Longitudinal analysis of decision-making deficits in binge-eating disorders using drift diffusion modeling

Area of Science:

• Cognitive Neuroscience
• Psychiatry
• Computational Psychiatry

Background:

• Binge-eating disorders (BEDs) involve compulsive eating despite negative consequences, indicating decision-making deficits.
• The precise cognitive mechanisms driving these alterations in BEDs remain unclear.
• Computational models like the Drift Diffusion Model (DDM) can dissect decision-making processes.

Purpose of the Study:

• To investigate the relationship between core decision-making components and binge-eating frequency over time using the DDM.
• To identify specific cognitive mechanisms contributing to the persistence of binge eating in adults with BEDs.

Main Methods:

• Longitudinal study of 95 adults with BEDs (69% BED, 15% BN).
• Participants completed a probabilistic reward task at baseline and 3-month follow-up.
• Binge-eating frequency was assessed concurrently and at 6-month follow-up.
• DDM parameters (drift rate, threshold, start bias) were analyzed in relation to binge-eating frequency.

Main Results:

• Slower evidence accumulation (lower drift rate) consistently predicted higher binge-eating frequency cross-sectionally and prospectively.
• Lower decision thresholds (less cautious decision-making) were linked to current binge-eating frequency but not future symptoms.
• Reward sensitivity (start bias) did not significantly correlate with binge-eating frequency.

Conclusions:

• Impaired integration of decision-relevant information (slower drift rate) may maintain binge eating in BEDs.
• DDM offers a valuable computational framework for understanding decision-making deficits in BEDs.
• Findings suggest potential novel intervention targets focused on improving information processing.