Delayed convergence between brain network structure and function in rolandic epilepsy

Besseling, René M.H.; Jansen, Jacobus F. A.; Overvliet, Geke M.; Kruijs, Sylvie J.M. van der; Ebus, Saskia C.M.; Louw, A.J.A. de; Hofman, Paul; Aldenkamp, Albert P.; Backes, Walter H.

doi:10.3389/fnhum.2014.00704

Cited by 36 publications

(31 citation statements)

References 53 publications

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“…For example, some authors stipulate that the structural and functional connectomes converge during normal brain maturation . This may aid the understanding of age‐specific changes associated with common forms of childhood epilepsy such as epilepsy with centrotemporal spikes …”

Section: Methodologic Limitationsmentioning

confidence: 99%

Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy

2015

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SUMMARYThe assessment of neural networks in epilepsy has become increasingly relevant in the context of translational research, given that localized forms of epilepsy are more likely to be related to abnormal function within specific brain networks, as opposed to isolated focal brain pathology. It is notable that variability in clinical outcomes from epilepsy treatment may be a reflection of individual patterns of network abnormalities. As such, network endophenotypes may be important biomarkers for the diagnosis and treatment of epilepsy. Despite its exceptional potential, measuring abnormal networks in translational research has been thus far constrained by methodologic limitations. Fortunately, recent advancements in neuroscience, particularly in the field of connectomics, permit a detailed assessment of network organization, dynamics, and function at an individual level. Data from the personal connectome can be assessed using principled forms of network analyses based on graph theory, which may disclose patterns of organization that are prone to abnormal dynamics and epileptogenesis. Although the field of connectomics is relatively new, there is already a rapidly growing body of evidence to suggest that it can elucidate several important and fundamental aspects of abnormal networks to epilepsy. In this article, we provide a review of the emerging evidence from connectomics research regarding neural network architecture, dynamics, and function related to epilepsy. We discuss how connectomics may bring together pathophysiologic hypotheses from conceptual and basic models of epilepsy and in vivo biomarkers for clinical translational research. By providing neural network information unique to each individual, the field of connectomics may help to elucidate variability in clinical outcomes and open opportunities for personalized medicine approaches to epilepsy. Connectomics involves complex and rich data from each subject, thus collaborative efforts to enable the systematic and rigorous evaluation of this form of "big data" are paramount to leverage the full potential of this new approach.

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Section: Methodologic Limitationsmentioning

confidence: 99%

Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy

2015

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“…Structural (T1‐weighted, T2‐weighted, fluid‐attenuated inversion recovery [FLAIR]) magnetic resonance (MR) imaging in BECTS usually fails to reveal pathological cerebral abnormalities on visual analyses . Several groups have recently investigated functional connectivity in children with RE . These studies have yielded divergent findings, in terms of directionality (increases or decreases) and localization of alterations in connectivity (Table ).…”

Section: Resting Functional Mri Connectivity Studies In Bectsmentioning

confidence: 99%

Decreased functional connectivity within a language subnetwork in benign epilepsy with centrotemporal spikes

et al. 2017

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SummaryObjectiveBenign epilepsy with centrotemporal spikes (BECTS, also known as Rolandic epilepsy) is a common epilepsy syndrome that is associated with literacy and language impairments. The neural mechanisms of the syndrome are not known. The primary objective of this study was to test the hypothesis that functional connectivity within the language network is decreased in children with BECTS. We also tested the hypothesis that siblings of children with BECTS have similar abnormalities.MethodsEcho planar magnetic resonance (MR) imaging data were acquired from 25 children with BECTS, 12 siblings, and 20 healthy controls, at rest. After preprocessing with particular attention to intrascan motion, the mean signal was extracted from each of 90 regions of interest. Sparse, undirected graphs were constructed from adjacency matrices consisting of Spearman's rank correlation coefficients. Global and nodal graph metrics and subnetwork and pairwise connectivity were compared between groups.ResultsThere were no significant differences in graph metrics between groups. Children with BECTS had decreased functional connectivity relative to controls within a four‐node subnetwork, which consisted of the left inferior frontal gyrus, the left superior frontal gyrus, the left supramarginal gyrus, and the right inferior parietal lobe (p = 0.04). A similar but nonsignificant decrease was also observed for the siblings. The BECTS groups had significant increases in connectivity within a five‐node, five‐edge frontal subnetwork.SignificanceThe results provide further evidence of decreased functional connectivity between key mediators of speech processing, language, and reading in children with BECTS. We hypothesize that these decreases reflect delayed lateralization of the language network and contribute to specific cognitive impairments.

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“…Here the focus of interest has been the impact of epilepsy and its treatment on brain development and understanding the relationship of abnormalities in brain structure with commonly occurring cognitive, academic, and behavioral comorbidities (Besseling et al, 2014; Bonilha et al, 2014; Braakman et al, 2014, 2015; Ibrahim et al, 2014; Widjaja et al, 2014a; Widjaja et al, 2015; Widjaja et al, 2014b). …”

Section: Introductionmentioning

confidence: 99%

Brain structure and organization five decades after childhood onset epilepsy

Garcia‐Ramos¹,

Bobholz²,

Dabbs³

et al. 2017

Human Brain Mapping

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The purpose of this project was to characterize brain structure and organization in persons with active and remitted childhood onset epilepsy 50 years after diagnosis compared to healthy controls. Participants from a population-based investigation of uncomplicated childhood onset epilepsy were followed up 5 decades later. Forty-one participants had a history of childhood onset epilepsy (mean age of onset= 5.2 yrs, current chronological age= 56.0 yrs) and were compared to 48 population-based controls (mean age= 55.9 yrs). Of the epilepsy participants, 8 had persisting active epilepsy and in 33 the epilepsy had remitted. All participants underwent 3T MRI with subsequent vertex analysis of cortical volume, thickness, surface area and gyral complexity. In addition, cortical and subcortical volumes, including regions of the frontal, parietal, temporal, and occipital lobes, and subcortical structures including amygdala, thalamus, and hippocampus, were analyzed using graph theory techniques. There were modest group differences in traditional vertex-based analyses of cortical volume, thickness, surface area and gyral index, as well as across volumes of subcortical structures, after correction for multiple comparisons. Graph theory analyses revealed suboptimal topological structural organization with enhanced network segregation and reduced global integration in the epilepsy participants compared to controls, these patterns significantly more extreme in the active epilepsy group. Furthermore, both groups with epilepsy presented a greater number of higher Z-score regions in betweenness centrality (BC) than lower Z-score regions compared to controls. Also, contrary to the group with remitted epilepsy, patients with active epilepsy presented most of their high BC Z-score regions in subcortical areas including the amygdala, thalamus, hippocampus, pallidum and accumbens. Overall, this population-based investigation of long term outcome (5 decades) of childhood onset epilepsy reveals persisting abnormalities, especially when examined by graph theoretical measurements, and provides new insights into the very long term outcomes of active and remitted epilepsy.

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Delayed convergence between brain network structure and function in rolandic epilepsy

Cited by 36 publications

References 53 publications

Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy

Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy

Decreased functional connectivity within a language subnetwork in benign epilepsy with centrotemporal spikes

Brain structure and organization five decades after childhood onset epilepsy

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