Thalamo-cortical Synchrony Shapes Seizure Expression in Human Temporal Lobe Epilepsy

Thalamo-cortical Synchrony Shapes Seizure Expression in Human Temporal Lobe Epilepsy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Thalamo-cortical Synchrony Shapes Seizure Expression in Human Temporal Lobe Epilepsy Thandar Aung, Jian Li, Tipakorn Tumnark, Chandana Belly, John Thomas, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7419263/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract In drug-resistant temporal lobe epilepsy (DR-TLE), electrographic seizures with clinical symptoms (CS) largely determine quality of life, yet some remain silent (NCS) despite arising from the same seizure-onset zone (SOZ). While surgical resection can be curative in select cases, many patients particularly those with bilateral TLE or unresectable networks are not surgical candidates. For these individuals, clarifying why some seizures produce symptoms while others do not is essential for advancing therapy. We hypothesized that thalamo-cortical network engagement may explain this divergence. 286 seizures from 62 DR-TLE patients, included coverage of the pulvinar and/or anterior thalamic group, were analyzed. Thalamo-cortical synchrony, quantified as the correlation between time–frequency patterns in thalamic nuclei and the cortical SOZ, was investigated in relation to seizure type, epilepsy subtype, thalamic region, and one-year post-resection surgical outcome. Thalamo-cortical synchrony was stronger during CS than NCS (p 0.6), regardless of epilepsy subtype, thalamic region, seizure subtype, or outcome, and confirmed within patients. Multivariate analysis identified seizure type as the only independent predictor (p < 0.001). These findings establish thalamo-cortical synchrony as a network-level marker of clinical seizure expression and highlight the potential of neuromodulation to modulate seizure expression when resection is not feasible. Health sciences/Medical research/Translational research Health sciences/Biomarkers/Diagnostic markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Temporal lobe epilepsy (TLE), the most common form of focal drug-resistant epilepsy (DRE), is frequently treated with anterior temporal lobectomy, particularly in mesial temporal sclerosis (MTS) 1 . However, despite comprehensive presurgical evaluation, 20–40% of patients, including those with MTS, experience recurrent seizures postoperatively 1 – 3 . This limitation has shifted the field toward viewing epilepsy as a disorder of distributed brain networks rather than an isolated cortical phenomenon 4 – 6 . Stereo-electroencephalography (SEEG) has been instrumental in this shift, revealing that subcortical structures, particularly the pulvinar (Pul), and the anterior thalamic nuclei, are active participants in seizure generation and modulation in TLE 5 , 7 , 16 , 8 – 15 . Thalamo-cortical interactions are not unique to epilepsy and across neurological disorders, they shape the expression of symptoms, from motor network dysregulation in movement disorders to functional deficits following stroke 17 , 18 . Although debate over the relative roles of the thalamus and cortex in seizure pathogenesis dates back to the 1800s 19 , 20 , evidence from imaging and SEEG neurophysiology studies highlights that the thalamus is not a passive relay but an active hub influencing seizure propagation, termination, and clinical manifestation, and may contribute to surgical failure 9 , 11 , 12 , 14 , 16 , 21 . Increasingly, the thalamus is recognized as a critical therapeutic target, particularly for patients with bilateral seizure onset or unresectable networks, where neuromodulation offers the next step beyond resection 22–2425 . In DR-TLE, clinical seizures (CS), epileptic discharges with overt subjective or observable objective clinical manifestations, are associated with reduced quality of life. With widespread SEEG use, nonclinical seizures (NCS), electrographic seizures without observable symptoms, are increasingly recognized alongside clinical seizures 26 – 29 . Although CS and NCS may originate from the same epileptogenic zone (EZ) in a given patient, the mechanisms underlying their divergent clinical expression remain poorly understood. Experimental studies suggest that differences in neuronal recruitment, synchrony, and propagation may account for this variability 28 , 30 – 32 . However, these hypotheses have not been systematically tested in humans, particularly regarding thalamic dynamics. Prior reports have described intra-subject variability in thalamic recruitment based on ictal frequency and spatial extent (broad vs. focal), but have not directly compared CS and NCS 10 , 33 . Furthermore, no study has comprehensively examined how thalamo–temporal dynamics differ across clinical subtypes, focal preserved consciousness (FPC), focal impaired consciousness (FIC), and focal to bilateral tonic–clonic (FBTC), or how these patterns relate to postoperative seizure outcomes. Understanding why some seizures produce symptoms while others remain silent remains a central challenge, hindered by the lack of a reproducible network-level biomarker. Addressing this gap is essential for advancing mechanistic understanding of seizure semiology and for guiding neuromodulatory strategies for nonresectable DR-TLE. We hypothesized that thalamo-cortical synchrony, particularly involving the Pul and anterior thalamic group (ATG), contributes to clinical seizure expression in DR-TLE. Specifically, we predicted that CS would exhibit stronger thalamo-temporal coupling than NCS. We further examined whether this coupling differs across seizure subtypes (FPC, FIC, FBTC) and whether it relates to post-surgical outcomes. Using SEEG-based time–frequency (TF) analysis in a multicenter cohort with targeted thalamic coverage, we quantified thalamo–temporal spectral correlation to examine its association with seizure semiology and surgical prognosis. Materials and Method Patient selection, demographic data and seizure selection The study was approved by the institutional review board at the University of Pittsburgh (January 2020 to June 2025) and the Duke University Hospital (June 2023 to June 2025). Consecutive patients (≥ 16 years) with focal DR-TLE from both centers were included if intracranial