Intersubject analysis of fMRI data using spatial normalization.

Abstract

Most approaches to the analysis of functional magnetic resonance imaging (fMRI) datasets have employed statistical analysis of data from single subjects. Although these approaches allow reliable detection of the location of task-related signal changes, they provide no mechanism to test statistical hypotheses concerning the behavior of the subject group as a whole (Bandettini et al, 1993; Friston et al., 1994). Neuroanatomical response localization is usually accomplished by visually examining the location and extent of the observed signal change with reference to a coplanar higher resolution image in which sulcal and gyral landmarks are more easily seen. Although accurate, this approach limits the range of signal amplitude changes studied to those detectable in every subject and cannot take advantage of the increased sensitivity possible with intersubject averaging techniques.KeywordsPositron Emission TomographySpatial NormalizationBlood Oxygen Level DependentEcho Planar ImagingLingual GyrusThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.