Title: "Neuroimaging-based predictive modeling of the brain and behavior"

Abstract: The fundamental goal of cognitive neuroscience is to have an understanding of human cognition in terms of the brain.  Under this goal, most studies have traditionally aimed at deducing a statistical relationship between the human brain and cognition - that is, making an inference within data we have.  Accumulating neuroimaging data such as fMRI and MEG enables us to move beyond making an inference on how the brain's functional properties correlate human cognition and behavior.  It has now been demonstrated that we can predict individuals' behaviors, and this could be achieved by computational predictive modelings. Neuroimaging-based predictive modeling, in particular, is for developing a model that can predict cognition of novel unseen individuals solely based on their brain-imaging data.  In this talk, I will discuss the computational predictive modeling of brain reorganization as well as human behavior.