exploration covered temporal and thalamic regions with at least one SEEG electrode contact in ATG, Pul, or both. Only patients who experienced at least one spontaneous habitual seizure during SEEG monitoring were eligible. Patients whose EZ extended beyond the temporal lobe were excluded ( Supplementary Fig. 1 ). Demographic and clinical data (age, sex, epilepsy onset, duration, MRI findings, SOZ, electrode placement, outcome, and follow-up duration) were collected from medical records. Anatomical and electrophysiological data on each patient's SOZ were obtained from the multidisciplinary patient management conferences held after SEEG evaluation. Two experienced epileptologists (T.A., T.T.) independently reviewed and confirmed the SOZ localization. Additionally, all recorded seizures were retrospectively reviewed and classified as clinical or nonclinical by the same two epileptologists (T.A., T.T.). In cases of disagreement, seizures were jointly re-reviewed, and if consensus could not be reached, those seizures were excluded. Seizures that were untested or unclear on video review were also excluded. Seizures were classified as non-clinical when patients, tested during the event, exhibited no observable clinical signs or reported symptoms, with such events defined as self-limited, broadly synchronized paroxysmal epileptiform discharges unaccompanied by behavioral manifestations. Seizures were clinical if patients reported subjective symptoms, or observable signs were present and further categorized using the updated ILAE classification 34 as FPC, FIC, or FTBC. FPC was defined as seizures with retained awareness and responsiveness; FIC as seizures with altered awareness or responsiveness; and FBTC as focal seizures that secondarily generalized to bilateral tonic–clonic activity. A maximum of four seizures per category (FPC, FIC, FBTC, and nonclinical) were analyzed per patient. For patients exhibiting multiple seizure types, up to four seizures from each type were included. Epilepsy subtypes were classified based on seizure onset zone. Mesial temporal lobe epilepsy (mTLE) was defined as seizures arising from the mesial limbic network, including the hippocampus, amygdala, entorhinal cortex, and mesial temporal pole. Mesio-lateral TLE involved both mesial and lateral temporal regions, while lateral TLE was defined as seizures originating exclusively from the lateral temporal neocortex, without evidence of mesial involvement 35 . For patients who underwent resective surgery or neurostimulation, follow-up duration was calculated from the date of surgery to the most recent clinic visit. Seizure outcomes were classified using the Engel system 36 , with only patients achieving Engel Class 1A and at least one year of follow-up considered seizure-free (SF). Electrode localization Electrode contacts were localized by co-registering post-implantation thin-sliced CT with preoperative 1 mm T1-weighted MRI using SPM12 37 (Fig. 1). Electrode positions were mapped in subject space using a 0.4 mm radius sphere and the Automated Anatomical Labeling atlas 3 (AAL3) 38 . T1 MRIs were then nonlinearly registered to the ICBM2023b MNI template 39 to obtain MNI coordinates. Pulvinar group contacts included any subnucleus within the pulvinar complex (e.g., PuA, PuM, PuL, PuI). ATG contacts included those labeled as ventral anterior (VA), anteroventral (AV), or ventral lateral anterior (VLa) per AAL3 ( Supplementary Table 1 ). Figure 1B shows electrode trajectories from all patients overlaid on the ICBM2023b cortical surfaces, with pulvinar and ATG contacts visualized using AAL3 surface-rendered thalamic segmentation (Fig. 1C) and ultra-high resolution 7 Tesla ex vivo brain scans in MNI space (Fig. 1D) 40 . Data selection, time-frequency decomposition, synchrony correlation analysis and epileptogenicity index SEEG signals were sampled at 2048 Hz at both institutions. For each seizure, 40 seconds (s) of SEEG data were extracted, comprising 20s before and 20s after seizure onset (Fig. 1A). Additionally, a 40-second baseline epoch was obtained at least two minutes prior to seizure onset. Data were preprocessed in Brainstorm 41 and imported to the Epileptogenic Zone Fingerprint software 42 for the following TF analyses. Both ictal and baseline TF decomposition was performed using the Morlet wavelets (1–200 Hz, 1 Hz steps; 3-s time resolution). Seizure TF maps (including grey and white matter electrode contacts) were normalized against the corresponding baseline maps across all frequencies, following our previously published methodology 43 , 44 . All analyses were performed using bipolar montages. To reduce artifacts, a complex independent component analysis was applied to the TF plots to identify and remove artifacts common across channels (e.g., muscle activity). Channels with channel-specific artifacts, including those located outside the brain or within the ventricular system, were excluded. Seizures with artifacts in SOZ or thalamic contacts were excluded. In patients with bilateral thalamic implantation, only ipsilateral thalamic contacts and ipsilateral mesial temporal SOZ electrodes were analyzed. Thalamic contacts were localized using subject-specific anatomical labels from the AAL3 atlas, and multiple bipolar pairs within the SOZ were selected. A Spectral Synchrony Correlation was applied to quantify frequency-specific thalamo-cortical SOZ coupling, i.e., thalamo-cortical synchrony. TF decomposition was performed using a continuous wavelet transform, and Pearson correlation coefficients were calculated between normalized power envelopes across sliding windows, generating frequency–correlation profiles. For each seizure, the median correlation value across all SOZ–thalamus pairs was used for statistical analysis (Fig. 1). In patients who underwent resection, one habitual stereotypic seizure, prefer clinical, per patient was additionally used to compute the epileptogenicity index (EI) following Bartolomei et al. 45 , using a 20-second window from ictal onset, to assess thalamic involvement in seizure initiation. By measuring the abruptness and magnitude of ictal power changes relative to interictal baseline, EI offers a standardized, quantitative assessment of a structure’s role in the early propagation of epileptic activity. Applying an EI threshold