Clarifying Cognitive Control Deficits in Psychosis via Drift Diffusion Modeling and Attractor Dynamics

Area of Science:

• Cognitive neuroscience
• Psychopathology research
• Computational psychiatry

Background:

• Cognitive control deficits are a hallmark of psychotic psychopathology.
• Previous research often overlooks trial-to-trial variability, potentially missing key factors contributing to these deficits.

Purpose of the Study:

• To investigate the specific contributors to cognitive control deficits in individuals with psychosis using drift-diffusion models (DDMs).
• To compare the efficacy of DDM parameters versus conventional measures in differentiating between individuals with psychosis, their relatives, and controls.

Main Methods:

• Employed hierarchical drift-diffusion models (DDMs) on individual trial response and reaction time data from a dot pattern expectancy (DPX) task.
• Included 122 people with psychosis (PwP), 78 first-degree biological relatives, and 50 controls.
• Utilized classification models to compare DDM parameters with traditional measures of cognitive control.

Main Results:

• People with psychosis (PwP) exhibited slower drift rates during proactive control, indicating less efficient cue information processing.
• Both PwP and relatives showed increased nondecision times for infrequent sequences, suggesting slowed perceptual processing.
• DDM parameters, particularly drift rates in proactive control and nondecision time in reactive control, better differentiated groups than conventional measures and correlated with real-world functioning.

Conclusions:

• Slow evidence accumulation and prolonged preparatory periods are primary drivers of cognitive control deficits in psychotic psychopathology.
• These findings suggest difficulties in maintaining neural state representations, potentially due to neural excitation or connectivity issues.