Learning and comparing functional connectomes across subjects

TL;DR

This paper reviews methods for estimating and comparing functional connectomes from fMRI data, highlighting their variability across subjects and conditions to understand brain architecture and pathology.

Contribution

It clarifies the relationships among different functional-connectivity methods and outlines steps for group analysis of connectomes.

Findings

Different methods capture various aspects of brain connectivity.

Variability in connectomes can indicate brain pathologies.

Standardized procedures improve comparability across studies.

Abstract

Functional connectomes capture brain interactions via synchronized fluctuations in the functional magnetic resonance imaging signal. If measured during rest, they map the intrinsic functional architecture of the brain. With task-driven experiments they represent integration mechanisms between specialized brain areas. Analyzing their variability across subjects and conditions can reveal markers of brain pathologies and mechanisms underlying cognition. Methods of estimating functional connectomes from the imaging signal have undergone rapid developments and the literature is full of diverse strategies for comparing them. This review aims to clarify links across functional-connectivity methods as well as to expose different steps to perform a group study of functional connectomes.