Multivariate AnalysisBR
Web ResourcesBR
Below is a list of web resources used in the talks BR
[http://www.cpu.bcm.edu/laconte/3dsvm.html AFNI 3dsvm plug-in]BR [http://code.google.com/p/princeton-mvpa-toolbox/ Princeton MVPA toolbox]BR [http://www.pymvpa.org/ PyMVPA toolbox]BR [http://www.csie.ntu.edu.tw/~cjlin/libsvm/ LIBSVM toolbox]BR
ReferencesBR
Mur, M. & Kriegeskorte, N. (due). Tutorial on Pattern Classification in Functional Imaging. In: Kriegeskorte, N. & Kreiman, G. (eds.). Visual Population Codes: Towards a Common Multivariate Framework for Cell Recording and Functional Imaging.BRBR
Mur, M., Bandettini, P. & Kriegeskorte, N. (2009). Revealing representational content with pattern-information fMRI – an introductory guide. Social Cognitive & Affective Neuroscience, 4(1): 101-109.BR [http://scan.oxfordjournals.org/content/4/1/101.short DOI:10.1093/scan/nsn044]BRBR
Kriegeskorte, N. (2011). Pattern-information analyses: from stimulus decoding to computational-model testing. Neuroimage. 56(2): 411-421. Norman, K.A., Polyn, S.M., Detre, G.J. & Haxby, J.V. (2006).BR [http://www.sciencedirect.com/science/article/pii/S1053811911000978 DOI:10.1016/j.neuroimage.2011.01.061]BRBR
Beyond mind-reading: multi-voxel pattern analysis of fMRI data. Trends in Cognitive Sciences, 10(9): 424-430.BR [http://www.ncbi.nlm.nih.gov/pubmed/16899397 PMID:16899397] BRBR
- Detailed mathematical background:
Bishop, Ch. (2006). Pattern recognition & machine learning. New York: Springer Science & Business Media.BR Duda RO, Hart PE, Stork DG (2001) Pattern Classification. New York, NY: John Wiley and Sons.BR