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Assessing the significance of focal activations using their spatial extent

Human Brain Mapping · 1994 · Vol. 1(3) · pp. 210–220
Karl FristonKeith J. WorsleyR. S. J. FrackowiakJ.C. MazziottaAlan C. Evans

Abstract

Current approaches to detecting significantly activated regions of cerebral tissue use statistical parametric maps, which are thresholded to render the probability of one or more activated regions of one voxel, or larger, suitably small (e. g., 0.05). We present an approximate analysis giving the probability that one or more activated regions of a specified volume, or larger, could have occurred by chance. These results mean that detecting significant activations no longer depends on a fixed (and high) threshold, but can be effected at any (lower) threshold, in terms of the spatial extent of the activated region. The substantial improvement in sensitivity that ensues is illustrated using a power analysis and a simulated phantom activation study. © 1994 Wiley-Liss, Inc.

Medical Image Segmentation TechniquesFunctional Brain Connectivity StudiesCell Image Analysis TechniquesVoxelStatistical powerStatistical parametric mappingParametric statisticsSensitivity (control systems)Imaging phantomStatistical analysisStatisticsComputer sciencePattern recognition (psychology)

Funding

  • Wellcome Trust
Citations
1,943
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57.76
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References
The Relationship between Global and Local Changes in PET Scans
Journal of Cerebral Blood Flow & Metabolism · 1990 · 863 citations
Comparing Functional (PET) Images: The Assessment of Significant Change
Journal of Cerebral Blood Flow & Metabolism · 1991 · 1,636 citations
A Three-Dimensional Statistical Analysis for CBF Activation Studies in Human Brain
Journal of Cerebral Blood Flow & Metabolism · 1992 · 2,053 citations
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