Abstract
Chronic stress contributes to the onset and exacerbation of major depressive disorder (MDD) through the oscillatory activity in the prefrontal cortex (PFC). However, the oscillations on which chronic social stress converges to yield the behavioral state of social avoidance are largely unknown. Here, we use a chronic social defeat stress model and in vivo electrophysiological recordings to uncover a novel neurophysiological measure that predicts the social behavioral state in stressed animals. First, in this study, we find that chronic social defeat stress model induces depression-like behaviors (anhedonia and social avoidance). Second, we find statistically significant differences in PFC oscillatory activity across different frequency ranges in social behavioral state, and the oscillatory activity correlates with stress-induced behavioral state. Finally, we show that the social behavioral states are accurately decoded from the oscillatory activity based on machine learning. Together, these results demonstrate that naturally occurring differences in PFC oscillation underlie the social behavioral state that accompanies the emergence of stress-induced behavioral dysfunction.
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