A unified statistical approach for determining significant signals in images of cerebral activation
Article first published online: 7 DEC 1998
Copyright © 1996 Wiley-Liss, Inc.
Human Brain Mapping
Volume 4, Issue 1, pages 58–73, 1996
How to Cite
Worsley, K. J., Marrett, S., Neelin, P., Vandal, A. C., Friston, K. J. and Evans, A. C. (1996), A unified statistical approach for determining significant signals in images of cerebral activation. Hum. Brain Mapp., 4: 58–73. doi: 10.1002/(SICI)1097-0193(1996)4:1<58::AID-HBM4>3.0.CO;2-O
- Issue published online: 7 DEC 1998
- Article first published online: 7 DEC 1998
- Manuscript Accepted: 6 MAR 1996
- Manuscript Received: 19 DEC 1995
- Natural Sciences and Engineering Research Council of Canada
- Euler characteristic;
- random fields
We present a unified statistical theory for assessing the significance of apparent signal observed in noisy difference images. The results are usable in a wide range of applications, including fMRI, but are discussed with particular reference to PET images which represent changes in cerebral blood flow elicited by a specific cognitive or sensorimotor task. Our main result is an estimate of the P-value for local maxima of Gaussian, t, χ2 and F fields over search regions of any shape or size in any number of dimensions. This unifies the P-values for large search areas in 2-D (Friston et al. : J Cereb Blood Flow Metab 11:690–699) large search regions in 3-D (Worsley et al. : J Cereb Blood Flow Metab 12:900–918) and the usual uncorrected P-value at a single pixel or voxel. © 1996 Wiley-Liss, Inc.