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Computational Neuroscience of Vision$
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Edmund Rolls and Gustavo Deco

Print publication date: 2001

Print ISBN-13: 9780198524885

Published to Oxford Scholarship Online: March 2012

DOI: 10.1093/acprof:oso/9780198524885.001.0001

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Principles and Conclusions

Principles and Conclusions

Chapter:
(p.456) 13 Principles and Conclusions
Source:
Computational Neuroscience of Vision
Author(s):

Edmund T. Rolls

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198524885.003.0013

This concluding chapter sums up the key findings of this study on the computational neuroscience of vision. The results show that the responses of many inferior temporal visual cortex neurons have transform invariant responses to objects and faces, but not all neurons have view invariance. The findings also indicate that much of the information available from the responses of the neurons about shapes and objects is available in short time periods and that invariant representations can be self-organized using a trace learning rule incorporated in a feature hierarchy network such as VisNet.

Keywords:   vision, computational neuroscience, visual cortex, neurons, view invariance, invariant representations, VisNet

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