@inproceedings{6a870e91488c43b68027e8a02b2a4115,
title = "Information-theoretic interpretation of tuning curves for multiple motion directions",
abstract = "We have developed an efficient information-maximization method for computing the optimal shapes of tuning curves of sensory neurons by optimizing the parameters of the underlying feedforward network model. When applied to the problem of population coding of visual motion with multiple directions, our method yields several types of tuning curves with both symmetric and asymmetric shapes that resemble what have been found in the visual cortex. Our result suggests that the diversity or heterogeneity of tuning curve shapes as observed in neurophysiological experiment might actually constitute an optimal population representation of visual motions with multiple components.",
keywords = "Area MT, Bidirectional visual motion, Fisher information, Shannon mutual information, Side bias, Unsupervised learning",
author = "Wentao Huang and Xin Huang and Kechen Zhang",
note = "Funding Information: Supported by grants NIH R01 EY022443 and NIH R01 DC013698. Publisher Copyright: {\textcopyright} 2017 IEEE.; 51st Annual Conference on Information Sciences and Systems, CISS 2017 ; Conference date: 22-03-2017 Through 24-03-2017",
year = "2017",
month = may,
day = "10",
doi = "10.1109/CISS.2017.7926142",
language = "English (US)",
series = "2017 51st Annual Conference on Information Sciences and Systems, CISS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2017 51st Annual Conference on Information Sciences and Systems, CISS 2017",
}