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 and 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.
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Notes
We fitted another variant of the mediation model, in which reaction times were described by a normal distribution instead of a diffusion model distribution to evaluate the benefits of diffusion modeling and the generalizability of our results (for details regarding modeling choices and results, see the online repository). The model predicted the same amount of in-sample variance in ERP latencies and intelligence test scores, but was less accurate in predicting reaction time data (75–84% of explained variance in percentiles of the RT distribution). The out-of-sample prediction of both reaction time data and cognitive ability test scores also deteriorated, with R2s ranging from − 1.79 to − 2.40 for the percentiles of the RT distribution and only 30% of explained variance in cognitive ability test scores. Taken together, these results illustrate the benefits of diffusion modeling and support the notion of a small mediating effect of drift rate, as predictability of cognitive abilities decreased when drift was not included in the model.
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Acknowledgments
The authors thank Gidon T. Frischkorn, Ramesh Srinivasan, and members of the Human Neuroscience Laboratory for their constructive criticism on work related to this manuscript.
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This work was supported by the National Science Foundation [No. 1658303] and the G.A.-Lienert-Foundation.
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Schubert, AL., Nunez, M.D., Hagemann, D. et al. Individual Differences in Cortical Processing Speed Predict Cognitive Abilities: a Model-Based Cognitive Neuroscience Account. Comput Brain Behav 2, 64–84 (2019). https://doi.org/10.1007/s42113-018-0021-5
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DOI: https://doi.org/10.1007/s42113-018-0021-5