ArticleScientific reports2021
Regional abnormality of functional connectivity is associated with clinical manifestations in individuals with intractable focal epilepsy.
Article in Scientific reports, 2021. 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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6 citing papers in PubMed, 9 citations in OpenAlex.
- Characterization and Classification of ADHD Subtypes: An Approach Based on the Nodal Distribution of Eigenvector Centrality and Classification Tree Model.Child psychiatry and human development · 2024Article
- Similarities and differences of dynamic and static spontaneous brain activity between left and right temporal lobe epilepsy.Brain imaging and behavior · 2024Article
- Focal to bilateral tonic-clonic seizures predict pharmacoresistance in focal cortical dysplasia-related epilepsy.Epilepsia · 2023Article
- Network structure mediates functional reorganization induced by optogenetic stimulation of non-human primate sensorimotor cortex.iScience · 2022Article
- More than just statics: Static and temporal dynamic changes in intrinsic brain activity in unilateral temporal lobe epilepsy.Frontiers in human neuroscience · 2022Article
- Networks of cortical activity in infants with epilepsy.Brain communications · 2022Article
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Authors and funding
6 authors at 2 institutions in 1 country.
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Abstract
We explored regional functional connectivity alterations in intractable focal epilepsy brains using resting-state functional MRI. Distributions of the network parameters (corresponding to degree and eigenvector centrality) measured at each brain region for all 25 patients were significantly different from age- and sex-matched control data that were estimated by a healthy control dataset (n = 582, 18-84 years old). The number of abnormal regions whose parameters exceeded the mean + 2 SD of age- and sex-matched data for each patient were associated with various clinical parameters such as the duration of illness and seizure severity. Furthermore, abnormal regions for each patient tended to have functional connections with each other (mean ± SD = 58.6 ± 20.2%), the magnitude of which was negatively related to the quality of life. The abnormal regions distributed within the default mode network with significantly higher probability (p < 0.05) in 7 of 25 patients. We consider that the detection of abnormal regions by functional connectivity analysis using a large number of control datasets is useful for the numerical assessment of each patient's clinical conditions, although further study is necessary to elucidate etiology-specific abnormalities.
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