Automated system for training and assessing string-pulling behaviors in rodents
Jordan, G. A.; Vishwanath, A.; Holguin, G.; Bartlett, M. J.; Tapia, A. K.; Winter, G. M.; Sexauer, M. M.; Stopera, C. J.; Falk, T.; Cowen, S. L.
Show abstract
String-pulling tasks have been used for centuries to study coordinated bimanual motor behavior and problem solving. String pulling is rapidly learned, ethologically grounded, and has been applied to many species and disease conditions. Typically, training of string-pulling behaviors is achieved through manual shaping and baiting. Furthermore, behavioral assessment of reaching, grasping, and pulling is often performed through labor intensive manual video scoring. No system, to our knowledge, currently exists for the automated shaping and assessment of string-pulling behaviors. Here we describe the PANDA system (Pulling And Neural Data Analysis), an inexpensive hardware and software system that utilizes a continuous string loop connected to a rotary encoder, feeder, microcontroller, high-speed camera, and analysis software for assessment and training of string-pulling behaviors and synchronization with neural recording data. We demonstrate this system in unimplanted rats and rats implanted with electrodes in motor cortex and hippocampus and show how the PANDA system can be used to assess relationships between paw movements and single-unit and local-field activity. We also found that automating the shaping procedure significantly improved overall performance, with rats regularly pulling >100 meters during a 15-minute session. In conclusion, the PANDA system will be of general use to researchers investigating motor control, motivation, and motor disorders such as Parkinsons disease, Huntingtons disease, and stroke. It will also support the investigation of neural mechanisms involved in sensorimotor integration. HighlightsO_LIHigh-speed tracking of continuous grasping and pulling behaviors. C_LIO_LIAutomated and adaptive reinforcement of string-pulling behavior. C_LIO_LIIntegration with neural recording and video tracking systems. C_LIO_LIOpen-source software and hardware. C_LI Supplemental FilesThe supplemental pdf contains additional designs and behavioral data and has been uploaded. Source code and 3D and laser cut design files can be found at: https://github.com/CowenLab/String_Pulling_System/ Videos are in the GitHub repository at: https://github.com/CowenLab/String_Pulling_System/tree/main/Videos
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Chronic Stability of Single-Channel Neurophysiological Correlates of Gross and Fine Reaching Movements in the Rat 96%
- High throughput machine learning pipeline to characterize larval zebrafish motor behavior 93%
- Automated, Stress-Free, and Precise Measurement of Songbird Weight in Neuroscience Experiments 93%
Similar papers in this journal
- ReachingBot: an automated and scalable benchtop device for highly parallel Single Pellet Reach-and-Grasp training and assessment in mice 96%
- RPM: an open-source rotation platform for open- and closed-loop vestibular stimulation in head-fixed mice 96%
- Adaptive Wheel Exercise for Mouse Models of Parkinson's Disease 95%
Similar papers in this journal
- Multifactorial motor behavior assessment for real-time evaluation of emerging therapeutics to treat neurologic impairments 95%
- GuPPy, a Python toolbox for the analysis of fiber photometry data 94%
- Repurposing a digital kitchen scale for neuroscience research: a complete hardware and software cookbook for PASTA 94%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.