Altered structural brain networks in refractory and non-refractory idiopathic generalised epilepsy

2021 ◽  
Author(s):  
Andrea McKavanagh ◽  
Barbara A.K Kreilkamp ◽  
Yachin Chen ◽  
Christine Denby ◽  
Martyn Bracewell ◽  
...  
Keyword(s):  
Brain Networks ◽  
Idiopathic Generalised Epilepsy ◽  
Structural Brain

scholarly journals Intergenerational transmission of the patterns of functional and structural brain networks

iScience ◽  
2021 ◽  
pp. 102708
Author(s):  
Yu Takagi ◽  
Naohiro Okada ◽  
Shuntaro Ando ◽  
Noriaki Yahata ◽  
Kentaro Morita ◽  
...  
Keyword(s):  
Intergenerational Transmission ◽  
Brain Networks ◽  
Structural Brain

scholarly journals Association between age of cannabis initiation and gray matter covariance networks in recent onset psychosis

2021 ◽  
Author(s):  
Nora Penzel ◽  
◽  
Linda A. Antonucci ◽  
Linda T. Betz ◽  
Rachele Sanfelici ◽  
...  
Keyword(s):  
Gray Matter ◽  
Inferior Frontal Gyrus ◽  
Brain Networks ◽  
Developmental Trajectory ◽  
Cannabis Use ◽  
Brain Maturation ◽  
Confounding Factors ◽  
Recent Onset ◽  
Increased Risk ◽  
Structural Brain

AbstractCannabis use during adolescence is associated with an increased risk of developing psychosis. According to a current hypothesis, this results from detrimental effects of early cannabis use on brain maturation during this vulnerable period. However, studies investigating the interaction between early cannabis use and brain structural alterations hitherto reported inconclusive findings. We investigated effects of age of cannabis initiation on psychosis using data from the multicentric Personalized Prognostic Tools for Early Psychosis Management (PRONIA) and the Cannabis Induced Psychosis (CIP) studies, yielding a total sample of 102 clinically-relevant cannabis users with recent onset psychosis. GM covariance underlies shared maturational processes. Therefore, we performed source-based morphometry analysis with spatial constraints on structural brain networks showing significant alterations in schizophrenia in a previous multisite study, thus testing associations of these networks with the age of cannabis initiation and with confounding factors. Earlier cannabis initiation was associated with more severe positive symptoms in our cohort. Greater gray matter volume (GMV) in the previously identified cerebellar schizophrenia-related network had a significant association with early cannabis use, independent of several possibly confounding factors. Moreover, GMV in the cerebellar network was associated with lower volume in another network previously associated with schizophrenia, comprising the insula, superior temporal, and inferior frontal gyrus. These findings are in line with previous investigations in healthy cannabis users, and suggest that early initiation of cannabis perturbs the developmental trajectory of certain structural brain networks in a manner imparting risk for psychosis later in life.

scholarly journals Altered Structural Brain Networks in Tuberous Sclerosis Complex

2015 ◽  
Vol 26 (5) ◽  
pp. 2046-2058 ◽  
Author(s):  
Kiho Im ◽  
Banu Ahtam ◽  
Daniel Haehn ◽  
Jurriaan M. Peters ◽  
Simon K. Warfield ◽  
...  
Keyword(s):  
Tuberous Sclerosis ◽  
Tuberous Sclerosis Complex ◽  
Brain Networks ◽  
Structural Brain

scholarly journals Functional and structural brain networks in epilepsy: What have we learned?

Epilepsia ◽  
2013 ◽  
Vol 54 (11) ◽  
pp. 1855-1865 ◽  
Author(s):  
Eric van Diessen ◽  
Sander J. H. Diederen ◽  
Kees P. J. Braun ◽  
Floor E. Jansen ◽  
Cornelis J. Stam
Keyword(s):  
Brain Networks ◽  
Structural Brain

scholarly journals Altered topology of large-scale structural brain networks in chronic stroke

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Bastian Cheng ◽  
Eckhard Schlemm ◽  
Robert Schulz ◽  
Marlene Boenstrup ◽  
Arnaud Messé ◽  
...  
Keyword(s):  
Information Transfer ◽  
Large Scale ◽  
Neuronal Degeneration ◽  
Brain Networks ◽  
Brain Regions ◽  
Local Network ◽  
Structural Connectome ◽  
The Impact ◽  
Structural Brain ◽  
Topological Changes

Abstract Beyond disruption of neuronal pathways, focal stroke lesions induce structural disintegration of distant, yet connected brain regions via retrograde neuronal degeneration. Stroke lesions alter functional brain connectivity and topology in large-scale brain networks. These changes are associated with the degree of clinical impairment and recovery. In contrast, changes of large scale, structural brain networks after stroke are less well reported. We therefore aimed to analyse the impact of focal lesions on the structural connectome after stroke based on data from diffusion-weighted imaging and probabilistic fibre tracking. In total, 17 patients (mean age 64.5 ± 8.4 years) with upper limb motor deficits in the chronic stage after stroke and 21 healthy participants (mean age 64.9 ± 10.3 years) were included. Clinical deficits were evaluated by grip strength and the upper extremity Fugl-Meyer assessment. We calculated global and local graph theoretical measures to characterize topological changes in the structural connectome. Results from our analysis demonstrated significant alterations of network topology in both ipsi- and contralesional, primarily unaffected, hemispheres after stroke. Global efficiency was significantly lower in stroke connectomes as an indicator of overall reduced capacity for information transfer between distant brain areas. Furthermore, topology of structural connectomes was shifted toward a higher degree of segregation as indicated by significantly higher values of global clustering and modularity. On a level of local network parameters, these effects were most pronounced in a subnetwork of cortico-subcortical brain regions involved in motor control. Structural changes were not significantly associated with clinical measures. We propose that the observed network changes in our patients are best explained by the disruption of inter- and intrahemispheric, long white matter fibre tracts connecting distant brain regions. Our results add novel insights on topological changes of structural large-scale brain networks in the ipsi- and contralesional hemisphere after stroke.

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