Podcast with Murray Shanahan on metastability and chimera states

What happens in the brain between perfect synchrony and total disorder , and why might that intermediate zone be where cognition lives? Computer scientist Murray Shanahan explains how metastable chimera states in coupled oscillator networks may capture the dynamic coalitions that govern brain function. Subscribe for more from the Convergent Science Network podcast series. Murray Shanahan joins Paul Verschure and Tony Prescott at the BCBT summer school to discuss his computational work on metastability and chimera states in brain-like networks. The conversation builds on Pascal Fries's communication-through-coherence hypothesis, which proposes that synchronized neuronal populations are positioned to exchange information and cooperate, while desynchronized populations are effectively shut out. Shanahan extends this framework by showing that abstract coupled oscillator models, Kuramoto oscillators, can produce chimera states where one subset of oscillators synchronizes while another remains desynchronized, and that these states are metastable, breaking apart and reforming in new configurations over time. The discussion explores how these dynamics relate to real brain phenomena, including binocular rivalry and resting-state fMRI data. When Kuramoto oscillators are placed on nodes of a real human connectome derived from diffusion tensor imaging, the model produces strong correlations with empirical resting-state functional connectivity , but only when operating in the metastable chimera regime. This finding surprised Shanahan and suggests that the brain may be poised at a critical point between order and disorder, where the richness of its dynamical repertoire is maximized. Key topics include how metastability differs from stable attractors and why it matters for cognition, what chimera states are and why physicists initially overlooked their relevance, how gamma-frequency oscillations facilitate competition and cooperation among distributed neuronal populations, why coupling strength and transmission delays are the key parameters governing these dynamics, and what the relationship is between fast oscillatory mechanisms and the slower dynamics captured by fMRI. Part of the Convergent Science Network podcast series from the BCBT Summer School.