Composite Measures of Brain Activation Predict Individual Differences in Behavioral Stroop Interference.

Abstract

The goal of the current study was to interrogate aspects of the cascade-of-control model [Banich, M. T. The Stroop effect occurs at multiple points along a cascade of control: Evidence from cognitive neuroscience approaches. Frontiers in Psychology, 10, 2164, 2019] (Banich, 2009), a neurocognitive model that posits how portions of pFC interact in a cascade-like manner to overcome interference from task-irrelevant information, and to test whether it could be used to predict individual differences in cognitive control outside the scanner. Participants (n = 62) completed two fMRI Word-Picture Stroop tasks, one containing emotional stimuli and one containing non-emotional stimuli, as well as a behavioral out-of-scanner Color-Word Stroop task at each of two time points. In a departure from the traditional approach of using a single task contrast to index neural activation across all ROIs, the current study utilized specific ROI by contrast pairings selected based on the specific level of control hypothesized by the cascade-of-control model to occur within that region. In addition, data across both tasks and both time points were combined to create composite measures of neural activation and of behavior. Consistent with the cascade-of-control model, individual differences in brain activation for specific contrasts within each of the three ROIs were associated with behavioral interference on the standard Color-Word Stroop task. Testing of alternative models revealed that these brain-behavior relationships were specific to the theoretically driven ROI by contrast pairings. Furthermore, such relationships were not observed across single-task and single-time point measures, but instead emerged from the composite measures. These findings provide evidence that brain activation observed across multiple regions of frontal cortex, each of which likely exerts cognitive control in a differential manner, is capable of predicting individual differences in behavioral performance.