TY - JOUR
T1 - The Dynamics of Functional Brain Networks
T2 - Integrated Network States during Cognitive Task Performance
AU - Shine, James M.
AU - Bissett, Patrick G.
AU - Bell, Peter T.
AU - Koyejo, Oluwasanmi
AU - Balsters, Joshua H.
AU - Gorgolewski, Krzysztof J.
AU - Moodie, Craig A.
AU - Poldrack, Russell A.
N1 - Funding Information:
The data reported in this paper were made publicly available by the HCP and 1000 Functional Connectomes project. We would like to thank Vanessa Sochat for her assistance with implementation; Peter Murphy, Redmond O’Connell, and Ian Robertson for their work collecting and analyzing the data used for the pupillometry analysis; Jamie Li for help with data analysis; Michael Riis and Ian Eisenberg for their insights; and Timothy Laumann, Claire O’Callaghan, Rick Shine, and Gaurav Suri for their critical review of the manuscript. This work was supported by NeuroVentures, which was sponsored by BIoX and the Stanford Neurosciences Institute, as well as fellowships from the National Health and Medical Research Council (GNT1072403 to J.M.S.) and the National Institute of Drug Administration (F32DA041773 to P.G.B.).
Publisher Copyright:
© 2016
PY - 2016/10/19
Y1 - 2016/10/19
N2 - Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.
AB - Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.
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U2 - 10.1016/j.neuron.2016.09.018
DO - 10.1016/j.neuron.2016.09.018
M3 - Article
C2 - 27693256
AN - SCOPUS:84992378782
SN - 0896-6273
VL - 92
SP - 544
EP - 554
JO - Neuron
JF - Neuron
IS - 2
ER -