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Article Dans Une Revue Journal of Computational Neuroscience Année : 2020

Fast simulation of extracellular action potential signatures based on a morphological filtering approximation

Harry Tran
Radu Ranta

Résumé

Simulating extracellular recordings of neuronal populations is an important and challenging task both for understanding the nature and relationships between extracellular field potentials at different scales, and for the validation of methodological tools for signal analysis such as spike detection and sorting algorithms. Detailed neuronal multicompartmental models with active or passive compartments are commonly used in this objective. Although using such realistic NEURON models could lead to realistic extracellular potentials, it may require a high computational burden making the simulation of large populations difficult without a workstation. We propose in this paper a novel method to simulate extracellular potentials of firing neurons, taking into account the NEURON geometry and the relative positions of the electrodes. The simulator takes the form of a linear geometry based filter that models the shape of an action potential by taking into account its generation in the cell body / axon hillock and its propagation along the axon. The validity of the approach for different NEURON morphologies is assessed. We demonstrate that our method is able to reproduce realistic extracellular action potentials in a given range of axon/dendrites surface ratio, with a time-efficient computational burden.
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Dates et versions

hal-02444750 , version 1 (19-01-2020)

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Harry Tran, Radu Ranta, Steven Le Cam, Valérie Louis-Dorr. Fast simulation of extracellular action potential signatures based on a morphological filtering approximation. Journal of Computational Neuroscience, 2020, 48 (1), pp.27-46. ⟨10.1007/s10827-019-00735-3⟩. ⟨hal-02444750⟩
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