The dynamic modular fingerprints of the human brain at rest
Author:
Kabbara Aya, Paban Veronique, Hassan MahmoudORCID
Abstract
AbstractThe human brain is a dynamic modular network that can be decomposed into a set of modules and its activity changes permanently over time. At rest, several brain networks, known as Resting-State Networks (RSNs), emerge and cross-communicate even at sub-second temporal scale. Here, we seek to decipher the fast reshaping in spontaneous brain modularity and its relationship to RSNs. We use Electro/Magneto-Encephalography (EEG/MEG) to track dynamics of modular brain networks, in three independent datasets (N= 568) of healthy subjects at rest. We show the presence of striking spatiotemporal network pattern consistent over participants. We also show that some RSNs, such as default mode network and temporal network, are not necessary ‘unified units’ but rather can be divided into multiple sub-networks over time. Using the resting state questionnaire, our results revealed also that brain network dynamics are strongly correlated to mental imagery at rest. These findings add new perspectives to brain dynamic analysis and highlight the importance of tracking fast reconfiguration of electrophysiological networks at rest.
Publisher
Cold Spring Harbor Laboratory
Reference91 articles.
1. Alexander, L.M. , Escalera, J. , Ai, L. , Andreotti, C. , Febre, K. , Mangone, A. , Vega-Potler, N. , Langer, N. , Alexander, A. , Kovacs, M. , Litke, S. , O’Hagan, B. , Andersen, J. , Bronstein, B. , Bui, A. , Bushey, M. , Butler, H. , Castagna, V. , Camacho, N. , Chan, E. , Citera, D. , Clucas, J. , Cohen, S. , Dufek, S. , Eaves, M. , Fradera, B. , Gardner, J. , Grant-Villegas, N. , Green, G. , Gregory, C. , Hart, E. , Harris, S. , Horton, M. , Kahn, D. , Kabotyanski, K. , Karmel, B. , Kelly, S.P. , Kleinman, K. , Koo, B. , Kramer, E. , Lennon, E. , Lord, C. , Mantello, G. , Margolis, A. , Merikangas, K.R. , Milham, J. , Minniti, G. , Neuhaus, R. , Levine, A. , Osman, Y. , Parra, L.C. , Pugh, K.R. , Racanello, A. , Restrepo, A. , Saltzman, T. , Septimus, B. , Tobe, R. , Waltz, R. , Williams, A. , Yeo, A. , Castellanos, F.X. , Klein, A. , Paus, T. , Leventhal, B.L. , Craddock, R.C. , Koplewicz, H.S. , Milham, M.P. , 2017. Data Descriptor: An open resource for transdiagnostic research in pediatric mental health and learning disorders. Sci. Data. https://doi.org/10.1038/sdata.2017.181 2. Tracking Whole-Brain Connectivity Dynamics in the Resting State 3. Andrews-Hanna, J.R. , Snyder, A.Z. , Vincent, J.L. , Lustig, C. , Head, D. , Raichle, M.E. , Buckner, R.L. , 2007. Disruption of large-scale brain systems in advanced aging. Neuron. https://doi.org/10.1016/j.neuron.2007.10.038 4. Baker, A.P. , Brookes, M.J. , Rezek, I.A. , Smith, S.M. , Behrens, T. , Smith, P.J.P. , Woolrich, M. , 2014. Fast transient networks in spontaneous human brain activity. Elife 2014. https://doi.org/10.7554/eLife.01867 5. Bassett, D.S. , Porter, M.A. , Wymbs, N.F. , Grafton, S.T. , Carlson, J.M. , Mucha, P.J. , 2013. Robust detection of dynamic community structure in networks. Chaos 23. https://doi.org/10.1063/1.4790830
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|