Leech, Robert, Dr., Simmonds, Anna and Leech, Dennis (2009) Parametric inference for functional information mapping. Working Paper. University of Warwick, Department of Economics, Coventry.

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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)
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
Date:	2009
Number:	No.899
Number of Pages:	17
Status:	Not Peer Reviewed
Access rights to Published version:	Open Access
References:	Cox, R. et al. (1996). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research, 29(3):162–173. Friston, K., Holmes, A., Worsley, K., Poline, J., Frith, C., Frackowiak, R., et al. (1994). Statistical parametric maps in functional imaging: a general linear approach. Human Brain Mapping, 2(4):189–210. Genovese, C., Lazar, N., and Nichols, T. (2002). Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage, 15(4):870–878. Greene, W. (2003). Econometric analysis. Prentice Hall Upper Saddle River, NJ. Hanson, S. and Halchenko, Y. (2008). Brain reading using full brain suport vector machines for object recognition: There is no ”face” identification area. Neural Computation, 20:486–503. Haxby, J., Gobbini, M., Furey, M., Ishai, A., Schouten, J., and Pietrini, P. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293(5539):2425–2430. Hernandez, A., Dapretto, M., Mazziotta, J., and Bookheimer, S. (2001). Language switching and language representation in Spanish-English bilinguals: an fMRI study. NeuroImage, 14:510–520. Jenkinson, M. and Smith, S. (2001). A global optimisation method for robust affine registration of brain images. Medical Image Analysis, 5(2):143–156. Kay, K., Naselaris, T., Prenger, R., and Gallant, J. (2008). Identifying natural images from human brain activity. Nature, 452(7185):352–355. Kriegeskorte, N. and Bandettini, P. (2007). Analyzing for information, not activation, to exploit high-resolution fMRI. Neuroimage, 38(4):649–662. Kriegeskorte, N., Formisano, E., Sorger, B., and Goebel, R. (2007). Individual faces elicit distinct response patterns in human anterior temporal cortex. Proceedings of the National Academy of Sciences, 104(51):20600. Kriegeskorte, N., Goebel, R., and Bandettini, P. (2006). Information-based functional brain mapping. Proceedings of the National Academy of Sciences, 103(10):3863–3868. Mahalanobis, P. (1936). On the generalized distance in statistics. In Proceedings of the National Institute of Science of India, volume 12, pages 49–55. Mitchell, T., Shinkareva, S., Carlson, A., Chang, K., Malave, V., Mason, R., and Just, M. (2008). Predicting human brain activity associated with the meanings of nouns. science, 320(5880):1191. Rao, C. and Rao, C. (1973). Linear statistical inference and its applications. Scott, S., Blank, C., Rosen, S., and Wise, R. (2000). Identification of a pathway for intelligible speech in the left temporal lobe. Brain, 123(12):2400. Serences, J. and Boynton, G. (2007a). Feature-based attentional modulations in the absence of direct visual stimulation. Neuron, 55(2):301–312. Serences, J. and Boynton, G. (2007b). The representation of behavioral choice for motion in human visual cortex. Journal of Neuroscience, 27(47):12893. Stokes, M., Thompson, R., Cusack, R., and Duncan, J. (2009). Top-Down Activation of Shape-Specific Population Codes in Visual Cortex during Mental Imagery. Journal of Neuroscience, 29(5):1565. Woolrich, M., Ripley, B., Brady, M., and Smith, S. (2001). Temporal autocorrelation in univariate linear modeling of FMRI data. Neuroimage, 14(6):1370–1386. Zellner, A. (1962). An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association, pages 348– 368.
URI:	http://wrap.warwick.ac.uk/id/eprint/1318

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