MC 6460
Speaker
Robert Butera
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA
Title
Slow noise — evidence for a new role for noise in neural systems?
Abstract
In this talk I review recent work from our lab, in collaboration with Carmen Canavier at LSU Health Science Center, discussing evidence and a putative role for “slow noise” in neural systems. Noise is typically considered a fast process on the time scale of the firing of an action potential. We studied a hybrid system — a real neuron bi-directionally coupled to a deterministic real-time model of a neuron. The synapses and simulated neuron are entirely deterministic, those all intrinsic noise in the system is predominantly due to the in vitro neuron. The firing dynamics of this coupled system are well-characterized by iterative maps derived from the component neurons phase-response curves (PRCs). We show that both the hybrid experiments and the iterative simulations derived from the experiments show slowly fluctuating stochastic dynamics that confer a history dependence on the firing intervals of the neuron in the coupled system. This is a time-scale of variability not typically discussed as a role for noise in neural systems. We subsequently studied the variability in firing rate of single isolated neurons, and found a similar variation in period, which we call “wander.” This wander is captured in an ARIMA model phenomenologically, and a simulated network of firing neurons with a stochastic adaptive current exhibited similar properties. We conclude that the observed autocorrelation structure may be a neural signature of slow stochastic adaptation, and wander generated in this manner may be a general mechanism for limiting episodes of synchronized activity in the nervous system.