A core component of psychological therapy causes adaptive changes in computational learning mechanisms

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Clinical Psychology

Background:

• Cognitive distancing is an emotion regulation strategy used in mental health treatment.
• The precise therapeutic mechanisms of cognitive distancing remain unclear.

Purpose of the Study:

• To investigate the computational mechanisms underlying cognitive distancing.
• To determine how cognitive distancing affects reinforcement learning parameters.

Main Methods:

• 935 participants completed an online reinforcement learning task.
• Half were randomized to a cognitive self-distancing intervention.
• Computational models (Q-learning) derived learning parameters from choices.

Main Results:

• Cognitive distancing improved task performance and value representation (higher inverse temperatures).
• Distancing increased sensitivity to negative feedback (higher loss learning rates).
• Participants shifted strategy towards greater sensitivity to negative feedback over time.

Conclusions:

• Cognitive distancing may improve mental health by altering computations in reward and loss learning.
• Practice with cognitive distancing can enhance engagement with negative information, potentially aiding symptom improvement.