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The Optimal Human Ventral Stream from Estimates of the Complexity of Visual Objects

Changizi, Mark A. (2006) The Optimal Human Ventral Stream from Estimates of the Complexity of Visual Objects. Biological Cybernetics, 94 (5). pp. 415-426. ISSN 0340-1200.

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The part of the primate visual cortex responsible for the recognition of objects is parcelled into about a dozen areas organized somewhat hierarchically (the region is called the ventral stream). Why are there approximately this many hierarchical levels? Here I put forth a generic information-processing hierarchical model, and show how the total number of neurons required depends on the number of hierarchical levels and on the complexity of visual objects that must be recognized. Because the recognition of written words appears to occur in a similar part of inferotemporal cortex as other visual objects, the complexity of written words may be similar to that of other visual objects for humans; for this reason, I measure the complexity of written words, and use it as an approximate estimate of the complexity more generally of visual objects. I then show that the information-processing hierarchy that accommodates visual objects of that complexity possesses the minimum number of neurons when the number of hierarchical levels is approximately 15.

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Additional Information:© 2006 Springer-Verlag. Received: 6 July 2005; Accepted: 16 January 2006; Published online: 3 March 2006. I wish to thank Shinsuke Shimojo and Dan Ryder, and one very helpful referee, for comments on the paper. Support for this research was given by NIH grant 5F32EY015370-02.
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Subject Keywords:Visual hierarchy; Number of visual areas; Sizes of areas; Optimization; Information theory; Object recognition; Intermediate-level features; Visual object complexity
Issue or Number:5
Record Number:CaltechAUTHORS:20200320-125912063
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Official Citation:Changizi, M.A. The Optimal Human Ventral Stream from Estimates of the Complexity of Visual Objects. Biol Cybern 94, 415–426 (2006).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:102027
Deposited By: Tony Diaz
Deposited On:20 Mar 2020 20:56
Last Modified:20 Mar 2020 20:56

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