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

Ryo Aoki, Tadashi Tsubota, Yuki Goya and Andrea Benucci ()
Additional contact information
Ryo Aoki: Wako-shi
Tadashi Tsubota: Wako-shi
Yuki Goya: Wako-shi
Andrea Benucci: Wako-shi

Nature Communications, 2017, vol. 8, issue 1, 1-9

Abstract: 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.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.nature.com/articles/s41467-017-01371-0 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-01371-0

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-017-01371-0

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().