The Ornstein - Uhlenbeck process does not reproduce spiking statistics of cortical neurons

Cortical neurons of behaving animals generate irregular spike sequences. Recently, there has been a heated discussion about the origin of this irregularity. Softky and Koch (1993) pointed out the inability of standard single neuron models to reproduce the irregularity of the observed spike sequences when the model parameters are chosen within a certain range which they consider to be plausible. Shadlen and Newsome (1994), on the other hand, demonstrated that a standard leaky integrator model can reproduce the irregularity if the inhibition is balanced with the excitation. Motivated by this discussion, we attempted to determine whether the Ornstein-Uhlenbeck process, which is naturally derived from the leaky integration assumption, can in fact reproduce higher order statistics of biological data. For this purpose, we consider actual neuronal spike sequences recorded from the monkey prefrontal cortex to calculate the higher order statistics of the inter-spike intervals. Consistency of the data with the model is examined on the basis of the coe cient of variation and the skewness coe cient, which are, respectively, the measure of the spiking irregularity and the measure of the asymmetry of the interval distribution. It is found that the biological data are not entirely consistent with the model. This fact suggests the need for a revision of our understanding of neuronal spiking mechanisms.