of > 0.3 14 , as previously suggested for the pulvinar, allowed classification of patients into high- and low-EI groups, enabling direct comparison with postoperative seizure outcomes. Statistical Analysis Due to non-normal distribution of thalamo–temporal correlation values, non-parametric tests were used. CS vs. NCS and SF (Engel IA) vs. NSF (Engel IB–IV) were compared using Mann–Whitney U tests (p < 0.05). For seizure subtypes (FPC, FIC, FBTC), the Kruskal–Wallis H test was followed by Bonferroni-adjusted pairwise tests (p < 0.0167). For combined outcome/semiology groups (SF-CS, SF-NCS, NSF-CS, NSF-NCS), six comparisons were tested with a threshold of p < 0.0083. The same threshold was applied to intra-subject comparisons involving thalamic region and seizure type (Pul-CS, ATG-CS, Pul-NCS, ATG-NCS) and stratified intra-subject outcome/semiology groups (SF-CS, SF-NCS, NSF-CS, NSF-NCS). Effect size was estimated using Cliff’s delta (δ). Effect sizes were classified as negligible (|δ| < 0.147), small (0.147–0.33), medium (0.33–0.474), or large (≥ 0.474). To assess independent predictors of thalamo–temporal coupling, multiple linear regression was performed with seizure type (CS vs. NCS) as the primary variable. Covariates included thalamic region (Pul vs. ATG), seizure outcome (SF vs. NSF), and TLE subtype (mesial, lateral, mesiolateral), selected based on clinical relevance and univariate findings. Model fit was assessed via R², F-statistics, and p-values. Analyses were conducted in MATLAB (The MathWorks Inc., Natick, MA) and Stata (StataCorp, College Station, TX). Results Patient Demographics A total of 62 consecutive patients with DR-TLE (286 seizures: 224 clinical seizures (CS), 62 nonclinical seizures (NCS)) were included. The average seizure duration was 158 seconds for CS and 67 seconds for NCS. The median age at SEEG evaluation was 37 ± 13.6 years (range: 16–68), and median epilepsy duration was 11.5 ± 11.2 years (range: 1–43.5). Most were right-handed males with non-lesional MRI; 10 had prior resective surgery or laser ablation (Table 1 ). During SEEG monitoring, 66.1% of the patients (n = 41) had only CS, 32.3% (n = 20) had both CS and NCS, and 1.6% (n = 1) had only NCS (1.6%). mTLE was diagnosed in 51.5% (n = 32), including five with bilateral onset. Thalamic coverage included Pul only (n = 48), both Pul and ATG (n = 11), and ATG only (n = 3). Surgical intervention was performed in 77.4% (n = 48, 46 surgical resections, 2 laser ablations). Of the 46 patients who underwent resection, 38 (178 seizures: 138 CS, 40 NCS) had ≥ 1 year of follow-up (mean: 21.4 months; range: 12–63), with 50% (n = 19) achieving seizure freedom (Engel IA). Among them, 30 had Pul-only coverage, 6 had both Pul and ATG, and 2 had ATG only. Table 1 Detailed demographics and clinical information of the patient population Total patient (N = 62 patients) Age at the time of SEEG recording (median, mean ± SD) (range) (y) 37.0, 38.4 ± 13.6 (16–68) Age at time of seizure onset (median, mean ± SD) (range) (y) 24.0, 24.6 ± 15.0 (0–65) Duration of epilepsy (median, mean ± SD) (range) (y) 11.5, 13.6 ± 11.2 (1-43.5) Handedness - Right - Left - Ambidextrous 53 (85.5%) 8 (12.9%) 1 (1.6%) Male (%) 39 (62.9%) MRI finding - None - Prior resection or laser ablation - Mesial temporal sclerosis - Temporal lobe encephalomalacia and temporal encephalocele - Nonspecific changes (cortical flair changes) - Cavernoma 30 (48.4%) 10 (16.1%) 8 (12.9%) 7 (11.3%) 5 (8.1%) 2 (3.25) SEEG implantation scheme - Unilateral o Left o Right - Bilateral 43 (69.4%) 33/43 10/43 19 (30.6%) Thalamus Implantation - Only Pulvinar - Only Anterior thalamus Group - Both Pulvinar and Anterior thalamus Group 48 (77.4%) 3 (4.8%) 11 (17.7%) Seizure semiology captured during SEEG evaluation - Only Clinical (FPC, FIC and FTBC) seizures - Only Nonclinical seizures - Both Clinical Nonclinical Seizures 41 (64.5%) 1 (1.6%) 20 (33.9%) Location of the confirmed epileptogenic zone # - Mesial temporal o Unilateral o Bilateral & - Mesial and lateral temporal o Unilateral o Bilateral - Lateral temporal # 32 (51.6%) 30/32 5/32 11 (17.7%) 10/11 1/11 19 (30.6%) Surgical Intervention - Resection o Corticectomy o Temporal lobectomy - Laser ablation - RNS - No intervention or waiting for surgical intervention* 46 (74.2%) 9 37 2 (3.2%) 6 (9.7%) 8 (12.9%) Total (N = 38 patients) The outcome of 38 patients who underwent resective or laser ablation surgery with at least 1 year follow-up - Engel IA outcome - Other Engel 1 outcome - Engel II-IV outcome 19 (50%) 6 (15.8%) 13 (34.2%) Follow-up duration of all 38 patients who underwent resective surgery (median, mean ± SD) (range) (m) 32, 32.4 ± 17.4 (12–63) Pathology - Reactive gliosis - Hippocampal sclerosis - FCD type IIB, and III - No pathology due to laser ablation - Lesion (cavernoma, AVM) 26 (68.4%) 5 (13.1%) 3 (7.9%) 2 (5.3%) 2 (5.3%) Abbreviations: N: number, SD: standard deviation, y: year, m: month, %: percentage, FPC: focal preserved consciousness, FIC: focal impaired consciousness, FTBC: Focal to bilateral tonic clonic seizure. (*including recent SEEG waiting for intervention) ( # Out of 18 patients, one patient had ipsilateral lateral temporal lobe epilepsy and contralateral mesial temporal lobe epilepsy in relation to the SEEG thalamus electrode analyzed) ( & Out of 5 patients, one patient had ipsilateral mesial temporal and contralateral lateral temporal epilepsy in relation to the SEEG thalamus electrode analyzed) Thalamo-Temporal Spectral Synchrony Correlation Analysis Descriptive statistics (median, mean ± SD, IQR) and subgroup comparisons are presented in Table 2 and Fig. 2 . Among the 62 patients analyzed, 11 had SEEG coverage of both the Pul and ATG. For these patients, 50 seizures (40 CS, 10 NCS) were analyzed twice, once per thalamic nucleus, resulting in a total of 347 seizure entries. Additionally, 20 patients with both CS and NCS contributed 82 paired within-subject comparisons. Table 2 Thalamo–Temporal Spectral Correlation Analysis: Comparisons by Thalamic Group With Stratification by Seizure Semiology and Post-Surgical Outcome (with significant p-value in Bold) No. of patients (No. of seizures analyzed) Thalamo-Temporal Correlation Median (mean ± SD), IQR P-value / *type of analysis (Bold as significant) Cliff’s delta/ effect size A) Both