Information theory and neural coding

Information theory quantifies how much information a neural response carrie s about the stimulus. This can be compared to the information transferred i n particular models of the stimulus-response function and to maximum possib le information transfer. Such comparisons are crucial because they validate assumptions present in any neurophysiological analysis. Here we review inf ormation-theory basics before demonstrating its use in neural coding. We sh ow how to use information theory to validate simple stimulus-response model s of neural coding of dynamic stimuli. Because these models require specifi cation of spike timing precision, they can reveal which time scales contain information in neural coding. This approach shows that dynamic stimuli can be encoded efficiently by single neurons and that each spike contributes t o information transmission. We argue, however, that the data obtained so fa r do not suggest a temporal code, in which the placement of spikes relative to each other yields additional information.