town, or in the media, that it is convenient for the brain to form a simplified (often language-based) picture based on past experience and context. More on this shortly.
In Freeman's integrated portrait of perception, it is useful to view regions of the brain, or shifting "neural networks", as the lowest useful level of analysis of perception, if not the entire brain itself. Given this, what would be the next expected level of complexity? A circular process could be described, going from perception to learning to experience to intelligence, then back to perception. But this includes only cognitive functions. Physiologically, a hierarchical system could be theorized going from neurons to brain/nervous system to musculature, to the body. This, too is incomplete, however. A more general (and thus more accomodating and useful) conception would be from perception to thought to action, then to social interaction, and on up through successively larger social bodies.
We might say that what holds social bodies together is shared perceptions; though it is perhaps more often true that it is biology or institutional rules that bind people, it appears true that small-scale social relationships are formed by people seeking "like minds". This is due to the tendency of people to define others' actions by their own, as Nicholas Humphrey persuasively argues.4
Consciousness in general, viewed from this integrated perspective, takes on a whole new meaning. Freeman defines consciousness narrowly, as "reafference and perception". He describes "gain" as the ratio of input to output, positively correlated.5 This is analagous to information versus feedback, stimulus versus response, or thought versus action.
Humphrey believes that consciousness is an adaptive trait, which evolved from, and for, social activity. It operates both externally, interacting with the physical and social environment, and autonomously, "collating information, hatching plans, and making decisions between one course of action and another".6 And it corresponds with mental states such as hunger, arousal, etc. It would be unwise to follow Alfred Kroeber's advice to "strip away" social, cultural and environmental factors to arrive at hereditary ("racial") bases for consciousness, for this would leave nothing.
There is an additional driving mechanism: that of human "will". This is an emergent property related to the size and complexity of the human brain. "Action" may be seen as a series of unbroken chemical steps, at the end of which is a certain behavior, but the "pathway" (or more accurately the neural network or configuration) is consciously chosen, for the most part.7 It also must be noted that consciousness is only a small part of mental activity; subconscious motivations and mid-level "covert awareness" must also be considered.8
Consciousness is, in addition, highly subjective. Wittgenstein's analogy of the "beetle in a box" makes sense.9 Freeman shows how sensory signals combine with other types of input and an individual's unique experiences to form a thoroughly individual perceptual gestalt. Language ability is also related to the formation of individual meaning, since all languages rely on certain, universal dichotomies such as male versus female, inside versus outside and some form of a "good" versus "bad" complex. Meme theory also applies, since when new memes are chosen by an individual, they are mutated by, and blend with, those already present.
Let us turn to how Freeman's work might affect the study of learning, which might be said to be a micro-process of evolution. Freeman describes perception as "a step in a trajectory by which brains grow, reorganize themselves and reach into their environment to change it to their advantage".10 He cites the Hebb Rule which states that synapses that fire together become stronger as long as there is a reward.11 It is also known that nerve cells connecting the amygdala (which evaluates incoming information for emotional significance) to the cortex are rich producers of opiates, which can enhance learning and memory.12 Emotion is linked to vividly remembered events, and Hubert Dreyfus demonstrates the link between emotion and "whole remembered situations" that appear to have a holistic, "three-dimensional quality".13
Indeed, most "learning" does not come from "teaching" as we know it, but from perception of various kinds. The perception of pain, for instance, is believed to be related to learning: a similar biochemical mechanism appears to regulate pain avoidance and task mastery, evident in the similar ways nerve cells become "hypersensitive" following a pain event, and the way that they change during learning. Edgar Walters believes that learning may have, in fact, evolved from pain avoidance: "Evolution is opportunistic," he says. "It takes advantage of pre-existing mechanisms".14 As for other types of perception, it is well-known that the presence of external stimuli, (including other individuals, as Humphrey shows15), is directly related to cognitive development. Presumably, the more heterogeneity in an environment or a population results in more diverse things to percieve, hence greater cognitive development.
Memory appears also to conform to Freeman's model. Recollection has been found to occur in unexpected parts of the brain: In addition to the hippocampus, (the visual processing area normally associated with perception), and the pre-frontal cortex (normally associated with higher thinking) are also involved. The latter area seems to direct the memory search.16 This may be added to Freeman's finding that the very act of recall changes the memorized event. A "nerve cell assembly," Freeman says, is a repository of past associations which interacts with incoming data during the perception process.
How, then, might this relate to human intelligence in general? Alice Heim defines intelligence as "the ability to grasp the essentials of a situation and respond appropriately". Humphrey adds that intelligence "modifies behavior on the basis of valid inference from evidence."17
Vincent Sarich includes in his general definition of intelligence: amount of knowledge, processing speed, and critical problem-solving ability.18 The amount of knowlege an individual brain can hold is deemed to be related to its size, though there are other factors. Processing speed, however, seems directly related to Freeman's findings. If a network of neurons can shift from complex activity to complex activity instantaneously, presumably a brain which is well-integrated, and well-developed in each of its "sub-complexes" (to use Simon's term), it might process faster. The "formal operational" stage of thinking, (the highest level, according to Sarich), could be related to the integratedness of a brain as well.
