Computational Cognitive Neuroscience

Mathematical psychologists and cognitive modelers develop and test quantitative theories of cognition, behavior, neuroscience, and other psychological phenomena. If you like mathematics and are looking for a challenging field in which to apply your skills, you may be interested in a career in mathematical psychology and cognitive modeling. There are quantitative theories of perception, motor performance, social interactions, memory, decision-making, learning, problem solving, and neuroscience. These theories can take the form of mathematical equations, but also of computational models and neural network simulations. Students in the mathematical psychology program at Purdue University acquire a solid background in mathematics, psychology, and statistics to use as a basis for creating mathematical, statistical, and computational models in a wide range of psychological areas ranging from low-level perception to higher-level cognitive function such as problem solving and reasoning. Researchers in the mathematical and computational cognitive science area use different research methodologies such as mathematical modeling, behavioral experiments, simulation experiments, and neuroimaging experiments. Psychology, of course, intersects every human activity, and students are encouraged to take advantage of the excellent opportunities at Purdue to delve into neighboring disciplines such as artificial intelligence, neuroimaging, neurophysiology, robotics, image and video processing, computer science, systems theory, and linguistics.

Graduate Faculty

• Ehtibar N. Dzhafarov, Ph.D.
  Methodologies: Mathematical modeling, behavioral experiments.
  Research Interests: Subjective dissimilarities among perceived stimuli, perceptual discrimination, theory of selective influences (which inputs influence which random outputs), theory of probabilistic context.
• Gregory Francis, Ph.D.
  Methodologies: Computational modeling, optimization, statistics, behavioral experiments.
  Research Interests: Visual perception, neural networks, publication bias, human factors, Internet-based educational resources.
• Sebastien Helie, Ph.D.
  Methodologies: Behavioral experiments, neuroimaging (fMRI), connectionism, computational cognitive neuroscience.
  Research Interests: The interaction between explicit and implicit knowledge, skill acquisition, automaticity, intuition.
• Zygmunt Pizlo, Ph.D.
  Methodologies: Behavioral experiments, computational modeling, robotic applications.
  Research Interests: Visual perception, visual navigation, problem solving, motor control.
• Richard J. Schweikert, Ph.D.
  Methodologies: Behavioral experiments, computer simulations, network theory.
  Research Interests: Mental process organization, short term memory, social networks, dream content analysis.