Automated analysis of mouse string-pulling is useful way for obtaining an objective kinematic assessment of movements, for identifying the contributions of different body parts to string-advancement, and for gaining insights into inter hand coordination ( Whishaw, 1996 Dunnett and Brooks, 2018).
#MATLAB TOOLS FOR VIDEO TRACKING MANUAL#
Currently, most of the analysis is carried out with manual annotation of frames leading to low yield of experiments. Thus, the analysis of complex changes in behavior require sophisticated whole-body behavioral analysis in addition to the analysis of skilled hand movements. Associated with strain differences or neurological impairment, any of these aspects of behavior may be impaired and compensated for by a variety of sensorimotor adjustments in not just the hands but by the entire body. Although most of the work of advancing the string by a mouse is done with the arms and hands, the movements rely on online sensory control and appropriate postural support.
The string-pulling task for mice has promise as an unconditioned motor task for phenotyping the growing number of transgenic mouse models of neurological and other diseases but requires an analytical method for its systematic analysis. The organized structure of string-pulling makes the task useful for investigating sensory, motor, cognitive and social learning, as well as studying pathophysiology of motor deficits in animal models of motor disorders ( Blackwell et al., 2018c). The reaching/grasping movements of string-pulling resemble the movements of reach-to-eat movements displayed by rodents in other tasks, including the staircase ( Dunnett, 2010) and the single-pellet reaching task ( Whishaw, 1996) but additionally both hands can be assessed concurrently and many reach movements can be collected rapidly.
The movement is an on-line act, guided by sensory information from snout vibrissea, and features four hand shaping movements for grasping and releasing the string, and five arm movements for retreiving and advancing the string that are similar in mice, rats, and humans ( Blackwell et al., 2018a Singh et al., 2019). Mice will even spontaneously reel in a string, but the behavior becomes more reliable when reinforced by a food reward attached to the string ( Laidre, 2008). If animals are presented with an overhanging string, they adopt a standing or sitting posture and use hand-over-hand movements to reel in the string ( Blackwell et al., 2018a Blackwell et al., 2018b Blackwell et al., 2018c). The task has been used to assess cognitive function, motivation, brain and spinal cord injury and disease consequences and work/reward relations in animals and as a therapy and exercise tool in humans. Variations of the behavior are observed in over 160 species of animals including birds, bees, rodents and primates and humans ( Jacobs and Osvath, 2015 Singh et al., 2019). String-pulling is a proto-tool behavior in which an animal pulls on a string to obtain a reward.
#MATLAB TOOLS FOR VIDEO TRACKING SOFTWARE#
The utility of the task and software is demonstrated by characterizing postural and hand kinematic differences in string-pulling behavior of two strains of mice, C57BL/6 and Swiss Webster. Based on image-segmentation and heuristic algorithms for object tracking, the software also allows tracking of body, ears, nose, and forehands for estimation of kinematic parameters such as body length, body angle, head roll, head yaw, head pitch, and path and speed of hand movements. Here, we describe a Matlab-based software that allows whole-body motion characterization 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. Typical analysis includes kinematic assessment of hand movements done by manually annotating frames.
String-pulling by rodents is a behavior in which animals make rhythmical body, head, and bilateral forearm as well as skilled hand movements to spontaneously reel in a string.
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