Dreyfus describes how formal rules (heuristic knowledge) simplify complex phenomena. But he also shows how "experts" often cannot generate the rules they supposedly use, suggesting that the rules become "internalized" and can be readily, but unconsciously, called up.19 A chaotic neural network would seem to be an effective way of mobilizing such rules and integrating them with other thoughts. The ability of "experts" to work instinctually, without formally reasoning or problem-solving, appears compatible with rapid, global, chaotic activity in the brain.
In meme theory, this is related to the economization of thought. Mihalyi Csikszentmihalyi has observed that the initial selection of memes involves conscious evaluation, but they must become "internalized" to be effective.20 The process is analagous to the way emergent properties become contingent in evolution. Just as memes float freely in the intellectual "climate", so may they "float" in the brain, perhaps in a shifting, temporal neural network.
The evolutionary significance of "chaotic brains" is intriguing to think about. Chaos is, Freeman says, a by-product of the brain's complexity. Since human brains are larger and more complex than rabbits', his subjects, the possibilities are probably unimaginable. But based on his research, it can be said that chaotic networks allow for the production of novel activity patterns, that is, the "trials" of trial-and-error problem solving. These networks can give rise to new memes. The survival of memes or meme complexes, then, could be thought of as the survival of the most stable neural networks over time.
Humphrey describes how previous life forms lacked a mechanism for looking in on their own thoughts. (He defines consciousness from a distinctly human point of view; it is temporal as well.) He says that hunter-gatherer societies facilitated the growth of intelligence through social ties. Success was, and is, success in social relations; and our minds are still "living in the past" in some ways.
Intelligence, in the mental sense, is not believed to be transmitted by genes. But certain significant, emotional, social events could have become "internalized" in past individuals' minds in the way Dreyfus and Csikszentmihalyi describe. (Perhaps conceptions of "natural laws" have also been passed this way.) As Humphrey says, "someone who starts with a slate on which the explanatory pattern is already half sketched in" is more likely to be "successful". Emergent properties can become contingent. A human community provides a medium for cultural and intellectual transmission, as Humphrey describes, by providing protection and food for the young, who, not having to fend for themselves, can explore and learn by trial-and-error and by perceiving and imitating older, more "experienced" individuals.
The reason why computers have not been designed to "think" like humans is because they lack a basic "common sense". Newer models utilizing neural network theory, "object-oriented programming" (a hierarchical system) and "massively parallel" techniques inch closer. But ultimately, as Freeman's research has shown, human mental activity is "chaotic" and integrated to a degree never thought possible. Computers could never "catch up" to humans since humans brains continue to grow and evolve through perception, learning, reconfiguring, and internalizing; and perhaps somehow transmitting their "knowledge" from generation to generation. "Chaos," as concerns the human brain, is likely to become more chaotic.
1. Gleick, James. (1987) Chaos, p.251. (New York: Viking Penguin)
2. Simon, H. (1962) "The Architecture of Complexity" Proceedings of the American Philosophical Society 106: 85-118.
3. Ibid., p.90.
4. Humphrey, Nicholas. (1982) "Consciousness: a Just-So Story" New Scientist, Aug. 19, 1982, 474-477.
5. Freeman, p.85.
6. Ibid., p.474.
7. From Anthro. 111 lecture.
8. For an interesting discussion of covert awareness, see Blakeslee, Sandra. "The Brain May 'See' What Eyes Cannot" New York Times, January 15, 1991, pp. B5-6
9. Cited in Humphrey 1982, p.474.
10. Freeman, p.85.
11. Ibid., p.81.
12. From research done by Mortimer Mishkin of the National Institute of Mental Health, reported in Patlak, Margie "What is Emotion for?" San Francisco Examiner, March 10, 1991, pp.D15-16.
13. Dreyfus, H.L. (1987) "From Socrates to Expert Systems: The Limits of Calculative Rationality" Bulletin of the American Academy of Arts and Sciences 50:4, p.26.
14. From Angier, Natalie. "Pain and Learning May Be Close Cousins in Chain of Evolution" New York Times, August 27, 1991, p.B6.
15. Humphrey, (1984) "The Social Function of Intellect", pp.19-20. Consciousness Regained. (Oxford Univ. Press).
16. From work by Larry Squire, reported in Hilts, Philip J. "Photos Show Mind Recalling a Word" New York Times, November 11, 1991, pp.A1, 8.
17. Humphrey 1984, p.15.
18. From lecture.
19. Dreyfus 1987, p.27-30.
20. Csikszentmihalyi, Mihaly. (1988) "Memes vs. Genes: Notes From the Culture Wars" The Reality Club. ed. John Brockman. (New York: Lynx Books)