Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory

Shruti Narasimham; Vikram Sundarajan; Eavan McGovern; Brendan Quinlivan; Owen Killian; Sean O'Riordan; Michael Hutchinson; Richard B. Reilly

doi:10.1109/EMBC.2019.8856624

Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory

Shruti Narasimham
, Vikram Sundarajan
, Eavan McGovern
, Brendan Quinlivan
, Owen Killian
, Sean O'Riordan
, Michael Hutchinson
, Richard B. Reilly

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Cervical Dystonia (CD) is a neurological movement disorder characterized by intermittent muscle contractions in the head and neck. The pathophysiology and neural networks underpinning this condition are incompletely understood. There is increasing evidence that isolated focal dystonias are due to network-wide functional alterations. An abnormal temporal discrimination threshold (TDT) is believed to be a mediational endophenotype due to its prevalence in unaffected first-degree relatives as well as patients. However the neural correlates linking abnormal TDT and CD remain poorly understood. Probing changes in large-scale network topology via graph theory with resting state fMRI data from relatives and patients may provide further insight into the pathophysiology of CD. In this study, resting state fMRI data were acquired and analyzed from 16 CD patients with abnormal TDT, 32 unaffected first degree relatives (16 with normal TDT and 16 with abnormal TDT) and 16 healthy controls. Graph theory metrics demonstrating network topology were extracted. The results indicate large-scale functional reorganization of networks in relatives (with abnormal TDT) along with a manifestation of topological aberrations similar to patients.

Original language	English
Title of host publication	2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1694-1697
Number of pages	4
ISBN (Electronic)	9781538613115
DOIs	https://doi.org/10.1109/EMBC.2019.8856624
State	Published - Jul 2019
Externally published	Yes
Event	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany Duration: 23 Jul 2019 → 27 Jul 2019

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Country/Territory	Germany
City	Berlin
Period	23/07/19 → 27/07/19

Access to Document

10.1109/EMBC.2019.8856624

Cite this

Narasimham, S., Sundarajan, V., McGovern, E., Quinlivan, B., Killian, O., O'Riordan, S., Hutchinson, M., & Reilly, R. B. (2019). Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 (pp. 1694-1697). Article 8856624 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2019.8856624

Narasimham, Shruti ; Sundarajan, Vikram ; McGovern, Eavan et al. / Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1694-1697 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

@inproceedings{2a14eb78f35a4e79a978bbf8ef67ef0a,

title = "Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory",

abstract = "Cervical Dystonia (CD) is a neurological movement disorder characterized by intermittent muscle contractions in the head and neck. The pathophysiology and neural networks underpinning this condition are incompletely understood. There is increasing evidence that isolated focal dystonias are due to network-wide functional alterations. An abnormal temporal discrimination threshold (TDT) is believed to be a mediational endophenotype due to its prevalence in unaffected first-degree relatives as well as patients. However the neural correlates linking abnormal TDT and CD remain poorly understood. Probing changes in large-scale network topology via graph theory with resting state fMRI data from relatives and patients may provide further insight into the pathophysiology of CD. In this study, resting state fMRI data were acquired and analyzed from 16 CD patients with abnormal TDT, 32 unaffected first degree relatives (16 with normal TDT and 16 with abnormal TDT) and 16 healthy controls. Graph theory metrics demonstrating network topology were extracted. The results indicate large-scale functional reorganization of networks in relatives (with abnormal TDT) along with a manifestation of topological aberrations similar to patients.",

author = "Shruti Narasimham and Vikram Sundarajan and Eavan McGovern and Brendan Quinlivan and Owen Killian and Sean O'Riordan and Michael Hutchinson and Reilly, \{Richard B.\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 ; Conference date: 23-07-2019 Through 27-07-2019",

year = "2019",

month = jul,

doi = "10.1109/EMBC.2019.8856624",

language = "English",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1694--1697",

booktitle = "2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019",

address = "United States",

}

Narasimham, S, Sundarajan, V, McGovern, E, Quinlivan, B, Killian, O, O'Riordan, S, Hutchinson, M & Reilly, RB 2019, Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory. in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019., 8856624, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc., pp. 1694-1697, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, Berlin, Germany, 23/07/19. https://doi.org/10.1109/EMBC.2019.8856624

Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory. / Narasimham, Shruti; Sundarajan, Vikram; McGovern, Eavan et al.
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1694-1697 8856624 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory

AU - Narasimham, Shruti

AU - Sundarajan, Vikram

AU - McGovern, Eavan

AU - Quinlivan, Brendan

AU - Killian, Owen

AU - O'Riordan, Sean

AU - Hutchinson, Michael

AU - Reilly, Richard B.

PY - 2019/7

Y1 - 2019/7

N2 - Cervical Dystonia (CD) is a neurological movement disorder characterized by intermittent muscle contractions in the head and neck. The pathophysiology and neural networks underpinning this condition are incompletely understood. There is increasing evidence that isolated focal dystonias are due to network-wide functional alterations. An abnormal temporal discrimination threshold (TDT) is believed to be a mediational endophenotype due to its prevalence in unaffected first-degree relatives as well as patients. However the neural correlates linking abnormal TDT and CD remain poorly understood. Probing changes in large-scale network topology via graph theory with resting state fMRI data from relatives and patients may provide further insight into the pathophysiology of CD. In this study, resting state fMRI data were acquired and analyzed from 16 CD patients with abnormal TDT, 32 unaffected first degree relatives (16 with normal TDT and 16 with abnormal TDT) and 16 healthy controls. Graph theory metrics demonstrating network topology were extracted. The results indicate large-scale functional reorganization of networks in relatives (with abnormal TDT) along with a manifestation of topological aberrations similar to patients.

AB - Cervical Dystonia (CD) is a neurological movement disorder characterized by intermittent muscle contractions in the head and neck. The pathophysiology and neural networks underpinning this condition are incompletely understood. There is increasing evidence that isolated focal dystonias are due to network-wide functional alterations. An abnormal temporal discrimination threshold (TDT) is believed to be a mediational endophenotype due to its prevalence in unaffected first-degree relatives as well as patients. However the neural correlates linking abnormal TDT and CD remain poorly understood. Probing changes in large-scale network topology via graph theory with resting state fMRI data from relatives and patients may provide further insight into the pathophysiology of CD. In this study, resting state fMRI data were acquired and analyzed from 16 CD patients with abnormal TDT, 32 unaffected first degree relatives (16 with normal TDT and 16 with abnormal TDT) and 16 healthy controls. Graph theory metrics demonstrating network topology were extracted. The results indicate large-scale functional reorganization of networks in relatives (with abnormal TDT) along with a manifestation of topological aberrations similar to patients.

UR - https://www.scopus.com/pages/publications/85077848286

U2 - 10.1109/EMBC.2019.8856624

DO - 10.1109/EMBC.2019.8856624

M3 - Conference contribution

C2 - 31946223

AN - SCOPUS:85077848286

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 1694

EP - 1697

BT - 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019

Y2 - 23 July 2019 through 27 July 2019

ER -

Narasimham S, Sundarajan V, McGovern E, Quinlivan B, Killian O, O'Riordan S et al. Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1694-1697. 8856624. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2019.8856624

Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory

Abstract

Publication series

Conference

Access to Document

Fingerprint

Cite this