Virtual EEG: A Software-Based Electroencephalogram Designed for Undergraduate Neuroscience-Related Courses

A current topic in neuroscience addresses the link between brain activity and visual awareness. The electroencephalogram (EEG), which uses non-invasive high temporal resolution scalp recordings to measure brain activity, is a common tool used to probe this question. EEG recordings, however, are difficult to implement in the curriculum of laboratory-based courses. Thus, undergraduate students often lack experience with EEG experiments. We report here an EEG program (Virtual EEG) that can be used in undergraduate courses to analyze averaged EEG data, termed Event Related Potentials (ERPs). The program was designed so that students can generate hypothesis-driven studies that address how the brain encodes categories of visual stimuli. The Virtual EEG is a large database of EEG recordings consisting of 32 channels taken from real human subjects who were shown 256 pictures of visual stimuli. The program provides a number of possible ways to group the stimuli. After selecting the appropriate stimuli, the program constructs graphs of the ERPs. The channels can be selected for statistical analysis. Because the program uses real data, students are encouraged to interpret their results in light of previously published work. Thus, students have the opportunity to discover something new about how the brain processes visual information. This article also includes a tutorial and summarizes the results of an assessment survey. Finally, we include information regarding the companion Virtual EEG website. The Virtual EEG has been used successfully for the past six years at Indiana University with over a thousand undergraduate students in a research methods course, and the assessment results illustrate its strengths and limitations.