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  Recent developments in representations of the connectome

Bijsterbosch, J. D., Valk, S. L., Wang, D., & Glasser, M. F. (2021). Recent developments in representations of the connectome. NeuroImage, 243: 118533. doi:10.1016/j.neuroimage.2021.118533.

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 Creators:
Bijsterbosch, Janine D.1, Author
Valk, Sofie L.2, 3, Author           
Wang, Danhong4, Author
Glasser, Matthew F.1, 5, Author
Affiliations:
1Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA, ou_persistent22              
2Otto Hahn Group Cognitive Neurogenetics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_3222264              
3Institute of Neuroscience and Medicine, Research Center Jülich, Germany, ou_persistent22              
4Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA, ou_persistent22              
5Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA, ou_persistent22              

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Free keywords: Connectome; Functional MRI; Functional connectivity; Individual variability; Resting state
 Abstract: Research into the human connectome (i.e., all connections in the human brain) with the use of resting state functional MRI has rapidly increased in popularity in recent years, especially with the growing availability of large-scale neuroimaging datasets. The goal of this review article is to describe innovations in functional connectome representations that have come about in the past 8 years, since the 2013 NeuroImage special issue on ‘Mapping the Connectome’. In the period, research has shifted from group-level brain parcellations towards the characterization of the individualized connectome and of relationships between individual connectomic differences and behavioral/clinical variation. Achieving subject-specific accuracy in parcel boundaries while retaining cross-subject correspondence is challenging, and a variety of different approaches are being developed to meet this challenge, including improved alignment, improved noise reduction, and robust group-to-subject mapping approaches. Beyond the interest in the individualized connectome, new representations of the data are being studied to complement the traditional parcellated connectome representation (i.e., pairwise connections between distinct brain regions), such as methods that capture overlapping and smoothly varying patterns of connectivity (‘gradients’). These different connectome representations offer complimentary insights into the inherent functional organization of the brain, but challenges for functional connectome research remain. Interpretability will be improved by future research towards gaining insights into the neural mechanisms underlying connectome observations obtained from functional MRI. Validation studies comparing different connectome representations are also needed to build consensus and confidence to proceed with clinical trials that may produce meaningful clinical translation of connectome insights.

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Language(s): eng - English
 Dates: 2021-07-162021-02-252021-08-282021-08-292021-11
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.neuroimage.2021.118533
Other: epub 2021
PMID: 34469814
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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 243 Sequence Number: 118533 Start / End Page: - Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166