THE CODING OF INFORMATION BY SPIKING NEURONS - AN ANALYTICAL STUDY

We analyse analytically the coding of information by a spiking neuron. The emphasis is on the question of how many spikes are necessary for the reliable discrimination of two different input signals. The discri mination ability is measured by the second-order Renyi mutual informat ion between the random variable describing the name of the signal and a sequence of n output spikes. Analysing this measure as a function of n, we study the coding strategy of a single spiking neuron, with the following main results. A small number of output spikes is required fo r efficient discrimination of input signals, i.e. for encoding them, i f the separation is easy; a large number of output spikes is required in the difficult case of separation of very similar input signals. Thr ee different versions of the spike response model of a single neuron a re studied. The approach presented can be regarded as a non-parametric version of the reconstruction method of Bialek.