SURF Mentoring

Potential projects/topics: The visual world around us is beautiful and complex, but our brains have a limited processing capacity. To achieve our goals, we need to select only a subset of information to pay attention to and remember. My lab uses cognitive neuroscience methods (EEG, fMRI) and innovative behavioral measures to address central questions about how we succeed (and fail) at deploying our limited attentional resources. For example, how do we successfully ignore irrelevant information that competes for our limited attention? How can we best detect (and correct) failures of attention that cascade into failures of memory?

Example project: Modeling fluctuations of attention over time
Example project: Measuring the contents of working memory using EEG

Potential skills gained: experimental design, data analysis, human subjects research, theoretical models of attention and memory (depending on student interest/prior experience: scientific programming, EEG and eye-tracking methods)

Required qualifications: most relevant majors: neuroscience, psychology, cognitive science

other potentially relevant majors/minors: computer science, statistics, bioengineering

specific skills that would be helpful (though not strictly required): some previous exposure to scientific programming (MATLAB, Python), data analysis (R, Python) or web-based presentation of stimuli (Javascript)

Direct mentor: Faculty/P.I.