Anderson, J.R. Tracking problem solving by multivariate pattern analysis and Hidden Markov Model algorithms.
Haxby, J. V., Connolly, A. C. & Guntupalli, J. S. Decoding neural representational spaces using multivariate pattern analysis.
Zeng, L.-L. et al. Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis.
Todd, M.T., Nystrom, L.E. & Cohen, J.D. Confounds in multivariate pattern analysis: theory and rule representation case study.
Here we used multivariate pattern analysis of magnetoencephalography (MEG) data to compare visual letter recognition with Braille reading.
Oosterhof, N. N., Connolly, A. C. & Haxby, J. V. CoSMoMVPA: multi-modal multivariate pattern analysis of neuroimaging data in Matlab / GNU Octave.
Grootswagers, T., Wardle, S. G. & Carlson, T. A. Decoding dynamic brain patterns from evoked responses: A tutorial on multivariate pattern analysis applied to time-series neuroimaging data.
Therefore, we instead employed multivariate pattern analysis, which can map multidimensional psychological states or processes to specific brain regions19,20,21,22,23,24.
Grootswagers, T., Wardle, S. G. & Carlson, T. A. Decoding dynamic brain patterns from evoked responses: a tutorial on multivariate pattern analysis applied to time series neuroimaging data.
Malone, P. S., Glezer, L. S., Kim, J., Jiang, X. & Riesenhuber, M. Multivariate pattern analysis reveals category-related organization of semantic representations in anterior temporal cortex.
Participants were also exposed to a functional localiser consisting of full-field flickering gratings, in order to allow multivariate pattern analysis of orientation-specific BOLD signals.
