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Parametric inference for functional information mapping
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Leech, Robert, Dr., Simmonds, Anna and Leech, Dennis (2009) Parametric inference for functional information mapping. Working Paper. Coventry: University of Warwick, Department of Economics. Warwick economic research papers (No.899).
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Official URL: http://www2.warwick.ac.uk/fac/soc/economics/resear...
Abstract
An increasing trend in functional MRI experiments involves discriminating between experimental conditions on the basis of fine-grained spatial patterns extending across many voxels. Typically, these approaches have used randomized resampling to derive inferences. Here, we introduce an analytical method for drawing inferences from multivoxel patterns. This approach extends the general linear model to the multivoxel case resulting in a variant of the Mahalanobis distance statistic which can be evaluated on the x2 distribution. We apply this parametric inference to a single-subject fMRI dataset and consider how the approach is both computationally more efficient and more sensitive than resampling inference.
Item Type: | Working or Discussion Paper (Working Paper) | ||||
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Subjects: | R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry | ||||
Divisions: | Faculty of Social Sciences > Economics | ||||
Library of Congress Subject Headings (LCSH): | Magnetic resonance imaging, Parametric devices, Inference, Pattern formation (Biology) | ||||
Series Name: | Warwick economic research papers | ||||
Publisher: | University of Warwick, Department of Economics | ||||
Place of Publication: | Coventry | ||||
Official Date: | 2009 | ||||
Dates: |
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Number: | No.899 | ||||
Number of Pages: | 17 | ||||
Status: | Not Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) |
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