Background: Rodent models of neurological disease such as stroke are often characterized by motor deficits. One of the tests that are used to assess these motor deficits is the tapered beam test, which provides a sensitive measure of bilateral motor function based on foot faults (slips) made by a rodent traversing a gradually narrowing beam. However, manual frame-by-frame scoring of video recordings is necessary to obtain test results, which is time-consuming and prone to human rater bias.
New method: We present a cost-effective method for automated touch sensing in the tapered beam test. Capacitive touch sensors detect foot faults onto the beam through a layer of conductive paint, and results are processed and stored on a Raspberry Pi computer.
Results: Automated touch sensing using this method achieved high sensitivity (96.2%) as compared to 'gold standard' manual video scoring. Furthermore, it provided a reliable measure of lateralized motor deficits in mice with unilateral photothrombotic stroke: results indicated an increased number of contralesional foot faults for up to 6days after ischemia.
Comparison with existing method: The automated adaptation of the tapered beam test produces results immediately after each trial, without the need for labor-intensive post-hoc video scoring. It also increases objectivity of the data as it requires less experimenter involvement during analysis.
Conclusions: Automated touch sensing may provide a useful adaptation to the existing tapered beam test in mice, while the simplicity of the hardware lends itself to potential further adaptations to related behavioral tests.
Keywords: Automation; Behavior; Mouse; Raspberry Pi; Stroke; Tapered beam test.
Copyright © 2017 Elsevier B.V. All rights reserved.