PLoS Computational Biology (Mar 2023)

Coding of object location by heterogeneous neural populations with spatially dependent correlations in weakly electric fish.

  • Myriah Haggard,
  • Maurice J Chacron

DOI
https://doi.org/10.1371/journal.pcbi.1010938
Journal volume & issue
Vol. 19, no. 3
p. e1010938

Abstract

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Understanding how neural populations encode sensory stimuli remains a central problem in neuroscience. Here we performed multi-unit recordings from sensory neural populations in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus in response to stimuli located at different positions along the rostro-caudal axis. Our results reveal that the spatial dependence of correlated activity along receptive fields can help mitigate the deleterious effects that these correlations would otherwise have if they were spatially independent. Moreover, using mathematical modeling, we show that experimentally observed heterogeneities in the receptive fields of neurons help optimize information transmission as to object location. Taken together, our results have important implications for understanding how sensory neurons whose receptive fields display antagonistic center-surround organization encode location. Important similarities between the electrosensory system and other sensory systems suggest that our results will be applicable elsewhere.