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Binge eating disorder is a significant mental health condition characterized by recurrent episodes of excessive food consumption within a short period, accompanied by a perceived loss of control over eating behavior. Unlike occasional overeating, binge eating disorder is marked by distressing emotions such as guilt, shame, and anxiety following binge episodes. The disorder affects individuals across different ages and backgrounds, with profound implications for physical and psychological...
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Longitudinal analysis of decision-making deficits in binge-eating disorders using drift diffusion modeling.

Glen Forester1, Brianne N Richson1, Erin E Reilly2

  • 1Center for Biobehavioral Research, Sanford Research, USA; Department of Psychiatry, University of North Dakota School of Medicine and Health Sciences, USA.

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Summary

Individuals with binge-eating disorders (BEDs) show impaired decision-making. Slower information processing, a key cognitive deficit, predicts more frequent binge eating over time, suggesting new treatment targets.

Keywords:
Binge eatingDecision makingDrift diffusion modelEating disordersImpulsivity

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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.