Shifts in structural connectome organization in the limbic and sensory systems of patients with episodic migraine.


Journal

The journal of headache and pain
ISSN: 1129-2377
Titre abrégé: J Headache Pain
Pays: England
ID NLM: 100940562

Informations de publication

Date de publication:
11 Jun 2024
Historique:
received: 29 03 2024
accepted: 06 06 2024
medline: 12 6 2024
pubmed: 12 6 2024
entrez: 11 6 2024
Statut: epublish

Résumé

Migraine is a complex neurological condition characterized by recurrent headaches, which is often accompanied by various neurological symptoms. Magnetic resonance imaging (MRI) is a powerful tool for investigating whole-brain connectivity patterns; however, systematic assessment of structural connectome organization has rarely been performed. In the present study, we aimed to examine the changes in structural connectivity in patients with episodic migraines using diffusion MRI. First, we computed structural connectivity using diffusion MRI tractography, after which we applied dimensionality reduction techniques to the structural connectivity and generated three low-dimensional eigenvectors. We subsequently calculated the manifold eccentricity, defined as the Euclidean distance between each data point and the center of the data in the manifold space. We then compared the manifold eccentricity between patients with migraines and healthy controls, revealing significant between-group differences in the orbitofrontal cortex, temporal pole, and sensory/motor regions. Between-group differences in subcortico-cortical connectivity further revealed significant changes in the amygdala, accumbens, and caudate nuclei. Finally, supervised machine learning effectively classified patients with migraines and healthy controls using cortical and subcortical structural connectivity features, highlighting the importance of the orbitofrontal and sensory cortices, in addition to the caudate, in distinguishing between the groups. Our findings confirmed that episodic migraine is related to the structural connectome changes in the limbic and sensory systems, suggesting its potential utility as a diagnostic marker for migraine.

Identifiants

pubmed: 38862883
doi: 10.1186/s10194-024-01806-2
pii: 10.1186/s10194-024-01806-2
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

99

Subventions

Organisme : National Research Foundation of Korea
ID : NRF2020R1A2B5B01001826
Organisme : National Research Foundation of Korea
ID : NRF2022R1A5A7033499
Organisme : Korea Medical Device Development Fund
ID : Project number: RS-2023-00229484
Organisme : Institute for Information and Communications Technology Promotion
ID : No. 2022-0-00448, Deep Total Recall: Continuous Learning for Human-Like Recall of Artificial Neural Networks
Organisme : Institute for Basic Science
ID : IBS-R015-D1

Informations de copyright

© 2024. The Author(s).

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Auteurs

Eunchan Noh (E)

College of Medicine, Inha University, Incheon, Republic of Korea.

Jong Young Namgung (JY)

Department of Data Science, Inha University, Incheon, Republic of Korea.

Yeongjun Park (Y)

Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea.

Yurim Jang (Y)

Department of Statistics and Data Science, Inha University, Incheon, Republic of Korea.

Mi Ji Lee (MJ)

Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea. mijilee.md@snu.ac.kr.

Bo-Yong Park (BY)

Department of Data Science, Inha University, Incheon, Republic of Korea. boyong.park@inha.ac.kr.
Department of Statistics and Data Science, Inha University, Incheon, Republic of Korea. boyong.park@inha.ac.kr.
Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea. boyong.park@inha.ac.kr.

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