literature
- Pereira, F., Mitchell, T., Botvinick, M., 2009. Machine learning classifiers and fMRI: A tutorial overview. Neuroimage 45, S199-S209.
- Etzel, J.A., Gazzola, V., Keysers, C., 2009. An introduction to anatomical ROI-based fMRI classification analysis. Brain Research 1282, 114-125.
- Mur, M., Bandettini, P.A., Kriegeskorte, N., 2009. Revealing representational content with pattern-information fMRI--an introductory guide. Soc Cogn Affect Neurosci, nsn044.
- Haynes JD. 2015. A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives. Neuron, 87 (2), 257-70. doi: 10.1016/j.neuron.2015.05.025 PMID: 26182413
- Mitchell, T.M., Hutchinson, R., Niculescu, R.S., Pereira, F., Wang, X., 2004. Learning to Decode Cognitive States from Brain Images. Machine Learning 57, 145-175.
- Norman, K.A., Polyn, S.M., Detre, G.J., Haxby, J.V., 2006. Beyond mind-reading: multi-voxel pattern analysis of fMRI data. Trends In Cognitive Sciences 10, 424-430.
software
There are a few software packages specifically for MVPA, though many people (myself included) use quite a bit of their own code. A nice comparison of packages is towards the end of Hebart2015.- PRoNTO (works with SPM)
- pyMVPA
- NeuroDebian (not for MVPA, but a useful virtual machine for running pyMVPA, afni, fsl, etc).
- Brain Imaging Analysis Kit (BrainIAK)
- parts of BrainVoyager.
- The Decoding Toolbox (TDT), also MATLAB-based and works with SPM
- the Princeton MVPA toolbox (defunct?)
workshops/conferences
- Pattern Recognition in Neuroimaging (PRNI) workshop, sort-of co-located with OHBM (on hiatus in 2019)
- Machine Learning and Interpretation in Neuroimaging(MLINI), occasional NIPS workshop
- Cognitive Computational Neuroscience (CCN), a new conference for "neuroscientists characterizing the neural computations that underlie complex behavior"
publicly-available fMRI datasets
- The 1 January 2016 issue of NeuroImage is devoted to public neuroimaging data repositories.
- I have two datasets up at the Open Science Foundation. Both of these are fully preprocessed (not raw images), with R code to reproduce the papers' MVPA results. My 2015 Cerebral Cortex paper is at doi:10.1093/cercor/bhu327, and Etzel JA, Valchev N, Gazzola V, Keysers C. (2016). Is Brain Activity during Action Observation Modulated by the Perceived Fairness of the Actor? PLOS ONE is osf.io/dg63m.
- OpenfMRI, a formal effort organized by Russ Poldrack, with 32 datasets as of 4 February 2015.
- the Human Connectome Project. Enormous dataset, in terms of number of people, size of files, and assortment of modalities. I've written some posts are working with this data; start with this one.
- CRCNS hosts datasets in various modalities, from fMRI to single-neuron.
- Kendrick Kay shares multiple datasets (including fMRI) and code on his site.
other things
- my "What MVPA detects" post
- the pyMVPA mailing list (many discussions delve into general MVPA topics)
updated 15 October 2013: added a link to PRoNTO; added the workshops section
updated 16 January 2015: added the link to The Decoding Toolbox and Hebart 2015.
updated 4 February 2015: added the public datasets section.
updated 11 September 2015: changed the reference from Haynes 2006 to Haynes 2015.
updated 21 March 2017: added a link to CCN.
updated 25 September 2017: added BrainIAK
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