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An automated platform for high-throughput mouse behavior and physiology with voluntary head-fixation.


ABSTRACT: Recording neural activity during animal behavior is a cornerstone of modern brain research. However, integration of cutting-edge technologies for neural circuit analysis with complex behavioral measurements poses a severe experimental bottleneck for researchers. Critical problems include a lack of standardization for psychometric and neurometric integration, and lack of tools that can generate large, sharable data sets for the research community in a time and cost effective way. Here, we introduce a novel mouse behavioral learning platform featuring voluntary head fixation and automated high-throughput data collection for integrating complex behavioral assays with virtually any physiological device. We provide experimental validation by demonstrating behavioral training of mice in visual discrimination and auditory detection tasks. To examine facile integration with physiology systems, we coupled the platform to a two-photon microscope for imaging of cortical networks at single-cell resolution. Our behavioral learning and recording platform is a prototype for the next generation of mouse cognitive studies.

SUBMITTER: Aoki R 

PROVIDER: S-EPMC5662625 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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An automated platform for high-throughput mouse behavior and physiology with voluntary head-fixation.

Aoki Ryo R   Tsubota Tadashi T   Goya Yuki Y   Benucci Andrea A  

Nature communications 20171030 1


Recording neural activity during animal behavior is a cornerstone of modern brain research. However, integration of cutting-edge technologies for neural circuit analysis with complex behavioral measurements poses a severe experimental bottleneck for researchers. Critical problems include a lack of standardization for psychometric and neurometric integration, and lack of tools that can generate large, sharable data sets for the research community in a time and cost effective way. Here, we introdu  ...[more]

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