1 research outputs found
The firing statistics of Poisson neuron models driven by slow stimuli
The coding properties of cells with different types of receptive fields have
been studied for decades. ON-type neurons fire in response to positive
fluctuations of the time-dependent stimulus, whereas OFF cells are driven by
negative stimulus segments. Biphasic cells, in turn, are selective to up/down
or down/up stimulus upstrokes. In this paper, we explore the way in which
different receptive fields affect the firing statistics of Poisson neuron
models, when driven with slow stimuli. We find analytical expressions for the
time-dependent peri-stimulus time histogram and the inter-spike interval
distribution in terms of the incoming signal. Our results enable us to
understand the interplay between the intrinsic and extrinsic factors that
regulate the statistics of spike trains. The former depend on biophysical
neural properties, whereas the latter hinge on the temporal characteristics of
the input signal.Comment: 15 pages, 9 figures, accepted in Biological Cybernetics (Springer