Decomposing decision components in the stop-signal task: a model-based approach to individual differences in...

Area of Science:

• Cognitive Neuroscience
• Neuroimaging
• Decision Science

Background:

• The stop-signal task assesses inhibitory control by requiring participants to suppress prepotent responses.
• Individual differences in inhibitory control are associated with distinct neural systems.
• Understanding these differences is crucial for comprehending decision-making variations.

Purpose of the Study:

• To investigate the relationship between individual differences in inhibitory control and other decision-making components.
• To explore how measures of decision making, derived from a drift-diffusion model, correlate with neural activation patterns.

Main Methods:

• A drift-diffusion model was applied to go-trial data from the stop-signal task for 123 participants.
• Measures of caution, motor execution time, and stimulus processing speed were extracted.
• Functional magnetic resonance imaging (fMRI) data were analyzed to correlate these measures with neural activation.

Main Results:

• Faster stimulus processing speed correlated with increased activation in the right frontal pole during both go and stop trials.
• Stimulus processing speed also correlated with activation in regions associated with inhibitory control (right inferior frontal gyrus, medial frontal gyrus, basal ganglia) on stop trials.
• Individual differences in motor execution time correlated with activation in the right parietal cortex.

Conclusions:

• A significant neural relationship exists between stimulus processing speed and inhibitory control.
• This model-based approach offers new insights into the interplay of decision-making components within inhibitory control.
• Findings raise questions about performance adjustments and neural underpinnings of inhibitory deficits in psychopathology.