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Adaptation optimizes sensory encoding for future stimuli.

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  • المؤلفون: Mao J;Mao J; Rothkopf CA; Rothkopf CA; Stocker AA; Stocker AA
  • المصدر:
    PLoS computational biology [PLoS Comput Biol] 2025 Jan 17; Vol. 21 (1), pp. e1012746. Date of Electronic Publication: 2025 Jan 17 (Print Publication: 2025).
  • نوع النشر :
    Journal Article
  • اللغة:
    English
  • معلومة اضافية
    • المصدر:
      Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE
    • بيانات النشر:
      Original Publication: San Francisco, CA : Public Library of Science, [2005]-
    • الموضوع:
    • نبذة مختصرة :
      Competing Interests: The authors have declared that no competing interests exist.
      Sensory neurons continually adapt their response characteristics according to recent stimulus history. However, it is unclear how such a reactive process can benefit the organism. Here, we test the hypothesis that adaptation actually acts proactively in the sense that it optimally adjusts sensory encoding for future stimuli. We first quantified human subjects' ability to discriminate visual orientation under different adaptation conditions. Using an information theoretic analysis, we found that adaptation leads to a reallocation of coding resources such that encoding accuracy peaks at the mean orientation of the adaptor while total coding capacity remains constant. We then asked whether this characteristic change in encoding accuracy is predicted by the temporal statistics of natural visual input. Analyzing the retinal input of freely behaving human subjects showed that the distribution of local visual orientations in the retinal input stream indeed peaks at the mean orientation of the preceding input history (i.e., the adaptor). We further tested our hypothesis by analyzing the internal sensory representations of a recurrent neural network trained to predict the next frame of natural scene videos (PredNet). Simulating our human adaptation experiment with PredNet, we found that the network exhibited the same change in encoding accuracy as observed in human subjects. Taken together, our results suggest that adaptation-induced changes in encoding accuracy prepare the visual system for future stimuli.
      (Copyright: © 2025 Mao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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    • الموضوع:
      Date Created: 20250117 Date Completed: 20250127 Latest Revision: 20250130
    • الموضوع:
      20250130
    • الرقم المعرف:
      PMC11771873
    • الرقم المعرف:
      10.1371/journal.pcbi.1012746
    • الرقم المعرف:
      39823517