Abstract

String-pulling in rodents (rats and mice) is a task in which animals make hand-over-hand movements to spontaneously reel in a string with or without a food reward attached to its end. The task elicits bilateral skilled hand movements for which rodents require little training. The task is suitable for phenotyping physiology and pathophysiology of sensorimotor integration in rodent models of neurological and motor disorders. Because a rodent stands in the same location and its movements are repetitive, the task lends itself to quantification of topographical and kinematic parameters for on-line tactile tracking of the string, skilled hand movements for grasping, and rhythmical bilateral forearm movements to advance the string. Here we describe a Matlab(R) based software with a graphical user interface to assist researchers in analyzing the video record of string pulling. The software allows global characterization of position and motion using optical flow estimation, descriptive statistics, principal component, and independent component analyses as well as temporal measures of Fano factor, entropy, and Higuchi fractal dimension. Based on image segmentation and object tracking heuristic algorithms, the software also allows independent tracking of the body, ears, nose, and forehands for estimation of kinematic parameters such as body length, body angle, head roll, head yaw, head pitch, movement paths and speed of hand movement. The utility of the task and that of the software is presented by describing mouse strain characteristics in string-pulling behavior of two strains of mice, C57BL/6 and Swiss Webster. Postural and skilled hand kinematic differences that characterize the strains highlight the utility of the task and assessment methods for phenotypic and neurological analysis of healthy and rodent models of diseases such as Parkinsons, Huntingtons, Alzheimers and other neurological and motor disorders. Significance statementMouse models are used to investigate the physiology and pathophysiology of motor deficits observed in human neurological conditions, for testing substances for therapeutic drug development, and to investigate the role of neural systems and their genetic basis in the expression of behavior. Behavioral tasks involving unconditioned and natural behavior can provide rich insights into motor performance in animal models and analyses can be aided by the automated processing of video data for reliable quantification and high throughput.