Neuropathic injury drives a generalized negative affective state in mice

Autor: Makenzie R. Norris, John Bilbily, Léa J. Becker, Gustavo Borges, Yu-Hsuan Chang, Samantha S. Dunn, Manish K. Madasu, Ream Al-Hasani, Meaghan C. Creed, Jordan G. McCall
Rok vydání: 2022
Popis: Neuropathic pain causes both sensory and emotional maladaptation. Preclinical animal studies of neuropathic pain-induced negative affect could result in novel insights into the mechanisms of chronic pain. Modeling pain-induced negative affect, however, is variable across research groups and conditions. The same injury may or may not produce robust negative affective behavioral responses across different species, strains, and laboratories. Here we sought to identify negative affective consequences of the spared nerve injury model on C57BL/6J male and female mice. We found no significant effect of spared nerve injury across a variety of approach-avoidance, hedonic choice, and coping strategy assays. We hypothesized these inconsistencies may stem in part from the short test duration of these assays. To test this hypothesis, we used the homecage-based Feeding Experimentation Device version 3 to conduct 12-hour, overnight progressive ratio testing to determine whether mice with chronic spared nerve injury had decreased motivation to earn palatable food rewards. Our data demonstrate that despite equivalent task learning, spared nerve injury mice are less motivated to work for a sugar pellet than sham controls. Further, when we normalized behavioral responses across all the behavioral assays we tested, we found that a combined normalized behavioral score is predictive of injury-state and significantly correlates with mechanical thresholds. Together these results suggest that homecage-based operant behaviors provide a useful platform for modeling nerve injury-induced negative affect and that valuable pain-related information can arise from agglomerative data analyses across behavioral assays - even when individual inferential statistics do not demonstrate significant mean differences.
Databáze: OpenAIRE