Functional connectomics from resting-state fMRI

Stephen M. Smith; Diego Vidaurre; Christian F. Beckmann; Matthew F. Glasser; Mark Jenkinson; Karla L. Miller; Thomas E. Nichols; Emma C. Robinson; Gholamreza Salimi-Khorshidi; Mark W. Woolrich; Deanna M. Barch; Kamil Uǧurbil; David C. Van Essen

doi:10.1016/j.tics.2013.09.016

Functional connectomics from resting-state fMRI

Stephen M. Smith^*, Diego Vidaurre, Christian F. Beckmann, Matthew F. Glasser, Mark Jenkinson, Karla L. Miller, Thomas E. Nichols, Emma C. Robinson, Gholamreza Salimi-Khorshidi, Mark W. Woolrich, Deanna M. Barch, Kamil Uǧurbil, David C. Van Essen

^*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Review › Research › peer-review

741 Citations (Scopus)

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.

Original language	English
Journal	Trends in Cognitive Sciences
Volume	17
Issue	12
Pages (from-to)	666-682
Number of pages	17
ISSN	1364-6613
DOIs	https://doi.org/10.1016/j.tics.2013.09.016
Publication status	Published - 1 Dec 2013
Externally published	Yes

Keywords

Connectomics
Network modelling
Resting-state fMRI

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10.1016/j.tics.2013.09.016

Cite this

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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",

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AU - Smith, Stephen M.

AU - Vidaurre, Diego

AU - Beckmann, Christian F.

AU - Glasser, Matthew F.

AU - Jenkinson, Mark

AU - Miller, Karla L.

AU - Nichols, Thomas E.

AU - Robinson, Emma C.

AU - Salimi-Khorshidi, Gholamreza

AU - Woolrich, Mark W.

AU - Barch, Deanna M.

AU - Uǧurbil, Kamil

AU - Van Essen, David C.

PY - 2013/12/1

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N2 - 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.

AB - 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.

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KW - Network modelling

KW - Resting-state fMRI

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Functional connectomics from resting-state fMRI

Abstract

Keywords

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