The supination assessment task: An automated method for quantifying forelimb rotational function in rats. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Neurological injuries or disease can impair the function of motor circuitry controlling forearm supination, and recovery is often limited. Preclinical animal models are essential tools for developing therapeutic interventions to improve motor function after neurological damage. Here we describe the supination assessment task, an automated measure of quantifying forelimb supination in the rat. NEW METHOD: Animals were trained to reach out of a slot in a cage, grasp a spherical manipulandum, and supinate the forelimb. The angle of the manipulandum was measured using a rotary encoder. If the animal exceeded the predetermined turn angle, a reward pellet was delivered. This automated task provides a large, high-resolution dataset of turn angle over time. Multiple parameters can be measured including success rate, peak turn angle, turn velocity, area under the curve, and number of rotations per trial. The task provides a high degree of flexibility to the user, with both software and hardware parameters capable of being adjusted. RESULTS: We demonstrate the supination assessment task can effectively measure significant deficits in multiple parameters of rotational motor function for multiple weeks in two models of ischemic stroke. COMPARISON WITH EXISTING METHODS: Preexisting motor assays designed to measure forelimb supination in the rat require high-speed video analysis techniques. This operant task provides a high-resolution, quantitative end-point dataset of turn angle, which obviates the necessity of video analysis. CONCLUSIONS: The supination assessment task represents a novel, efficient method of evaluating forelimb rotation and may help decrease the cost and time of running experiments.

publication date

  • March 11, 2016

Research

keywords

  • Automation, Laboratory
  • Supination

Identity

PubMed Central ID

  • PMC5081185

Scopus Document Identifier

  • 84962129350

Digital Object Identifier (DOI)

  • 10.1016/j.jneumeth.2016.03.007

PubMed ID

  • 26976724

Additional Document Info

volume

  • 266