Quantifying significance of topographical similarities of disease-related brain metabolic patterns.
Multivariate analytical routines have become increasingly popular in the study of cerebral function in health and in disease states. Spatial covariance analysis of functional neuroimaging data has been used to identify and validate characteristic topographies associated with specific brain disorders. Voxel-wise correlations can be used to assess similarities and differences that exist between covariance topographies. While the magnitude of the resulting topographical correlations is critical, statistical significance can be difficult to determine in the setting of large data vectors (comprised of over 100,000 voxel weights) and substantial autocorrelation effects. Here, we propose a novel method to determine the p-value of such correlations using pseudo-random network simulations.
Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, United States of America.
Ji Hyun
JH
Ko
Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, United States of America.
Phoebe
P
Spetsieris
Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, United States of America.
Yilong
Y
Ma
Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, United States of America.
Vijay
V
Dhawan
Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, United States of America.
David
D
Eidelberg
D001921:Brain / Q000000981:diagnostic imaging / Q000378:metabolism; D001927:Brain Diseases / Q000000981:diagnostic imaging / Q000378:metabolism; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D011859:Radiography