Symmetry-breaking, grouped images and multistability with transient unconsciousness

Multistability in consciousness is characterised by transient switches in which the attributes of space and time are locally absent. An extensive number of studies has attempted to describe and predict the causes and duration of such switches, and many are obviously incomplete models or wrong, but some show promise. Models have, for example, drawn on neural network theory, psychophysics, signal detection theory, Markov matrices, and Shilnikov dynamics. Levels of macro-, meso- and micro-dynamics are employed by writers and contrasted. We compare some of those models and find problems in attempting to identify their properties and causality. Discontinuities in the observed local evolution of dynamical time series may be modelled in various ways; they are observed in multistability switches, in saddle-node bifurcations, and in cusp catastrophes. Three models, involving psychophysics, rapid recurrence, and neural networks, are considered as complementing rather than competing for representation.