We study the performance of a spiking network model based on Integrate-andFire neurons when performing a benchmark discrimination task. The task consists of determining the direction of moving dots in a noisy context. By varying the synaptic parameters of the Integrate-and-Fire neurons, we illustrate the counter-intuitive importance of the second order statistics (input noise) in improving the ...
