Advanced search
1 file | 1.12 MB Add to list

Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis

(2015) NEUROIMAGE-CLINICAL. 7. p.98-104
Author
Organization
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, Structural connectivity, Neuropsychology, IDIOPATHIC GENERALIZED EPILEPSY, ABSENCE SEIZURES, WAVE DISCHARGES, BRAIN NETWORKS, DIFFUSION MRI, EEG-FMRI, CONNECTIVITY, TRACTOGRAPHY, ABNORMALITIES, SPIKE

Downloads

  • caeyenberghs hyperconnectivity in juvenile myoclonic epilepsy.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 1.12 MB

Citation

Please use this url to cite or link to this publication:

MLA
Caeyenberghs, Karen et al. “Hyperconnectivity in Juvenile Myoclonic Epilepsy: a Network Analysis.” NEUROIMAGE-CLINICAL 7 (2015): 98–104. Print.
APA
Caeyenberghs, K., Powell, H., Thomas, R., Brindley, L., Church, C., Evans, J., Muthukumaraswamy, S., et al. (2015). Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis. NEUROIMAGE-CLINICAL, 7, 98–104.
Chicago author-date
Caeyenberghs, Karen, HWR Powell, RH Thomas, L Brindley, C Church, J Evans, SD Muthukumaraswamy, DK Jones, and K Hamandi. 2015. “Hyperconnectivity in Juvenile Myoclonic Epilepsy: a Network Analysis.” Neuroimage-clinical 7: 98–104.
Chicago author-date (all authors)
Caeyenberghs, Karen, HWR Powell, RH Thomas, L Brindley, C Church, J Evans, SD Muthukumaraswamy, DK Jones, and K Hamandi. 2015. “Hyperconnectivity in Juvenile Myoclonic Epilepsy: a Network Analysis.” Neuroimage-clinical 7: 98–104.
Vancouver
1.
Caeyenberghs K, Powell H, Thomas R, Brindley L, Church C, Evans J, et al. Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis. NEUROIMAGE-CLINICAL. 2015;7:98–104.
IEEE
[1]
K. Caeyenberghs et al., “Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis,” NEUROIMAGE-CLINICAL, vol. 7, pp. 98–104, 2015.
@article{5865586,
  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.},
  author       = {Caeyenberghs, Karen and Powell, HWR and Thomas, RH and Brindley, L and Church, C and Evans, J and Muthukumaraswamy, SD and Jones, DK and Hamandi, K},
  issn         = {2213-1582},
  journal      = {NEUROIMAGE-CLINICAL},
  keywords     = {Diffusion MRI,Epilepsy,Graph theory,Structural connectivity,Neuropsychology,IDIOPATHIC GENERALIZED EPILEPSY,ABSENCE SEIZURES,WAVE DISCHARGES,BRAIN NETWORKS,DIFFUSION MRI,EEG-FMRI,CONNECTIVITY,TRACTOGRAPHY,ABNORMALITIES,SPIKE},
  language     = {eng},
  pages        = {98--104},
  title        = {Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis},
  url          = {http://dx.doi.org/10.1016/j.nicl.2014.11.018},
  volume       = {7},
  year         = {2015},
}

Altmetric
View in Altmetric
Web of Science
Times cited: