CLARA, a Closed-Loop Automated Reaching Apparatus is a system developed by Spencer Bowles, W. Ryan Williamson and colleagues from the University of Colorado Anschutz Medical Campus. CLARA automatically acquires data for the study of motor behaviors. It features a complex reaching task in freely behaving mice and integrates an automatic pellet delivery system, high-speed object tracking, and a low-latency behavior classifier. The CLARA system tracks and classifies unconstrained skilled reaching behavior without physical markers using modules from DeepLabCut. The system is also compatible with advanced neurophysiological tools for stimulation and recording. This enables the testing of neurostimulation devices and the identification of novel neurological biomarkers. The CLARA system is able to track mice performing a skilled reach task at a proficiency similar to manually trained animals. The authors demonstrate the capabilities of CLARA by performing closed-loop vagus nerve stimulation during the reaching task to investigate whether VNS could alter motor dexterous learning in healthy animals. Details about CLARA and it’s implementation can be found in the recent Journal of Neural Engineering publication.
This research tool was created by your colleagues. Please acknowledge the Principal Investigator, cite the article in which the tool was described, and include an RRID in the Materials and Methods of your future publications. RRID:SCR_022365
Read the Paper
Learn more about CLARA, its implementation, and validation data from the JNE publication!
This post was brought to you by Samantha Sutcliffe. This project summary is a part of the collection from neuroscience undergraduate and graduate students in the Computational Methods course at American University.
Check out projects similar to this!