Cognitive chimera states in human brain networks

被引:117
作者
Bansal, Kanika [1 ,2 ,3 ]
Garcia, Javier O. [1 ,4 ]
Tompson, Steven H. [1 ,4 ]
Verstynen, Timothy [5 ]
Vettel, Jean M. [1 ,4 ,6 ]
Muldoon, Sarah F. [3 ,7 ,8 ]
机构
[1] US Army, Res Lab, Human Res & Engn Directorate, Aberdeen Proving Ground, MD 21005 USA
[2] Columbia Univ, Dept Biomed Engn, New York, NY 10027 USA
[3] SUNY Buffalo, Math Dept, Buffalo, NY 14260 USA
[4] Univ Penn, Dept Biomed Engn, Philadelphia, PA 19104 USA
[5] Carnegie Mellon Univ, Dept Psychol, Pittsburgh, PA 15213 USA
[6] Univ Calif Santa Barbara, Dept Psychol & Brain Sci, Santa Barbara, CA 93106 USA
[7] SUNY Buffalo, CDSE Program, Buffalo, NY 14260 USA
[8] SUNY Buffalo, Neurosci Program, Buffalo, NY 14260 USA
来源
SCIENCE ADVANCES | 2019年 / 5卷 / 04期
关键词
FUNCTIONAL ARCHITECTURE; ORGANIZATION; CONNECTIVITY; POPULATIONS; CONNECTOME; DYNAMICS; MODEL;
D O I
10.1126/sciadv.aau8535
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The human brain is a complex dynamical system, and how cognition emerges from spatiotemporal patterns of regional brain activity remains an open question. As different regions dynamically interact to perform cognitive tasks, variable patterns of partial synchrony can be observed, forming chimera states. We propose that the spatial patterning of these states plays a fundamental role in the cognitive organization of the brain and present a cognitively informed, chimera-based framework to explore how large-scale brain architecture affects brain dynamics and function. Using personalized brain network models, we systematically study how regional brain stimulation produces different patterns of synchronization across predefined cognitive systems. We analyze these emergent patterns within our framework to understand the impact of subject-specific and region-specific structural variability on brain dynamics. Our results suggest a classification of cognitive systems into four groups with differing levels of subject and regional variability that reflect their different functional roles.
引用
收藏
页数:14
相关论文
共 56 条
[1]   Chimera states for coupled oscillators [J].
Abrams, DM ;
Strogatz, SH .
PHYSICAL REVIEW LETTERS, 2004, 93 (17) :174102-1
[2]   The Brain Activity Map Project and the Challenge of Functional Connectomics [J].
Alivisatos, A. Paul ;
Chun, Miyoung ;
Church, George M. ;
Greenspan, Ralph J. ;
Roukes, Michael L. ;
Yuste, Rafael .
NEURON, 2012, 74 (06) :970-974
[3]   All together now: Analogies between chimera state collapses and epileptic seizures [J].
Andrzejak, Ralph G. ;
Rummel, Christian ;
Mormann, Florian ;
Schindler, Kaspar .
SCIENTIFIC REPORTS, 2016, 6
[4]  
[Anonymous], ENEURO
[5]  
[Anonymous], GEN LOUVAIN METHOD C
[6]   Data-driven brain network models differentiate variability across language tasks [J].
Bansal, Kanika ;
Medaglia, John D. ;
Bassett, Danielle S. ;
Vettel, Jean M. ;
Muldoon, Sarah F. .
PLOS COMPUTATIONAL BIOLOGY, 2018, 14 (10)
[7]   Personalized brain network models for assessing structure-function relationships [J].
Bansal, Kanika ;
Nakuci, Johan ;
Muldoon, Sarah Feldt .
CURRENT OPINION IN NEUROBIOLOGY, 2018, 52 :42-47
[8]   Network neuroscience [J].
Bassett, Danielle S. ;
Sporns, Olaf .
NATURE NEUROSCIENCE, 2017, 20 (03) :353-364
[9]   Robust detection of dynamic community structure in networks [J].
Bassett, Danielle S. ;
Porter, Mason A. ;
Wymbs, Nicholas F. ;
Grafton, Scott T. ;
Carlson, Jean M. ;
Mucha, Peter J. .
CHAOS, 2013, 23 (01)
[10]   Chimera states in bursting neurons [J].
Bera, Bidesh K. ;
Ghosh, Dibakar ;
Lakshmanan, M. .
PHYSICAL REVIEW E, 2016, 93 (01)