Understanding brain states across spacetime informed by whole-brain modelling

Journal article : Review

In order to survive in a complex environment, the human brain relies on the ability to flexibly adapt ongoing behaviour according to intrinsic and extrinsic signals. This capability has been linked to specific whole-brain activity patterns whose relative stability (order) allows for consistent functioning, supported by sufficient intrinsic instability needed for optimal adaptability. The emergent, spontaneous balance between order and disorder in brain activity over spacetime underpins distinct brain states. For example, depression is characterized by excessively rigid, highly ordered states, while psychedelics can bring about more disordered, sometimes overly flexible states. Recent developments in systems, computational and theoretical neuroscience have started to make inroads into the characterization of such complex dynamics over space and time. Here, we review recent insights drawn from neuroimaging and whole-brain modelling motivating using mechanistic principles from dynamical system theory to study and characterize brain states. We show how different healthy and altered brain states are associated to characteristic spacetime dynamics which in turn may offer insights that in time can inspire new treatments for rebalancing brain states in disease. This article is part of the theme issue ‘Emergent phenomena in complex physical and socio-technical systems: from cells to societies’.

Authors: Vohryzek, J; Cabral, J; Vuust, P; Deco, G; Kringelbach, ML

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: The Royal Society
• Journal: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
• Volume: 380
• Issue: 2227
• Pages: 20210247
• Article number: 20210247
• Publication date: 2022-05-23
• Acceptance date: 2021-11-23
• DOI: 10.1098/rsta.2021.0247
• EISSN: 1471-2962
• ISSN: 1364503X, 1364-503X
• Language: English
• Keywords: emergence; functional magnetic resonance imaging; complexity; connectomics; whole-brain models; spatio-temporal dynamics
• Subtype: Review