CODING OF TIME-VARYING SIGNALS IN SPIKE TRAINS OF LINEAR AND HALF-WAVE RECTIFYING NEURONS

The encoding of time-varying stimuli in linear and half-wave rectifyin g neurons is studied. The information carried in single spike trains i s assessed by reconstructing part of the stimulus using mean square es timation methods. For the class of models considered here, the mean sq uare error in the reconstructions and estimates of the rate of informa tion transmission are computed analytically. The optimal encoding of s timuli having statistical properties of natural images predicts a chan ge in the temporal filtering characteristics with mean firing rate. Th is change relates to those observed experimentally at the early stages of visual processing. The transmission of information by model neuron s is shown to be fundamentally limited to a maximum of 1.13 bit/spike and it is conjectured that nonlinear processing is necessary to explai n higher rates which have been observed experimentally in certain prep arations. In spite of the fact mat single neurons might not transmit i nformation efficiently, a substantial part of a time-varying stimulus can be recovered from single spike trains. In particular, our results demonstrate that a small number of 'noisy' neurons can carry precise t emporal information in their spike trains.