Gallistel has made experimental and theoretical contributions to several areas of behavioral and cognitive neuroscience: 1) The nature and development of the representation of numerosity in young children, in collaboration with his wife, Rochel Gelman.[3] 2) The psychophysical analysis of the neural substrate for electrical self-stimulation of the brain.[4] 3) The theory of action and its close relation to the theory of motivation.[5] 4) The theory of learning.[6] 5) What it means to say that brains represent the experienced world.[7] 6) The brain's representation of the abstract variables central to conceptions of space (distance & direction), time (duration and phase), numerosity, rate (number/duration) and probability (subset numerosity/set numerosity).[8] 7) The nature of the engram, the physical realization of memory in brains.[9]
Gallistel is an advocate of the computational theory of mind, and as such he criticized the view of memory as an alteration of synaptic connections (a view that is related to Associationism). His critique, in particular, focuses on how the Associationist theory of mind allegedly cannot explain how the brain encodes quantitative data such as distances, directions, and temporal durations. Gallistel rather argues that such memories could be collected inside the neurons, at the molecular level, and to support his claim he remarks the considerable capacity of polynucleotides for storing information.[10][11][12][13][14][15]
Books
Gallistel, C. R.; King, Adam Philip (2009). Memory and the computational brain: why cognitive science will transform neuroscience. Wiley-Blackwell. ISBN9781444310498.
Gallistel, C. R. (1990). The organization of learning. MIT Press. ISBN0262071134.
Gelman, Rochel; Gallistel, C. R. (1978). The child’s understanding of number. Harvard University Press. ISBN0674116364.
Gallistel, C. R.; Gibbon, John (2002). The symbolic foundations of conditioned behavior. Lawrence Erlbaum Associates. ISBN0805829342.
Gallistel, C. R. (1980). The organization of action: A new synthesis. Lawrence Erlbaum Associates. ISBN0262071134.
References
^Haselgrove, Mark (2016). Learning: A Very Short Introduction. Oxford University Press.
^R. Gelman et C. R. Gallistel, The Child's Understanding of Number.
^C. R. Gallistel, Electrical self-stimulation and its theoretical implications in Psychological Bulletin, 1964, 61, 23-34
^C. R. Gallistel, The organization of action: A new synthesis, Hillsdale, N. J.: Lawrence Erlbaum Associates, Inc. 432 pp, 1980
^C. R. Gallistel, P. D. Balsam, S. Fairhurst, The learning curve: Implications of a quantitative analysis. Proceedings of the National Academy of Sciences, R 101(36), 2004, p. 13124-13131
^C. R. Gallistel, Learning and Representation. In: R. Menzel (ed.), Learning. Theory and Behavior, Vol. 1 of Learning and Memory: A Comprehensive Reference, p. 141-154, Academic Press, Oxford
^C. R. Gallistel, 2018, Finding numbers in the brain. Proceedings of the Royal Society (London). Series B, 373(1740): 20170119
^Gallistel, C.R. The coding question., 2017, Trends in Cognitive Sciences, 21(7), 498-508. doi: 10.1016/j.tics.2017.04.012
^C. R. Gallistel, Machinery of cognition, chapitre 3, in Evolution and the Mechanisms of Decision Making. Strüngmann Forum Reports, Cambridge, MA, MIT Press, 2003, p. 39-52
^C. R. Gallistel, A. P. King, Memory and the Computational Brain : Why cognitive Science will transform Neuroscience, New York: Blackwell/Wiley, 2009
^C.R Gallistel, 2017 The neurobiological bases for the computational theory of mind, in R. G. d. Almeida & L. Gleitman (Eds.), On Concepts, Modules, and Language New York: Oxford University Press.p. 275-296
^C. R. Gallistel, 2017, The coding question. Trends in Cognitive Sciences, 21(7), p. 498-508
^C. R. Gallistel, 2017, Numbers and brains. Learning & Behavior, 45(4), p. 327-328
^C. R. Gallistel, 2018, Finding numbers in the brain. Proceedings of the Royal Society (London). Series B, 373(1740): 20170119