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Updated: Sep 27, 2025

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
Published on: December 18, 2016
Connectomic Profiles and Cognitive Trajectories After Epilepsy Surgery in Children
Olivia N Arski1, Daniel J Martire1, Julia M Young1
1From the Program in Neuroscience and Mental Health (O.N.A., D.J.M., J.M.Y., S.M.W., M.L.S., G.M.I.), Hospital for Sick Children Research Institute; Institute of Medical Science (O.N.A., G.M.I.), University of Toronto; Department of Psychology (J.M.Y., E.N.K., M.L.S.), Hospital for Sick Children, University of Toronto; Institute of Biomaterials and Biomedical Engineering (S.M.W., G.M.I.), University of Toronto; Division of Neurosurgery (H.S., G.M.I.), Hospital for Sick Children, Department of Surgery, University of Toronto; Division of Neurology (A.O., H.O., R.S., O.C.S., P.J., E.J.D.) and Diagnostic Imaging (E.W.), Hospital for Sick Children, University of Toronto; and Department of Psychology (M.L.S.), University of Toronto Mississauga, Ontario, Canada.
Background And Objectives:
Neurocognitive outcomes after surgery for temporal lobe epilepsy in childhood are variable. Postoperative changes are not directly predicted by seizure freedom, and associations between epilepsy, neuropsychological function, and developing neural networks are poorly understood. Here, we leveraged whole-brain connectomic profiling in magnetoencephalography (MEG) to retrospectively study associations between brain connectivity and neuropsychological function in children with temporal lobe epilepsy undergoing resective surgery.
Methods:
Clinical and MEG data were retrospectively analyzed for children who underwent temporal lobe epilepsy surgery at the Hospital for Sick Children from 2000 to 2021. Resting-state connectomes were constructed from neuromagnetic oscillations via the weighted-phase lag index. Using a partial least-squares (PLS) approach, we assessed multidimensional associations between patient connectomes, neuropsychological scores, and clinical covariates. Bootstrap resampling statistics were performed to assess statistical significance.
Results:
A total of 133 medical records were reviewed, and 5 PLS analyses were performed. Each PLS analysis probed a particular neuropsychological domain and the associations between its baseline and postoperative scores and the connectomic data. In each PLS analysis, a significant latent variable was identified, representing a specific percentage of the variance in the data and relating neural networks to clinical covariates, which included changes in rote verbal memory (n = 41, p = 0.01, σ2 = 0.38), narrative/verbal memory (n = 57, p = 0.00, σ2 = 0.52), visual memory (n = 51, p = 0.00, σ2 = 0.43), working memory (n = 44, p = 0.00, σ2 = 0.52), and overall intellectual function (n = 59, p = 0.00, σ2 = 0.55). Children with more diffuse, bilateral intrinsic connectivity across several frequency bands showed lower scores on all neuropsychological assessments but demonstrated a greater propensity for gains after resective surgery.
Discussion:
Here, we report that connectomes characterized by diffuse connectivity, reminiscent of developmentally immature networks, are associated with lower preoperative cognition and postoperative cognitive improvement. These findings provide a potential means to understand neurocognitive function in children with temporal lobe epilepsy and expected changes postoperatively.
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