@article{386ad2d58dcb4758a39187e2f28786d1,
title = "Functional connectomics from resting-state fMRI",
abstract = "Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI (rfMRI) for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image-processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project and highlight some upcoming challenges in functional connectomics.",
keywords = "Connectomics, Network modelling, Resting-state fMRI",
author = "Smith, {Stephen M.} and Diego Vidaurre and Beckmann, {Christian F.} and Glasser, {Matthew F.} and Mark Jenkinson and Miller, {Karla L.} and Nichols, {Thomas E.} and Robinson, {Emma C.} and Gholamreza Salimi-Khorshidi and Woolrich, {Mark W.} and Barch, {Deanna M.} and Kamil Uǧurbil and {Van Essen}, {David C.}",
note = "Funding Information: The authors are grateful for funding via the following grants: 1U54MH091657-01 (NIH Blueprint for Neuroscience Research), P30-NS057091, P41-RR08079/EB015894, F30-MH097312 (NIH), and 098369/Z/12/Z (Wellcome Trust). They thank their many colleagues within the WU–Minn HCP Consortium for their invaluable contributions in generating the publicly available HCP data and in implementing the many procedures needed to acquire, analyse, visualise, and share these datasets. ",
year = "2013",
month = dec,
doi = "10.1016/j.tics.2013.09.016",
language = "English",
volume = "17",
pages = "666--682",
journal = "Trends in Cognitive Sciences",
issn = "1364-6613",
number = "12",
}