Pulvinar and ATG group: seizure analysis (N = 62) i) Clinical versus Nonclinical seizures P < 0.0001* 0.63/ large Clinical seizure group 61 (275) 0.19 (0.25 ± 0.23), 0.20 Nonclinical seizure group 21 (72) 0.06 (0.08 ± 0.14), 0.08 ii) Clinical Seizure Subtypes P = 0.4266** NA Focal preserved conscious (FPC) 24 (82) 0.19 (0.24 ± 0.21), 0.22 Focal impaired conscious (FIC) 43 (140) 0.20 (0.25 ± 0.22), 0.18 Focal to bilateral clonic (FTBC) 23 (53) 0.16 (0.25 ± 0.26), 0.24 FPC vs FIC P = 0.932*** 0.04/negligible FIC vs FTBC P = 0.437*** 0.12/small FPC vs FTBC P = 0.905*** 0.06/ negligible iii) Types of temporal lobe epilepsy a) Mesial temporal P < 0.0001* 0.67/ large Clinical 31 (155) 0.21 (0.28 ± 0.24), 0.24 Nonclinical 13 (49) 0.06 (0.08 ± 0.10), 0.07 b) Lateral temporal P = 0.0003* 0.60/ large Clinical 19 (71) 0.11 (0.16 ± 0.18), 0.10 Nonclinical 5 (15) 0.02 (0.10 ± 0.25), 0.06 c) Mesio-lateral temporal P = 0.0031 * 0.66/ large Clinical 11 (49) 0.20 (0.26 ± 0.21). 0.22 Nonclinical 3 (8) 0.05 (0.08 ± 0.07), 0.11 B) Both Pulvinar and ATG group: Post-surgical Resection Patients with one year outcome (N = 38) i) Clinical vs Nonclinical: Post-surgical Resection Patients with one year outcome P < 0.0001* 0.72/ large Clinical seizure group 37 (162) 0.20 (0.25 ± 0.20), 0.21 Nonclinical seizure group 13 (43) 0.05 (0.08 ± 0.16), 0.07 ii) Seizure freedom status: Post-surgical Resection Patients with one year outcome P = 0.7514* NA Seizure free (SF) group (Engel 1A) 25 (105) 0.16 (0.20 ± 0.18), 0.16 Nonseizure free (NSF) group (Engel other than 1A) 25 (100) 0.16 (0.23 ± 0.22), 0.26 iii) Post-surgical Resection Patients with one year outcome (Seizure and SF groups) P < 0.0001** NA SF Clinical seizure (SF-CS) group 19 (84) 0.19 (0.24 ± 0.18), 0.15 SF Nonclinical seizure (SF-NCS) group 6 (21) 0.04 (0.05 ± 0.05), 0.06 NSF Clinical seizure (NSF-CS) group 18 (78) 0.22 (0.26 ± 0.22). 0.24 NSF Nonclinical seizure (NSF-NCS) group 7 (22) 0.06 (0.11 ± 0.22), 0.08 SF-CS vs SF-NCS P < 0.0001 # 0.64/large NSF-CS vs NSF-NCS P = 0.0007 # 0.37/medium NSF-CS vs SF-NCS P < 0.0001 # 0.52/large NSF-NC vs SF-NCS P = 0.391 # 0.10/negligible SF-CS vs NSF-NCS P < 0.0001 # 0.46/ medium SF-CS vs NSF-CS P = 0.0003 # 0.32/ medium C) Intrasubject analysis in patients who had both clinical and nonclinical seizures (N = 20) i) Clinical versus Nonclinical seizures P = 0.0003 * 0.37/medium Clinical 20 (65) 0.12 (0.12 ± 0.09), 0.15 Nonclinical 20 (68) 0.06 (0.09 ± 0.15), 0.08 ii) Post-surgical Resection Patients with one year outcome P < 0.0001 * 0.52/ large Clinical 12 (39) 0.13 (0.13 ± 0.08), 0.13 Nonclinical 12 (39) 0.05 (0.09 ± 0.17), 0.07 D) Intrasubject analysis in patients who had both Pulvinar and ATG (N = 11) i) Clinical versus Nonclinical seizures Clinical in Pulvinar group (Pul-CS) 11 (51) 0.21 (0.27 ± 0.23), 0.17 P = 0.0004* NA Nonclinical in Pulvinar group (Pul-NCS) 3 (10) 0.06 (0.09 ± 0.10), 0.07 Clinical in ATG group (ATG-CS) 11 (51) 0.28 (0.20 ± 0.28), 0.24 Nonclinical in ATG group (ATG-NCS) 3 (10) 0.07 (0.11 ± 0.13), 0.10 Pul-CS vs ATG CS P = 0.6757 # 0.05/negligible Pul-NCS vs ATG -NCS P = 0.6776 # 0.12/negligible Pul-CS vs ATG-NCS P = 0.0049 # 0.57/large ATG-CS vs Pul_NCS P = 0.0023 # 0.62/large Pul-CS vs Pul-NCS P = 0.0006 # 0.69/large ATG-CS vs ATG-NCS P = 0.0144 # 0.49/large E) Pulvinar Group: seizure analysis (N = 59) i) Clinical versus Nonclinical seizures P < 0.0001* 0.64/large Clinical 58 (216) 0.19 (0.24 ± 0.22), 0.19 Nonclinical 19 (57) 0.06 (0.08 ± 0.15), 0.08 ii) Clinical Seizure Subtypes P = 0.3685** NA FPC 22 (58) 0.22 (0.25 ± 0.20), 0.22 FIC 42 (111) 0.20 (0.24 ± 0.20), 0.14 FTBC 22 (47) 0.16 (0.25 ± 0.28), 0.25 FPC vs FIC P = 0.63*** 0.05/negligible FTBC vs FIC P = 0.19*** 0.13/negligible FPC vs FTBC P = 0.27*** 0.12/negligible F) Pulvinar Group: Post-resection patients with one year outcome (N = 36) i) Clinical vs Nonclinical: Post-surgical Resection Patients with one year outcome P < 0.0001* 0.69/large Clinical 35 (133) 0.21 (0.26 ± 0.21), 0.23 Nonclinical 12 (36) 0.05 (0.09 ± 0.18), 0.08 ii) Seizure freedom status: Post-surgical Resection Patients with one year outcome P = 0.6427* NA Seizure free 18 (87) 0.17 (0.21 ± 019), 0.14 Nonseizure free 18 (82) 0.18 (0.24 ± 0.24), 0.29 iii) Post-surgical Resection Patients with one year outcome (Seizure and SF groups) P < 0.0001** NA SF-CS 18 (70) 0.19 (0.25 ± 0.19), 0.14 SF-NCS 5 (17) 0.04 (0.05 ± 0.05), 0.07 NSF-CS 17 (63) 0.28 (0.25 ± 0.23), 0.28 NSF-NCS 7 (19) 0.13 (0.06 ± 0.24), 0.08 SF-CS vs SF NCS P < 0.0001 # 0.85/large SF-C vs NSF-NCS P < 0.0001 # 0.66/large NSF-CS vs SF-NCS P < 0.0001 # 0.72/large NSF-CS vs NSF-NCS P = 0.0003 # 0.55/large NSF-CS vs SF-CS P = 0.408 # 0.08/negligible NSF-NCS vs SF-NCS P = 0.568 # 0.12/negligible G) ATG group: Seizure analysis (N = 14) i) Clinical versus Nonclinical seizures P = 0.0005* 0.58/large Clinical 14 (59) 0.15 (0.25 ± 0.27), 0.23 Nonclinical 5 (15) 0.06 (0.08 ± 0.11), 0.07 ii) Clinical Seizure Subtypes P = 0.3571** NA FPC 9 (24) 0.13 (0.21 ± 0.24),0.18 FIC 9 (29) 0.20 (0.30 ± 0.30), 0.27 FTBC 4 (6) 0.21 (0.18 ± 0.13), 0.14 FPC vs FIC P = 0.1831*** 0.22/small FIC vs FTBC P = 0.9477*** 0.02/negligible FTBC vs FPC P = 0.3642*** 0.25/small H) ATG group: Post-resection patients with one year outcome (N = 8) i) Clinical vs Nonclinical: Post-surgical Resection Patients with one year outcome P = 0.0001* 0.94/large Clinical 8(29) 0.15 (0.18 ± 0.10), 0.15 Nonclinical 2 (7) 0.05 (0.03 ± 0.04), 0.08 ii) Seizure freedom status: Post-surgical Resection Patients with one year outcome P = 0.8868* NA Seizure free 4 (18) 0.13 (0.15 ± 0.11), 0.18 Nonseizure free 4 (18) 0.12 (0.15 ± 0.12), 0.09 * p value calculated using Mann–Whitney U tests ** p value calculated using Kruskal–Wallis H test *** Corrected p value (Bonferroni-adjusted threshold for pair-wise analysis using Mann-Whitney U test) p < 0.0165 # Corrected p value (Bonferroni-adjusted threshold for pair-wise analysis using Mann-Whitney U test) = P < 0.0083 Significant p-values are highlighted in bold. (Abbreviation: No: number, SF: seizure free, NSF: nonseizure free, CS: clinical seizure, NCS: nonclinical seizure, FPC: focal preserved consciousness seizure, FICL: focal impaired consciousness, FTBC: focal to bilateral tonic clonic seizure, SD: standard deviation, IQR: 25–75% Interquartile range, Pul: Pulvinar, ATG: