title: Detecting auditory cortex: a comparison of SPM and WSPM.
abstract: Nowadays, statistical parametric mapping (SPM) is the most widely-used method for the analysis of fMRI data. As the progress of SPM, some researchers have proposed WSPM, a new method based on wavelet transform. The advantage of WSPM is that it can not only reduce the spatial bias of SPM, but also shows the closer result to the true active areas. In this paper, there are eight sets of fMRI data stimulated by voice, from which we want to figure out the active brain areas under the stimulation. To confirm the active areas, we used the two methods based on different smoothing methods and made comparison. WSPM was showed to have stronger control of type-I error (false positives) than SPM.
authors.affiliation: College of Biomedical Engineering, Capital Medical University, Beijing, China. sunshinelj@126.com
authors.forename: Shaojie
authors.initials: S
authors.lastname: Sun
authors.forename: Liuhong
authors.initials: L
authors.lastname: Zhu
authors.forename: Shuqian
authors.initials: S
authors.lastname: Luo
mesh_terms: D000161:Acoustic Stimulation; D000465:Algorithms; D001303:Auditory Cortex / Q000033:anatomy & histology* / Q000473:pathology; D001921:Brain / Q000033:anatomy & histology / Q000473:pathology; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D012372:ROC Curve; D015203:Reproducibility of Results