Capturing the non-stationarity of whole-brain dynamics underlying human brain states
J.A. Galadí,
S. Silva Pereira,
Y. Sanz Perl,
M.L. Kringelbach,
I. Gayte,
H. Laufs,
E. Tagliazucchi,
J.A. Langa,
G. Deco
Affiliations
J.A. Galadí
Corresponding author at: Departamento de Ecuaciones Diferenciales y Análisis Numérico, Universidad de Sevilla, Spain.; Departamento de Ecuaciones Diferenciales y Análisis Numérico, Universidad de Sevilla, Spain; Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
S. Silva Pereira
Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
Y. Sanz Perl
Buenos Aires Physics Institute and Physics Department, University of Buenos Aires, Argentina; Laboratory of Experimental Psychology and Neuroscience, Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, Argentina
M.L. Kringelbach
Department of Psychiatry, University of Oxford, UK; Centre for Music in the Brain, Department of Clinical Medicine, Aarhus University, Denmark; Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Portugal
I. Gayte
Departamento de Ecuaciones Diferenciales y Análisis Numérico, Universidad de Sevilla, Spain
H. Laufs
Department of Neurology, Christian-Albrechts-University Kiel, Germany
E. Tagliazucchi
Buenos Aires Physics Institute and Physics Department, University of Buenos Aires, Argentina
J.A. Langa
Departamento de Ecuaciones Diferenciales y Análisis Numérico, Universidad de Sevilla, Spain
G. Deco
Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Spain
Brain dynamics depicts an extremely complex energy landscape that changes over time, and its characterisation is a central unsolved problem in neuroscience. We approximate the non-stationary landscape sustained by the human brain through a novel mathematical formalism that allows us characterise the attractor structure, i.e. the stationary points and their connections. Due to its time-varying nature, the structure of the global attractor and the corresponding number of energy levels changes over time. We apply this formalism to distinguish quantitatively between the different human brain states of wakefulness and different stages of sleep, as a step towards future clinical applications.