Anterior thalamus group, N; Number of patients, NA: not applicable) Across all seizures, thalamo–temporal spectral correlation values were significantly lower in NCS (n = 72) compared to CS (n = 275) (p < 0.0001, δ = 0.63; Table 2 A, Fig. 2 A (i) ). This pattern persisted across temporal epilepsy subtypes: correlations in NCS were significantly lower than in CS for mesial temporal (p < 0.0001, δ = 0.67), lateral temporal (p = 0.0003, δ = 0.60), and mesiolateral subtypes (p = 0.0032, δ = 0.66) (Table 2 A). When stratifying CS into FPC (n = 83), FIC (n = 140), and FTBC (n = 52), no significant differences were found (Table 2 A, Fig. 2 A (ii) ), suggesting that awareness level or generalization does not further modulate resonance strength beyond the clinical vs. nonclinical dichotomy. In the subset of 38 patients with ≥ 1 year of surgical follow-up (250 seizure entries), CS again demonstrated significantly higher thalamo–temporal correlation than NCS (p < 0.0001, δ = 0.72; Table 2 B, Fig. 2 A(iii)). No overall difference was observed between SF and NSF groups (p = 0.7514); however, when stratified into four subgroups (SF-CS, SF-NCS, NSF-CS, NSF-NCS), significant differences emerged (Kruskal–Wallis p < 0.0001; Table 2 B, Fig. 2 A(iv)). Notably, SF-CS showed significantly higher correlation than SF-NCS and NSF-NCS (p < 0.0001), while NSF-CS also exceeded NSF-NCS (p = 0.0007) (Table 2 B, Fig. 2 A (iv) ). In a multiple linear regression model (N = 347), seizure type was the only significant predictor of thalamo–temporal correlation values (F(4, 342) = 8.94, p < 0.001, R² = 0.095). Nonclinical seizures were associated with significantly lower correlation values compared to clinical seizures (β = − 0.166, p 0.12) ( Supplementary Table 3 ). Within-Subject Comparisons Intra-subject analyses were performed to confirm these findings. In 20 patients with both CS and NCS, correlation remained higher in CS (p = 0.0003, δ = 0.37; Table 2 C, Fig. 2 B (i) ), with a stronger difference in the subset with ≥ 1 year of outcome data (p < 0.0001, δ = 0.52; Fig. 2 B (ii) ). Figure 3 illustrates two representative patients with both clinical and nonclinical seizure types, where thalamic involvement was observed only during CS, despite identical EZ. In the 11 patients with both Pul and ATG coverage, Pul-CS showed the highest correlation values, significantly exceeding Pul-NCS (p = 0.0006) and ATG-NCS (p = 0.005). No difference was found between Pul-CS and ATG-CS (Table 2 D, Fig. 2 C). Figure 4 A-B highlights two patients with mesial and lateral temporal epilepsy showing bilateral thalamic coupling during CS. Thalamic Subregion Analysis The pulvinar group (273 seizures (216 CS, 57 NCS) from 59 patients) mirrored the global findings: CS had significantly stronger pulvinar–temporal synchrony than NCS (p < 0.0001, δ = 0.64; Table 2 E, Fig. 2 D (i) ), regardless of clinical subtype (FPC, FIC and FTBC) or surgical outcome (SF vs NSF). Stratified analysis again showed that SF-CS had higher coupling than all other subgroups (Kruskal–Wallis p < 0.0001; Fig. 2 D (ii)) and no differences were found in comparisons between SF-C and NSF-C (p = 0.408) and between SF-NC and NSF-NC (p = 0.568). Figure 4 C illustrates three mTLE patients with the Pul involvement during CS. ATG-specific analysis (74 seizures (59 CS, 15 NCS) from 14 patients) similarly showed a higher correlation in CS than NCS (p = 0.0005, δ = 0.58; Table 2 F ), with no differences across FPC, FIC, and FTBC. Eight patients underwent resective surgery (mean follow-up = 33.3 months), contributing 36 seizures (29 CS, 7 NCS). NCS again showed lower correlation than CS (p = 0.0001, δ = 0.94), but no significant difference was observed between SF and NSF groups (p = 0.8868). Epileptogenicity index and Surgical outcome EI values were analyzed in 38 patients with ≥ 12 months of postoperative follow-up ( Supplementary Table 2 ). Of these, 37 patients had at least one clinical seizure subtype, and one patient had only NCS. Using a threshold of EI > 0.3 based on previously suggested threshold in the Pul, 5.3% (n = 2) patients were classified as high EI, one was seizure-free. Of the 36 with EI ≤ 0.3, 23 (63.9%) achieved SF, suggesting that limited thalamic recruitment at seizure onset may be associated with a higher likelihood of postoperative seizure control. Discussion By leveraging thalamic and temporal SEEG in drug-resistant TLE, we show that thalamo-cortical spectral synchrony is markedly stronger during clinically manifest seizures than during non-clinical seizures, a state-dependent effect that holds across seizure subtypes, temporal onset classes, and thalamic nuclei (pulvinar and anterior group). Within-patient comparisons confirm the phenomenon irrespective of prognosis, and multivariable modeling identifies seizure type as the sole independent predictor of coupling strength. These findings reposition the thalamus from a passive relay to a symptomatogenic hub whose dynamic coupling with cortex governs clinical expression. Conceptually, this resolves prior inconsistencies in thalamic involvement by focusing on synchrony strength rather than onset timing alone. Practically, it defines a quantitative signature that could guide neuromodulation, suggesting that attenuating thalamo-cortical synchrony may suppress symptoms even when resection is not feasible. Beyond epilepsy, the framework generalizes to disorders where thalamo-cortical coupling shapes cognition and behavior, offering a mechanistic bridge from network dynamics to clinical phenomenology. Crucially, our finding raises the therapeutic possibility that targeted disruption of thalamo-cortical synchrony through neuromodulation or focused ablations could suppress clinical symptoms even in the presence of ongoing electrographic seizures. Such an approach could shift the treatment paradigm from seizure elimination to symptom prevention, offering meaningful quality-of-life improvements for patients with DRE. In addition, our results highlight the importance of incorporating seizure semiology, particularly the CS–NCS distinction, when evaluating thalamo–temporal network dynamics in both the Pul and ATG in DR-TLE. Over the past several decades, SEEG has fundamentally reshaped our understanding of epilepsy, shifting the paradigm from a focal disorder