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CCN Curriculum

The activities and requirements of the Cognition and Cognitive Neuroscience program are designed primarily to develop the student's competence as a researcher. They are also expected to enhance the teaching, communication, and administrative skills each student will need in his or her professional career. Along with Departmental and Graduate School requirements, Cognition and Cognitive Neuroscience students must take two courses in the program (e.g., perception or learning and memory), and one advanced seminar. Required research activities include empirical research projects, a review or theoretical research paper, and a dissertation project. Before candidacy is achieved, each student must also pass a general preliminary examination in cognition. Students may chose to augment their training with additional programs of study such as the Cognitive Science and Cognitive Neuroscience certificate program and the Formal Modeling, Mathematical Psychology, and Quantitative Methods specialization described below.

Formal Modeling, Mathematical Psychology, and Quantitative Methods

As part of their work in the Cognition and Cognitive Neuroscience program, interested students may pursue a specialization in Formal Modeling, Mathematical Psychology, and Quantitative Methods. We believe that skills in formal modeling are an important aspect of research in Cognition and Cognitive Neuroscience . The core features of the option area as follows:

  1. The student earns a master's degree in one of the mathematical sciences, such as statistics, applied mathematics, industrial and operations engineering, management information systems, or computer science.
  2. The student completes a seminar in formal modeling and methods offered by the Cognition and Cognitive Neuroscience area.
  3. The student completes a closely supervised project in which he or she can develop expert-level competence in one particular technique.

Examples of the substantive domains students have pursued in the past include, but are not limited to:

  • Decision making and judgment
  • Social interaction
  • Sensation
  • Perception
  • Motor programming
  • Human factors
  • Problem solving
  • Memory

Illustrative research techniques include: psychophysical methods, measurement theory, psychometrics, scaling procedures, computer stimulation, artificial intelligence, stochastic modeling, decision analysis, operations research and statistics.