ArticleEpilepsia2023
Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy.
Article in Epilepsia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Abnormal functional connectivity patterns in temporal lobe epilepsy-An international ENIGMA-epilepsy study.Epilepsia open · 2026Article
- Learning From Our Failures: When Anterior Temporal Lobectomies Fail.Epilepsy currents · 2026Article
- Bitemporal Lobe Epilepsy: Evolving Diagnostic and Treatment Paradigms.Epilepsy currents · 2026Article
- White matter signals reflect information transmission between brain regions during seizures.Brain : a journal of neurology · 2026Article
- Stronger pre-surgical functional connectivity networks are associated with improved surgical outcome in temporal lobe epilepsy.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025Article
- Evaluation of limbic microstructural abnormalities in temporal lobe epilepsy: A neurite orientation distribution and density imaging study.Epilepsia · 2025Article
- Closed-loop electrical stimulation prevents focal epilepsy progression and long-term memory impairment.Nature neuroscience · 2025Article
- Brain network alterations in mobile phone use problem severity: A multimodal neuroimaging analysis.Journal of behavioral addictions · 2025Article
- Dynamic reconfiguration of aperiodic brain activity supports cognitive functioning in epilepsy: A neural fingerprint identification.iScience · 2025Article
- Connectivity of the Piriform Cortex and its Implications in Temporal Lobe Epilepsy.medRxiv : the preprint server for health sciences · 2024Article
- iEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.Epilepsia · 2024Article
- Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy.Brain communications · 2024Article
- Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy.medRxiv : the preprint server for health sciences · 2023Article
- Subcortical Functional Connectivity Gradients in Temporal Lobe Epilepsy.medRxiv : the preprint server for health sciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
objectiveTemporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE).
methodsIn this study, using a multicenter resting state functional magnetic resonance imaging (rs-fMRI) data set, we constructed whole-brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the "integration-segregation axis," by combining whole-brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)-based dimensionality reduction.
resultsCompared to UTLE, BiTLE had decreased global efficiency (p = .031), and decreased whole brain average participation coefficient across a range of network densities (p = .019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p = .020). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration-segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE. SIGNIFICANCE: Increased interictal whole-brain network segregation, as measured by rs-fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non-invasively identifying this patient population prior to intracranial electroencephalography or device implantation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.