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

Center for Magnetic Resonance Research

Research output: Contribution to journal › Review article › peer-review

714 Scopus citations

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 (US)
Pages (from-to)	666-682
Number of pages	17
Journal	Trends in Cognitive Sciences
Volume	17
Issue number	12
DOIs	https://doi.org/10.1016/j.tics.2013.09.016
State	Published - Dec 2013

Bibliographical 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.

Keywords

Connectomics
Network modelling
Resting-state fMRI

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10.1016/j.tics.2013.09.016

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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.",

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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",

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doi = "10.1016/j.tics.2013.09.016",

language = "English (US)",

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pages = "666--682",

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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.

N1 - 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.

PY - 2013/12

Y1 - 2013/12

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.

KW - Connectomics

KW - Network modelling

KW - Resting-state fMRI

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Functional connectomics from resting-state fMRI

Abstract

Bibliographical note

Keywords

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