Dimensional psychiatry: mental disorders as dysfunctions of basic learning mechanisms

Area of Science:

• Neurobiology
• Computational Psychiatry
• Learning Mechanisms

Background:

• Current disease classification systems list over 300 mental disorders, but distinct neurobiological correlates for each are questioned.
• Basic dimensions of mental dysfunction, such as alterations in reinforcement learning, may underlie various syndromes.
• Individual vulnerability and psychosocial stress interact with these basic dimensions to contribute to distress.

Purpose of the Study:

• To support the idea that basic dimensions of mental dysfunction, like reinforcement learning alterations, can be identified.
• To propose that computational modeling of learning behavior can identify specific alterations in decision-making and their neurobiological correlates.
• To suggest a shift in neurobiological research focus from single disorders to these fundamental dimensions.

Main Methods:

• Computational modeling of learning behavior to identify alterations in reinforcement-based decision-making.
• Analyzing neurobiological correlates associated with learning mechanisms in addiction, schizophrenia, and depression.
• Examining Pavlovian-to-instrumental transfer, reward prediction errors, and their brain activation patterns.

Main Results:

• Attribution of salience to drug cues in addiction can increase habitual decision-making via Pavlovian-to-instrumental transfer, linked to dopamine dysfunction.
• Schizophrenia shows reduced reward prediction error encoding in the ventral striatum and compensatory frontal cortex activation.
• Depression involves reduced ventral striatum activation, stress-axis activation, and altered amygdala activity, interacting with serotonin transporter availability.

Conclusions:

• Basic learning mechanisms (e.g., conditioning, transfer) represent a fundamental dimension of mental disorders.
• Computational modeling provides a framework to mechanistically characterize these dimensions and their neurobiological underpinnings.
• Research should focus on these basic dimensions, comparable across multiple mental disorders, rather than solely on traditional diagnostic categories.