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Department of Psychology

Department of Psychology

Cognition and Cognitive Neuroscience Header Image

Cognition and Cognitive Neuroscience

The Cognition and Cognitive Neuroscience (CCN) area comprises diverse faculty and students whose research investigates mental processes and their neural substrates. We are interested in understanding how those processes and substrates affect how individuals interact with the world. 

The CCN graduate program offers research training and coursework in:

  • Applied cognition and learning science
  • Attention
  • Learning and memory
  • Motor control and action
  • Neuroimaging methodologies
  • Planning and decision-making
  • Speech and language
  • Visual and auditory perception

Graduate training within the CCN area is geared toward students who wish to learn about cognitive theory and applications of cognitive science and develop skills in neuroscience, statistics, computer programming, and mathematics.

CCN faculty use and provide training in a variety of cutting-edge behavioral paradigms, computational modeling approaches, and neuroscience techniques, including electroencephalography (EEG/ERP), non-invasive transcranial stimulation methods (including tACS, tDCS, and TMS), and structural and functional magnetic resonance imaging (MRI/fMRI). Facilities include the Center for Advanced Neuroimaging, which houses our MRI scanner and MRI-compatible EEG, physiological recording, eye-tracking, and neurostimulation equipment.

Graduate students in the CCN program are most often mentored by CCN faculty. However, students can have primary mentors from any area in the Psychology department. We also mentor graduate students from other programs across campus, such as the Neuroscience Program and Genetics, Genomics, and Bioinformatics departments. 

NIH R01: How LC Integrity in Older Adults Mediates Perceptual and Memory Processes. This project aims to test the role of locus coeruleus structure and function for cognition in aging.

Co-Principal Investigator: Aaron Seitz

Co-Investigators: Ilana Bennett, Weiwei Zhang, Megan Peters

NIH RO1: A Neurocognitive Mechanism for Precision of Visual Working Memory Representations. This project aims to assess the core cognitive and neural mechanisms for maintaining precise mental representations over a few seconds in working memory.

Principal Investigator: Weiwei Zhang

NIH R21: MRI biomarkers of glial-specific metabolites and microstructure in aging. This project aims to test whether diffusion-weighted magnetic resonance spectroscopy can measure glial-specific neuroinflammation in aging.

Co-Principal Investigator: Ilana Bennett

NSF Improving Undergraduate STEM Education (I-USE): “Show me the data”: Exploring the impact of observation protocol data in changing instructor motivation and practice. This project aims to Identify how college STEM instructors make sense of classroom observation data and measure the extent to which interacting with their classroom observation data affects instructor motivation to change their teaching practices.

Co-Principal Investigator: Annie S. Ditta

  • Weiwei Zhang has published work about driving abilities in older adults that may have important implications for policies regarding driving safety.
  • Annie Ditta has studied the effects of technology in the classroom–taking photos of lecture slides may benefit memory for content in online lectures.