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Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations

Sinha, M and Narayanan, R (2022) Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations. In: Neuroscience, 489 . 111 -142.

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Official URL: https://doi.org/10.1016/j.neuroscience.2021.08.035

Abstract

Neurons and glial cells are endowed with membranes that express a rich repertoire of ion channels, transporters, and receptors. The constant flux of ions across the neuronal and glial membranes results in voltage fluctuations that can be recorded from the extracellular matrix. The high frequency components of this voltage signal contain information about the spiking activity, reflecting the output from the neurons surrounding the recording location. The low frequency components of the signal, referred to as the local field potential (LFP), have been traditionally thought to provide information about the synaptic inputs that impinge on the large dendritic trees of various neurons. In this review, we discuss recent computational and experimental studies pointing to a critical role of several active dendritic mechanisms that can influence the genesis and the location-dependent spectro-temporal dynamics of LFPs, spanning different brain regions. We strongly emphasize the need to account for the several fast and slow dendritic events and associated active mechanisms — including gradients in their expression profiles, inter- and intra-cellular spatio-temporal interactions spanning neurons and glia, heterogeneities and degeneracy across scales, neuromodulatory influences, and activitydependent plasticity — towards gaining important insights about the origins of LFP under different behavioral states in health and disease. We provide simple but essential guidelines on how to model LFPs taking into account these dendritic mechanisms, with detailed methodology on how to account for various heterogeneities and electrophysiological properties of neurons and synapses while studying LFPs.

Item Type: Journal Article
Publication: Neuroscience
Publisher: Elsevier Ltd
Additional Information: The copyright for this article belongs to the Authors.
Keywords: computational models; degeneracy; heterogeneity; ion channels; neural plasticity; oscillations
Department/Centre: Division of Biological Sciences > Molecular Biophysics Unit
Date Deposited: 03 Dec 2021 08:41
Last Modified: 24 Jun 2022 05:07
URI: https://eprints.iisc.ac.in/id/eprint/70394

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