THE STOCHASTIC NATURE OF SINGLE NEURONS

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Much effort has focused in recent years on the temporal precision with which neurons respond to synaptic input or to direct current injection. This precision relates to the crucial issue of the nature of the neuronal code used to represent and transmit information. We propose to quantify the fundamental limits that noise places on temporal precision by measuring and analyzing the various noise sources, including (i) noise due to the stochastic nature of voltage-dependent ionic channels, (ii) the effect of "spontaneous" synaptic background firing and (iii) the noise introduced by the unreliable, probabilistic nature of synaptic transmission. 1. We intend to experimentally characterize these noise sources in neocortical neurons using pharmacological manipulations which allow us to isolate the contribution of individual noise sources like Na+, K+ or Ca2+ channels. We will use whole-cell patch recordings at the soma and dendrites of single neurons, and in pairs of connected neurons of an in vitro preparation, visualized using infrared optics. 2. We will repeatedly inject frozen current noise into the soma, the dendrite and the presynaptic neuron (using dual electrodes), and record the noise in the post-synaptic potential (sub-threshold PSPs) as well as the fitter in timing of the resulting spike train. This will allow us to compute the mutual information between the injected current and the output spike train. 3. We will compare these measurements with analytical and numerical models of thermal, channel and synaptic noise in weakly- active linear cables, obtained by incorporating the detailed morphology (that we will reconstruct following infra-cellular injection of biocytin) and the electrophysiological properties of these cells. 4. We will use theoretical techniques to derive measures of spike fitter and similarity between spike trains in terms of the noise sources and compare them against the experimental data obtained in step 2. Our research plan will lead to a quantitative picture of the properties of neuronal noise sources and their effect on the information capacity of individual cortical neurons.