Constructing and Forgetting Temporal Context in the Human Cerebral Cortex
How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We...
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Published in | Neuron (Cambridge, Mass.) Vol. 106; no. 4; pp. 675 - 686.e11 |
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20.05.2020
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Abstract | How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions that are slower to integrate new information should also be slower to forget old information. However, we found that higher-order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error.
•Distinct cortical responses when the same stimulus is preceded by different contexts•Responses align as common input continues: sensory cortex, then higher-order cortex•Cortical regions maintain a distributed and hierarchical representation of context•Distributed cortical memory is gated and prior context can be flexibly forgotten
Chien and Honey measured how sequential information in a spoken narrative is integrated and separated in the human cerebral cortex. They observed a hierarchical representation of temporal context, distributed across the cortex. Computational modeling suggests the distributed context representation is flexibly updated or reset based on surprise. |
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AbstractList | How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions that are slower to integrate new information should also be slower to forget old information. However, we found that higher-order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error. How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different, but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions which are slower to integrate new information should also be slower to forget old information. However, we found that higher order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error. Chien and Honey measured how information in a spoken narrative is integrated and separated in the human cerebral cortex. They observed a hierarchical representation of temporal context, distributed across the cortex. Computational modeling suggests the distributed context is flexibly updated or reset based on surprise. SummaryHow does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions that are slower to integrate new information should also be slower to forget old information. However, we found that higher-order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error. How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions that are slower to integrate new information should also be slower to forget old information. However, we found that higher-order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error. •Distinct cortical responses when the same stimulus is preceded by different contexts•Responses align as common input continues: sensory cortex, then higher-order cortex•Cortical regions maintain a distributed and hierarchical representation of context•Distributed cortical memory is gated and prior context can be flexibly forgotten Chien and Honey measured how sequential information in a spoken narrative is integrated and separated in the human cerebral cortex. They observed a hierarchical representation of temporal context, distributed across the cortex. Computational modeling suggests the distributed context representation is flexibly updated or reset based on surprise. How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions that are slower to integrate new information should also be slower to forget old information. However, we found that higher-order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error.How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions that are slower to integrate new information should also be slower to forget old information. However, we found that higher-order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error. |
Author | Chien, Hsiang-Yun Sherry Honey, Christopher J. |
AuthorAffiliation | 2 Lead Contact 1 Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA |
AuthorAffiliation_xml | – name: 1 Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA – name: 2 Lead Contact |
Author_xml | – sequence: 1 givenname: Hsiang-Yun Sherry surname: Chien fullname: Chien, Hsiang-Yun Sherry organization: Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA – sequence: 2 givenname: Christopher J. orcidid: 0000-0002-0745-5089 surname: Honey fullname: Honey, Christopher J. email: chris.honey@jhu.edu organization: Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32164874$$D View this record in MEDLINE/PubMed |
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Keywords | event boundary fMRI temporal integration hierarchy inter-subject correlation temporal context timescales prediction error computational modeling sequence processing |
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Snippet | How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a... SummaryHow does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same... |
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SubjectTerms | Adolescent Adult Brain Cerebral cortex Cerebral Cortex - physiology Cognition - physiology computational modeling Cortex (somatosensory) Cortex (temporal) Echo-Planar Imaging event boundary Female fMRI hierarchy Humans Information processing Integration inter-subject correlation Male Memory - physiology Models, Neurological prediction error Quantitative psychology sequence processing temporal context temporal integration Time timescales Young Adult |
Title | Constructing and Forgetting Temporal Context in the Human Cerebral Cortex |
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