Multistability and metastability: understanding dynamic coordination in the brain

By J. A. S. Kelso. Philosophical Transactions of the Royal Society B: Biological Sciences, 2012

542 citations recorded by the source corpus.

Multistable coordination dynamics exists at many levels, from multifunctional neural circuits in vertebrates and invertebrates to large-scale neural circuitry in humans. Moreover, multistability spans (at least) the domains of action and perception, and has been found to place constraints upon, even dictating the nature of, intentional change and the skill-learning process. This paper reviews some of the key evidence for multistability in the aforementioned areas, and illustrates how it has been measured, modelled and theoretically understood. It then suggests how multistability—when combined with essential aspects of coordination dynamics such as instability, transitions and (especially) metastability—provides a platform for understanding coupling and the creative dynamics of complex goal-directed systems, including the brain and the brain–behaviour relation.

Subfields: Cognitive Neuroscience, Social Psychology

View Paper: https://www.semanticscholar.org/paper/77f132ed3ded32b18e28836b1d28c37664320cc6

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Citations in the corpus

The Metastable Brain (2014, unknown): “If this event occurs with sufficient magnitude, and if the coordination dynamics is multistable (Kelso, 2012), both brain and behavior may switch to another coordination state (Kelso, 1984, 2010; Kelso et al., 1991, 1992; Meyer-Lindenberg et al., 2002; Schöner and Kelso, 1988).”
Key Properties of Expert Movement Systems in Sport (2013, background): “Previously, Kelso [71] demonstrated the presence of multistability in performance of a bi-manual coordination task.”
Ecological-Enactive Cognition as engaging with a field of relevant affordances (2018, background): “Metastable attunement is a technical term for the ease with which a system can switch to another state (Kelso 2012; Bruineberg and Rietveld 2014) and the study of it in the brain-body-environment system as a whole provides a paradigm for understanding hypergrip.”
Ecological cognition: expert decision-making behaviour in sport (2017, background): “Multistability refers to the principle of ‘functional equivalence’ (Kelso, 2012, p. 907), also known as ‘degeneracy’ (Edelman & Gally, 2001).”
The dynamics of expertise acquisition in sport : the role of affective learning design (2015, unknown): “Systematically manipulating control parameters perturbs attractor states (stable) and facilitates phase transitions and new organisational states or behaviours to emerge (Kelso, 1995, 2012).”
Brain network dynamics are hierarchically organized in time (2017, background): “Nonrandom transitions have also been found between brain states defined as electroencephalographic microstates (11), attractors in metastable systems (12), or local minima in energy landscape analysis (13).”
The anticipating brain is not a scientist: the free-energy principle from an ecological-enactive perspective (2016, background): “This metastable attunement allows for rapid and flexible switching between relevant action possibilities (Kelso 2012; Rietveld 2008b; Bruineberg and Rietveld 2014).”
The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives (2024, background): “…2011; Bick and Field, 2017; Morrison and Young, 2022; Meyer-Ortmanns, 2023) multistability (Lopes da Silva et al., 2003; Takeshita et al., 2007; Rothkegel and Lehnertz, 2009; Breakspear, 2017; Pisarchik and Hramov, 2022), and metastability (Kelso, 2012; Tognoli and Kelso, 2014; Rossi et al., 2023).”
Mechanisms and Controversies of tACS (Transcranial Alternating Current Stimulation) (2024, background): “Beyond the classical theories of synchronization and mode-locking, another cross-frequency mechanism of interest is metastability (Kelso, 2012; Tognoli & Kelso, 2014).”
Task‐specific topology of brain networks supporting working memory and inhibition (2024, methodology): “According to data from the HCP (Barch et al., 2013), 38 – 76% of connections in functional connectivity networks are different across the two states (Kelso, 2012).”