A model-based cognitive neuroscience account of cognitive control

Cognitive control processes play an important role in many substantial psychological theories, but are hard to reliably and validly measure on the subject-level (Hedge et al., 2018; Rouder et al., 2019). Therefore, associations between individual differences in cognitive control and other variables are often inconsistent. Here we present a model-based cognitive neuroscience approach of cognitive control in which we integrated a mathematical model– the dual-stage two-phase model (Hübner et al., 2010) – with electrophysiological correlates of selective attention. We analyzed data from 149 participants who completed the Eriksen Flanker task while their EEG was recorded. We used structural equation modeling to a) improve the reliability and precision subject-level estimates by modeling them on a latent level and b) directly test competing theoretical higher-order linking structures between model estimates and latencies of the lateralized readiness potential. We will demonstrate that model parameters and neural correlates showed convergent validity and could be meaningfully related to each other. Together, these neurocognitive process parameters jointly predicted 37 % of the variance in individual differences in higher-order cognitive abilities. We propose that model-based cognitive neuroscience approaches can be used to overcome the measurement crisis of individual differences in cognitive control.