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

Area of Science:

• Neuroscience
• Psychiatry
• Computational Biology

Background:

• Major depressive disorder (MDD) affects billions, with current therapies often ineffective due to heterogeneous pathologies.
• Anhedonia, a core symptom of MDD, is linked to altered medial prefrontal cortex (mPFC) activity, but its specific role in stress-induced anhedonia remains unclear.
• Individual differences in stress susceptibility and resilience are observed even in controlled environments, highlighting the need to understand underlying mechanisms.

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 explore the potential of ketamine treatment in reversing stress-induced anhedonia-related neural changes.

Main Methods:

• Implemented the unpredictable chronic mild stress (CMS) protocol in mice to induce anhedonia.
• Utilized unsupervised clustering to analyze individual variability in hedonic behavior.
• Performed 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 from mPFC valence-encoding properties.
• Applied markerless pose tracking computer vision to predict resilience or susceptibility based on facial expressions.

Main Results:

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

Conclusions:

• Granular measurement of behavior and neural activity can predict predisposition to stress-induced anhedonia.
• mPFC valence encoding properties are crucial in understanding and potentially treating anhedonia.
• This research supports the development of more precise diagnostic and therapeutic strategies for MDD by differentiating underlying pathologies.