The Statistical Analysis of Multi-Voxel Patterns in Functional Imaging

PLoS ONE

Volumn 8, Issue 7, 2013, Pages

  Schreiber, Kai ^a   Krekelberg, Bart ^a  

^a RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BINOMIAL TEST; BOLD SIGNAL; CLASSIFICATION; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HEMODYNAMIC RESPONSE FUNCTION; HEMODYNAMICS; MULTIVOXEL PATTERN ANALYSIS; SIGNAL PROCESSING; SIMULATION; STATISTICAL ANALYSIS; STUDENT T TEST; SUPPORT VECTOR MACHINE;

HUMANS; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SUPPORT VECTOR MACHINES;

EID: 84879919468     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0069328     Document Type: Article

References (18)

1. Haxby JV, Gobbini MI, Furey ML, Ishai A, Schouten JL, et al. (2001) Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293: 2425-2430. doi:10.1126/science.1063736. PubMed: 11577229.
2. Kamitani Y, Tong F, (2005) Decoding the visual and subjective contents of the human brain. Nat Neurosci 8: 679-685. doi:10.1038/nn1444. PubMed: 15852014.
3. Kamitani Y, Tong F, (2006) Decoding seen and attended motion directions from activity in the human visual cortex. Curr Biol 16: 1096-1102. doi:10.1016/j.cub.2006.04.003. PubMed: 16753563.
4. Pereira F, Mitchell T, Botvinick M, (2009) Machine learning classifiers and fMRI: a tutorial overview. Neuroimage 45: S199-S209. doi:10.1016/j.neuroimage.2008.11.007. PubMed: 19070668.
5. Mur M, Bandettini PA, Kriegeskorte N, (2009) Revealing representational content with pattern-information fMRIan introductory guide. Social Cognitive and Affective Neuroscience 4: 101-109.
6. Norman KA, Polyn SM, Detre GJ, Haxby JV, (2006) Beyond mind-reading: multi-voxel pattern analysis of fMRI data. Trends Cogn Sci 10: 424-430. doi:10.1016/j.tics.2006.07.005. PubMed: 16899397.
7. Efron B, Tibshirani RJ, (1994) An Introduction to the Bootstrap. Boca Raton, FL: Chapman & Hall/CRC.
8. Golland P, Fischl B, (2003) Permutation tests for classification: Towards statistical significance in image-based studies. Info Process Medical Imaging Proc 2732: 330-341. doi:10.1007/978-3-540-45087-0_28. PubMed: 15344469.
9. Cohen MS, (1997) Parametric analysis of fMRI data using linear systems methods. Neuroimage 6: 93-103. doi:10.1006/nimg.1997.0278. PubMed: 9299383.
10. Chang C-C, Lin C-J, (2001) LIBSVM: a library for support vector machines.
11. Cristianini N, Shawe-Taylor J, (2000) An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge, UK: Cambridge University Press.
12. Vapnik VN, (1995) The nature of statistical learning theory. New York, New York: Springer Verlag.
13. Mourão-Miranda J, Reynaud E, McGlone F, Calvert G, Brammer M, (2006) The impact of temporal compression and space selection on SVM analysis of single-subject and multi-subject fMFI data. NeuroImage 33: 1055-1065. doi:10.1016/j.neuroimage.2006.08.016. PubMed: 17010645.
14. Logothetis NK, Wandell BA, (2004) Interpreting the BOLD Signal. Annu Rev Physiol 66: 735-769. doi:10.1146/annurev.physiol.66.082602.092845. PubMed: 14977420.
15. Nieuwenhuis S, Forstmann BU, Wagenmakers EJ, (2011) Erroneous analyses of interactions in neuroscience: a problem of significance. Nat Neurosci 14: 1105-1107. doi:10.1038/nn.2886. PubMed: 21878926.
16. Averbeck BB, Latham PE, Pouget A, (2006) Neural correlations, population coding and computation. Nat Rev Neurosci 7: 358-366. doi:10.1038/nrn1888. PubMed: 16760916.
17. Gardner JL, (2010) Is cortical vasculature functionally organized? Neuroimage 49: 1953-1956. doi:10.1016/j.neuroimage.2009.07.004. PubMed: 19596071.
18. Kriegeskorte N, Cusack R, Bandettini P, (2010) How does an fMRI voxel sample the neuronal activity pattern: Compact-kernel or complex spatiotemporal filter? Neuroimage 49: 1965-1976. doi:10.1016/j.neuroimage.2009.09.059. PubMed: 19800408.