ArticleNeurosurgery2018
Granger Causality Analysis of Interictal iEEG Predicts Seizure Focus and Ultimate Resection.
Article in Neurosurgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- A geometry aware framework enhances noninvasive mapping of whole human brain dynamics.Nature biomedical engineering · 2026Article
- Utility of Interictal Data in Guiding Pediatric Epilepsy Surgery.Pediatric neurosurgery · 2026Review
- Spatial and spectral structure of local functional connectivity of the background intracranial EEG in patients with focal epilepsy.Frontiers in network physiology · 2025Article
- Epilepsy lesion localization method based on brain function network.Frontiers in human neuroscience · 2024Article
- Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy.Brain : a journal of neurology · 2023Article
- Interictal Functional Connectivity in Focal Refractory Epilepsies Investigated by Intracranial EEG.Brain connectivity · 2022Review
- Interictal Connectivity Revealed by Granger Analysis of Stereoelectroencephalography: Association With Ictal Onset Zone, Resection, and Outcome.Neurosurgery · 2022Article
- Extensions of Granger Causality Calculations on Brain Networks for Efficient and Accurate Seizure Focus Identification via iEEGs.Brain sciences · 2021Article
- Combination of Matching Responsive Stimulations of Hippocampus and Subiculum for Effective Seizure Suppression in Temporal Lobe Epilepsy.Frontiers in neurology · 2021Article
- The value of intra-operative electrographic biomarkers for tailoring during epilepsy surgery: from group-level to patient-level analysis.Scientific reports · 2020Article
- Interictal intracranial electroencephalography for predicting surgical success: The importance of space and time.Epilepsia · 2020Article
- Seizure Onset Zone Lateralization Using a Non-linear Analysis of Micro vs. Macro Electroencephalographic Recordings During Seizure-Free Stages of the Sleep-Wake Cycle From Epilepsy Patients.Frontiers in neurology · 2020Article
- Prediction of epilepsy seizure from multi-channel electroencephalogram by effective connectivity analysis using Granger causality and directed transfer function methods.Cognitive neurodynamics · 2019Article
- Changing concepts in presurgical assessment for epilepsy surgery.Nature reviews. Neurology · 2019Review
- Brain-Computer Interface (BCI) Applications in Mapping of Epileptic Brain Networks Based on Intracranial-EEG: An Update.Frontiers in neuroscience · 2019Article
- The Ventral Intermediate Nucleus Differently Modulates Subtype-Related Networks in Parkinson's Disease.Frontiers in neuroscience · 2019Article
- BECTS Substate Classification by Granger Causality Density Based Support Vector Machine Model.Frontiers in neurology · 2019Article
- Magnetoencephalographic Mapping of Epileptic Spike Population Using Distributed Source Analysis: Comparison With Intracranial Electroencephalographic Spikes.Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society · 2018Article
- Localization of the Epileptogenic Zone Using Interictal MEG and Machine Learning in a Large Cohort of Drug-Resistant Epilepsy Patients.Frontiers in neurology · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA critical conceptual step in epilepsy surgery is to locate the causal region of seizures. In practice, the causal region may be inferred from the set of electrodes showing early ictal activity. There would be advantages in deriving information about causal regions from interictal data as well. We applied Granger's statistical approach to baseline interictal data to calculate causal interactions. We hypothesized that maps of the Granger causality network (or GC maps) from interictal data might inform about the seizure network, and set out to see if "causality" in the Granger sense correlated with surgical targets.
objectiveTo determine whether interictal baseline data could produce GC maps, and whether the regions of high GC would statistically resemble the topography of the ictally active electrode (IAE) set and resection.
methodsTwenty-minute interictal baselines obtained from 25 consecutive patients were analyzed. The "GC maps" were quantitatively compared to conventionally constructed surgical plans, by using rank order and Cartesian distance statistics.
resultsIn 16 of 25 cases, the interictal GC rankings of the electrodes in the IAE set were lower than predicted by chance (P < .05). The aggregate probability of such a match by chance alone is very small (P < 10-20) suggesting that interictal GC maps correlated with ictal networks. The distance of the highest GC electrode to the IAE set and to the resection averaged 4 and 6 mm (Wilcoxon P < .001).
conclusionGC analysis has the potential to help localize ictal networks from interictal data.
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