Advances in the automation of whole-cell patch clamp technology.


Journal

Journal of neuroscience methods
ISSN: 1872-678X
Titre abrégé: J Neurosci Methods
Pays: Netherlands
ID NLM: 7905558

Informations de publication

Date de publication:
01 10 2019
Historique:
received: 02 04 2019
revised: 05 07 2019
accepted: 10 07 2019
pubmed: 25 7 2019
medline: 21 10 2020
entrez: 24 7 2019
Statut: ppublish

Résumé

Electrophysiology is the study of neural activity in the form of local field potentials, current flow through ion channels, calcium spikes, back propagating action potentials and somatic action potentials, all measurable on a millisecond timescale. Despite great progress in imaging technologies and sensor proteins, none of the currently available tools allow imaging of neural activity on a millisecond timescale and beyond the first few hundreds of microns inside the brain. The patch clamp technique has been an invaluable tool since its inception several decades ago and has generated a wealth of knowledge about the nature of voltage- and ligand-gated ion channels, sub-threshold and supra-threshold activity, and characteristics of action potentials related to higher order functions. Many techniques that evolve to be standardized tools in the biological sciences go through a period of transformation in which they become, at least to some degree, automated, in order to improve reproducibility, throughput and standardization. The patch clamp technique is currently undergoing this transition, and in this review, we will discuss various aspects of this transition, covering advances in automated patch clamp technology both in vitro and in vivo.

Identifiants

pubmed: 31336060
pii: S0165-0270(19)30214-6
doi: 10.1016/j.jneumeth.2019.108357
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

108357

Subventions

Organisme : NINDS NIH HHS
ID : R01 NS102727
Pays : United States
Organisme : NEI NIH HHS
ID : R01 EY023173
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH103910
Pays : United States
Organisme : NINDS NIH HHS
ID : DP1 NS087724
Pays : United States
Organisme : Howard Hughes Medical Institute
Pays : United States

Informations de copyright

Copyright © 2019. Published by Elsevier B.V.

Auteurs

Ho-Jun Suk (HJ)

Health Sciences and Technology, MIT, Cambridge, MA 02139, USA; Media Lab, MIT, Cambridge, MA 02139, USA; McGovern Institute, MIT, Cambridge, MA 02139, USA.

Edward S Boyden (ES)

Media Lab, MIT, Cambridge, MA 02139, USA; McGovern Institute, MIT, Cambridge, MA 02139, USA; Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA.

Ingrid van Welie (I)

Neural Dynamics Technologies LLC, Cambridge, MA 02142, USA. Electronic address: ingrid@neuraldynamicstechnologies.com.

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Classifications MeSH