Year: 2024
Type: article
Abstract: Spontaneously fluctuating brain activity patterns that emerge at rest have been linked to the brain's health and cognition. Despite detailed descriptions of the spatio-temporal brain patterns, our understanding of their generative mechanism is still incomplete. Using a combination of computational modeling and dynamical systems analysis we provide a mechanistic description of the formation of a resting state manifold via the network connectivity. We demonstrate that the symmetry breaking by the connectivity creates a characteristic flow on the manifold, which produces the major data features across scales and imaging modalities. These include spontaneous high-amplitude co-activations, neuronal cascades, spectral cortical gradients, multistability, and characteristic functional connectivity dynamics. When aggregated across cortical hierarchies, these match the profiles from empirical data. The understanding of the brain's resting state manifold is fundamental for the construction of task-specific flows and manifolds used in theories of brain function. In addition, it shifts the focus from the single recordings towards the brain's capacity to generate certain dynamics characteristic of health and pathology.
Source: Scientific Reports
Authors: Jan Fousek, Giovanni Rabuffo, Kashyap Gudibanda, Hiba Sheheitli, Spase Petkoski, Viktor Jirsa
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,590
Awards: G1190173965, G119252271, Virtual Brain Twin for personalised treatment of Psychiatric Disorders, Personalized Recommendations for Neurodegenerative Disease, G2789362503, EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health, G3936970252, G434337789, G5303564930, G6032406926, Brain Health Trajectories, G8301431789, G8441428806, Human Brain Project Specific Grant Agreement 3
OpenAlex ID: W4405897574
