Literature DB >> 34637091

MouseVenue3D: A Markerless Three-Dimension Behavioral Tracking System for Matching Two-Photon Brain Imaging in Free-Moving Mice.

Yaning Han1,2, Kang Huang1,2, Ke Chen1,2, Hongli Pan1, Furong Ju1, Yueyue Long1,3, Gao Gao1,4, Runlong Wu5, Aimin Wang6,7, Liping Wang8,9, Pengfei Wei10,11.   

Abstract

Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional (3-D) space. However, there is no available three-dimensional behavior capture system that focuses on rodents. Here, we present MouseVenue3D, an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents. We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module. Then, we validated this process in behavior recognition tasks, and showed that 3-D behavioral data achieved higher accuracy than 2-D data. Subsequently, MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse. Finally, we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice. Our findings reveal that subtle, spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.
© 2021. Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences.

Entities:  

Keywords:  3-D pose estimation; Automatic calibration; Behavioral and neural recording; Computational neuroethology; Multi-view cameras

Mesh:

Year:  2021        PMID: 34637091      PMCID: PMC8975979          DOI: 10.1007/s12264-021-00778-6

Source DB:  PubMed          Journal:  Neurosci Bull        ISSN: 1995-8218            Impact factor:   5.203


  64 in total

1.  Mapping Sub-Second Structure in Mouse Behavior.

Authors:  Alexander B Wiltschko; Matthew J Johnson; Giuliano Iurilli; Ralph E Peterson; Jesse M Katon; Stan L Pashkovski; Victoria E Abraira; Ryan P Adams; Sandeep Robert Datta
Journal:  Neuron       Date:  2015-12-16       Impact factor: 17.173

Review 2.  Deep learning.

Authors:  Yann LeCun; Yoshua Bengio; Geoffrey Hinton
Journal:  Nature       Date:  2015-05-28       Impact factor: 49.962

Review 3.  Secondary Motor Cortex: Where 'Sensory' Meets 'Motor' in the Rodent Frontal Cortex.

Authors:  Florent Barthas; Alex C Kwan
Journal:  Trends Neurosci       Date:  2016-12-22       Impact factor: 13.837

4.  A novel automated rodent tracker (ART), demonstrated in a mouse model of amyotrophic lateral sclerosis.

Authors:  Brett M Hewitt; Moi Hoon Yap; Emma F Hodson-Tole; Aneurin J Kennerley; Paul S Sharp; Robyn A Grant
Journal:  J Neurosci Methods       Date:  2017-04-13       Impact factor: 2.390

5.  An automated behavior analysis system for freely moving rodents using depth image.

Authors:  Zheyuan Wang; S Abdollah Mirbozorgi; Maysam Ghovanloo
Journal:  Med Biol Eng Comput       Date:  2018-03-21       Impact factor: 2.602

6.  3-D motion capture for long-term tracking of spontaneous locomotor behaviors and circadian sleep/wake rhythms in mouse.

Authors:  Melissa Sourioux; Emma Bestaven; Etienne Guillaud; Sandrine Bertrand; Magali Cabanas; Lea Milan; Willy Mayo; Maurice Garret; Jean-René Cazalets
Journal:  J Neurosci Methods       Date:  2017-11-29       Impact factor: 2.390

7.  A 3D-video-based computerized analysis of social and sexual interactions in rats.

Authors:  Jumpei Matsumoto; Susumu Urakawa; Yusaku Takamura; Renato Malcher-Lopes; Etsuro Hori; Carlos Tomaz; Taketoshi Ono; Hisao Nishijo
Journal:  PLoS One       Date:  2013-10-30       Impact factor: 3.240

Review 8.  Freeze for action: neurobiological mechanisms in animal and human freezing.

Authors:  Karin Roelofs
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-04-19       Impact factor: 6.237

9.  DeepBehavior: A Deep Learning Toolbox for Automated Analysis of Animal and Human Behavior Imaging Data.

Authors:  Ahmet Arac; Pingping Zhao; Bruce H Dobkin; S Thomas Carmichael; Peyman Golshani
Journal:  Front Syst Neurosci       Date:  2019-05-07

10.  DeepFly3D, a deep learning-based approach for 3D limb and appendage tracking in tethered, adult Drosophila.

Authors:  Pavan Ramdya; Pascal Fua; Semih Günel; Helge Rhodin; Daniel Morales; João Campagnolo
Journal:  Elife       Date:  2019-10-04       Impact factor: 8.140

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