Strength-dependent perturbation of whole-brain model working in different regimes reveals the role of fluctuations in brain dynamics

• Published in: PLoS computational biology Vol. 18; no. 11; p. e1010662
• Main Authors: Sanz Perl, Yonatan, Escrichs, Anira, Tagliazucchi, Enzo, Kringelbach, Morten L, Deco, Gustavo
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 02-11-2022; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Brain; Brain cancer; Brain research; Computational neuroscience; Computer and Information Sciences; Energy dissipation; Flexibility; Fluctuations; Mathematical models; Medical imaging; Medicine and Health Sciences; Metastasis; Neural networks; Neural oscillations; Neuroimaging; Oscillations; Perturbation; Physical Sciences; Physiological aspects; Research and Analysis Methods; Stimulation; Transcranial magnetic stimulation; Turbulence; Spain
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1010662

Despite decades of research, there is still a lack of understanding of the role and generating mechanisms of the ubiquitous fluctuations and oscillations found in recordings of brain dynamics. Here, we used whole-brain computational models capable of presenting different dynamical regimes to reproduce empirical data’s turbulence level. We showed that the model’s fluctuations regime fitted to turbulence more faithfully reproduces the empirical functional connectivity compared to oscillatory and noise regimes. By applying global and local strength-dependent perturbations and subsequently measuring the responsiveness of the model, we revealed each regime’s computational capacity demonstrating that brain dynamics is shifted towards fluctuations to provide much-needed flexibility. Importantly, fluctuation regime stimulation in a brain region within a given resting state network modulates that network, aligned with previous empirical and computational studies. Furthermore, this framework generates specific, testable empirical predictions for human stimulation studies using strength-dependent rather than constant perturbation. Overall, the whole-brain models fitted to the level of empirical turbulence together with functional connectivity unveil that the fluctuation regime best captures empirical data, and the strength-dependent perturbative framework demonstrates how this regime provides maximal flexibility to the human brain.