Neural decoding of social attitudes: How can neuroimaging methods contribute to psychological research? Seminar

Event details

In this talk, I will discuss two studies which highlight the utility of multi-voxel pattern analysis (MVPA) of neuroimaging data to solve fundamental questions in social psychology. The first study investigated whether we are able to predict individuals' attitudes toward other people just by looking at their brain activations (i.e., neural measure of attitude). The second study investigated whether implicit self-esteem (as measured by an Implicit Association Test [IAT]) is associated with robust neural representations, thus aiming to establish the neural validity of the implicit self-esteem measure. Our results indicated both attitude toward other people and implicit self-esteem can be reliably decoded from brain activations, suggesting the potential utility of this method to 1) objectively measure individual’s attitude and 2) test the validity of a behavioral measure without relying on other behavioral measures.