Cited by 326Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesClassical Anatomy and Histology

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DTI mapping of human brain connectivity: statistical fibre tracking and virtual dissection

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Hagmann, P., Thiran, J.-P., Jonasson, L., Vandergheynst, P., Clarke, S., Maeder, P., Meuli, R.·2003·NeuroImage

DOI 10.1016/s1053-8119(03)00142-3

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Abstract

Several approaches have been used to trace axonal trajectories from diffusion MRI data. If such techniques were first developed in a deterministic framework reducing the diffusion information to one single main direction, more recent approaches emerged that were statistical in nature and that took into account the whole diffusion information. Based on diffusion tensor MRI data coming from normal brains, this paper presents how brain connectivity could be modelled globally by means of a random walk algorithm. The mass of connections thus generated was then virtually dissected to uncover different tracts. Corticospinal, corticobulbar, and corticothalamic tracts, the corpus callosum, the limbic system, several cortical association bundles, the cerebellar peduncles, and the medial lemniscus were all investigated. The results were then displayed in the form of an in vivo brain connectivity atlas. The connectivity pattern and the individual fibre tracts were then compared to known anatomical data; a good matching was found.

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Authors: Hagmann, P., Thiran, J.-P., Jonasson, L., Vandergheynst, P., Clarke, S., Maeder, P., & Meuli, R.
Affiliations: Centre Hospitalier Universitaire Vaudois (CH)
École Polytechnique Fédérale de Lausanne (CH)
Corresponding author: Hagmann, P.
ORCID: Hagmann, P.
Thiran, J.-P.
Vandergheynst, P.
Clarke, S.
Maeder, P.
Meuli, R.
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2003-07
Volume: 19
Issue: 3
Pages: 545-554
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/s1053-8119(03)00142-3
OpenAlex: W2131478329
Cited by: 326
References: 39
Citations by year: 2026: 3 · 2025: 1 · 2024: 3 · 2023: 3 · 2022: 4 · 2021: 5 · 2020: 12 · 2019: 9 · 2018: 10 · 2017: 8 · 2016: 9 · 2015: 8 · 2014: 16 · 2013: 30 · 2012: 20
FWCI: 16.56
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
doi.org/10.15223/policy-017 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-012 (stm-asf)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-004 (stm-asf)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
IRIS (submittedVersion)
SERVAL (Université de Lausanne) (submittedVersion)
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 › Anatomy › Classical Anatomy and Histology
Keywords: diffusion tensor imaging, brain connectivity, random walk algorithm, virtual dissection, corticospinal tract, corticobulbar tract, corpus callosum, limbic system, cerebellar peduncles, medial lemniscus, axonal trajectories
MeSH terms: Algorithms, Axons, Brain, Brain Mapping, Cerebellum, Cerebral Cortex, Computer Graphics, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Models, Neurological, Nerve Fibers, Neural Pathways, Pyramidal Tracts, Thalamus

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DTI mapping of human brain connectivity: statistical fibre tracking and virtual dissection

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