Mathematical Psychology

Within the Cognitive Psychology area at Indiana University, a central theme of many (but not all) of the faculty members involves mathematical-psychology approaches. Mathematical psychology encourages and develops the use of mathematical and computational modeling in psychology, cognition, and cognitive science. Formal mathematical and computer-simulation models are developed to express theories of mental processes and behavior. Such models are tested using data from laboratory experiments, data from web-based experiments, or data sets (often very large) from real-world sources.

• human learning and memory
• categorization
• decision processes
• choice
• semantic representation
• quantum cognition
• perception and action
• dynamics
• complex cognitive processes
• response-time modeling
• network and deep-learning models
• Bayesian modeling and statistics
• computer simulation
• data science and statistical techniques

Students who intend to specialize in Mathematical/Cognitive Psychology are expected to have a research interest in at least one of the major content areas of cognitive psychology. Students are also encouraged to undertake ancillary study in mathematics, statistics, computer science, or cognitive science.

The curriculum in Mathematical Psychology deals with progressively deeper and more advanced application of mathematical thinking in psychology. Students planning to double-major in Psychological and Brain Sciences and Cognitive Science would plan to take the required Q550 (Models in Cognitive Science). Mathematically oriented courses and seminars in specialized topics such as learning, memory, attention, information processing, speech perception, psycholinguistics, perception, decision making, choice, categorization, scaling, and test theory are offered on a regular basis, as are advanced courses and seminars in computer applications, multivariate analysis, and advanced statistical theory.