Neurocognitive Psychometrics of Intelligence: How Measurement Advancements Unveiled the Role of Mental Speed in Intelligence Differences

Abstract

More intelligent individuals typically show faster reaction times. However, individual differences in reaction times do not represent individual differences in a single cognitive process but in multiple cognitive processes. Thus, it is unclear whether the association between mental speed and intelligence reflects advantages in a specific cognitive process or in general processing speed. In this article, we present a neurocognitive-psychometrics account of mental speed that decomposes the relationship between mental speed and intelligence. We summarize research employing mathematical models of cognition and chronometric analyses of neural processing to identify distinct stages of information processing strongly related to intelligence differences. Evidence from both approaches suggests that the speed of higher-order processing is greater in smarter individuals, which may reflect advantages in the structural and functional organization of brain networks. Adopting a similar neurocognitive-psychometrics approach for other cognitive processes associated with intelligence (e.g., working memory or executive control) may refine our understanding of the basic cognitive processes of intelligence.

Impaired Evidence Accumulation as a Transdiagnostic Vulnerability Factor in Psychopathology

“…Interestingly, while the EEA construct has been extensively invoked to explain task performance in hundreds of studies, the mechanistic basis of individual-differences in EEA, and how these differences relate to differences in other cognitive constructs, are much less explored (but see 29,48). Several studies using perceptual decision tasks find drift rates are related to general intelligence [54][55][56][57] , similar to the pattern we found in the present study. But, again similar to prior work, the correlations we found in this study between EEA and general intelligence were moderate in size, with individuals' general intelligence explaining less than 25% of the variance in EEA in this sample.…”

The Evidence for Geary’s Theory on the Role of Mitochondrial Functioning in Human Intelligence Is Not Entirely Convincing

“…While our reservations based on neurocognitive and cognitive enhancement research only concerned certain parts of Geary’s theory, the discussed evidence from behavioral genetics research questioned a core assumption of the theory, namely that variations in mitochondrial DNA have an effect on mitochondrial functioning, which, in turn, has an effect on human intelligence. While we cannot and do not want to rule out that some amount of variation in human intelligence can be attributed to individual differences in mitochondrial functioning, the findings discussed above let us conclude that there are likely many more factors contributing to individual differences in intelligence, ranging from genes (e.g., genome-wide polygenic scores explain up to 10% of variance in intelligence; ( Plomin and von Stumm 2018 )) to structural (e.g., white-matter tract integrity in the forceps minor, the corticospinal tract, the anterior thalamic radiation, the right superior longitudinal fasciculus, the uncinate fasciculus, the rostrolateral prefrontal cortex, and the inferior parietal lobe; ( Booth et al 2013 ; Pineda-Pardo et al 2016 ; Kievit et al 2016 ; Tamnes et al 2010 ; Wendelken et al 2017 )) and functional brain characteristics (e.g., activation of fronto-parietal brain networks and functional connectivity related to higher-order cognitive processes; ( Basten et al 2015 ; Jung and Haier 2007 ; Hilger et al 2017 ; Schubert et al 2020 )), mediating cognitive processes (e.g., processing speed, attentional control, working memory; ( Engle 2018 ; Kovacs and Conway 2016 ; Schubert and Frischkorn 2020 )), environmental influences (e.g., prenatally available polyunsaturated fatty acids; ( Cohen et al 2005 ; Lassek and Gaulin 2008 )), and developmental interdependencies ( Van Der Maas et al 2006 ).…”

Do Non-Decision Times Mediate the Association between Age and Intelligence across Different Content and Process Domains?

“…As the authors did not find non-decision time to be related to early ERP latencies that might reflect encoding (i.e., N1 and P1), they proposed two possible (contrasting) explanations for the observed mediation effect of non-decision time: First, differences in non-decision time might reflect age-related differences in anterior brain regions that are associated with motor planning and response execution. Importantly, the same anterior brain regions might also affect latencies of ERP components occurring later in the stream of information-processing such as the P3 that are closely related to higher-order processing and intelligence ( Schubert and Frischkorn 2020 ; Schubert et al 2017 ). Second, the mediation via non-decision time might reflect the influence of non-decisional processes on the intelligence test scores because the test used (Berlin Intelligence Structure Test; Jäger et al 1997 ) has strict time limits for each task and scores are thus affected by the speed of motor response execution (i.e., hand-writing).…”