A novel method for determining the phase-response curves of neurons based on minimizing spike-time prediction error
نویسندگان
چکیده
Regular firing neurons can be seen as oscillators. The phase-response curve (PRC) describes how such neurons will respond to small excitatory perturbations. Knowledge of the PRC is important as it is associated to the excitability type of neurons and their capability to synchronize in networks. In this work we present a novel method to estimate the PRC from experimental data. We assume that continuous noise signal can be discretized into independent perturbations at evenly spaced phases and predict the next spike based on these independent perturbations. The difference between the predicted next spike made at every discretized phase and the actual next spike time is used as the error signal used to optimize the PRC. We test our method on model data and experimentally obtained data and find that the newly developed method is robust and reliable method for the estimation of PRCs from experimental data.
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