CRCNS: Physiological and Computational Approaches to Understanding Neuronal Synch

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DESCRIPTION (provided by applicant): Neurons convey messages more effectively when firing together. Even modest increases in synchronization result in large changes in firing rate for downstream neurons. Synchronous activity, especially oscillatory synchrony, is observed in many brain networks and is thought to play an important role in representation of stimuli, propagation of activity and computation. Alterations of synchrony, especially in the gamma frequency range, have recently been implicated in the etiology in a number of cognitive disorders, most notably schizophrenia. However, linking the alterations in synchrony with the alterations in synaptic and cellular properties has proven difficult. Here we describe experiments designed to examine a novel mechanism for the generation of synchronous oscillations which we call stochastic synchrony. Recently, substantial interest has arisen in theoretical work describing synchronization of oscillating neurons by aperiodic, partially correlated, noisy inputs. We have shown experimentally that such inputs can generate oscillatory synchrony in uncoupled neurons (olfactory bulb mitral cells) and have proposed that this mechanism may account for the development of fast (gamma frequency) synchronous oscillations in the olfactory bulb. Here we propose further theoretical and experimental investigations of noise-induced synchronization in neurons more generally. Specifically, we propose to analyze the dependence of noise-induced synchronization on properties of the noisy inputs and on the dynamics of the oscillators. By combined experimental and theoretical investigation, we will determine which channel types are most critical for the development of synchrony by this mechanism. We also propose to study the interaction of noise-induced and connectivity-induced synchronization, as in many cases these two phenomena are likely to both be involved in generating patterns of synchronous activity across brain networks. By exploring this novel mechanism of gamma oscillations we hope to better understand how alteration of cellular and circuit-level properties can interfere with the development of normal gamma oscillations. Such work will have importance for understanding disorders such as schizophrenia, which are associated with altered gamma activity.