Individual Differences in Cortical Processing Speed Predict Cognitive Abilities: a Model-Based Cognitive Neuroscience Account

Abstract

Previous research has shown that individuals with greater cognitive abilities display a greater speed of higher-order cognitive processing. These results suggest that speeded neural information-processing may facilitate evidence accumulation during decision making and memory updating and thus yield advantages in general cognitive abilities. We used a hierarchical Bayesian cognitive modeling approach to test the hypothesis that individual differences in the velocity of evidence accumulation mediate the relationship between neural processing speed and cognitive abilities. We found that a higher neural speed predicted both the velocity of evidence accumulation across behavioral tasks as well as cognitive ability test scores. However, only a negligible part of the association between neural processing speed and cognitive abilities was mediated by individual differences in the velocity of evidence accumulation. The model demonstrated impressive forecasting abilities by predicting 36% of individual variation in cognitive ability test scores in an entirely new sample solely based on their electrophysiological and behavioral data. Our results suggest that individual differences in neural processing speed might affect a plethora of higher-order cognitive processes, that only in concert explain the large association between neural processing speed and cognitive abilities, instead of the effect being entirely explained by differences in evidence accumulation speeds.

Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

“…We replicated the finding that age differences did not account for correlation between reaction times and fluid intelligence (Bors and Forrin 1995) and could show that this also held true for the relationships of drift rates and ERP latencies with fluid intelligence. This is fairly important, because it demonstrates that it is unlikely that the previously reported associations of drift rates and ERP latencies with intelligence (Bazana and Stelmack 2002;McGarry-Roberts et al 1992;Ratcliff et al 2010;Schmiedek et al 2007;Schmitz and Wilhelm 2016;Schmitz et al 2018;Schubert et al 2015;Troche et al 2009;Ratcliff et al 2011;Troche et al 2015;Schubert et al 2017;Schubert et al 2019) can be attributed to age differences as a confounding factor. Instead, our results suggest that these associations are largely invariant with regard to age, although our results do not rule out the possibility that the form and strength of these associations might change across the lifespan.…”

“…Because the diffusion model provides a process-based account of decision making that allows the measurement and mathematical separation of different processes involved in decision making, it has become increasingly popular in individual differences and aging research (e.g., Dirk et al 2017;Dully et al 2018;Frischkorn and Schubert 2018;Huff and Aschenbrenner 2018;Nunez et al 2015;Ratcliff et al 2003;Schubert et al 2015Schubert et al , 2016Schubert et al , 2019Schmiedek et al 2007;Schmitz and Wilhelm 2016;Schmitz et al 2018;Spaniol et al 2008;Yap et al 2012;Ratcliff et al 2004;Ratcliff et al 2010;Ratcliff et al 2011). The drift rate parameter in particular has been consistently associated with intelligence (Ratcliff et al 2010(Ratcliff et al , 2011Schmiedek et al 2007;Schmitz and Wilhelm 2016;Schmitz et al 2018;Schubert et al 2015;Schubert et al 2019), suggesting that smarter individuals benefit from a higher rate of evidence accumulation. In comparison, there is no consistent evidence that more intelligent individuals also show shifts in boundary separation or shorter non-decision times in comparison to less intelligent individuals (but see, Ratcliff et al 2010;Ratcliff et al 2011;Schmiedek et al 2007).…”

Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

“…Because the diffusion model provides a process-based account of decision making that allows the measurement and mathematical separation of different processes involved in decision making, it has become increasingly popular in individual differences and aging research [e.g., [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47]. The drift rate parameter in particular has been consistently associated with intelligence [38][39][40][42][43][44][45], suggesting that smarter individuals benefit from a higher rate of evidence accumulation. In comparison, there is no consistent evidence that more intelligent individuals also show shifts in boundary separation or shorter non-decision times in comparison to less intelligent individuals [but see 38,39,43].…”

Unraveling the relation between EEG-correlates of attentional orienting and sound localization performance: a diffusion model approach

“…Previous applications of the diffusion model have shown that it can validly describe decision making in four-choice alternative response tasks (Schubert et al, 2015;Schubert, Nunez, Hagemann, & Vandekerckhove, 2018b). To eliminate outliers that could bias model results (Voss, Voss, & Lerche, 2015), extremely fast (< 150 ms) and extremely slow (> 3000 ms) RTs were discarded.…”

“…In the present study, the diffusion modelling approach (Ratcliff, 1978) was applied, allowing for a more detailed understanding of behavioral patterns in discrimination tasks (for recent reviews, see Ratcliff & McKoon, 2008;Voss, Nagler, & Lerche, 2013). Although diffusion models are still only rarely used in cognitive neuroscience research (see, e.g., Nunez, Vandekerckhove, & Srinivasan, 2017;Philiastides, Ratcliff, & Sajda, 2006;Ratcliff, Philiastides, & Sajda, 2009;Schubert, Hagemann, Voss, Schankin, & Bergmann, 2015;Schubert, Nunez, Hagemann, & Vandekerckhove, 2018a), the interest in and the application of this methodological approach has increased considerably during the past decade. The general purpose of diffusion models is to decompose the cognitive processes underlying a binary decision.…”