Dynamic models of large-scale brain activity

Cognitive activity requires the collective behavior of cortical, thalamic and spinal neurons across large-scale systems of the CNS. This paper provides an illustrated introduction to dynamic models of large-scale brain activity, from the tenets of the underlying theory to challenges, controversies a...

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Published in	Nature neuroscience Vol. 20; no. 3; pp. 340 - 352
Main Author	Breakspear, Michael
Format	Journal Article
Language	English
Published	New York Nature Publishing Group US 01.03.2017 Nature Publishing Group
Subjects	59/36 631/114/2397 631/378/116/2393 Animal Genetics and Genomics Animals Behavioral Sciences Biological Techniques Biomedicine Brain - physiology Brain research Cognition - physiology Dynamical systems Humans Medical imaging Models, Neurological Movement - physiology Nerve Net - physiology Neurobiology Neuroimaging Neurons Neurons - physiology Neurophysiology Neurosciences review-article System theory Velocity United States Queensland Australia Australia
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Abstract	Cognitive activity requires the collective behavior of cortical, thalamic and spinal neurons across large-scale systems of the CNS. This paper provides an illustrated introduction to dynamic models of large-scale brain activity, from the tenets of the underlying theory to challenges, controversies and recent breakthroughs. Movement, cognition and perception arise from the collective activity of neurons within cortical circuits and across large-scale systems of the brain. While the causes of single neuron spikes have been understood for decades, the processes that support collective neural behavior in large-scale cortical systems are less clear and have been at times the subject of contention. Modeling large-scale brain activity with nonlinear dynamical systems theory allows the integration of experimental data from multiple modalities into a common framework that facilitates prediction, testing and possible refutation. This work reviews the core assumptions that underlie this computational approach, the methodological framework that fosters the translation of theory into the laboratory, and the emerging body of supporting evidence. While substantial challenges remain, evidence supports the view that collective, nonlinear dynamics are central to adaptive cortical activity. Likewise, aberrant dynamic processes appear to underlie a number of brain disorders.
AbstractList	Movement, cognition and perception arise from the collective activity of neurons within cortical circuits and across large-scale systems of the brain. While the causes of single neuron spikes have been understood for decades, the processes that support collective neural behavior in large-scale cortical systems are less clear and have been at times the subject of contention. Modeling large-scale brain activity with nonlinear dynamical systems theory allows the integration of experimental data from multiple modalities into a common framework that facilitates prediction, testing and possible refutation. This work reviews the core assumptions that underlie this computational approach, the methodological framework that fosters the translation of theory into the laboratory, and the emerging body of supporting evidence. While substantial challenges remain, evidence supports the view that collective, nonlinear dynamics are central to adaptive cortical activity. Likewise, aberrant dynamic processes appear to underlie a number of brain disorders. Cognitive activity requires the collective behavior of cortical, thalamic and spinal neurons across large-scale systems of the CNS. This paper provides an illustrated introduction to dynamic models of large-scale brain activity, from the tenets of the underlying theory to challenges, controversies and recent breakthroughs. Movement, cognition and perception arise from the collective activity of neurons within cortical circuits and across large-scale systems of the brain. While the causes of single neuron spikes have been understood for decades, the processes that support collective neural behavior in large-scale cortical systems are less clear and have been at times the subject of contention. Modeling large-scale brain activity with nonlinear dynamical systems theory allows the integration of experimental data from multiple modalities into a common framework that facilitates prediction, testing and possible refutation. This work reviews the core assumptions that underlie this computational approach, the methodological framework that fosters the translation of theory into the laboratory, and the emerging body of supporting evidence. While substantial challenges remain, evidence supports the view that collective, nonlinear dynamics are central to adaptive cortical activity. Likewise, aberrant dynamic processes appear to underlie a number of brain disorders.
