title: Vascular contributions to pattern analysis: comparing gradient and spin echo fMRI at 3T.
abstract: Multivariate pattern analysis is often assumed to rely on signals that directly reflect differences in the distribution of particular neural populations. The source of the signal used in these analyses remains unclear however, and an alternative model suggests that signal from larger draining veins may play a significant role. The current study was designed to investigate the vascular contribution to pattern analyses at 3T by comparing the results obtained from gradient and spin echo data. Classification analyses were carried out comparing line orientations in V1, tone frequencies in A1, and responses from different fingers in M1. In all cases, classification accuracy in the spin echo data was not significantly different from chance. In contrast, classification accuracies in the gradient echo data were significantly above chance, and significantly higher than the accuracies observed for the spin echo data. These results suggest that at the field strength and spatial resolution used for the majority of fMRI studies, a considerable proportion of the signal used by pattern analysis originates in the vasculature.
authors.affiliation: MRC Cognition and Brain Sciences Unit, Cambridge, UK. russell.thompson@mrc-cbu.cam.ac.uk
authors.forename: Russell
authors.initials: R
authors.lastname: Thompson
authors.forename: Marta
authors.initials: M
authors.lastname: Correia
authors.forename: Rhodri
authors.initials: R
authors.lastname: Cusack
mesh_terms: D000328:Adult; D001921:Brain / Q000098:blood supply* / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D002560:Cerebrovascular Circulation / Q000502:physiology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D055815:Young Adult