What's in a pattern? Examining the type of signal multivariate analysis uncovers at the group level

Roee Gilron, Jonathan Rosenblatt, Oluwasanmi Koyejo, Russell A. Poldrack, Roy Mukamel

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Multivoxel pattern analysis (MVPA) has gained enormous popularity in the neuroimaging community over the past few years. At the group level, most MVPA studies adopt an “information based” approach in which the sign of the effect of individual subjects is discarded and a non-directional summary statistic is carried over to the second level. This is in contrast to a directional “activation based” approach typical in univariate group level analysis, in which both signal magnitude and sign are taken into account. The transition from examining effects in one voxel at a time vs. several voxels (univariate vs. multivariate) has thus tacitly entailed a transition from directional to non-directional signal definition at the group level. While a directional group-level MVPA approach implies that individuals have similar multivariate spatial patterns of activity, in a non-directional approach each individual may have a distinct spatial pattern. Using an experimental dataset, we show that directional and non-directional group-level MVPA approaches uncover distinct brain regions with only partial overlap. We propose a method to quantify the degree of spatial similarity in activation patterns over subjects. Applied to an auditory task, we find higher values in auditory regions compared to control regions.

Original languageEnglish
Pages (from-to)113-120
Number of pages8
JournalNeuroImage
Volume146
DOIs
StatePublished - 1 Feb 2017

Keywords

  • Group MVPA
  • Multivariate statistics
  • Searchlight
  • fMRI

Fingerprint

Dive into the research topics of 'What's in a pattern? Examining the type of signal multivariate analysis uncovers at the group level'. Together they form a unique fingerprint.

Cite this