A Diversity of Intrinsic Timescales Underlie Neural Computations

Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of...

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Published in:Frontiers in neural circuits Vol. 14; p. 615626
Main Authors: Cavanagh, Sean E., Hunt, Laurence T., Kennerley, Steven W.
Format: Journal Article
Language:English
Published: Switzerland Frontiers Research Foundation 21.12.2020
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ISSN:1662-5110, 1662-5110
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Abstract Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of these representations allows animals to behave adaptively. Short temporal windows facilitate adaptive responding in dynamic environments, while longer temporal windows promote the gradual integration of information across time. In the cognitive and motor domains, the brain sets overarching goals to be achieved within a long temporal window, which must be broken down into sequences of actions and precise movement control processed across much shorter temporal windows. Previous human neuroimaging studies and large-scale artificial network models have ascribed different processing timescales to different cortical regions, linking this to each region’s position in an anatomical hierarchy determined by patterns of inter-regional connectivity. However, even within cortical regions, there is variability in responses when studied with single-neuron electrophysiology. Here, we review a series of recent electrophysiology experiments that demonstrate the heterogeneity of temporal receptive fields at the level of single neurons within a cortical region. This heterogeneity appears functionally relevant for the computations that neurons perform during decision-making and working memory. We consider anatomical and biophysical mechanisms that may give rise to a heterogeneity of timescales, including recurrent connectivity, cortical layer distribution, and neurotransmitter receptor expression. Finally, we reflect on the computational relevance of each brain region possessing a heterogeneity of neuronal timescales. We argue that this architecture is of particular importance for sensory, motor, and cognitive computations.
AbstractList Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of these representations allows animals to behave adaptively. Short temporal windows facilitate adaptive responding in dynamic environments, while longer temporal windows promote the gradual integration of information across time. In the cognitive and motor domains, the brain sets overarching goals to be achieved within a long temporal window, which must be broken down into sequences of actions and precise movement control processed across much shorter temporal windows. Previous human neuroimaging studies and large-scale artificial network models have ascribed different processing timescales to different cortical regions, linking this to each region’s position in an anatomical hierarchy determined by patterns of inter-regional connectivity. However, even within cortical regions, there is variability in responses when studied with single-neuron electrophysiology. Here, we review a series of recent electrophysiology experiments that demonstrate the heterogeneity of temporal receptive fields at the level of single neurons within a cortical region. This heterogeneity appears functionally relevant for the computations that neurons perform during decision-making and working memory. We consider anatomical and biophysical mechanisms that may give rise to a heterogeneity of timescales, including recurrent connectivity, cortical layer distribution, and neurotransmitter receptor expression. Finally, we reflect on the computational relevance of each brain region possessing a heterogeneity of neuronal timescales. We argue that this architecture is of particular importance for sensory, motor, and cognitive computations.
Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of these representations allows animals to behave adaptively. Short temporal windows facilitate adaptive responding in dynamic environments, while longer temporal windows promote the gradual integration of information across time. In the cognitive and motor domains, the brain sets overarching goals to be achieved within a long temporal window, which must be broken down into sequences of actions and precise movement control processed across much shorter temporal windows. Previous human neuroimaging studies and large-scale artificial network models have ascribed different processing timescales to different cortical regions, linking this to each region’s position in an anatomical hierarchy determined by patterns of inter-regional connectivity. However, even within cortical regions, there is variability in responses when studied with single neuron electrophysiology. Here, we review a series of recent electrophysiology experiments that demonstrate a heterogeneity of temporal receptive fields at the level of single neurons within a cortical region. This heterogeneity appears functionally relevant for the computations that neurons perform during decision-making and working memory. We consider anatomical and biophysical mechanisms which may give rise to a heterogeneity of timescales, including recurrent connectivity, cortical layer distribution, and neurotransmitter receptor expression. Finally, we reflect on the computational relevance of each brain region possessing a heterogeneity of neuronal timescales. We argue that this architecture is of particular importance for sensory, motor, and cognitive computations.
Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of these representations allows animals to behave adaptively. Short temporal windows facilitate adaptive responding in dynamic environments, while longer temporal windows promote the gradual integration of information across time. In the cognitive and motor domains, the brain sets overarching goals to be achieved within a long temporal window, which must be broken down into sequences of actions and precise movement control processed across much shorter temporal windows. Previous human neuroimaging studies and large-scale artificial network models have ascribed different processing timescales to different cortical regions, linking this to each region's position in an anatomical hierarchy determined by patterns of inter-regional connectivity. However, even within cortical regions, there is variability in responses when studied with single-neuron electrophysiology. Here, we review a series of recent electrophysiology experiments that demonstrate the heterogeneity of temporal receptive fields at the level of single neurons within a cortical region. This heterogeneity appears functionally relevant for the computations that neurons perform during decision-making and working memory. We consider anatomical and biophysical mechanisms that may give rise to a heterogeneity of timescales, including recurrent connectivity, cortical layer distribution, and neurotransmitter receptor expression. Finally, we reflect on the computational relevance of each brain region possessing a heterogeneity of neuronal timescales. We argue that this architecture is of particular importance for sensory, motor, and cognitive computations.Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of these representations allows animals to behave adaptively. Short temporal windows facilitate adaptive responding in dynamic environments, while longer temporal windows promote the gradual integration of information across time. In the cognitive and motor domains, the brain sets overarching goals to be achieved within a long temporal window, which must be broken down into sequences of actions and precise movement control processed across much shorter temporal windows. Previous human neuroimaging studies and large-scale artificial network models have ascribed different processing timescales to different cortical regions, linking this to each region's position in an anatomical hierarchy determined by patterns of inter-regional connectivity. However, even within cortical regions, there is variability in responses when studied with single-neuron electrophysiology. Here, we review a series of recent electrophysiology experiments that demonstrate the heterogeneity of temporal receptive fields at the level of single neurons within a cortical region. This heterogeneity appears functionally relevant for the computations that neurons perform during decision-making and working memory. We consider anatomical and biophysical mechanisms that may give rise to a heterogeneity of timescales, including recurrent connectivity, cortical layer distribution, and neurotransmitter receptor expression. Finally, we reflect on the computational relevance of each brain region possessing a heterogeneity of neuronal timescales. We argue that this architecture is of particular importance for sensory, motor, and cognitive computations.
Author Cavanagh, Sean E.
Hunt, Laurence T.
Kennerley, Steven W.
AuthorAffiliation 2 Wellcome Trust Centre for Neuroimaging, University College London , London , United Kingdom
4 Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, University of Oxford , Oxford , United Kingdom
3 Max Planck-UCL Centre for Computational Psychiatry and Aging, University College London , London , United Kingdom
1 Department of Clinical and Movement Neurosciences, University College London , London , United Kingdom
AuthorAffiliation_xml – name: 3 Max Planck-UCL Centre for Computational Psychiatry and Aging, University College London , London , United Kingdom
– name: 1 Department of Clinical and Movement Neurosciences, University College London , London , United Kingdom
– name: 4 Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, University of Oxford , Oxford , United Kingdom
– name: 2 Wellcome Trust Centre for Neuroimaging, University College London , London , United Kingdom
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Copyright © 2020 Cavanagh, Hunt and Kennerley. 2020 Cavanagh, Hunt and Kennerley
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Keywords time constant
decision-making
working memory
neuronal timescale
autocorrelation
Language English
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These authors have contributed equally to this work
Reviewed by: Ken-ichi Amemori, Kyoto University, Japan; Timothy D. Hanks, University of California, Davis, United States
Edited by: Emmanuel Procyk, Institut National de la Santé et de la Recherche Médicale (INSERM), France
OpenAccessLink https://www.proquest.com/docview/2471583014?pq-origsite=%requestingapplication%
PMID 33408616
PQID 2471583014
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pubmed_primary_33408616
crossref_citationtrail_10_3389_fncir_2020_615626
crossref_primary_10_3389_fncir_2020_615626
PublicationCentury 2000
PublicationDate 2020-12-21
PublicationDateYYYYMMDD 2020-12-21
PublicationDate_xml – month: 12
  year: 2020
  text: 2020-12-21
  day: 21
PublicationDecade 2020
PublicationPlace Switzerland
PublicationPlace_xml – name: Switzerland
– name: Lausanne
PublicationTitle Frontiers in neural circuits
PublicationTitleAlternate Front Neural Circuits
PublicationYear 2020
Publisher Frontiers Research Foundation
Frontiers Media S.A
Publisher_xml – name: Frontiers Research Foundation
– name: Frontiers Media S.A
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SubjectTerms Animals
autocorrelation
Brain - physiology
Brain research
Cerebral Cortex - physiology
Cognitive ability
Computational neuroscience
Decision making
Electrophysiology
Humans
Information processing
Listening
Medical imaging
Memory, Short-Term - physiology
Nerve Net - physiology
Neural networks
Neural Pathways - physiology
Neuroimaging
neuronal timescale
Neurons
Neurons - physiology
Neuroscience
Short term memory
time constant
working memory
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