Imaging the awake visual cortex with a genetically encoded voltage indicator

Matteo Carandini, Daisuke Shimaoka, L. Federico Rossi, Tatsuo K. Sato, Andrea Benucci, Xthomas Knopfel

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66 Citations (Scopus)

Abstract

Genetically encoded voltage indicators (GEVIs) promise to reveal the membrane potential of genetically targeted neuronal populations through noninvasive, chronic imaging of large portions of cortical space. Here we test a promising GEVI in mouse cortex during wakefulness, a challenging condition due to large hemodynamic activity, and we introduce a straightforward projection method to separate a signal dominated by membrane voltage from a signal dominated by hemodynamic activity. We expressed VSFP-Butterfly 1.2 plasmid in layer 2/3 pyramidal cells of visual cortex through electroporation in utero. We then used wide-field imaging with two cameras to measure both fluorophores of the indicator in response to visual stimuli. By taking weighted sums and differences of the two measurements, we obtained clear separation of hemodynamic and voltage signals. The hemodynamic signal showed strong heartbeat oscillations, superimposed on slow dynamics similar to blood oxygen level-dependent (BOLD) or “intrinsic” signals. The voltage signal had fast dynamics similar to neural responses measured electrically, and showed an orderly retinotopic mapping. We compared this voltage signal with calcium signals imaged in transgenic mice that express a calcium indicator (GCaMP3) throughout cortex. The voltage signal from VSFP had similar signal-to-noise ratios as the calcium signal, it was more immune to vascular artifacts, and it integrated over larger regions of visual space, which was consistent with its reporting mostly subthreshold activity rather than the spiking activity revealed by calcium signals. These results demonstrate that GEVIsprovide apowerfultoolto study the dynamics of neural populations at mesoscopic spatial scales in the awake cortex.

Original languageEnglish
Pages (from-to)53-63
Number of pages11
JournalJournal of Neuroscience
Volume35
Issue number1
DOIs
Publication statusPublished - 7 Jan 2015
Externally publishedYes

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