Spatial Functional Models for Event-Related Potential Data, with Application to Smoking Cessation Study

In this talk, I will describe a set of spatial functional regression modeling strategies for modeling event-related potential data. These strategies attempt to flexibly account for their complex spatio-temporal structure while relating the ERPs to covariates while providing rigorous multiplicity-adjusted inference and scaling up to large studies. Various model comparison measures are introduced and described to assess which models best fit the data, and the methods are applied to a smoking cessation study to assess neurological response to different types of visual stimuli. These methods are also applicable to other types of neuroimaging data. ; Non UBC ; Unreviewed ; Author affiliation: The University of Texas M.D. Anderson Cancer Center ; Faculty