Beyond Functional Connectivity: Investigating Networks of Multivariate Representations

Stefano Anzellotti; Marc N Coutanche

doi:10.1016/j.tics.2017.12.002

Beyond Functional Connectivity: Investigating Networks of Multivariate Representations

Trends Cogn Sci. 2018 Mar;22(3):258-269. doi: 10.1016/j.tics.2017.12.002. Epub 2018 Jan 2.

Authors

Stefano Anzellotti¹, Marc N Coutanche²

Affiliations

¹ Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA; These authors contributed equally.
² Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA; These authors contributed equally. Electronic address: marc.coutanche@pitt.edu.

PMID: 29305206
DOI: 10.1016/j.tics.2017.12.002

Abstract

For over two decades, interactions between brain regions have been measured in humans by asking how the univariate responses in different regions co-vary ('Functional Connectivity'). Thousands of Functional Connectivity studies have been published investigating the healthy brain and how it is affected by neural disorders. The advent of multivariate fMRI analyses showed that patterns of responses within regions encode information that is lost by averaging. Despite this, connectivity methods predominantly continue to focus on univariate responses. In this review, we discuss the recent emergence of multivariate and nonlinear methods for studying interactions between brain regions. These new developments bring sensitivity to fluctuations in multivariate information, and offer the possibility to ask not only whether brain regions interact, but how they do so.

Keywords: Informational Connectivity; MVPA; decoding; fMRI; multi-voxel; multivariate pattern dependence.

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Brain / diagnostic imaging
Brain / physiology*
Connectome / methods*
Humans
Image Processing, Computer-Assisted / methods*
Magnetic Resonance Imaging / methods*
Multivariate Analysis*
Nerve Net / diagnostic imaging
Nerve Net / physiology*