Investigation of dynamic functional connectivity of the source reconstructed epileptiform discharges in focal epilepsy: a graph theory approach

2021 ◽  
pp. 106745
Author(s):  
Gian Marco Duma ◽  
Alberto Danieli ◽  
Airis Vettorel ◽  
Lisa Antoniazzi ◽  
Giovanni Mento ◽  
...  
Keyword(s):  
Graph Theory ◽  
Functional Connectivity ◽  
Focal Epilepsy ◽  
Theory Approach ◽  
Dynamic Functional Connectivity ◽  
Epileptiform Discharges

16. Functional connectivity in fronto-temporal focal epilepsy from EEG analysis: A study via graph theory

2015 ◽  
Vol 126 (1) ◽  
pp. e4-e5
Author(s):  
F. Vecchio ◽  
F. Miraglia ◽  
G. Curcio ◽  
G. Della Marca ◽  
C. Vollono ◽  
...  
Keyword(s):  
Graph Theory ◽  
Functional Connectivity ◽  
Focal Epilepsy ◽  
Eeg Analysis

scholarly journals Integration and Segregation of Dynamic Functional Connectivity States for Mild Cognitive Impairment Revealed by Graph Theory Indicators

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhuqing Jiao ◽  
Peng Gao ◽  
Yixin Ji ◽  
Haifeng Shi
Keyword(s):  
Graph Theory ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Time Window ◽  
Clustering Coefficient ◽  
Dynamic Functional Connectivity ◽  
Disease Evolution ◽  
Functional Connections ◽  
Window Method

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Researchers tend to discuss its early state (early MCI, eMCI) due to its high conversion rate of dementia and poor treatment effect in the middle and late stages. Currently, the research on the disease evolution of the brain functional networks of patients with MCI has gradually become a research hotspot. In this study, we compare the differences in dynamic functional connectivity among eMCI, late MCI (lMCI), and normal control (NC) groups, and their graph theory indicators reveal the integration and segregation of functional connectivity states. Firstly, dynamic functional network windows were constructed based on the sliding time window method, and then these window samples were clustered by k-means to extract the functional connectivity states. The differences in the three groups were compared by analyzing the graph theory indicators, such as the participation coefficient, module degree distribution, clustering coefficient, global efficiency, and local efficiency, which distinguish the functional connectivity states. The results reveal that the NC group has the strongest integration and segregation, followed by the eMCI group, and the lMCI group has the weakest integration and segregation. We conclude that with the aggravation of MCI, the integration and segregation of dynamic functional connectivity states tend to decline. The results also reflect that the lMCI group has significantly more brain functional connections in some states, such as IPL.L-MTG.R and DCG.R-SMG.L, than the eMCI group, while the lMCI group has significantly less OLF.L-SPG.L than the NC group.

scholarly journals Alterations in Dynamic Functional Connectivity in Individuals With Subjective Cognitive Decline

2021 ◽  
Vol 13 ◽  
Author(s):  
Qian Chen ◽  
Jiaming Lu ◽  
Xin Zhang ◽  
Yi Sun ◽  
Wenqian Chen ◽  
...  
Keyword(s):  
Graph Theory ◽  
Functional Connectivity ◽  
Cognitive Decline ◽  
Cognitive Performance ◽  
Dwell Time ◽  
Subjective Cognitive Decline ◽  
Control Group ◽  
Dynamic Functional Connectivity ◽  
Neuropsychological Evaluations ◽  
Window Approach

Purpose: To investigate the dynamic functional connectivity (DFC) and static parameters of graph theory in individuals with subjective cognitive decline (SCD) and the associations of DFC and topological properties with cognitive performance.Methods: Thirty-three control subjects and 32 SCD individuals were enrolled in this study, and neuropsychological evaluations and resting-state functional magnetic resonance imaging scanning were performed. Thirty-three components were selected by group independent component analysis to construct 7 functional networks. Based on the sliding window approach and k-means clustering, distinct DFC states were identified. We calculated the temporal properties of fractional windows in each state, the mean dwell time in each state, and the number of transitions between each pair of DFC states. The global and local static parameters were assessed by graph theory analysis. The differences in DFC and topological metrics, and the associations of the altered neuroimaging measures with cognitive performance were assessed.Results: The whole cohort demonstrated 4 distinct connectivity states. Compared to the control group, the SCD group showed increased fractional windows and an increased mean dwell time in state 4, characterized by hypoconnectivity both within and between networks. The SCD group also showed decreased fractional windows and a decreased mean dwell time in state 2, dominated by hyperconnectivity within and between the auditory, visual and somatomotor networks. The number of transitions between state 1 and state 2, between state 2 and state 3, and between state 2 and state 4 was significantly reduced in the SCD group compared to the control group. No significant differences in global or local topological metrics were observed. The altered DFC properties showed significant correlations with cognitive performance.Conclusion: Our findings indicated DFC network reconfiguration in the SCD stage, which may underlie the early cognitive decline in SCD subjects and serve as sensitive neuroimaging biomarkers for the preclinical detection of individuals with incipient Alzheimer's disease.

scholarly journals Functional Connectivity of the Anterior Nucleus of the Thalamus in Pediatric Focal Epilepsy

2021 ◽  
Vol 12 ◽  
Author(s):  
Rory J. Piper ◽  
Chayanin Tangwiriyasakul ◽  
Elhum A. Shamshiri ◽  
Maria Centeno ◽  
Xiaosong He ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Focal Epilepsy ◽  
Epileptiform Activity ◽  
Epileptogenic Zone ◽  
Healthy Children ◽  
Anterior Nucleus ◽  
Epileptiform Discharges ◽  
Significant Difference ◽  
Before And After ◽  
Drug Resistant Epilepsy

Objective: Whilst stimulation of the anterior nucleus of the thalamus has shown efficacy for reducing seizure frequency in adults, alterations in thalamic connectivity have not been explored in children. We tested the hypotheses that (a) the anterior thalamus has increased functional connectivity in children with focal epilepsy, and (b) this alteration in the connectome is a persistent effect of the disease rather than due to transient epileptiform activity.Methods: Data from 35 children (7–18 years) with focal, drug-resistant epilepsy and 20 healthy children (7–17 years) were analyzed. All subjects underwent functional magnetic resonance imaging (fMRI) whilst resting and were simultaneously monitored with scalp electroencephalography (EEG). The fMRI timeseries were extracted for each Automated Anatomical Labeling brain region and thalamic subregion. Graph theory metrics [degree (DC) and eigenvector (EC) centrality] were used to summarize the connectivity profile of the ipsilateral thalamus, and its thalamic parcellations. The effect of interictal epileptiform discharges (IEDs) captured on EEG was used to determine their effect on DC and EC.Results: DC was significantly higher in the anterior nucleus (p = 0.04) of the thalamus ipsilateral to the epileptogenic zone in children with epilepsy compared to controls. On exploratory analyses, we similarly found a higher DC in the lateral dorsal nucleus (p = 0.02), but not any other thalamic subregion. No differences in EC measures were found between patients and controls. We did not find any significant difference in DC or EC in any thalamic subregion when comparing the results of children with epilepsy before, and after the removal of the effects of IEDs.Conclusions: Our data suggest that the anterior and lateral dorsal nuclei of the thalamus are more highly functionally connected in children with poorly controlled focal epilepsy. We did not detect a convincing change in thalamic connectivity caused by transient epileptiform activity, suggesting that it represents a persistent alteration to network dynamics.

Sign in / Sign up

Export Citation Format

Share Document