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11:00 - 12:30
Parallel sessions 5
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11:00 - 12:30
Room: HSZ - N4
Chair/s:
Nicola Schneider
The diffusion decision model (DDM) is a mathematical framework that jointly describes choice behavior and response time distributions, offering a process-level account of how people make decisions. Conceptualizing decisions as the accumulation of noisy evidence, the DDM has provided insights into the cognitive mechanisms underlying perception, attention, memory, and higher-order decision-making. Its flexibility and explanatory power have made it one of the most widely used tools in experimental psychology, bridging cognitive theory, mathematical modeling, and empirical research.
The explanatory power and versatility of the DDM have made it indispensable for testing psychological theories. By illustrating how the model bridges the gap between quantitative modeling and psychological theory, we aim to highlight the value of DDMs for understanding individual and group differences, clinical dysfunctions, and social-cognitive processes. Together, these studies illustrate the breadth of DDM applications across experimental psychology and highlight how cognitive modeling can inform theoretical and applied research alike.
This symposium is the second of a two-part series on DDMs at TeaP. While Part I emphasizes model development, theoretical extensions, and computational innovation, Part II turns to applied research, demonstrating how DDMs can help us better understand cognitive processes across different populations and domains. By being open to scholars from all areas of experimental psychology, the series offers a forum for presenting new ideas, establishing collaborations, and identifying future directions in the modeling of human cognition.
Submission 221
Reconciling Inconsistent Age Effects in Speed of Information Processing: The Role of Task Difficulty
SymposiumTalk-02
Presented by: Veronika Lerche
Veronika Lerche
Kiel University, Germany
Previous research in age-related cognition has shown that older adults typically exhibit longer response times than younger adults, while their accuracy is often comparable. To better understand these differences, diffusion model analyses have been applied and have consistently revealed two key patterns: older adults tend to adopt larger threshold separations and show longer nondecision times. Findings regarding drift rate, a parameter indexing the speed of information accumulation, have been less consistent. Some studies reported higher drift rates for younger adults, whereas others found no age differences or even reversed effects. In the present research, we identified a moderating factor that may account for these inconsistencies. In Study 1, young and older participants completed three perceptual and three verbal response time tasks, each with two different levels of difficulty. As expected, we replicated the typical age-related differences in threshold separation and nondecision time. More importantly, an interaction between age and task difficulty emerged for drift rate: although younger adults generally processed information faster, this advantage was markedly reduced for more difficult stimuli. Study 2 replicated this pattern for the perceptual tasks, but not for three recognition memory tasks. These results suggest that increased task difficulty may attenuate age-related differences in information processing speed for perceptual and verbal tasks, but not for recognition memory tasks.