Title : Extracting synaptic conductances from single membrane potential traces
Authors : Martin Pospischil, Zuzanna Piwkowska, Thierry Bal and Alain Destexhe
Year : 2009
Journal : Neuroscience
Volume : 158
Pages : 545-552
In awake animals, the activity of the cerebral cor- tex is highly complex, with neurons ?ring irregularly with apparent Poisson statistics. One way to characterize this complexity is to take advantage of the high interconnectivity of cerebral cortex and use intracellular recordings of cortical neurons, which contain information about the activity of thousands of other cortical neurons. Identifying the mem- brane potential (Vm) to a stochastic process enables the extraction of important statistical signatures of this complex synaptic activity. Typically, one estimates the total synaptic conductances (excitatory and inhibitory) but this type of es- timation requires at least two Vm levels and therefore cannot be applied to single Vm traces. We propose here a method to extract excitatory and inhibitory conductances (mean and variance) from single Vm traces. This “VmT method” esti- mates conductance parameters using maximum likelihood criteria, under the assumption that synaptic conductances are described by gaussian stochastic processes and are in- tegrated by a passive leaky membrane. The method is illus- trated using models and is tested on guinea-pig visual cortex neurons in vitro using dynamic-clamp experiments. The VmT method holds promises for extracting conductances from single-trial measurements, which has a high potential for in vivo applications.