Sensory representation by non-equilibrium flows of neural activity at the mesoscale of cortex

We present a non-equilibrium theory of sensory perception and the mesoscale of sensory cortex. We propose that local neuron assemblies (cortical columns) toggle spontaneously between activity states (on and off) and that small populations of columns are coupled within and between areas of sensory cortex. The resulting network generates sudden, large-scale fluctuations and represents sensory inputs and perceptions by characteristic patterns of activity flows . The non-equilibrium dynamic is governed by the variational principle of maximal path entropy, or Maximum Caliber. Many current theories, by contrast, posit equilibrium dynamics and representation with activity states Our minimal model of sensory cortex describes populations of columns from two cortical areas and is fully constrained by empirical observations of `reversals' in perceived appearance, which occur spontaneously for visual, auditory, and tactile stimulation. We formalize representation by activity flows with dynamic Hamiltonian functions. Surprisingly, effective representation requires small-number fluctuations of toggling columns, as larger numbers would be dominated by hysteresis. Finally, we detail predictions for the microscale of spiking neurons that follow from on-off toggling and non-equilibrium dynamics. We conclude that the neural levels underlying perception are functionally organized in terms of activity flows . The inherent instability of non-equilibrium ensures active updating and renders all perceptions open to immediate revision. We conjecture that current theories of brain function (such as the Free Energy Principle) could be reformulated in terms of the variational principle of non-equilibrium, Maximum Caliber.