localized to discrete cortical regions to a dynamic network disease involving both cortical and subcortical structures, particularly the thalamus 5 , 7 . Although the involvement of subcortical involvement is a known mechanistic process in generalized epilepsy 46 , the concept is evolving in the role of focal epilepsy. Within this network-based framework applied to focal epilepsy, increasing attention has concentrated on specific thalamic subregions, such as the Pul and the ANT, both of which have been implicated in TLE pathophysiology 8 – 10 . Despite its long-term efficacy (up to 70% median seizure reduction), the mechanism of ANT neuromodulation in TLE remains unclear whether through disrupted propagation, altered excitability, or broader network reorganization 8 . While ANT has been traditionally selected for TLE due to its anatomical position within the Papez circuitry 47 , recent studies highlight the medial pulvinar (PuM) nucleus as a functionally relevant target 9 , 12 , 14 , 15 , 48 . The PuM exhibits strong reciprocal connectivity with mesial temporal structures, particularly the hippocampus and amygdala, and is engaged in up to 80% of mesial TLE seizures 9 , 12 , 14 , 15 . Multi-nucleus thalamic recordings reveal variable seizure recruitment patterns across subregions, with visual analysis suggesting that the PuM may engage earlier and more prominently than the ANT 10 , 49 . However, visual inspection alone has proven insufficient to reliably characterize thalamic involvement, given the complexity and variability of recorded signals, a limitation we also encountered in our dataset. Our findings, using quantitative spectral correlation analysis, extend prior work by demonstrating that indeed thalamo-cortical synchrony during ictal events is not limited to mesial temporal seizures but is also present in seizures originating from lateral and mesiolateral neocortical temporal regions. This broader cortical engagement, coupled with strong thalamic synchrony, suggests that the thalamus participates in a more extensive seizure network than previously appreciated. Our observations of comparable thalamic engagement in both Pul and ATG during clinical seizures support the idea of convergent thalamo-cortical pathways contributing to the emergence of semiology, expanding the current concept of epileptic network and offering scientific insights into the mechanism of action of thalamic neuromodulation by hypothesizing that is by the disruption of thalamo-cortical synchrony through electrical stimulation that the translation of electrographic seizures into clinical symptoms is disrupted.. Our findings complement existing work on thalamic functional connectivity (FC) in seizure dynamic. Soulier et al. reported increased thalamo-cortical FC during seizures, although they found no global differences between ANT and PuM 16 . They did, however, identify stronger pulvinar involvement during synchronous seizure termination 16 . Conversely, Ilyas et al. suggested that ANT may actively facilitate seizure propagation in TLE 50 . These findings suggest subregional heterogeneity and emphasize moving beyond static anatomical assumptions when evaluating seizure networks. Although our study did not assess FC via graph theory metrics, our TF correlation approach revealed robust thalamo–temporal synchrony in both pulvinar and ATG during CS, and significantly reduced synchrony during NCS, suggesting state-dependent thalamo-cortical coupling across both nuclei, reinforcing their consistent engagement during behaviorally expressive seizures. A recent study by Salami et al. reported that seizures with broader cortical onset or higher-frequency activity (< 20 Hz) were more likely to propagate early (within 1–6 seconds) to the centromedian and pulvinar thalamic nuclei, whereas mesial temporal onset seizures tended to spread earlier to the ANT 33 . Their findings suggested that seizure onset pattern, whether spatially broad or spectrally fast, may influence thalamic recruitment 33 . Our results are broadly consistent with these observations but offers an important complementary perspective. In our cohort, both mesial and lateral temporal seizures demonstrated early engagement of the pulvinar and ATG, but this was contingent on seizure semiology, whether the event was clinically manifest. Here, the intrasubject comparisons revealed that, even within the same patient, thalamic recruitment was evident only during clinical seizures and absent or markedly reduced during NCS, even with similar onset patterns or faster mesial temporal onset in NCS. This suggests that thalamic involvement is not solely dictated by onset frequency or spatial spread but is more closely linked to the clinical expression of seizures. In this context, our findings extend Salami et al. 33 by highlighting thalamo–cortical spectral synchrony as a network-level correlate of behavioral expression. These results support the idea that thalamic recruitment is an active epileptogenic mechanism, reflecting the emergence of clinical symptomatology, and not merely passive propagation. It is interesting to note that in our cohort, limited thalamic involvement at seizure onset, reflected by a low EI, was associated with a higher likelihood of postoperative seizure freedom, reflecting the incomplete treatment of a more broader pathological process that goes beyond the cortical treated areas. Our findings align with and extend prior findings linking thalamic synchrony to semiology. Guye et al. found greater thalamo-cortical synchrony in seizures with impaired consciousness compared to those with preserved awareness, although their cohort did not include FTBC 9 . Other studies have shown that excessive thalamo–associative cortical synchronization may underlie impaired awareness and cognitive symptoms in TLE 9 , 14 , 51 . Supporting a causal role, a proof-of-concept study showed that stimulation of the medial pulvinar during hippocampal seizures improved consciousness, possibly suggesting that modulation of thalamic activity can alter behavioral outcomes 52 . Pizarro et al., although not focused on the pulvinar, demonstrated that ictal power changes within the ANT closely paralleled activity in the seizure onset zone (SOZ) and were significantly heightened during seizures that impaired consciousness