Perturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness

Journal article

Human behavior and cognitive function correlate with complex patterns of spatio-temporal brain dynamics, which can be simulated using computational models with different degrees of biophysical realism. We used a data-driven optimization algorithm to determine and classify the types of local dynamics that enable the reproduction of different observables derived from functional magnetic resonance recordings. The phase space analysis of the resulting equations revealed a predominance of stable spiral attractors, which optimized the similarity to the empirical data in terms of the synchronization, metastability, and functional connectivity dynamics. For stable limit cycles, departures from harmonic oscillations improved the fit in terms of functional connectivity dynamics. Eigenvalue analyses showed that proximity to a bifurcation improved the accuracy of the simulation for wakefulness, whereas deep sleep was associated with increased stability. Our results provide testable predictions that constrain the landscape of suitable biophysical models, while supporting noise-driven dynamics close to a bifurcation as a canonical mechanism underlying the complex fluctuations that characterize endogenous brain activity.Fil: Piccinini, Juan Ignacio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Deco, Gustavo. Universitat Pompeu Fabra; EspañaFil: Kringelbach, Morten. University of Oxford; Reino UnidoFil: Laufs, Helmut. University of Kiel; AlemaniaFil: Sanz Perl Hernandez, Yonatan. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tagliazucchi, Enzo Rodolfo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Authors: Perl, YS; Pallavicini, C; Ipiña, IP; Demertzi, A; Bonhomme, V

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Public Library of Science
• Journal: PLoS Computational Biology
• Volume: 17
• Issue: 7
• Pages: e1009139-e1009139
• Publication date: 2021-07-27
• DOI: 10.1371/journal.pcbi.1009139
• EISSN: 1553-7358
• ISSN: 1553-734X
• Language: English
• Keywords: Machine learning; Sleep (system call); Stability (learning theory); Electroencephalography; Wakefulness; Computer science; Consciousness; Brain activity and meditation; Cognitive psychology; Neuroscience; Persistent vegetative state; Psychology; Minimally conscious state; Cognitive science