The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
A Theory of How the Brain Might Work
Open accessAbstract
I wish to propose a quite speculative new version of the grandmother cell theory to explain how the brain, or parts of it, may work. In particular, I discuss how the visual system may learn to recognize 3D objects. The model would apply directly to the cortical cells involved in visual face recognition. I will also outline the relation of our theory to existing models of the cerebellum and of motor control. Specific biophysical mechanisms can be readily suggested as part of a basic type of neural circuitry that can learn to approximate multidimensional input-output mappings from sets of examples and that is expected to be replicated in different regions of the brain and across modalities. The main points of the theory are: -the brain uses modules for multivariate function approximation as basic components of several of its information processing subsystems. -these modules are realized as HyperBF networks (Poggio and Girosi, 1990a,b). -HyperBF networks can be implemented in terms of biologically plausible mechanisms and circuitry. The theory predicts a specific type of population coding that represents an extension of schemes such as look-up tables. I will conclude with some speculations about the trade-off between memory and computation and the evolution of intelligence.
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Cites
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Marr, D. (1969) · The Journal of Physiology · doi:10.1113/jphysiol.1969.sp008820 · Cited by 3,253
A theory of cerebellar function
Albus, J. S. (1971) · Mathematical Biosciences · doi:10.1016/0025-5564(71)90051-4 · Cited by 2,539
Cited by
Adaptive representation of dynamics during learning of a motor task
Shadmehr, R., & Mussa-Ivaldi, F. (1994) · The Journal of Neuroscience · doi:10.1523/jneurosci.14-05-03208.1994 · Cited by 2,612
Bayesian inference with probabilistic population codes
Ma, W. J., Beck, J. M., Latham, P. E., & Pouget, A. (2006) · Nature Neuroscience · doi:10.1038/nn1790 · Cited by 1,457
On the computational architecture of the neocortex: II The role of cortico-cortical loops
Mumford, D. (1992) · Biological Cybernetics · doi:10.1007/bf00198477 · Cited by 1,074
Neural mechanisms for the recognition of biological movements
Giese, M. A., & Poggio, T. (2003) · Nature Reviews Neuroscience · doi:10.1038/nrn1057 · Cited by 955
Self-citationOn the computational architecture of the neocortex: I. The role of the thalamo-cortical loop
Mumford, D. (1991) · Biological Cybernetics · doi:10.1007/bf00202389 · Cited by 929
Metadata
- Authors
- Poggio, T.
- Venue
- Cold Spring Harbor Symposia on Quantitative Biology
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 1990-01-01
- Volume
- 55
- Issue
- 0
- Pages
- 899-910
- ISSN
- 0091-7451 (ISSN-L)
- 1943-4456
- OpenAlex
- W2087629825
- Cited by
- 252
- References
- 3
- Type
- posted content
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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