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Optimal Sensory Coding By Populations Of ON And OFF Neurons

Gjorgjieva, Julijana and Meister, Markus and Sompolinsky, Haim (2017) Optimal Sensory Coding By Populations Of ON And OFF Neurons. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20181030-105013410

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Abstract

In many sensory systems the neural signal is coded by multiple parallel pathways, suggesting an evolutionary fitness benefit of general nature. A common pathway splitting is that into ON and OFF cells, responding to stimulus increments and decrements, respectively. According to efficient coding theory, sensory neurons have evolved to an optimal configuration for maximizing information transfer given the structure of natural stimuli and circuit constraints. Using the efficient coding framework, we describe two aspects of neural coding: how to optimally split a population into ON and OFF pathways, and how to allocate the firing thresholds of individual neurons given realistic noise levels, stimulus distributions and optimality measures. We find that populations of ON and OFF neurons convey equal information about the stimulus regardless of the ON/OFF mixture, once the thresholds are chosen optimally, independent of stimulus statistics and noise. However, an equal ON/OFF mixture is the most efficient as it uses the fewest spikes to convey this information. The optimal thresholds and coding efficiency, however, depend on noise and stimulus statistics if information is decoded by an optimal linear readout. With non-negligible noise, mixed ON/OFF populations reap significant advantages compared to a homogeneous population. The best coding performance is achieved by a unique mixture of ON/OFF neurons tuned to stimulus asymmetries and noise. We provide a theory for how different cell types work together to encode the full stimulus range using a diversity of response thresholds. The optimal ON/OFF mixtures derived from the theory accord with certain biases observed experimentally.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/131946DOIDiscussion Paper
ORCID:
AuthorORCID
Gjorgjieva, Julijana0000-0001-7118-4079
Meister, Markus0000-0003-2136-6506
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license. JG was supported by the Max Planck Society and a Burroughs-Wellcome Career Award at the Scientific Interface. All authors were supported by the NIH, the Gatsby Charitable Foundation and the Swartz Foundation.
Funders:
Funding AgencyGrant Number
Max Planck SocietyUNSPECIFIED
Burroughs Wellcome FundUNSPECIFIED
NIHUNSPECIFIED
Gatsby Charitable FoundationUNSPECIFIED
Swartz FoundationUNSPECIFIED
Record Number:CaltechAUTHORS:20181030-105013410
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20181030-105013410
Official Citation:Optimal Sensory Coding By Populations Of ON And OFF Neurons Julijana Gjorgjieva, Markus Meister, Haim Sompolinsky bioRxiv 131946; doi: https://doi.org/10.1101/131946
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90498
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:30 Oct 2018 20:09
Last Modified:03 Oct 2019 20:25

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