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Abstract

Intelligence is one of the most studied constructs in psychological research and fascinates scientists and the general public alike. Accordingly, researchers have spent decades trying to identify the processes underlying individual differences in intelligence, eventually proposing two widely accepted candidates: the information processing speed (IPS; also referred to as mental speed) and the working memory capacity (WMC). Research consistently shows that higher intelligence is associated with greater speed of information processing on the one hand, and higher WMC on the other. While this nomological network is well established, recent findings on the measurement of WMC and IPS suggest that further research could refine our understanding of this relationship. Thus, the central aim of this dissertation is to gain insights into the processes underlying individual differences in intelligence by integrating recent findings from different streams of cognitive psychology, neuroscience, and intelligence research. I propose that, in order to gain new insights, we must first improve our understanding of the measures used, in particular WMC and IPS, and secondly examine the boundary conditions under which the respective correlations occur. In line with this agenda, three central research approaches are outlined as part of this dissertation: 1) First, to enhance our understanding of the processes involved in WM, I examined the neurophysiological representation of WM tasks commonly used to measure WMC. 2) Second, to improve the measurement of IPS, I investigated the conditions under which researchers may obtain reliable and valid neurophysiological indicators of IPS. 3) Third, I tested the boundary conditions of the relationship between IPS, WMC, and intelligence. Together, this dissertation provides guidance for intelligence research and allows conclusions to be drawn about the nature of the mechanisms underlying intelligence. In particular, the findings suggest that a) general short-term maintenance may account for the relationship between WMC and intelligence, b) analytical decisions affect the validity and reliability of neurocognitive IPS measurements, supporting the use of latent modeling, and c) the speed of decision-related processes is most likely the driver of the relationship between IPS and intelligence.