New Ideas in Computational Neuroscience

Oscillatory multiplexing of population codes for selective communication in neural circuits

Speaker(s)
Thomas Akam Champalimaud (Centre for the Unknown, Lisbon)
Practical information
16 October 2014
LNC2

Mammalian brains exhibit spatio-temporal patterns of network oscillation, the structure of which varies with behaviour. A longstanding hypothesis holds that changes in the structure of network
oscillations play a causal role in controlling effective connectivity between brain regions, though concrete evidence for or against this hypothesis remains elusive. One challenge in evaluating whether observed oscillatory activity is consistent with this proposed function is the lack of a clear quantitative picture about how such selective communication might work. We have approached this question from a neural coding perspective; asking what coding schemes and readout algorithms may support selective oscillatory communication. We argue that selective communication necessarily requires multiplexed coding; i.e. coding schemes in which a single spatio-temporal pattern of spike activity carries multiple independently accessible information channels. We propose that multiplexing is achieved through multiplicative modulation of firing rate population codes. In this coding scheme, variables are encoded into the spatial pattern of average firing rate over the oscillation cycle, with multiplicative oscillatory modulation used to create separate communication channels differentiated by the frequency or phase of modulation. We have identified readout mechanisms which allow a network to selectively respond to inputs with a specific modulation while ignoring distracting inputs; in principle allowing changes in oscillatory activity to control information flow. I will present work with spiking network simulations and simplified models which illustrate these ideas and identify constraints on those structures of oscillatory activity which can efficiently support selective oscillatory communication.