Stochastic dynamic clamping as a method for studying the effects of biological noise sources

A crucial issue in the study of the nervous system is the determination of how biophysical noise from probabilistic voltage-dependent and synaptic processes acts to limit neuronal reliability. Experimental and computational work provides indirect evidence that synaptic noise is the major noise source in many cases, but that intrinsic noise from voltage-gated channels makes important contributions in some cells. Rigorous evaluation of the effects and importance of biological noise sources requires one to block the natural noise source pharmacologically, then replace it with an accurate artificial analog. Using this method, which the authors call stochastic dynamic clamping, one can manipulate levels of artificial noise to measure unequivocally the effects of each noise source on neuronal dynamics, excitability, and reliability. The authors are currently developing such systems using two approaches: one that depends on a dedicated digital signal processing card, and one that uses Real-Time Linux