Automated monitoring of early neurobehavioral changes in mice following traumatic brain injury

Traumatic brain injury often causes a variety of behavioral and emotional impairments that can develop into chronic disorders. Therefore, there is a need to shift towards identifying early symptoms that can aid in the prediction of traumatic brain injury outcomes and behavioral endpoints in patients with traumatic brain injury after early interventions. In this study, we used the Smart Cage system, an automated quantitative approach to assess behavior alterations in mice during an early phase of traumatic brain injury in their home cages. Female C57BL/6 adult mice were subjected to moderate controlled cortical impact（CCI） injury. The mice then received a battery of behavioral assessments including neurological score, locomotor activity, sleep/wake states, and anxiety-like behaviors on days 1, 2, and 7 after CCI. Histological analysis was performed on day 7 after the last assessment. Spontaneous activities on days 1 and 2 after injury were significantly decreased in the CCI group. The average percentage of sleep time spent in both dark and light cycles were significantly higher in the CCI group than in the sham group. For anxiety-like behaviors, the time spent in a light compartment and the number of transitions between the dark/light compartments were all significantly reduced in the CCI group than in the sham group. In addition, the mice suffering from CCI exhibited a preference of staying in the dark compartment of a dark/light cage. The CCI mice showed reduced neurological score and histological abnormalities, which are well correlated to the automated behavioral assessments. Our findings demonstrate that the automated Smart Cage system provides sensitive and objective measures for early behavior changes in mice following traumatic brain injury.

Automated Behavioral Phenotyping Reveals Presymptomatic Alterations in a SCA3 Genetrap Mouse Model

Characterization of disease models of neurodegenerative disorders requires a systematic and comprehensive phenotyping in a highly standardized manner. Therefore, automated high-resolution behavior test systems such as the homecage based LabMaster system are of particular interest. We demonstrate the power of the automated LabMaster system by discovering previously unrecognized features of a recently characterized atxn3 mutant mouse model. This model provided neurological symptoms including gait ataxia, tremor, weight loss and premature death at the age of 12 months usually detectable just 2 weeks before the mice died. Moreover, using the LabMaster system we were able to detect hypoactivity in presymptomatic mutant mice in the dark as well as light phase. Additionally, we analyzed inflammation, immunological and hematological parameters, which indicated a reduced immune defense in phenotypic mice. Here we demonstrate that a detailed characterization even of organ systems that are usually not affected in SCA3 is important for further studies of pathogenesis and required for the preclinical therapeutic studies.