Effortful control is associated with executive attention: A computational study

The moderating role of cognitive fusion in the relationship between trait and state anger in episodic migraine, chronic migraine and healthy controls

This study aimed to examine the combined moderating role of cognitive fusion and migraine in the relationship between trait and state anger. A total of 213 patients diagnosed with chronic migraine, 136 with episodic migraine and 131 healthy controls, participated in the study. Interactions between trait anger and cognitive fusion, and between trait anger and group (chronic migraine, episodic migraine, and controls) on state anger were examined using SPSS PROCESS. Participants with chronic or episodic migraines showed higher levels of trait anger and cognitive fusion than controls. Only chronic migraine patients reported higher levels of state anger than controls. At low levels of cognitive fusion, there was no association between trait anger and state anger; however, at moderate levels, the relationship was significant for people with chronic or episodic migraines. At higher levels of cognitive fusion, the relationship also was significant in healthy individuals. These findings suggest that frequent anger in migraine may be explained by higher trait anger and cognitive fusion, which may occur in the context of an inhibitory deficit related to effortful control. In migraineurs, inhibitory dysfunction may exacerbate cognitive fusion which may, in turn, reinforce negative interpretations and facilitate the transition from trait to situational anger, even at moderate levels of fusion. Consequently, repeated experiences of anger may strengthen an angry disposition. This study highlights the role of cognitive fusion in anger in migraine and its potential clinical relevance given its modifiable nature.

Psychometrics of drift-diffusion model parameters derived from the Eriksen flanker task: Reliability and validity in two independent samples

The flanker task is a widely used measure of cognitive control abilities. Drift-diffusion modeling of flanker task behavior can yield separable parameters of cognitive control-related subprocesses, but the parameters' psychometrics are not well-established. We examined the reliability and validity of four behavioral measures: (1) raw accuracy, (2) reaction time (RT) interference, (3) NIH Toolbox flanker score, and (4) two drift-diffusion model (DDM) parameters-drift rate and boundary separation-capturing evidence accumulation efficiency and speed-accuracy trade-off, respectively. Participants from two independent studies - one cross-sectional (N = 381) and one with three timepoints (N = 83) - completed the flanker task while electroencephalography data were collected. Across both studies, drift rate and boundary separation demonstrated comparable split-half and test-retest reliability to accuracy, RT interference, and NIH Toolbox flanker score, but better incremental convergent validity with psychophysiological measures (i.e., the error-related negativity; ERN) and neuropsychological measures of cognitive control than the other behavioral indices. Greater drift rate (i.e., faster and more accurate responses) to congruent and incongruent stimuli, and smaller boundary separation to incongruent stimuli were related to 1) larger ERN amplitudes (in both studies) and 2) faster and more accurate inhibition and set-shifting over and above raw accuracy, reaction time, and NIH Toolbox flanker scores (in Study 1). Computational models, such as DDM, can parse behavioral performance into subprocesses that exhibit comparable reliability to other scoring approaches, but more meaningful relationships with other measures of cognitive control. The application of these computational models may be applied to existing data and enhance the identification of cognitive control deficits in psychiatric disorders.