Audience	Academic
Author	Breakspear, Michael
Author_xml	– sequence: 1 givenname: Michael surname: Breakspear fullname: Breakspear, Michael email: michael.breakspear@qimrberghofer.edu.au organization: QIMR Berghofer Medical Research Institute, Metro North Mental Health Service
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/28230845$$D View this record in MEDLINE/PubMed
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Copyright	Springer Nature America, Inc. 2017 COPYRIGHT 2017 Nature Publishing Group Copyright Nature Publishing Group Mar 2017
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7 Hoel, Albantakis, Tononi (CR3) 2013; 110 Chang, Glover (CR113) 2009; 47 Coombes (CR8) 2007; 76 Wilson, Cowan (CR22) 1972; 12 Jirsa, Stacey, Quilichini, Ivanov, Bernard (CR96) 2014; 137 Friston, Breakspear, Deco (CR106) 2012; 6 Rennie, Robinson, Wright (CR66) 2002; 86 Altenburg, Vermeulen, Strijers, Fetter, Stam (CR93) 2003; 114 CR99 CR10 Prichard, Theiler (CR88) 1994; 73 Honey, Kötter, Breakspear, Sporns (CR16) 2007; 104 Wolf, Swift, Swinney, Vastano (CR75) 1985; 16 Friston (CR40) 2010; 11 Breakspear, Williams, Stam (CR54) 2004; 16 Loh, Rolls, Deco (CR135) 2007; 3 Breakspear (CR128) 2003; 20 Deco, Jirsa (CR109) 2012; 32 Woolrich, Stephan (CR58) 2013; 80 Larter, Speelman, Worth (CR48) 1999; 9 Stephan, Friston, Frith (CR127) 2009; 35 Paluš (CR86) 1996; 75 CR25 Haken, Kelso, Bunz (CR27) 1985; 51 Zalesky, Breakspear (CR115) 2015; 114 Stefanescu, Jirsa (CR50) 2011; 83 Lopes da Silva (CR94) 2003; 44 Wagner (CR129) 2015; 66 Breakspear, Stam (CR55) 2005; 360 Henderson, Robinson (CR71) 2011; 107 Roberts, Iyer, Finnigan, Vanhatalo, Breakspear (CR12) 2014; 34 Babloyantz, Destexhe (CR81) 1986; 83 Theiler, Eubank, Longtin, Galdrikian, Doyne Farmer (CR87) 1992; 58 Miller, Brody, Romo, Wang (CR52) 2003; 13 CJ Rennie (BFnn4497_CR66) 2002; 86 BFnn4497_CR10 RJ Moran (BFnn4497_CR146) 2015; 40 LM Harrison (BFnn4497_CR38) 2005; 360 BFnn4497_CR99 I Bojak (BFnn4497_CR15) 2005; 71 F Freyer (BFnn4497_CR91) 2009; 29 KE Stephan (BFnn4497_CR132) 2016; 3 K Friston (BFnn4497_CR40) 2010; 11 P Miller (BFnn4497_CR52) 2003; 13 VT Nguyen (BFnn4497_CR114) 2016; 124 AJ Phillips (BFnn4497_CR14) 2007; 22 M Breakspear (BFnn4497_CR55) 2005; 360 P Grassberger (BFnn4497_CR76) 1983; 50 RA Gregson (BFnn4497_CR80) 1990; 31 M Rubinov (BFnn4497_CR143) 2011; 7 JA Roberts (BFnn4497_CR12) 2014; 34 N Leonardi (BFnn4497_CR116) 2015; 104 BFnn4497_CR25 R Larter (BFnn4497_CR48) 1999; 9 LL Gollo (BFnn4497_CR108) 2014; 369 N Friedman (BFnn4497_CR43) 2012; 108 VM Eguíluz (BFnn4497_CR142) 2005; 94 VK Jirsa (BFnn4497_CR96) 2014; 137 AA Faisal (BFnn4497_CR28) 2008; 9 F Freyer (BFnn4497_CR19) 2011; 31 BFnn4497_CR148 DT Liley (BFnn4497_CR125) 2013; 7 H Haken (BFnn4497_CR27) 1985; 51 M Breakspear (BFnn4497_CR128) 2003; 20 CJ Honey (BFnn4497_CR16) 2007; 104 RJ Moran (BFnn4497_CR74) 2007; 37 G Deco (BFnn4497_CR109) 2012; 32 MP Hyett (BFnn4497_CR130) 2015; 72 S El Boustani (BFnn4497_CR36) 2009; 21 K Friston (BFnn4497_CR106) 2012; 6 BFnn4497_CR140 BH Jansen (BFnn4497_CR45) 1995; 73 D Millman (BFnn4497_CR145) 2010; 6 D Rubino (BFnn4497_CR69) 2006; 9 PL Nunez (BFnn4497_CR62) 1974; 21 G Deco (BFnn4497_CR37) 2008; 4 G Wagner (BFnn4497_CR129) 2015; 66 BFnn4497_CR73 F Freyer (BFnn4497_CR31) 2012; 8 M Breakspear (BFnn4497_CR133) 2015; 138 T Petermann (BFnn4497_CR141) 2009; 106 S Coombes (BFnn4497_CR8) 2007; 76 CC Ruff (BFnn4497_CR137) 2006; 16 H Poincaré (BFnn4497_CR24) 1899; 10 I Tsuda (BFnn4497_CR110) 2001; 24 JD Murray (BFnn4497_CR136) 2014; 24 A Babloyantz (BFnn4497_CR79) 1985; 111 A Omurtag (BFnn4497_CR34) 2000; 8 KE Stephan (BFnn4497_CR56) 2001; 356 M Breakspear (BFnn4497_CR11) 2006; 16 JA Henderson (BFnn4497_CR71) 2011; 107 A Wolf (BFnn4497_CR75) 1985; 16 PA Robinson (BFnn4497_CR67) 2016; 142 VK Jirsa (BFnn4497_CR26) 2010; 148 KE Stephan (BFnn4497_CR131) 2015; 87 WS Pritchard (BFnn4497_CR85) 1995; 32 PA Robinson (BFnn4497_CR7) 1997; 56 S Amari (BFnn4497_CR61) 1977; 27 A Levina (BFnn4497_CR144) 2007; 3 I Bojak (BFnn4497_CR13) 2015; 9 JA Roberts (BFnn4497_CR44) 2015; 31 BFnn4497_CR134 VK Jirsa (BFnn4497_CR51) 2011; 73 H Bruns (BFnn4497_CR23) 1887; 11 J Theiler (BFnn4497_CR82) 1986; 34 AC Marreiros (BFnn4497_CR47) 2008; 42 AR Osborne (BFnn4497_CR83) 1989; 35 KE Stephan (BFnn4497_CR127) 2009; 35 J Daunizeau (BFnn4497_CR21) 2012; 62 WJ Ma (BFnn4497_CR39) 2006; 9 AL Hodgkin (BFnn4497_CR1) 1952; 140 VK Jirsa (BFnn4497_CR6) 1996; 77 RA Stefanescu (BFnn4497_CR50) 2011; 83 JF Mejias (BFnn4497_CR59) 2016; 2 K-F Wong (BFnn4497_CR53) 2006; 26 M Breakspear (BFnn4497_CR54) 2004; 16 PA Robinson (BFnn4497_CR64) 2006; 73 KJ Friston (BFnn4497_CR100) 2003; 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Snippet	Cognitive activity requires the collective behavior of cortical, thalamic and spinal neurons across large-scale systems of the CNS. This paper provides an... Movement, cognition and perception arise from the collective activity of neurons within cortical circuits and across large-scale systems of the brain. While...
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SubjectTerms	59/36 631/114/2397 631/378/116/2393 Animal Genetics and Genomics Animals Behavioral Sciences Biological Techniques Biomedicine Brain - physiology Brain research Cognition - physiology Dynamical systems Humans Medical imaging Models, Neurological Movement - physiology Nerve Net - physiology Neurobiology Neuroimaging Neurons Neurons - physiology Neurophysiology Neurosciences review-article System theory Velocity
Title	Dynamic models of large-scale brain activity
URI	https://link.springer.com/article/10.1038/nn.4497 https://www.ncbi.nlm.nih.gov/pubmed/28230845 https://www.proquest.com/docview/1891851539 https://www.proquest.com/docview/1871550342 https://www.proquest.com/docview/1897378651
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