Trial reportPLoS computational biology2015
Predicting Surgery Targets in Temporal Lobe Epilepsy through Structural Connectome Based Simulations.
Trial report in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
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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
43 citing papers in PubMed, 1 synthesis or guideline pooled it, 97 citations in OpenAlex.
- Progress in TLE treatment from 2003 to 2023: scientific measurement and visual analysis based on CiteSpace.Frontiers in neurology · 2023Pooled it
- Seizure recruitment properties are dependent upon dynamotype: A modeling study.PLoS computational biology · 2026Article
- Article
- Effective Connectivity Predicts Surgical Outcomes in Temporal Lobe Epilepsy: A SEEG Study.CNS neuroscience & therapeutics · 2025Article
- Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy.NPJ systems biology and applications · 2025Article
- Mesoscale connectivity of the human hippocampus and fimbria revealed by ex vivo diffusion MRI.NeuroImage · 2025Article
- Bifurcations and bursting in the Epileptor.PLoS computational biology · 2024Article
- Construction and Analysis of a New Resting-State Whole-Brain Network Model.Brain sciences · 2024Article
- Individualized epidemic spreading models predict epilepsy surgery outcomes: A pseudo-prospective study.Network neuroscience (Cambridge, Mass.) · 2024Article
- The role of epidemic spreading in seizure dynamics and epilepsy surgery.Network neuroscience (Cambridge, Mass.) · 2023Article
- Control of epileptic activities in a cortex network of multiple coupled neural populations under electromagnetic induction.Applied mathematics and mechanics · 2023Article
- Article
- Towards network-guided neuromodulation for epilepsy.Brain : a journal of neurology · 2022Review
- Diffusion tractography predicts propagated high-frequency activity during epileptic spasms.Epilepsia · 2022Article
- Epidemic models characterize seizure propagation and the effects of epilepsy surgery in individualized brain networks based on MEG and invasive EEG recordings.Scientific reports · 2022Article
- Computational Models in Electroencephalography.Brain topography · 2022Review
- Optimization of epilepsy surgery through virtual resections on individual structural brain networks.Scientific reports · 2021Article
- Connectivity within regions characterizes epilepsy duration and treatment outcome.Human brain mapping · 2021Article
- Data-driven method to infer the seizure propagation patterns in an epileptic brain from intracranial electroencephalography.PLoS computational biology · 2021Article
- Spatial multi-scaled chimera states of cerebral cortex network and its inherent structure-dynamics relationship in human brain.National science review · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
Abstract
Temporal lobe epilepsy (TLE) is a prevalent neurological disorder resulting in disruptive seizures. In the case of drug resistant epilepsy resective surgery is often considered. This is a procedure hampered by unpredictable success rates, with many patients continuing to have seizures even after surgery. In this study we apply a computational model of epilepsy to patient specific structural connectivity derived from diffusion tensor imaging (DTI) of 22 individuals with left TLE and 39 healthy controls. We validate the model by examining patient-control differences in simulated seizure onset time and network location. We then investigate the potential of the model for surgery prediction by performing in silico surgical resections, removing nodes from patient networks and comparing seizure likelihood post-surgery to pre-surgery simulations. We find that, first, patients tend to transit from non-epileptic to epileptic states more often than controls in the model. Second, regions in the left hemisphere (particularly within temporal and subcortical regions) that are known to be involved in TLE are the most frequent starting points for seizures in patients in the model. In addition, our analysis also implicates regions in the contralateral and frontal locations which may play a role in seizure spreading or surgery resistance. Finally, the model predicts that patient-specific surgery (resection areas chosen on an individual, model-prompted, basis and not following a predefined procedure) may lead to better outcomes than the currently used routine clinical procedure. Taken together this work provides a first step towards patient specific computational modelling of epilepsy surgery in order to inform treatment strategies in individuals.
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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.