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Brain states and transitions: Insights from computational neuroscience

MPG-Autoren
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Deco,  Gustavo
Computational Neuroscience Group, Department of Information and Communication Technologies, Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain;
Catalan Institution for Research and Advanced Studies (ICREA), University Pompeu Fabra, Barcelona, Spain;
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
School of Psychological Sciences, Monash University, Melbourne, Australia;

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Kringelbach_Deco_2020.pdf
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Zitation

Kringelbach, M. L., & Deco, G. (2020). Brain states and transitions: Insights from computational neuroscience. Cell Reports, 32(10): 108128. doi:10.1016/j.celrep.2020.108128.


Zitierlink: https://hdl.handle.net/21.11116/0000-0007-040B-9
Zusammenfassung
Within the field of computational neuroscience there are great expectations of finding new ways to rebalance the complex dynamic system of the human brain through controlled pharmacological or electromagnetic perturbation. Yet many obstacles remain between the ability to accurately predict how and where best to perturb to force a transition from one brain state to another. The foremost challenge is a commonly agreed definition of a given brain state. Recent progress in computational neuroscience has made it possible to robustly define brain states and force transitions between them. Here, we review the state of the art and propose a framework for determining the functional hierarchical organization describing any given brain state. We describe the latest advances in creating sophisticated whole-brain computational models with interacting neuronal and neurotransmitter systems that can be studied fully in silico to predict and design novel pharmacological and electromagnetic interventions to rebalance them in disease.