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

Anna-Lena Schubert,Dirk Hagemann,Christoph Löffler,Gidon T Frischkorn

doi:10.3390/jintelligence8010001

Anna-Lena Schubert, Dirk Hagemann + Show 2 more

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https://doi.org/10.3390/jintelligence8010001

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Abstract

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined.

Highlights

Age-related changes in cognitive abilities across the lifespan follow a multi-directional pattern (Baltes 1987)
Age differences in latencies of the N2 and P3 component are well-documented (Friedman 2012; Gajewski et al 2018; Hämmerer et al 2014; Polich 1996; Price et al 2017; Schapkin et al 2014), indicating that older adults show slower higher-order cognitive and attentional processes, as both event-related potential (ERP) components have been associated with attentional processes such as memory updating (Polich 2007), cognitive control (Folstein and Van Petten 2008), and attention (Folstein and Van Petten 2008). Both fluid intelligence and age differences are substantially related to latencies of ERP components associated with higher-order cognitive processes, suggesting that the same neural mechanisms underlying age-independent variation in cognitive abilities may underlie age-dependent variation
Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes

Summary

Introduction

Age-related changes in cognitive abilities across the lifespan follow a multi-directional pattern (Baltes 1987). Fluid intelligence tends to gradually decline from young or middle adulthood (Horn and Cattell 1967; Nettelbeck and Burns 2010; Salthouse 2004), a recent study demonstrated substantial heterogeneity in the timing of developmental peaks and the subsequent decline of different fluid abilities (Hartshorne and Germine 2015). Crystallized intelligence tends to increase across the lifespan (Horn and Cattell 1967; Salthouse 2004), reflecting knowledge and abilities accumulated throughout life that remain relatively stable until late life and may be used to compensate losses in fluid abilities (Hedden et al 2005; Hedden and Gabrieli 2004).

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