Work

Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories

Year: 2019

Type: article

Abstract: Rodent skilled reaching is commonly used to study dexterous skills, but requires significant time and effort to implement the task and analyze the behavior. Several automated versions of skilled reaching have been developed recently. Here, we describe a version that automatically presents pellets to rats while recording high-definition video from multiple angles at high frame rates (300 fps). The paw and individual digits are tracked with DeepLabCut, a machine learning algorithm for markerless pose estimation. This system can also be synchronized with physiological recordings, or be used to trigger physiologic interventions (e.g., electrical or optical stimulation).

Source: Journal of Visualized Experiments

DOI: 10.3791/59979

Authors: Alexandra Bova, Krista Kernodle, Kaitlyn Mulligan, Daniel Leventhal

Institutions: University of Michigan, VA Ann Arbor Healthcare System, Michigan Medicine, Ann Arbor VA Medical Center

Language: English

Topic: Motor Control and Adaptation

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funder: National Institute of Neurological Disorders and Stroke

Award: Neuronal Oscillations and Dysregulated Motor Learning in Parkinsonian Rats