Feedback optimizes neural coding and perception of natural stimuli
Abstract
Growing evidence suggests that sensory neurons achieve optimal encoding by matching their tuning properties to the natural stimulus statistics. However, the underlying mechanisms remain unclear. Here we demonstrate that feedback pathways from higher brain areas mediate optimized encoding of naturalistic stimuli via temporal whitening in the weakly electric fish Apteronotus leptorhynchus. While one source of direct feedback uniformly enhances neural responses, a separate source of indirect feedback selectively attenuates responses to low frequencies, thus creating a high-pass neural tuning curve that opposes the decaying spectral power of natural stimuli. Additionally, we recorded from two populations of higher brain neurons responsible for the direct and indirect descending inputs. While one population displayed broadband tuning, the other displayed high-pass tuning and thus performed temporal whitening. Hence, our results demonstrate a novel function for descending input in optimizing neural responses to sensory input through temporal whitening that is likely to be conserved across systems and species.
Data availability
All data have been deposited on Figshare under the URL: https://figshare.com/s/b9e094a67a38e29212e8
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Figure source data for: Feedback optimizes neural coding and perception of natural stimulihttps://figshare.com/s/b9e094a67a38e29212e8.
Article and author information
Author details
Funding
Canadian Institutes of Health Research
- Maurice J Chacron
Fonds de Recherche du Québec - Nature et Technologies
- Maurice J Chacron
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All procedures were approved by McGill University's animal care committee and were performed in accordance to the guidelines set out by the Canadian Council of Animal Care. Protocol 5285.
Copyright
© 2018, Huang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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