Contralateral limb specificity for movement preparation in the parietal reach region

The canonical view of motor control is that distal musculature is controlled primarily by the contralateral cerebral hemisphere; unilateral brain lesions typically affect contralateral but not ipsilateral musculature. Contralateral-only limb deficits following a unilateral lesion suggest but do not prove that control is strictly contralateral: the loss of a contribution of the lesioned hemisphere to the control of the ipsilesional limb could be masked by the intact contralateral drive from the nonlesioned hemisphere. To distinguish between these possibilities, we serially inactivated the parietal reach region, comprising the posterior portion of medial intraparietal area, the anterior portion of V6a, and portions of the lateral occipital parietal area, in each hemisphere of 2 monkeys (23 experimental sessions, 46 injections total) to evaluate parietal reach region\u27s contribution to the contralateral reaching deficits observed following lateralized brain lesions. Following unilateral inactivation, reach reaction times with the contralesional limb were slowed compared with matched blocks of control behavioral data; there was no effect of unilateral inactivation on the reaction time of either ipsilesional limb reaches or saccadic eye movements. Following bilateral inactivation, reaching was slowed in both limbs, with an effect size in each no different from that produced by unilateral inactivation. These findings indicate contralateral organization of reach preparation in posterior parietal cortex

Open-Source Tools for Behavioral Video Analysis: Setup, Methods, and Development

Recently developed methods for video analysis, especially models for pose estimation and behavior classification, are transforming behavioral quantification to be more precise, scalable, and reproducible in fields such as neuroscience and ethology. These tools overcome long-standing limitations of manual scoring of video frames and traditional "center of mass" tracking algorithms to enable video analysis at scale. The expansion of open-source tools for video acquisition and analysis has led to new experimental approaches to understand behavior. Here, we review currently available open source tools for video analysis, how to set them up in a lab that is new to video recording methods, and some issues that should be addressed by developers and advanced users, including the need to openly share datasets and code, how to compare algorithms and their parameters, and the need for documentation and community-wide standards. We hope to encourage more widespread use and continued development of the tools. They have tremendous potential for accelerating scientific progress for understanding the brain and behavior.Comment: 20 pages, 2 figures, 2 tables; this is a commentary on video methods for analyzing behavior in animals that emerged from a working group organized by the OpenBehavior project (openbehavior.com

Deep behavioural phenotyping of the Q175 Huntington disease mouse model: effects of age, sex, and weight

Abstract Background Huntington disease (HD) is a neurodegenerative disorder with complex motor and behavioural manifestations. The Q175 knock-in mouse model of HD has gained recent popularity as a genetically accurate model of the human disease. However, behavioural phenotypes are often subtle and progress slowly in this model. Here, we have implemented machine-learning algorithms to investigate behaviour in the Q175 model and compare differences between sexes and disease stages. We explore distinct behavioural patterns and motor functions in open field, rotarod, water T-maze, and home cage lever-pulling tasks. Results In the open field, we observed habituation deficits in two versions of the Q175 model (zQ175dn and Q175FDN, on two different background strains), and using B-SOiD, an advanced machine learning approach, we found altered performance of rearing in male manifest zQ175dn mice. Notably, we found that weight had a considerable effect on performance of accelerating rotarod and water T-maze tasks and controlled for this by normalizing for weight. Manifest zQ175dn mice displayed a deficit in accelerating rotarod (after weight normalization), as well as changes to paw kinematics specific to males. Our water T-maze experiments revealed response learning deficits in manifest zQ175dn mice and reversal learning deficits in premanifest male zQ175dn mice; further analysis using PyMouseTracks software allowed us to characterize new behavioural features in this task, including time at decision point and number of accelerations. In a home cage-based lever-pulling assessment, we found significant learning deficits in male manifest zQ175dn mice. A subset of mice also underwent electrophysiology slice experiments, revealing a reduced spontaneous excitatory event frequency in male manifest zQ175dn mice. Conclusions Our study uncovered several behavioural changes in Q175 mice that differed by sex, age, and strain. Our results highlight the impact of weight and experimental protocol on behavioural results, and the utility of machine learning tools to examine behaviour in more detailed ways than was previously possible. Specifically, this work provides the field with an updated overview of behavioural impairments in this model of HD, as well as novel techniques for dissecting behaviour in the open field, accelerating rotarod, and T-maze tasks

Mapping the neuroethological signatures of pain, analgesia, and recovery in mice.

Ongoing pain is driven by the activation and modulation of pain-sensing neurons, affecting physiology, motor function, and motivation to engage in certain behaviors. The complexity of the pain state has evaded a comprehensive definition, especially in non-verbal animals. Here, in mice, we used site-specific electrophysiology to define key time points corresponding to peripheral sensitivity in acute paw inflammation and chronic knee pain models. Using supervised and unsupervised machine learning tools, we uncovered sensory-evoked coping postures unique to each model. Through 3D pose analytics, we identified movement sequences that robustly represent different pain states and found that commonly used analgesics do not return an animal's behavior to a pre-injury state. Instead, these analgesics induce a novel set of spontaneous behaviors that are maintained even after resolution of evoked pain behaviors. Together, these findings reveal previously unidentified neuroethological signatures of pain and analgesia at heightened pain states and during recovery