Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis

Caeyenberghs, K., Powell, H.W.R., Thomas, Rhys Huw, Brindley, Lisa, Church, C., Evans, J., Muthukumaraswamy, S.D., Jones, Derek and Hamandi, Khalid 2015. Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis. NeuroImage: Clinical 7 , pp. 98-104. 10.1016/j.nicl.2014.11.018

Full text not available from this repository.

Abstract

OBJECTIVE: Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. METHODS: Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. RESULTS: Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. CONCLUSIONS: Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Subjects: R Medicine > R Medicine (General)
Publisher: Elsevier: Creative Commons
ISSN: 2213-1582
Last Modified: 14 Mar 2019 11:18
URI: http://orca.cf.ac.uk/id/eprint/74800

Citation Data

Cited 9 times in Google Scholar. View in Google Scholar

Cited 16 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item