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Differentially synchronized spiking enables multiplexed neural coding

Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural sc...

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Autores principales: Lankarany, Milad, Al-Basha, Dhekra, Ratté, Stéphanie, Prescott, Steven A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525513/
https://www.ncbi.nlm.nih.gov/pubmed/31028148
http://dx.doi.org/10.1073/pnas.1812171116
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author Lankarany, Milad
Al-Basha, Dhekra
Ratté, Stéphanie
Prescott, Steven A.
author_facet Lankarany, Milad
Al-Basha, Dhekra
Ratté, Stéphanie
Prescott, Steven A.
author_sort Lankarany, Milad
collection PubMed
description Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high-contrast features. We refer to this strategy as synchrony-division multiplexing.
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spelling pubmed-65255132019-05-28 Differentially synchronized spiking enables multiplexed neural coding Lankarany, Milad Al-Basha, Dhekra Ratté, Stéphanie Prescott, Steven A. Proc Natl Acad Sci U S A Biological Sciences Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high-contrast features. We refer to this strategy as synchrony-division multiplexing. National Academy of Sciences 2019-05-14 2019-04-26 /pmc/articles/PMC6525513/ /pubmed/31028148 http://dx.doi.org/10.1073/pnas.1812171116 Text en Copyright © 2019 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Lankarany, Milad
Al-Basha, Dhekra
Ratté, Stéphanie
Prescott, Steven A.
Differentially synchronized spiking enables multiplexed neural coding
title Differentially synchronized spiking enables multiplexed neural coding
title_full Differentially synchronized spiking enables multiplexed neural coding
title_fullStr Differentially synchronized spiking enables multiplexed neural coding
title_full_unstemmed Differentially synchronized spiking enables multiplexed neural coding
title_short Differentially synchronized spiking enables multiplexed neural coding
title_sort differentially synchronized spiking enables multiplexed neural coding
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525513/
https://www.ncbi.nlm.nih.gov/pubmed/31028148
http://dx.doi.org/10.1073/pnas.1812171116
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