A unified statistical approach for determining significant signals in images of cerebral activation

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. [1991]: J Cereb Blood Flow Metab 11:690–699) large search regions in 3‐D (Worsley et al. [1992]: J Cereb Blood Flow Metab 12:900–918) and the usual uncorrected P‐value at a single pixel or voxel. © 1996 Wiley‐Liss, Inc.

• Publication year

  1996

• Venue

  Human Brain Mapping

• Publication date

  Unknown publication date

• Fields of study

  Mathematics, Computer Science, Medicine

• Identifiers
  DOI 10.1002/(SICI)1097-0193(1996)4:1<58::AID-HBM4>3.0.CO;2-OPMID 20408186
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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