Stimulating human prefrontal cortex increases reward learning.

Area of Science:

• Computational psychiatry
• Neuroscience
• Cognitive psychology

Background:

• Mood disorders may involve aberrant reinforcement learning.
• Depression is linked to prioritizing negative event learning.
• Computational psychiatry models these learning deficits.

Purpose of the Study:

• Investigate if transcranial direct current stimulation (tDCS) alters reinforcement learning rates for affective outcomes.
• Explore tDCS effects on learning from rewards and losses.
• Assess tDCS modulation of computational parameters relevant to mood disorders.

Main Methods:

• Healthy adults performed a reinforcement learning task with manipulated outcome information content.
• Stimulation applied to dorsolateral prefrontal cortex (DLPFC) or motor cortex (M1).
• Computational models quantified learning rates from reward and loss outcomes.

Main Results:

• tDCS over DLPFC, not M1, increased learning rates for reward outcomes.
• Cognitive state-dependency observed: tDCS during task performance increased win learning rates; pre-task tDCS decreased both win and loss learning rates.
• Replication study confirmed DLPFC tDCS during task performance specifically enhanced reward learning rates.

Conclusions:

• tDCS over DLPFC can modulate reinforcement learning rates for affective outcomes.
• The timing of tDCS application influences its effect on learning rates.
• Findings support tDCS as a potential intervention for mood disorders by targeting computational mechanisms of reinforcement learning.