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This paper considers state-dependent dynamics that mediate perception in the brain. In particular, it considers the formal basis of self-organised instabilities that enable perceptual transitions during Bayes-optimal perception. The basic phenomena we consider are perceptual transitions that lead to conscious ignition (Dehaene & Changeux, 2011) and how they depend on dynamical instabilities that underlie chaotic itinerancy (Tsuda, 2001; Breakspear, 2001) and self-organised criticality (Shew, Yang, Yu, Roy, & Plenz, 2011; Plenz & Thiagarajan, 2007; Beggs & Plenz, 2003). Our approach is based on a dynamical formulation of perception as approximate Bayesian inference, in terms of variational free energy minimisation. This formulation suggests that perception has an inherent tendency to induce dynamical instabilities (critical slowing) that enable the brain to respond sensitively to sensory perturbations. We briefly review the dynamics of perception, in terms of generalised Bayesian filtering and free energy minimisation, present a formal conjecture about self-organised instability and then test this conjecture, using neuronal (numerical) simulations of perceptual categorisation. |
