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High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns

Lucy L. W. Owen, Thomas H. Chang, View ORCID ProfileJeremy R. Manning
doi: https://doi.org/10.1101/763821
Lucy L. W. Owen
1Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH
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Thomas H. Chang
1Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH
2Amazon.com, Seattle, WA
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Jeremy R. Manning
1Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH
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  • ORCID record for Jeremy R. Manning
  • For correspondence: jeremy.r.manning@dartmouth.edu
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Abstract

Our thoughts arise from coordinated patterns of interactions between brain structures that change with our ongoing experiences. High-order dynamic correlations in neural activity patterns reflect different subgraphs of the brain’s connectome that display homologous lower-level dynamic correlations. We tested the hypothesis that high-level cognition is supported by high-order dynamic correlations in brain activity patterns. We developed an approach to estimating high-order dynamic correlations in timeseries data, and we applied the approach to neuroimaging data collected as human participants either listened to a ten-minute story, listened to a temporally scrambled version of the story, or underwent a resting state scan. We trained across-participant pattern classifiers to decode (in held-out data) when in the session each neural activity snapshot was collected. We found that classifiers trained to decode from high-order dynamic correlations yielded the best performance on data collected as participants listened to the (unscrambled) story. By contrast, classifiers trained to decode data from scrambled versions of the story or during the resting state scan yielded the best performance when they were trained using first-order dynamic correlations or non-correlational activity patterns. We suggest that as our thoughts become more complex, they are supported by higher-order patterns of dynamic network interactions throughout the brain.

Footnotes

  • https://github.com/ContextLab/timecorr-paper

  • https://timecorr.readthedocs.io

Copyright 
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.
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Posted September 10, 2019.
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High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns
Lucy L. W. Owen, Thomas H. Chang, Jeremy R. Manning
bioRxiv 763821; doi: https://doi.org/10.1101/763821
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High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns
Lucy L. W. Owen, Thomas H. Chang, Jeremy R. Manning
bioRxiv 763821; doi: https://doi.org/10.1101/763821

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