Neural oscillations as a signature of efficient coding in the presence of synaptic delays
Cortical networks exhibit 'global oscillations', in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterise...
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doaj-cd6073cc95cb4283b2c5881e4da1ff6c2021-05-05T00:28:27ZengeLife Sciences Publications LtdeLife2050-084X2016-07-01510.7554/eLife.13824Neural oscillations as a signature of efficient coding in the presence of synaptic delaysMatthew Chalk0https://orcid.org/0000-0001-7782-4436Boris Gutkin1Sophie Denève2Institute of Science and Technology Austria, Klosterneuburg, AustriaÉcole Normale Supérieure, Paris, France; Center for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, RussiaÉcole Normale Supérieure, Paris, FranceCortical networks exhibit 'global oscillations', in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays and noise. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a 'prediction error' while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code.https://elifesciences.org/articles/13824neural oscillationsneural codingcomputational neuroscience |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Matthew Chalk Boris Gutkin Sophie Denève |
spellingShingle |
Matthew Chalk Boris Gutkin Sophie Denève Neural oscillations as a signature of efficient coding in the presence of synaptic delays eLife neural oscillations neural coding computational neuroscience |
author_facet |
Matthew Chalk Boris Gutkin Sophie Denève |
author_sort |
Matthew Chalk |
title |
Neural oscillations as a signature of efficient coding in the presence of synaptic delays |
title_short |
Neural oscillations as a signature of efficient coding in the presence of synaptic delays |
title_full |
Neural oscillations as a signature of efficient coding in the presence of synaptic delays |
title_fullStr |
Neural oscillations as a signature of efficient coding in the presence of synaptic delays |
title_full_unstemmed |
Neural oscillations as a signature of efficient coding in the presence of synaptic delays |
title_sort |
neural oscillations as a signature of efficient coding in the presence of synaptic delays |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2016-07-01 |
description |
Cortical networks exhibit 'global oscillations', in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays and noise. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a 'prediction error' while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code. |
topic |
neural oscillations neural coding computational neuroscience |
url |
https://elifesciences.org/articles/13824 |
work_keys_str_mv |
AT matthewchalk neuraloscillationsasasignatureofefficientcodinginthepresenceofsynapticdelays AT borisgutkin neuraloscillationsasasignatureofefficientcodinginthepresenceofsynapticdelays AT sophiedeneve neuraloscillationsasasignatureofefficientcodinginthepresenceofsynapticdelays |
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