Talk by Dr. Udo Ernst

We hereby announce the next talk in the 'CSN Virtual Seminar':

Flexibility in the visual system: Dynamics, function, and theory

by: Dr. Udo Ernst, Institute for Theoretical Physics, University of Bremen

Abstract

Neural information processing in dynamic, natural environments requires the brain to flexibly allocate limited computational resources to varying task demands. One example is selective attention in the visual system, which allows to preferentially route signals from behaviorally relevant stimuli to downstream visual areas, while suppressing irrelevant visual information. It is an open question which neural mechanisms realize flexible computation, and how this process is controlled.

Here we propose that spontaneous synchronization in recurrent networks is one of the key mechanism for selective processing. Using a recently developed mathematical theory for spike avalanche generation in structured networks with arbitrary connection topology, we analyze a hierarchical system consisting of recurrently coupled populations of spiking neurons which send activation to a common receiver/output population. The network is driven by two external signals of which one has to be routed to the output, while the other signal has to be ignored. Selective communication is established by enhancing synchrony in the sending population which facilitates propagation of spike avalanches to the receiver populations.

We show that the model reproduces a series of key experimental observations and reveals a trade-off between simultaneously maximizing signal representation and signal transfer, resulting in an optimal recurrent coupling for obtaining a good routing performance. In contrast to previously proposed routing schemes based on oscillatory dynamics such as Communication-through-Coherence, formal analysis proves that routing by avalanches does not rely on gamma oscillations, even if they naturally emerge as a side effect of the existence of feedback loops or typical neural time constants in the system.

I will end my presentation by giving a broader perspective on future challenges in understanding flexibility in neural processing.