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

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  • Yonatan Sanz Perl, Pompeu Fabra University, Universidad de Buenos Aires, Universidad de San Andrés
  • ,
  • Anira Escrichs, Pompeu Fabra University
  • ,
  • Enzo Tagliazucchi, Universidad de Buenos Aires, Universidad Adolfo Ibanez
  • ,
  • Morten L. Kringelbach
  • Gustavo Deco, Pompeu Fabra University, ICREA, Max Planck Institute for Human Cognitive and Brain Sciences, Monash University

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.

Original languageEnglish
Article numbere1010662
JournalPLOS Computational Biology
Volume18
Issue11
ISSN1553-734X
DOIs
Publication statusPublished - Nov 2022

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