Regional activity and interregional functional connectivity uniquely contribute to social cognitive judgments during movie-watching.
The 1 match
- [1] § ANALYTIC APPROACH › Individual-Level Analysis: Linear Model Construction ↔ level1/stepwise_ver/ets_sub_linreg_prewhiten_stepwise.py, lines 79–128 · score 0.75 · fit autoregressive models, statsmodels, residuals, squares, prewhitening, ij
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Python · 293 lines · 7.6 KB · no license · 1 match
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Overview
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Department of Informatics & Program in Cognitive Science, Indiana University, Bloomington, IN, USA
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
Abstract
Understanding how the brain gives rise to social cognition has been a key goal of neuroimaging research. Both changes in regional activation as well as functional connectivity have been implicated as potential mechanisms underlying social cognition, but the two have rarely been examined concurrently. Moreover, because the neural processes underlying social cognition are dynamic, developing approaches to capture dynamic changes in regional activity and functional connectivity are critical. Here, we describe a novel analysis approach that captures both regional activity and dynamic functional connectivity simultaneously during a naturalistic, socially focused movie-watching task. We found that both regional activation and functional connectivity were uniquely related to awkwardness, a judgment associated with social faux pas detection and theory of mind. Regional activation within sensorimotor networks was positively associated with awkwardness, whereas activation in the default network was negatively associated. Models including functional connectivity accounted for unique variance beyond models with activity alone. Specifically, dynamic functional connectivity between networks, primarily the frontoparietal control network, was positively associated with awkwardness. Together, these findings suggest that both dynamic regional brain activity and functional connectivity each uniquely contribute to complex and dynamic social judgments.
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OSF 8bvu9
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rcf004/edge-timeseries-linear-interaction
cbb342dd19c1b76b63f294a3823a30a65ec06234, 21 July 2025Availability: 1 check, the latest on 27 September 2026: the link answers
- 27 September 2026: the link answers
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non_prewhitened_ver/ — Python, 124 lines, shown from its sourceets_sub_linreg_noprewhit en.py - level1/
non_prewhitened_ver/ — Shell, 13 lines, shown from its sourcesublevel_linreg.sh - level1/
non_prewhitened_ver/ — Shell, 35 lines, shown from its sourcesubmit_sub_linreg.sh - level1/
prewhitened_ver/ — Python, 213 lines, shown from its sourceets_sub_linreg_prewhiten .py - level1/
prewhitened_ver/ — Shell, 14 lines, shown from its sourcesublevel_linreg.sh - level1/
prewhitened_ver/ — Shell, 37 lines, shown from its sourcesubmit_sub_linreg.sh - level1/
regprep.py — Python, 129 lines, shown from its source - level1/
stepwise_ver/ — Python, 293 lines, 1 match, shown from its sourceets_sub_linreg_prewhiten _stepwise.py - level1/
stepwise_ver/ — Shell, 14 lines, shown from its sourcesublevel_linreg.sh - level1/
stepwise_ver/ — Shell, 35 lines, shown from its sourcesubmit_sub_linreg.sh - level2/
non_prewhitened_ver/ — Python, 402 lines, shown from its sourcemat_manip.py - level2/
non_prewhitened_ver/ — Python, 74 lines, shown from its sourceoutput_driver_no-prewhit en.py - level2/
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prewhitened_ver/ — Python, 402 lines, shown from its sourcemat_manip.py - level2/
prewhitened_ver/ — Python, 171 lines, shown from its sourceoutput_driver.py - level2/
prewhitened_ver/ — Python, 178 lines, shown from its sourceplotting_funcs.py - level2/
prewhitened_ver/ — Python, 381 lines, shown from its sourcetermpull.py - level2/
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stepwise_ver/ — Python, 106 lines, shown from its sourceoutput_driver_stepwise.p y - level2/
stepwise_ver/ — Python, 178 lines, shown from its sourceplotting_funcs.py - level2/
stepwise_ver/ — Python, 439 lines, shown from its sourcetermpull_stepwise.py - README.md — Text, 17 lines, shown from its source
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This paper
French, R. C., Merritt, H., Hughes, C., Betzel, R., & Krendl, A. C. (2026). Regional activity and interregional functional connectivity uniquely contribute to social cognitive judgments during movie-watching. Network neuroscience (Cambridge, Mass.), 10(3), 738-760. https://
BibTeX
@article{french2026regio
author = {French, Roberto C and Merritt, Haily and Hughes, Colleen and Betzel, Richard and Krendl, Anne C},
title = {{Regional activity and interregional functional connectivity uniquely contribute to social cognitive judgments during movie-watching}},
journal = {Network neuroscience (Cambridge, Mass.)},
year = {2026},
month = jul,
volume = {10},
number = {3},
pages = {738--760},
publisher = {MIT Press},
issn = {2472-1751},
doi = {10.1162/
url = {https://
pmid = {42529782},
pmcid = {PMC13418520}
}
RIS
TY - JOUR
AU - French, Roberto C
AU - Merritt, Haily
AU - Hughes, Colleen
AU - Betzel, Richard
AU - Krendl, Anne C
TI - Regional activity and interregional functional connectivity uniquely contribute to social cognitive judgments during movie-watching
T2 - Network neuroscience (Cambridge, Mass.)
J2 - Netw Neurosci
PY - 2026
DA - 2026/
VL - 10
IS - 3
SP - 738
EP - 760
SN - 2472-1751
PB - MIT Press
DO - 10.1162/
UR - https://
LA - en
ER -
CSL-JSON
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