Predicting Future Development of Stress-Induced Anhedonia From Cortical Dynamics and Facial Expression

Area of Science:

• Neuroscience
• Behavioral Science
• Pharmacology

Background:

• Major depressive disorder (MDD) affects billions, with current treatments often ineffective due to heterogeneous pathologies.
• Anhedonia, a key symptom of MDD, is characterized by the inability to experience pleasure and is linked to medial prefrontal cortex (mPFC) dysfunction.
• Individual variability in stress susceptibility and resilience exists, even under identical conditions, highlighting the need for personalized treatment strategies.

Purpose of the Study:

• To investigate how mPFC valence-specific neuronal population activity is affected during anhedonic states induced by chronic mild stress (CMS).
• To identify predictive markers for stress susceptibility and resilience using neural activity and behavioral analysis.
• To assess the potential of ketamine treatment in reversing stress-induced anhedonia and mPFC dysfunction.

Main Methods:

• Implemented the unpredictable chronic mild stress (CMS) protocol in mice to induce anhedonia and stress susceptibility.
• Utilized unsupervised clustering to analyze individual variability in hedonic behavior post-stress.
• Performed longitudinal in vivo 2-photon calcium imaging to track mPFC neuronal population dynamics during a Pavlovian discrimination task.
• Employed a linear classifier to decode stress susceptibility based on pre-stress mPFC valence-encoding properties.
• Applied markerless pose tracking computer vision to predict resilience or susceptibility from facial expressions during behavioral tasks.

Main Results:

• CMS mice showed a blunted ratio of mPFC neural responses to rewards versus punishments, which reversed after ketamine treatment.
• Stress susceptibility could be decoded from mPFC valence-encoding properties prior to stress exposure and behavioral manifestation.
• Facial expressions during a Pavlovian discrimination task predicted whether mice would become resilient or susceptible to stress.
• mPFC valence encoding and behavioral patterns are indicative of anhedonic states and predict predisposition to stress-induced anhedonia.

Conclusions:

• Increased granularity in measuring behavior and neural activity is crucial for understanding and predicting stress-induced anhedonia.
• mPFC valence encoding and specific facial expressions serve as potential biomarkers for identifying individuals at risk for anhedonia.
• These findings support the development of more precise diagnostic tools and personalized antidepressant therapies by differentiating heterogeneous depressive conditions.