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High-Accuracy Detection of Neuronal Ensemble Activity in Two-Photon Functional Microscopy Using Smart Line Scanning

Authors :
Marco Brondi
Monica Moroni
Dania Vecchia
Manuel Molano-Mazón
Stefano Panzeri
Tommaso Fellin
Source :
Cell Reports, Vol 30, Iss 8, Pp 2567-2580.e6 (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Summary: Two-photon functional imaging using genetically encoded calcium indicators (GECIs) is one prominent tool to map neural activity. Under optimized experimental conditions, GECIs detect single action potentials in individual cells with high accuracy. However, using current approaches, these optimized conditions are never met when imaging large ensembles of neurons. Here, we developed a method that substantially increases the signal-to-noise ratio (SNR) of population imaging of GECIs by using galvanometric mirrors and fast smart line scan (SLS) trajectories. We validated our approach in anesthetized and awake mice on deep and dense GCaMP6 staining in the mouse barrel cortex during spontaneous and sensory-evoked activity. Compared to raster population imaging, SLS led to increased SNR, higher probability of detecting calcium events, and more precise identification of functional neuronal ensembles. SLS provides a cheap and easily implementable tool for high-accuracy population imaging of neural GCaMP6 signals by using galvanometric-based two-photon microscopes. : Using galvanometric mirrors and fast smart line scan trajectories, Brondi et al. present a method to significantly increase the signal-to-noise ratio in population GCaMP6s imaging. The method is validated in anesthetized and awake mice, and it leads to more precise identification of functional neuronal ensembles. Keywords: two-photon imaging, GCaMP6, barrel cortex, neuronal ensembles, spatiotemporal neural responses

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
22111247
Volume :
30
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Cell Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.72319e7b2cd04b86a9c68caebd23c553
Document Type :
article
Full Text :
https://doi.org/10.1016/j.celrep.2020.01.105