title: Region of interest based analysis of functional imaging data.
abstract: fMRI analysis techniques are presented that test functional hypotheses at the region of interest (ROI) level. An SPM-compatible Matlab toolbox has been developed that allows the creation of subject-specific ROI masks based on anatomical markers and the testing of functional hypotheses on the regional response using multivariate time-series analysis techniques. The combined application of subject-specific ROI definition and region-level functional analysis is shown to appropriately compensate for intersubject anatomical variability, offering finer localization and increased sensitivity to task-related effects than standard techniques based on whole-brain normalization and voxel or cluster-level functional analysis, while providing a more direct link between discrete brain region hypotheses and the statistical analyses used to test them.
authors.affiliation: Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA 02215, USA. alfnie@bu.edu
authors.forename: Alfonso
authors.initials: A
authors.lastname: Nieto-Castanon
authors.forename: Satrajit S
authors.initials: SS
authors.lastname: Ghosh
authors.forename: Jason A
authors.initials: JA
authors.lastname: Tourville
authors.forename: Frank H
authors.initials: FH
authors.lastname: Guenther
mesh_terms: D016477:Artifacts; D001931:Brain Mapping / Q000379:methods*; D002540:Cerebral Cortex / Q000033:anatomy & histology / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008432:Mathematical Computing; D009010:Monte Carlo Method; D015999:Multivariate Analysis; D016571:Neural Networks, Computer