Atlasing the frontal lobe connections and their variability due to age and education: a spherical deconvolution tractography study

Rojkova, K.; Volle, E.; Urbanski, M.; Humbert, F.; Dell’Acqua, F.; Thiebaut de Schotten, M.

doi:10.1007/s00429-015-1001-3

Cited by 361Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesCerebrovascular and genetic disorders

Atlasing the frontal lobe connections and their variability due to age and education: a spherical deconvolution tractography study

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Rojkova, K., Volle, E., Urbanski, M., Humbert, F., Dell’Acqua, F., Thiebaut de Schotten, M.·2016·Brain Structure and Function

DOI 10.1007/s00429-015-1001-3

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Abstract

In neuroscience, there is a growing consensus that higher cognitive functions may be supported by distributed networks involving different cerebral regions, rather than by single brain areas. Communication within these networks is mediated by white matter tracts and is particularly prominent in the frontal lobes for the control and integration of information. However, the detailed mapping of frontal connections remains incomplete, albeit crucial to an increased understanding of these cognitive functions. Based on 47 high-resolution diffusion-weighted imaging datasets (age range 22-71 years), we built a statistical normative atlas of the frontal lobe connections in stereotaxic space, using state-of-the-art spherical deconvolution tractography. We dissected 55 tracts including U-shaped fibers. We further characterized these tracts by measuring their correlation with age and education level. We reported age-related differences in the microstructural organization of several, specific frontal fiber tracts, but found no correlation with education level. Future voxel-based analyses, such as voxel-based morphometry or tract-based spatial statistics studies, may benefit from our atlas by identifying the tracts and networks involved in frontal functions. Our atlas will also build the capacity of clinicians to further understand the mechanisms involved in brain recovery and plasticity, as well as assist clinicians in the diagnosis of disconnection or abnormality within specific tracts of individual patients with various brain diseases.

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Authors: Rojkova, K., Volle, E., Urbanski, M., Humbert, F., Dell’Acqua, F., & Thiebaut de Schotten, M.
Affiliations: Centre National de la Recherche Scientifique (FR)
Pitié-Salpêtrière Hospital (FR)
King's College London (GB)
ORCID: Dell’Acqua, F.
Venue: Brain Structure and Function
Publisher: Springer Science and Business Media LLC
Published: 2015-02-15
Volume: 221
Issue: 3
Pages: 1751-1766
ISSN: 1863-2653 (ISSN-L)
1863-2661
DOI: 10.1007/s00429-015-1001-3
OpenAlex: W2041138630
Cited by: 361
References: 140
Citations by year: 2026: 17 · 2025: 33 · 2024: 16 · 2023: 30 · 2022: 42 · 2021: 51 · 2020: 40 · 2019: 48 · 2018: 31 · 2017: 22 · 2016: 26 · 2015: 3 · 2014: 1
FWCI: 22.15
Type: journal article
Language: en
Open access: green
hal.sorbonne-universite.fr
Licence: other-oa
www.springer.com/tdm (tdm)
Locations: Brain Structure and Function (publishedVersion)
PubMed (publishedVersion)
HAL (submittedVersion, other-oa)
Research Portal (King's College London) (submittedVersion, other-oa)
Funders: Agence Nationale de la Recherche (ANR-10-IAIHU06, ANR‐09‐RPDOC‐004‐01, ANR-13-JSV4-0001, 10-IAIHU-06, ANR-10)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Neurology › Cerebrovascular and genetic disorders
Keywords: white matter tracts, age differences, educational attainment, diffusion-weighted imaging, U-shaped fiber, frontal network, neuroplasticity, brain disconnection
MeSH terms: Adult, Aged, Aging, Atlases as Topic, Brain, Educational Status, Female, Frontal Lobe, Humans, Male, Middle Aged, Neural Pathways, Diffusion Magnetic Resonance Imaging, Young Adult, Diffusion Tensor Imaging

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Atlasing the frontal lobe connections and their variability due to age and education: a spherical deconvolution tractography study

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