ArticleNeuroImage. Clinical2019
Connectivity strength, time lag structure and the epilepsy network in resting-state fMRI.
Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 14 citations in OpenAlex.
- States of dynamic connectivity flow in temporal multiplex networks: A case study in human epilepsy and postictal aphasia.Network neuroscience (Cambridge, Mass.) · 2026Article
- Altered coupling of cerebral blood perfusion and neuronal activity in children with MRI-negative drug refractory epilepsy.Quantitative imaging in medicine and surgery · 2025Article
- Effective connectivity relates seizure outcome to electrode placement in responsive neurostimulation.Brain communications · 2024Article
- Directed Brain Connectivity Identifies Widespread Functional Network Abnormalities in Parkinson's Disease.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- Topographical reorganization of brain functional connectivity during an early period of epileptogenesis.Epilepsia · 2021Article
- Lag Analysis of Fast fMRI Reveals Delayed Information Flow Between the Default Mode and Other Networks in Narcolepsy.Cerebral cortex communications · 2020Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The relationship between the epilepsy network, intrinsic brain networks and hypersynchrony in epilepsy remains incompletely understood. To converge upon a synthesized understanding of these features, we studied two elements of functional connectivity in epilepsy: correlation and time lag structure using resting state fMRI data from both SEEG-defined epileptic brain regions and whole-brain fMRI analysis. Functional connectivity (FC) was analyzed in 15 patients with epilepsy and 36 controls. Correlation strength and time lag were selected to investigate the magnitude of and temporal interdependency across brain regions. Zone-based analysis was carried out investigating directed correlation strength and time lag between both SEEG-defined nodes of the epilepsy network and between the epileptogenic zone and all other brain regions. Findings were compared between patients and controls and against a functional atlas. FC analysis on the nodal and whole brain levels identifies consistent patterns of altered correlation strength and altered time lag architecture in epilepsy patients compared to controls. These patterns include 1) broadly distributed increased strength of correlation between the seizure onset node and the remainder of the brain, 2) decreased time lag within the seizure onset node, and 3) globally increased time lag throughout all regions of the brain not involved in seizure onset or propagation. Comparing the topographic distribution of findings against a functional atlas, all resting state networks were involved to a variable degree. These local and whole brain findings presented here lead us to propose the network steal hypothesis as a possible mechanistic explanation for the non-seizure clinical manifestations of epilepsy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.