Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-28T13:25:42.707Z Has data issue: false hasContentIssue false
  • English
  • Français

Not just a bad metaphor, but a little piece of a big bad metaphor

Published online by Cambridge University Press:  28 November 2019

George N. Reeke Jr. Open the ORCID record for George N. Reeke Jr. [Opens in a new window]
George N. Reeke Jr.*
Affiliation:
Laboratory of Biological Modeling, The Rockefeller University, New York, NY10065. reeke@rockefeller.eduhttps://www.rockefeller.edu/our-scientists/heads-of-laboratories/892-george-n-reeke-jr/
Get access Rights & Permissions [Opens in a new window]

Abstract

Besides failing for the reasons Brette gives, codes fail to help us understand brain function because codes imply algorithms that compute outputs without reference to the signals' meanings. Algorithms cannot be found in the brain, only manipulations that operate on meaningful signals and that cannot be described as computations, that is, sequences of predefined operations.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 42 , 2019 , e239
Check for updates
Copyright
Copyright © Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bickhard, M. H. & Terveen, L. (1996) Foundational issues in artificial intelligence and cognitive science: Impasse and solution (Advances in psychology, Vol. 109). Elsevier/North-Holland.Google Scholar
Fodor, J. A. & Pylyshyn, Z. W. (1988) Connectionism and cognitive architecture: A critical analysis. In: Connections and symbols, ed. Pinker, S. & Mehler, J.. MIT Press.Google Scholar
Gilbert, C. D. (1996) Plasticity in visual perception and physiology. Current Opinion in Neurobiology 6(2):269–74.CrossRefGoogle ScholarPubMed
Harnad, S. (1990a) The symbol grounding problem. In: Emergent computation, ed. Forrest, S., pp. 335–46. North-Holland.Google Scholar
Izhikevich, E. M. (2006) Polychronization: Computation with spikes. Neural Computation 18(2):245–82. doi: 10.1162/089976606775093882.CrossRefGoogle ScholarPubMed
Reeke, G. N. Jr. & Edelman, G. M. (1988) Real brains and artificial intelligence. Daedalus 117:143–73.Google Scholar
Reeke, G. N. Jr., Finkel, L. H., Sporns, O. & Edelman, G. M. (1990) Synthetic neural modeling: A multilevel approach to the analysis of brain complexity. In: Signal and sense: Local and global order in perceptual maps, ed. Edelman, G. M., Gall, W. E. & Cowan, W. M., pp. 607–706. Wiley.Google Scholar
Rumelhart, D. E., McClelland, J. L. & The PDP Research Group. (1986) Parallel distributed processing: Explorations in the microstructure of cognition: Vol. 1. Foundations. MIT Press.Google Scholar
Tsotsos, J. K. (2011) A computational perspective on visual attention. MIT Press.CrossRefGoogle Scholar