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  • 标题:Habituation as a neural algorithm for online odor discrimination
  • 本地全文:下载
  • 作者:Yang Shen ; Sanjoy Dasgupta ; Saket Navlakha
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2020
  • 卷号:117
  • 期号:22
  • 页码:12402-12410
  • DOI:10.1073/pnas.1915252117
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:Habituation is a form of simple memory that suppresses neural activity in response to repeated, neutral stimuli. This process is critical in helping organisms guide attention toward the most salient and novel features in the environment. Here, we follow known circuit mechanisms in the fruit fly olfactory system to derive a simple algorithm for habituation. We show, both empirically and analytically, that this algorithm is able to filter out redundant information, enhance discrimination between odors that share a similar background, and improve detection of novel components in odor mixtures. Overall, we propose an algorithmic perspective on the biological mechanism of habituation and use this perspective to understand how sensory physiology can affect odor perception. Our framework may also help toward understanding the effects of habituation in other more sophisticated neural systems.
  • 关键词:habituation ; odor discrimination ; background subtraction ; systems neuroscience ; unsupervised algorithm
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