Abstract
We develop a simple model which simulates neuronal activity as observed in a neuronal network cultivated on a multielectrode array neurochip. The model is based on an inhomogeneous Poisson process to simulate neurons which are active without external input or stimulus as observed in neurochip experiments. Spike train statistics are applied to validate the resulting spike data. Calculated features adapted from spikes and bursts as well as the spike train statistics show that the presented model has potential to simulate neuronal activity.
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Lenk, K. (2011). A Simple Phenomenological Neuronal Model with Inhibitory and Excitatory Synapses. In: Travieso-González, C.M., Alonso-Hernández, J.B. (eds) Advances in Nonlinear Speech Processing. NOLISP 2011. Lecture Notes in Computer Science(), vol 7015. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25020-0_30
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DOI: https://doi.org/10.1007/978-3-642-25020-0_30
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