CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave
University of Trento · Dartmouth College
Indexed incrossrefdoajpubmed
Abstract
Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural…
Citation impact
718
total citations
- FWCI
- 32.79
- Percentile
- 100%
- References
- 58
Citations per year
Authors
3Topics & keywords
Topics
Keywords
- Computer science
- Neuroimaging
- Cluster analysis
- Artificial intelligence
- Pattern recognition (psychology)
- Functional magnetic resonance imaging
- Octave (electronics)
- Multivariate statistics
UN Sustainable Development Goals
- Quality Education
No related works found for this paper.