Modeling Placebo Response Using EEG Data

• Activity Number: 243
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Mental Health Statistics Section
• Author(s): Bei Jiang* and Eva Petkova and Thaddeus Tarpey and R. Todd Ogden
• Companies: Columbia University/New York University and New York University School of Medicine and Wright State University and Columbia University
• Keywords: functional data ; placebo response ; brain imaging data ; SVM

Abstract

There is growing evidence that individual differences among depression patients on Electrophysiology (EEG), fMRI and other brain imaging measurements may be predictive of potential treatment response. In this talk we discuss approaches to identifying potential placebo responders, i.e., a subgroup who benefits sufficiently from inactive drug treatments, using EEG measurements as a functional predictor. We propose to formulate this task as a statistical learning problem with support vector machine (SVM) classifier. Our approach will be evaluated through simulations and will be applied to data from a large clinical trial for patients with major depressive disorders.