This project involves measuring workload and emotion while participants view music videos. Uses the DEAP dataset as stimuli and machine learning on cognitive data to develop classification models for new brain states.
This experiment asked: “Can we measure the brain activity of consumers watching advertisements?” The project explores correlating brain activity with user experience while viewing ads to predict product success and market-readiness with a new research modality, fNIRS.
Project measures EEG activity and GSR of a participant watching the democratic and republican debates. Pilot work was proposed to TEDx Syracuse to engage and seek collaboration with the local neuroscience and political community. Measurement of electrical dermal and brain activity is used to identify cognitive metaphors that characterize conservatives and liberals.
My project measures brain states of individuals on Facebook who consider sharing trending digital media events. In a modification of Matthew Lieberman of UCLA’s experiment, this fNIRS project measures “buzz” in the brain when participants share or do not share viral or trending media.
My project has 3 experiments in an investigation of the overall neural activity of change in state suspicion (CISS). Instant messaging between partners, fNIRS measurement of state suspicion, and an experiment conducted online with authentic and fake phishing websites.
The meditation project involves using fNIRS to detect differences in brain state of individuals meditating. A collaboration with Hamilton State College faculty and students, the meditation experiment is aimed at assessing the effects of meditative states on the brain. Longitudinal studies with vulnerable populations such as trauma victims, veterans, and other local individuals is part of future work.
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