Imaging-based parcellations of the human brain

Eickhoff, Simon B.; Yeo, B. T. Thomas; Genon, Sarah

doi:10.1038/s41583-018-0071-7

Cited by 489Functional Brain Connectivity StudiesAdvanced Neuroimaging Techniques and ApplicationsMedical Image Segmentation Techniques

Imaging-based parcellations of the human brain

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Eickhoff, Simon B., Yeo, B. T. Thomas, Genon, Sarah·2018·Nature reviews. Neuroscience

DOI 10.1038/s41583-018-0071-7

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Abstract

A defining aspect of brain organization is its spatial heterogeneity, which gives rise to multiple topographies at different scales. Brain parcellation - defining distinct partitions in the brain, be they areas or networks that comprise multiple discontinuous but closely interacting regions - is thus fundamental for understanding brain organization and function. The past decade has seen an explosion of in vivo MRI-based approaches to identify and parcellate the brain on the basis of a wealth of different features, ranging from local properties of brain tissue to long-range connectivity patterns, in addition to structural and functional markers. Given the high diversity of these various approaches, assessing the convergence and divergence among these ensuing maps is a challenge. Inter-individual variability adds to this challenge but also provides new opportunities when coupled with cross-species and developmental parcellation studies.

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Using regions with a high probability of being the tract of interest according to normative atlases ensured that the regions were representative of the general population, minimizing inter-subject variability without completely removing it.
“This ensured that the regions were representative of the general population, minimizing inter-subject variability without completely removing it.”
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Authors: Eickhoff, S. B., Yeo, B. T. T., & Genon, S.
Affiliations: Forschungszentrum Jülich (DE)
Harvard University (US)
Corresponding author: Eickhoff, Simon B.
ORCID: Eickhoff, Simon B.
Yeo, B. T. Thomas
Genon, Sarah
Venue: Nature reviews. Neuroscience
Publisher: Springer Science and Business Media LLC
Published: 2018-10-09
Volume: 19
Issue: 11
Pages: 672-686
ISSN: 1471-003X (ISSN-L)
1471-0048
DOI: 10.1038/s41583-018-0071-7
OpenAlex: W2896587207
Cited by: 484
References: 150
Citations by year: 2026: 50 · 2025: 66 · 2024: 66 · 2023: 63 · 2022: 69 · 2021: 84 · 2020: 52 · 2019: 28 · 2018: 5 · 2017: 1
FWCI: 5.66
Type: journal article
Language: en
Open access: green
orbi.uliege.be
Licence: other-oa
www.springer.com/tdm (tdm)
Locations: Nature reviews. Neuroscience (publishedVersion)
PubMed (publishedVersion)
National University of Singapore (submittedVersion)
ORBi (University of Liège) (submittedVersion, other-oa)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Keywords: brain parcellation, brain networks, structural connectivity, functional connectivity, cytoarchitecture, interindividual variability
MeSH terms: Brain, Brain Mapping, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Neural Pathways, Reproducibility of Results

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Imaging-based parcellations of the human brain

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