As part of our larger project on Real Time Classification of Cognitive States, we are developing methods of statistical pattern analysis (machine learning) applied to multimodal imaging data to correctly identify cognitive processes.

• Common Component Classification - What can be learned from machine learning?
• Categorization and Generation of group-wide independent components in fMRI using clustering
• Naïve Bayes Classification of Belief versus Disbelief using Event Related Neuroimaging Data
• Classification of Schizophrenic and Normal Resting State fMRI scans using Temporal Network Associations
• Real-Time Decoding (MLINI Conference 2011) paper - or - Poster