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Deep-learning networks and the functional architecture of executive control

Published online by Cambridge University Press:  10 November 2017

Richard P. Cooper
Richard P. Cooper*
Affiliation:
Centre for Cognition, Computation and Modelling, Department of Psychological Sciences, Birkbeck, University of London, London WC1E 7HX, United Kingdom. R.Cooper@bbk.ac.uk http://www.bbk.ac.uk/psychology/our-staff/richard-cooper
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Abstract

Lake et al. underrate both the promise and the limitations of contemporary deep learning techniques. The promise lies in combining those techniques with broad multisensory training as experienced by infants and children. The limitations lie in the need for such systems to possess functional subsystems that generate, monitor, and switch goals and strategies in the absence of human intervention.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 40 , 2017 , e261
Copyright
Copyright © Cambridge University Press 2017 

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References

Cooper, R. P. (2016) Executive functions and the generation of “random” sequential responses: A computational account. Journal of Mathematical Psychology 73:153–68. doi: 10.1016/j.jmp.2016.06.002.CrossRefGoogle Scholar
Daw, N. D., Niv, Y. & Dayan, P. (2005) Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nature Neuroscience 8(12):1704–11. doi:10.1038/nn1560.CrossRefGoogle ScholarPubMed
Fodor, J. A. & Pylyshyn, Z. W. (1988) Connectionism and cognitive architecture: A critical analysis. Cognition 28(1–2):3–71.Google Scholar
Fox, J., Cooper, R. P. & Glasspool, D. W. (2013) A canonical theory of dynamic decision-making. Frontiers in Psychology 4(150):1–19. doi: 10.3389/fpsyg.2013.00150.Google Scholar
Newell, A. (1990) Unified theories of cognition. Harvard University Press.Google Scholar
Norman, D. A. & Shallice, T. (1986) Attention to action: willed and automatic control of behaviour. In: Advances in research: Vol. IV. Consciousness and self regulation, ed. Davidson, R., Schwartz, G. & Shapiro, D.. Plenum.Google Scholar
Shallice, T. & Cooper, R. P. (2011) The organisation of mind. Oxford University Press.Google Scholar
Vygotsky, L. S. (1978) Interaction between learning and development. In: Mind in society: The development of higher psychological processes, ed. Cole, M., John-Steiner, V., Scribner, S. & Souberman, E., pp. 79–91. Harvard University Press.Google Scholar