RT Journal Article
SR Electronic
T1 High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 763821
DO 10.1101/763821
A1 Lucy L. W. Owen
A1 Thomas H. Chang
A1 Jeremy R. Manning
YR 2021
UL http://biorxiv.org/content/early/2021/06/10/763821.abstract
AB 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 functional connectome that display homologous lower-level dynamic correlations. We tested the hypothesis that high-level cognition is reflected in 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 or listened to a temporally scrambled version of the story. 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 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 reflected in higher-order patterns of dynamic network interactions throughout the brain.Competing Interest StatementThe authors have declared no competing interest.