The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Could information theory provide an ecological theory of sensory processing?
Abstract
The sensory pathways of animals are well adapted to processing a special class of signals, namely stimuli from the animal's environment. An important fact about natural stimuli is that they are typically very redundant and hence the sampled representation of these signals formed by the array of sensory cells is inefficient. One could argue for some animals and pathways, as the author does in this review, that efficiency of information representation in the nervous system has several evolutionary advantages. Consequently, one might expect that much of the processing in the early levels of these sensory pathways could be dedicated towards recording incoming signals into a more efficient form. The author explores the principle of efficiency of information representation as a design principle for sensory processing. He gives a preliminary discussion on how this principle could be applied in general to predict neural processing and then discuss concretely some neural systems where it recently has been shown to be successful. In particular, he examines the fly's LMC coding strategy and the mammalian retinal coding in the spatial, temporal and chromatic domains.
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Citations
Cites
The contrast sensitivity of retinal ganglion cells of the cat
Enroth-Cugell, C., & Robson, J. G. (1966) · The Journal of Physiology · doi:10.1113/jphysiol.1966.sp008107 · Cited by 2,625
Predictive coding: a fresh view of inhibition in the retina
Srinivasan, M. V., Laughlin, S. B., & Dubs, A. (1982) · Proceedings of the Royal Society of London. Series B. Biological Sciences · doi:10.1098/rspb.1982.0085 · Cited by 1,042
Human contrast discrimination and the threshold of cortical neurons
Barlow, H. B., Hawken, M., Parker, A. J., & Kaushal, T. P. (1987) · Journal of the Optical Society of America A · doi:10.1364/josaa.4.002366 · Cited by 79
Cited by
Rao, R. P. N., & Ballard, D. H. (1999) · Nature Neuroscience · doi:10.1038/4580 · Cited by 5,483
Emergence of simple-cell receptive field properties by learning a sparse code for natural images
Olshausen, B. A., & Field, D. J. (1996) · Nature · doi:10.1038/381607a0 · Cited by 5,694
Sparse coding with an overcomplete basis set: A strategy employed by V1?
Olshausen, B. A., & Field, D. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00169-7 · Cited by 3,642
Sparse coding of sensory inputs
Olshausen, B. A., & Field, D. J. (2004) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2004.07.007 · Cited by 1,404
Neural Processing of Amplitude-Modulated Sounds
JORIS, P. X., SCHREINER, C. E., & REES, A. (2004) · Physiological Reviews · doi:10.1152/physrev.00029.2003 · Cited by 938
Metadata
- Authors
- Atick, J. J.
- Venue
- Network: Computation in Neural Systems
- Publisher
- Informa UK Limited
- Published
- 1992-01
- Volume
- 3
- Issue
- 2
- Pages
- 213-251
- ISSN
- 0954-898X (ISSN-L)
- 1361-6536
- OpenAlex
- W4232132600
- Cited by
- 446
- References
- 3
- FWCI
- 8.89
- Type
- journal article
- Language
- en
- Open access
- closed
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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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