Scientific reports · 2026
Activity as a readout parameter for neurobehavioral research and severity assessment in laboratory rodents: a systematic comparison and meta-analysis of measurement techniques.
СтатьяМетаанализСравнительное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Pérez-Pérez Daniel, Maihöfner Miriam, Munk Anna, Reiber Maria, Bach-Hagemann Anika, Bleich André, Gass Peter, Häger Christine, Johne Marie, Kumstel Simone, Lindauer Ute, Mallien Anne S, Schwabe Kerstin, Tix Leonie, Tolba René H, Warner Laura, Vollmar Brigitte, Zechner Dietmar, Potschka Heidrun
Аннотация
Despite the widespread use of locomotion and activity analyses in neurobehavioral research and severity assessment, comparative evidence on the sensitivity and informative value of available monitoring techniques remains limited. Our study addresses these gaps by systematically evaluating activity data from multiple techniques across different interventions and disease models. The meta-analysis of datasets from the DFG FOR2591 consortium assessed how horizontal activity and locomotion change following surgical procedures, during stress paradigms, and in non-genetic and genetic disease models. Invasive interventions consistently resulted in post-surgical declines in activity, while neurological and psychiatric models were associated either with hypo- or hyperlocomotion, highlighting the bidirectional nature of activity alterations. A comparative evaluation of the techniques revealed that continuous home-cage telemetry and video-based tracking during the dark phase were more sensitive than clinical scoring systems, Neuroscores, or Open field tests. Voluntary wheel running emerged as the most informative of the alternatives. The analysis supports the integration of automated, continuous monitoring technologies to overcome the limitations of traditional daytime and observer-dependent methods. Since horizontal activity and locomotion have proven to be valuable readout parameters for most interventions and disease models, it is recommended that a sensitive analysis be integrated into multidimensional approaches to severity assessment.