%0 Generic
%A Löffler, Christoph
%C Heidelberg
%D 2025
%F heidok:36772
%R 10.11588/heidok.00036772
%T Measuring Cognitive Control through Neurocognitive Process   Parameters to Understand Individual Differences in Intelligence
%U https://archiv.ub.uni-heidelberg.de/volltextserver/36772/
%X Previous research has shown that both individual differences in working memory capacity (WMC) and differences in information processing speed can each explain more than 50% of the variance in intelligence. Accordingly, there has to be at least one shared process underlying these two predictors of intelligence that contributes to explaining interindividual differences in higher-order cognitive processes. In the present dissertation, cognitive control processes are examined in detail to investigate whether they can bridge the gap between WMC, information processing speed, and intelligence. Various theories of working memory conceptualize cognitive control processes as underlying mechanisms that determine differences in WMC and consider them strong predictors of intelligence. In recent years, current research has also increasingly discussed the contribution of cognitive control processes to explaining individual differences in information processing speed. Conducting three studies and employing various neurocognitive process parameters derived from behavioral and psychophysiological data from the EEG, we investigated the role of cognitive control processes in order to better understand the relationships between WMC, information processing speed, and intelligence. In this context, we examined whether cognitive control processes can account for the correlational pattern of the Worst Performance Rule (WPR; Manuscript 1). The WPR is a phenomenon showing that slower intraindividual reaction times in a task are more predictive of intelligence than medium or fast responses. Furthermore, we examined the factor structure of several cognitive control abilities (executive functions) and their specific contributions to explaining differences in WMC, information processing speed, and intelligence, as well as their interrelations. We conducted this examination at the behavioral level using the drift parameter from the drift-diffusion model (Manuscript 2) and at the psychophysiological level using event-related potentials from the EEG (Manuscript 3). Our results indicated that interindividual differences in cognitive control processes partially accounted for the WPR. However, the effects were very small, and the data still exhibited a significant WPR pattern after controlling for cognitive control. Moreover, it became evident that valid measurement of cognitive control processes is challenging. We found that classical cognitive control tasks commonly used in research primarily capture task-general processes in a hierarchical factor, which generally represented information processing. The findings of this dissertation shed critical light on previous cognitive control research and indicate that future research should focus on more precise definitions, the development of specific mathematical models for more accurate measurement, and the development of suitable tasks to validly capture cognitive control processes.