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We present a method of estimating the input parameters and through them, the input synchrony, of a stochastic leaky integrate-and-fire neuronal model based on the Ornstein–Uhlenbeck process when it is driven by time-dependent sinusoidal input signal and noise. By driving the neuron using sinusoidal inputs, we simulate the effects of periodic synchrony on the membrane voltage and the firing of the...
The reverse correlation and its analytical counterpart, the response-stimulus correlation, describe the expected stimulus just before a present response. With growing complexity of the neuron model, calculating the response-stimulus correlation becomes more and more difficult. We present an approximation of this measure for the integrate-and-fire neuron with reversal potentials and introduce some...
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