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Neuroimage Clin. 2014 Nov 27;7:98-104. doi: 10.1016/j.nicl.2014.11.018. eCollection 2015.

Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis.

Author information

1
Department of Physical Therapy and Motor Rehabilitation, Faculty of Medicine and Health Sciences, University of Ghent, Ghent, Belgium ; Department of Movement and Sports Sciences, University of Ghent, Ghent, Belgium.
2
Department of Neurology, Morriston Hospital, Swansea, United Kingdom ; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
3
Department of Neurology, University Hospital of Wales, Alan Richens Welsh Epilepsy Centre, Cardiff, United Kingdom ; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Cathays, United Kingdom.
4
Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
5
Department of Neurology, University Hospital of Wales, Alan Richens Welsh Epilepsy Centre, Cardiff, United Kingdom.
6
Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom ; Department of Neurology, University Hospital of Wales, Alan Richens Welsh Epilepsy Centre, Cardiff, United Kingdom.

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.

KEYWORDS:

Diffusion MRI; Epilepsy; Graph theory; Neuropsychology; Structural connectivity

PMID:
25610771
PMCID:
PMC4299970
DOI:
10.1016/j.nicl.2014.11.018
[Indexed for MEDLINE]
Free PMC Article

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