Journal
PLOS ONE
Volume 13, Issue 6, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0199196
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Categories
Funding
- Canadian Institutes of Health Research [3531979]
- Natural Science and Engineering Research Council of Canada
- Canada Research Chairs Program
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First-order tactile neurons have spatially complex receptive fields. Here we use machine-learning tools to show that such complexity arises for a wide range of training sets and network architectures. Moreover, we demonstrate that this complexity benefits network performance, especially on more difficult tasks and in the presence of noise. Our work suggests that spatially complex receptive fields are normatively good given the biological constraints of the tactile periphery.
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