MIT Encyclopedia of the Cognitive Sciences - Cryptome

and similar form, which suggests they have a common function;
an attractive hypothesis is that this is prediction.and
Sense organs are slow, but an animal’s competitive survival
often depends upon speedy response; therefore, a representation
that is up to the moment, or even ahead of the
moment, would be of very great advantage. Prediction
depends upon identifying a commonly occurring sequential
pattern of events at an early stage in the sequence and
assuming that the pattern will be completed. This requires
knowledge of the spatio-temporal sequences that commonly
occur, and the critical or sensitive periods, which neurophysiologists
have studied in the visual cortex (Hubel and
Wiesel 1970; Movshon and Van Sluyters 1981) but which
are also known to occur in the development of other cognitive
systems, may be periods when spatio-temporal
sequences that occur commonly encourage the development
of neurons with a selectivity of response to these patterns. If
such phase sequences, as HEBB (1949) called them, were
recognized by individual cells, one would have a computational
unit that, with appropriate connections, would be of
selective advantage in an enormous range of circumstances.
The survival value of neurons with the power of prediction
could have led to the explosive enlargement of the neocortex
that culminated in the human brain.
See also ADAPTATION AND ADAPTATIONISM; CORTICAL
LOCALIZATION, HISTORY OF; EVOLUTION; HEMISPHERIC SPE-
CIALIZATION; NEURON
——Horace Barlow
References
Barlow, H. B. (1981). Critical limiting factors in the design of the
eye and visual cortex. The Ferrier Lecture, 1980. Proceedings
of the Royal Society, London Series B 212: 1–34.
Barlow, H. B. (1994). What is the computational goal of the neocortex?
In C. Koch and J. Davis, Eds., Large Scale Neuronal
Theories of the Brain. Cambridge, MA: MIT Press.
Braitenberg, V., and A. Schuz. (1991). Anatomy of the Cortex: Statistics
and Geometry. Berlin: Springer-Verlag.
Hebb, D. O. (1949). The Organisation of Behaviour. New York:
Wiley.
Herrick, C. J. (1926). Brains of Rats and Men. Chicago: University
of Chicago Press.
Hubel, D. H., and T. N. Wiesel. (1970). The period of susceptibility
to the physiological effects of unilateral eye closure in kittens.
Journal of Physiology 206: 419–436.
Jerison, H. J. (1973). Evolution of the Brain and Intelligence. New
York: Academic Press.
Macphail, E. (1982). Brain and Intelligence in Vertebrates. New
York: Oxford University Press.
Movshon, J. A., and R. C. Van Sluyters. (1981). Visual neural
development. Annual Review of Psychology 32: 477–522.
Phillips, C. G., S. Zeki, and H. B. Barlow. (1984). Localisation of
function in the cerebral cortex. Brain 107: 327–361.
Sarnat, H. B., and M. G. Netsky. (1981). Evolution of the Nervous
System. New York: Oxford University Press.
Thompson, R. F. (1990). Neural mechanisms of classical conditioning
in mammals. Philosophical Transactions of the Royal
Society of London Series B 329:171–178.
Yeo, C. H., M. J. Hardiman, and M. Glickstein. (1985). Classical
conditioning of the nictitating membrane response of the rabbit
(3 papers). Experimental Brain Research 60: 87–98; 99–113;
114–125.
Further Readings
Chess, Psychology of 113
Abeles, M. (1991). Corticonics: Neural Circuits of the Cerebral
Cortex. Cambridge: Cambridge University Press.
Creuzfeldt, O. D. (1983). Cortex cerebri: leistung, strukturelle und
functionelle Organisation der Hirnrinde. Berlin: Springer-Verlag.
Translated by Mary Creuzfeldt et al. as “Cortex cerebri:
performance, structural and functional organisation of the cortex,”
Gottingen 1993.
Jones, E. G., and A. Peters. (1985). Cerebral Cortex. Five volumes.
New York: Plenum Press.
Martin, R. D. (1990). Primate Origins and Evolution. London:
Chapman and Hall.
Cerebral Specialization
See HEMISPHERIC SPECIALIZATION
Chess, Psychology of
Historically, chess has been one of the leading fields in the
study of EXPERTISE (see De Groot and Gobet 1996 and
Holding 1985 for reviews). This popularity as a research
domain is explained by the advantages that chess offers for
studying cognitive processes: (i) a well-defined task; (ii)
the presence of a quantitative scale to rank chess players
(Elo 1978); and (iii) cross-fertilization with research on
game-playing in computer science and artificial intelligence.
Many of the key chess concepts and mechanisms to be
later developed in cognitive psychology were anticipated by
Adriaan De Groot’s book Thought and Choice in Chess
(1946/1978). De Groot stressed the role of selective search,
perception, and knowledge in expert chess playing. He also
perfected two techniques that were to be often used in later
research: recall of briefly presented material from the
domain of expertise, and use of thinking-aloud protocols to
study problem-solving behavior. His key empirical findings
were that (i) world-class chess grandmasters do not search
more, in number of positions considered and in depth of
search, than weaker (but still expert) players; and (ii) grandmasters
and masters can recall and replace positions (about
two dozen pieces) presented for a few seconds almost perfectly,
while weaker players can replace only a half dozen
pieces.
De Groot’s theoretical ideas, based on Otto Selz’s psychology,
were not as influential as his empirical techniques
and results. It was only about twenty-five years later that
chess research would produce a theory with a strong impact
on the study of expertise and of cognitive psychology in
general. In their chunking theory, Simon and Chase (1973)
stressed the role of perception in skilled behavior, as did De
Groot, but they added a set of elegant mechanisms. Their
key idea was that expertise in chess requires acquiring a
large collection of relatively small chunks (each at most six
pieces) denoting typical patterns of pieces on the chess
board. These chunks are accessed through a discrimination
net and act as the conditions of a PRODUCTION SYSTEM: they
evoke possible moves in this situation. In other respects,
chess experts do not differ from less expert players: they