Disentangling Mental Speed, Working Memory Capacity, and Fluid Intelligence
Final Report Abstract
The aim of this project was to dissociate human cognitive abilities to improve our understanding why and to what extent ability measure are related with each other. As a starting point, we considered the well-known finding that mental speed tests predict intelligence the better the more complex they are. We hypothesized that task complexity results from requirements on working memory capacity (WMC) in the speed test. In turn, WMC has been postulated to be determined by requirements on bindings (relational integration), secondary memory (activated long-term memory), and executive attention, depending on theoretical stance. We tested these predictions by experimentally manipulating WM requirements in computerized speed measures in line with these theories. Individual differences obtained in these measures were decomposed by means of bifactor CFA. This allowed to dissociate individual differences in the respective WM functions from basic speed of processing. Next, these purified factors were used as predictors of cognitive ability, namely WMC, fluid (Gf) and crystalized (Gc) intelligence. Results showed that binding, executive attention, and secondary memory could be dissociated from basic speed. Further, all factors contributed to cognitive ability, with binding a little stronger than the other WM requirements. Predictions of mental speed varied depending on the kind of task used, confirming the multi-facetted nature of this construct. Generally, results indicate that the underpinnings of human ability are complex and numerous factors may exert in influence, some more some less. Another aim was to test the effects of speed pressure in ability assessment. To this end, we manipulated trial-wise response deadlines in ability tests. While this manipulation exerted some effects on response times and marginal effects on accuracy, it did not affect substantially validity of the ability tests from an individual-differences perspective. However, self-paced speediness turned out to be clearly related with the accuracy of responding. Conditional accuracy functions revealed that maximal accuracy was reached if person ability and item difficulty were in congruence, while lower accuracy resulted when speed was either too fast or too slow. The increasing part of the function can be reconciled with beneficial effects of investing more time into tasks processing, whereas the decreasing part may indicate slow guessing if participants cannot solve the task. Additionally, we tested relations of non-cognitive factors with performance in ability assessment. Supporting the OFCI model of intelligence development, we found Openness to be the only personality trait to be consistently but very moderately related with WMC as a relatively pure indicator of fluid intelligence. Moreover, we tested effects of emotional and motivational states on variation in task performance across the research battery. This revealed some moderate relations that could be reconciled with theory. However, the effects were generally weak, indicating no major threat to the validity of the ability measures. Finally, we conducted a couple more analyses that underscore the complexity of the mental speed construct and the supposedly elementary tasks used for its assessment. This shed light at the moderators and the circumstances under which meaningful relations are observed with higher cognitive abilities.
Publications
- (2016). Modeling mental speed: Decomposing response time distributions in elementary cognitive tasks and relations with working memory capacity and fluid intelligence. Journal of Intelligence, 4(13), 1-23
Schmitz, F., & Wilhelm, O.
(See online at https://doi.org/10.3390/jintelligence4040013) - (2018). Scoring alternatives for mental speed tests: Measurement issues and validity for working memory capacity and the attentional blink effect. Journal of Intelligence, 6(47), 1-30
Schmitz, F., Rotter, D., & Wilhelm, O.
(See online at https://doi.org/10.3390/jintelligence6040047) - (2019). Mene mene tekel upharsin: Clerical speed and elementary cognitive speed are different by virtue of test mode only. Journal of Intelligence, 7(3), 16
Schmitz, F., & Wilhelm, O.
(See online at https://doi.org/10.3390/jintelligence7030016) - (2019). The Effect of Stimulus Response Compatibility on the Association of Fluid Intelligence and Working Memory with Choice Reaction Times. Journal of Cognition, 2(1):1-19
Hülür, G., Keye-Ehing, D., Oberauer, K., Wilhelm, O.
(See online at https://doi.org/10.5334/joc.66) - (2020). Decomposing alpha and 1/f brain activities reveals their differential associations with cognitive processing speed. NeuroImage, 205, 116304
Ouyang, G., Hildebrandt, A., Schmitz, F., & Herrmann, C. S.
(See online at https://doi.org/10.1016/j.neuroimage.2019.116304) - (2021). Binding costs in processing efficiency as determinants of cognitive ability. Journal of Intelligence, 9(2), 18
Goecke, B., Schmitz, F., & Wilhelm, O.
(See online at https://doi.org/10.3390/jintelligence9020018) - (2021). Cognitive ability and personality: Testing broad to nuanced associations with a smartphone app. Intelligence, 88, 101578
Rozgonjuk, D.f, Schmitz, F. f, Kannen, C., & Montag, C.
(See online at https://doi.org/10.1016/j.intell.2021.101578) - (2021). To predict the future, consider the past: Revisiting Carroll (1993) as a guide to the future of intelligence research. Intelligence, 89, 101585
Wilhelm, O., & Kyllonen, P.
(See online at https://doi.org/10.1016/j.intell.2021.101585)
