Computational mechanisms underlying multi-step planning deficits in methamphetamine use disorder

Area of Science:

• Neuroscience
• Psychology
• Addiction Research

Background:

• Methamphetamine use disorder (iMUDs) is linked to impaired decision-making and difficulty with long-term outcome evaluation.
• Aversive interoceptive states like stress and withdrawal exacerbate relapse risk in iMUDs.

Purpose of the Study:

• To investigate the computational mechanisms of planning in iMUDs.
• To examine how inducing an aversive interoceptive state impacts planning and decision-making in iMUDs.

Main Methods:

• 40 individuals with iMUDs and 49 healthy controls performed a multi-step planning task.
• The task was conducted with and without an anxiogenic breathing resistance manipulation to induce an aversive state.
• Computational modeling was used to analyze planning strategies.

Main Results:

• iMUDs exhibited a specific deficit in identifying optimal plans requiring endurance of negative short-term outcomes, termed 'aversive pruning'.
• Increased craving levels in iMUDs correlated with more pronounced aversive pruning.
• The induction of an aversive state did not significantly alter this core deficit but was associated with craving.

Conclusions:

• Aversive pruning deficits represent a novel computational mechanism contributing to poor decision-making in iMUDs.
• This deficit may underlie vulnerability to relapse in individuals recovering from methamphetamine use disorder.
• Targeting aversive pruning could offer new therapeutic avenues for iMUD treatment.