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

Autor: Valérie Louis-Dorr, Steven Le Cam, Harry Tran, Radu Ranta
Přispěvatelé: Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2020
Předmět:
0301 basic medicine
Sorting algorithm
Computer science
[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology
Cognitive Neuroscience
Models
Neurological
Action Potentials
LFP
Axon hillock
03 medical and health sciences
Cellular and Molecular Neuroscience
0302 clinical medicine
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Extracellular
medicine
Humans
Computer Simulation
Axon
Electrodes
Neurons
Signal processing
[SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences
Dendrites
Filter (signal processing)
Axons
Sensory Systems
Electrophysiological Phenomena
030104 developmental biology
medicine.anatomical_structure
Computational modelling
nervous system
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
Extracellular action potential
Spike (software development)
Neuron
Extracellular Space
Biological system
Algorithms
030217 neurology & neurosurgery
Zdroj: Journal of Computational Neuroscience
Journal of Computational Neuroscience, Springer Verlag, 2020, 48 (1), pp.27-46. ⟨10.1007/s10827-019-00735-3⟩
ISSN: 1573-6873
0929-5313
DOI: 10.1007/s10827-019-00735-3
Popis: International audience; 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.
Databáze: OpenAIRE
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