Exploring the mind: Integrating questionnaires and fMRI

Esther Salazar, Ryan Bogdan, Adam Gorka, Ahmad R. Hariri, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

A new model is developed for joint analysis of ordered, categorical, real and count data. The ordered and categorical data are answers to questionnaires, the (word) count data correspond to the text questions from the questionnaires, and the real data correspond to fMRI responses for each subject. The Bayesian model employs the von Mises distribution in a novel manner to infer sparse graphical models jointly across people, questions, fMRI stimuli and brain region, with this integrated within a new matrix factorization based on latent binary features. The model is compared with simpler alternatives on two real datasets. We also demonstrate the ability to predict the response of the brain to visual stimuli (as measured by fMRI), based on knowledge of how the associated person answered classical questionnaires. Copyright 2013 by the author(s).
Original languageEnglish (US)
Title of host publication30th International Conference on Machine Learning, ICML 2013
PublisherInternational Machine Learning Society (IMLS)rasmussen@ptd.net
Pages921-929
Number of pages9
StatePublished - Jan 1 2013
Externally publishedYes

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