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.