Articles by Samuel D. Butensky in JoVE
The Knob Supination Task: A Semi-automated Method for Assessing Forelimb Function in Rats Samuel D. Butensky1, Thelma Bethea1, Joshua Santos1, Anil Sindhurakar1, Eric Meyers2,3, Andrew M. Sloan2,3, Robert L. Rennaker II2,3, Jason B. Carmel1,4,5 1Burke Medical Research Institute, 2Texas Biomedical Center, The University of Texas at Dallas, 3Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, 4Brain and Mind Research Institute, Weill Cornell Medical College, 5Departments of Neurology and Pediatrics, Weill Cornell Medical College This manuscript describes a semi-automated task that quantifies supination in rats. Rats reach, grasp, and supinate a spherical manipulandum. The rat is rewarded with a pellet if the turn angle exceeds a criterion set by the user. This task increases throughput, sensitivity to injury, and objectivity compared to traditional tasks.
Other articles by Samuel D. Butensky on PubMed
An Automated Test of Rat Forelimb Supination Quantifies Motor Function Loss and Recovery After Corticospinal Injury Neurorehabilitation and Neural Repair. Feb, 2017 | Pubmed ID: 27530125 Rodents are the primary animal model of corticospinal injury and repair, yet current behavioral tests do not show the large deficits after injury observed in humans. Forearm supination is critical for hand function and is highly impaired by corticospinal injury in both humans and rats. Current tests of rodent forelimb function do not measure this movement.
Dexterity: A MATLAB-based Analysis Software Suite for Processing and Visualizing Data from Tasks That Measure Arm or Forelimb Function Journal of Neuroscience Methods. Jul, 2017 | Pubmed ID: 28583476 Hand function is critical for independence, and neurological injury often impairs dexterity. To measure hand function in people or forelimb function in animals, sensors are employed to quantify manipulation. These sensors make assessment easier and more quantitative and allow automation of these tasks. While automated tasks improve objectivity and throughput, they also produce large amounts of data that can be burdensome to analyze. We created software called Dexterity that simplifies data analysis of automated reaching tasks.