or secondarily generalized 14 . Ye et al. further reported that preictal functional connectivity variability within the cortical SOZ was greater for CS than NCS in TLE 28 , although their analysis did not include thalamic data. These studies suggest that behavioral expression may depend more on thalamo-cortical dynamics in addition to seizure onset site or frequency, directly supported by our observation that thalamic spectral synchrony consistently distinguished CS from NCS. Importantly, thalamic synchrony was not influenced by seizure subtype, further supporting its role as a state-dependent marker of clinical expression. Altogether, our findings support thalamic spectral correlation as a direct physiological marker of semiology than conventional measures such as cortical onset patterns or EEG morphology. Thalamic involvement has been proposed as a prognostic marker in TLE, with imaging studies linking pulvinar atrophy and disrupted thalamo-temporal connectivity to poor surgical outcomes, even after adequate cortical resection 2 , 53 . Some reports have associated higher thalamic epileptogenicity (EI > 0.3) 14 or early thalamic synchronization 9 with poor surgical failure, while others found that delayed thalamic recruitment predicted poor surgical outcomes 33 . These discrepancies raise questions about whether thalamic involvement is causative, compensatory, or epiphenomenal. Our findings provide a complementary perspective, showing that thalamic spectral synchrony was strongly associated with seizure semiology but not with surgical outcome. Thalamic recruitment consistently followed or coincided with cortical seizure onset, but coupling strength was significantly higher in clinical than nonclinical seizures, regardless of postoperative seizure freedom. This suggests that thalamo-cortical synchrony governs behavioral expression rather than underlying epileptogenicity. Focusing on synchrony strength, as opposed to timing alone 9 , 33 , may help reconcile previous discrepancies and better capture the functional relevance of thalamic dynamics in TLE. In summary, our findings suggest that thalamo–temporal spectral synchrony is a robust physiological marker of seizure expression. It reliably tracks clinical symptoms across TLE subtypes and is unrelated to seizure onset zone or surgical outcome. By prioritizing seizure semiology, our work repositions thalamo-cortical dynamics as a key driver of behavioral manifestations and a novel therapeutic target for symptom suppression. Limitations and Future Directions Although our study offers valuable insights, it has several limitations. First, its post-hoc nature and heterogeneity in electrode coverage, particularly the fact that not all patients had recordings from both the pulvinar and ATG, may limit generalizability, despite inclusion of data from two centers. The small sample size for subgroup analyses, especially for the ATG-only group, also warrants caution. Second, while our time–frequency correlation approach effectively quantified thalamo-cortical synchrony, it did not assess causal relationships or directional connectivity. Future studies incorporating causality measures (e.g., Granger causality, transfer entropy) or phase–amplitude coupling could better delineate how different thalamic subregions contribute to seizure generation and propagation. Third, our analysis focused on the first 20 seconds of ictal activity, which may limit interpretation of how clinical semiology evolves or emergent, particularly in motor features or progression to FBTC seizures. Future studies should examine the full duration of seizures, including ictal evolution, to better characterize how thalamo-cortical dynamics shape the emergence and progression of clinical symptoms. This approach may help differentiate synchrony patterns among distinct clinical seizure subtypes, such as FPC, FIC and FTBC. Additionally, thalamic electrode placement varied between patients, and precise subnuclear localization was not always feasible, introducing potential anatomical variability. Standardized implantation strategies and prospective multicenter studies with larger cohorts will be essential for validating and expanding these findings. Despite these limitations, the robustness of results bring evidence that thalamic-cortical synchrony is marker of a broader symptomatogenic process in focal epilepsies. Our results highlight the need to explore the therapeutic potential of targeting thalamo-cortical pathways. In patients with diffuse, non-localizable, or eloquent cortex-involving epileptogenic zones, the thalamus may serve as a key hub for stabilizing cortical networks. Modulating thalamo-cortical circuits, via deep brain stimulation or closed-loop neuromodulation, could offer a means of suppressing seizure symptoms when resection is not an option. Future studies should evaluate whether thalamic engagement, via closed-loop or open-loop stimulation, or other techniques, can be harnessed to modulate semiology, improve seizure control, and preserve cognitive function in challenging cases of DR-TLE. Abbreviations anterior thalamus group (ATG), stereo-electroencephalography (SEEG), anterior temporal lobectomy (ATL), mesial temporal sclerosis (MTS), focal preserved consciousness seizure (FPC), focal impaired consciousness seizures (FIC), focal to bilateral tonic-clonic (FBTC), time-frequency (TF), standard deviation (SD), Interquartile range (IQR), Clinical seizure (CS), Nonclinical seizure (NCS), Seizure free (SF), nonseizure free (NSF), Clinical seizure in pulvinar group (Pul-CS), Nonclinical seizure in pulvinar group (Pul-NCS), Clinical seizure in ATG group (ATG-CS), Nonclinical seizure in ATG group (ATG-NCS), drug-resistant temporal lobe epilepsy (DR-TLE), Epileptogenic zone (EZ), Seizure onset zone (SOZ). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7419263","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":503589905,"identity":"8ded773a-398e-4310-b967-465c96a5d426","order_by":0,"name":"Thandar 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1","display":"","copyAsset":false,"role":"figure","size":1580978,"visible":true,"origin":"","legend":"\u003cp\u003eA) Schematic representation of the co-registration process, in which each patient's pre-implantation T1-weighted MRI (1 mm resolution) was co-registered with the post-implantation MRI or CT to localize electrode contacts within the thalamus. Thalamic contacts in the pulvinar (Pul) and anterior thalamic group (ATG) were identified using the AAL3 atlas. For each seizure, 40 seconds of SEEG data (20 seconds before and after seizure onset) were extracted and transformed into time-frequency representations (TFA) using bipolar derivations. Seizure TFA was normalized to baseline (pre-ictal) TFA, and correlation analyses were performed between the thalamic contacts and all seizure onset zone (SOZ) contacts. The median correlation value per seizure was then computed.\u003c/p\u003e\n\u003cp\u003e1B) Schematic showing the SEEG electrode trajectories for all 62 implanted patients.\u003c/p\u003e\n\u003cp\u003e1C) AAL3 thalamic atlas\u003csup\u003e38\u003c/sup\u003e overlay showing the location, divided into ATG (ventral anterior (VA), anteroventral (AV), or ventral lateral anterior (VLa)) and Pulvinar groups (Pul_A, Pul_Med, Pul_Inf, Pul_Lat).\u003c/p\u003e\n\u003cp\u003e1D) Localization of thalamic electrodes from all 62 patients displayed on the 7T MRI ex vivo brain MNI template\u003csup\u003e40\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/ed9fbac900925580a39a890b.jpg"},{"id":89994172,"identity":"8a123568-5660-4010-b296-74e174e6e516","added_by":"auto","created_at":"2025-08-27 07:48:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":803316,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThalamo–Temporal Spectral Correlation Analysis Across Seizure Types and Outcomes (Combined Pulvinar and ATG)\u003c/strong\u003e\u003cbr\u003e\n \u003cstrong\u003e2A) Thalamo-temporal spectral correlation across all seizures (n = 347 entries).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e2A (i): Violin plot comparing thalamo–temporal spectral correlation values between clinical seizures (CS) and nonclinical seizures (NCS) Correlation was significantly higher in CS (p \u0026lt; 0.0001, δ = 0.63). \u003cbr\u003e\n2A (ii): Spectral correlation values among three clinical subtypes: focal preserved consciousness (FPC), focal impaired consciousness (FIC), and focal to bilateral tonic-clonic seizures (FTBC); no significant group differences were observed.\u003cbr\u003e\n2A (iii): Violin plot showing spectral correlation differences between CS and NCS in patients with ≥1 year post-surgical follow-up (n = 250 seizure entries), CS showed significantly higher correlation values than NCS (p \u0026lt; 0.0001, δ = 0.72).\u003cbr\u003e\n2A (iv): Volin plot showing stratified thalamo-temporal spectral correlation analyzed by seizure outcome and semiology: seizure-free clinical (SF-CS), seizure-free nonclinical (SF-NCS), non-seizure-free clinical (NSF-CS), and non-seizure-free nonclinical (NSF-NCS). Significant group differences were detected (Kruskal–Wallis p \u0026lt; 0.0001) with post-hoc comparisons showing significant differences between SF-CS \u0026gt; SF-NCS and NSF-NCS, and NSF-CS \u0026gt; SF-NCS and NSF-NCS.Bonferroni-adjusted post-hoc comparisons (α = 0.0083) revealed that SF-CS seizures exhibited significantly higher correlation values than both SF-NCS (p \u0026lt; 0.0001, δ = 0.64) and NSF-NCS (p \u0026lt; 0.0001, δ = 0.46), indicating stronger thalamo-cortical synchrony in clinically manifest seizures among seizure-free patients. Similarly, NSF-CS also showed greater synchrony than NSF-NCS (p = 0.0007, δ = 0.37) and SF-NCS (p \u0026lt; 0.0001, δ = 0.52). No significant differences between SF-NCS and NSF-NCS (p = 0.391) and between SF-CS and NSF-CS (p = 0.0007) groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2B) Intrasubject analysis: Thalamo-temporal spectral correlation across 20 patients with both CS and NCS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e2B (i): Volin plot showing intrasubject analysis of thalamo-temporal spectral correlation in (n = 133 seizures): CS showed significantly higher correlation than NCS (p = 0.0003, δ = 0.37).\u003c/p\u003e\n\u003cp\u003e2B (ii): Volin plot showing intrasubject thalamo-temporal spectral correlation values stratified by surgical outcome in patients who underwent resective surgery with at least 12 months follow up (12 patients). CS showed significantly higher correlation than NCS (p \u0026lt; 0.0001, δ = 0.52).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2C) Violin plot illustrating intrasubject thalamo–temporal spectral correlation values in 11 patients with SEEG coverage of both the pulvinar and anterior thalamic group (ATG),\u003c/strong\u003e stratified by seizure type (clinical [CS] vs. nonclinical [NCS]). Correlation was highest in Pul-CS, which was significantly greater than Pul-NCS (p = 0.0006, δ = 0.69) and ATG-NCS (p = 0.0049, δ = 0.57). Pul-NCS also had significantly lower correlation than ATG-CS (p = 0.0023, δ = 0.62). No significant differences were observed between Pul-CS and ATG-CS, ATG-CS and ATG-NCS, or Pul-NCS and ATG-NCS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2D) Pul-temporal spectral correlation analysis (Pulvinar Subgroup)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e2D (i)\u003cstrong\u003e \u003c/strong\u003eViolin plot comparing pulvinar–temporal spectral correlation values between clinical seizures (CS) and nonclinical seizures (NCS) across all 273 seizures from 59 patients. CS showed significantly higher correlation (p \u0026lt; 0.0001, δ = 0.64).\u003c/p\u003e\n\u003cp\u003e2D (ii): Volin plot comparing the subgroups analysis based on the seizure types and seizure outcome: seizure-free clinical (SF-CS), seizure-free nonclinical (SF-NCS), non-seizure-free clinical (NSF-CS), and non-seizure-free nonclinical (NSF-NCS). SF-CS showed higher correlation values than both SF-NCS (p \u0026lt; 0.0001, δ = 0.85) and NSF-NC (p \u0026lt; 0.0001, δ = 0.66). Similarly, NSF-CS showed higher correlation than NSF-NCS (p \u0026lt; 0.001, δ = 0.55) and SF-NCS (p \u0026lt; 0.0001, δ = 0.72). No difference between SF-CS and NSF-CS (p = 0.408) and between SF-NC and NSF-NCS (p = 0.578).\u003c/p\u003e\n\u003cp\u003e2E) ATG–Temporal spectral correlation analysis (Anterior thalamus group (ATG) Subgroup)\u003c/p\u003e\n\u003cp\u003eViolin plot comparing ATG–temporal spectral correlation values between clinical seizures (CS) and nonclinical seizures (NCS) across all 74 seizures from 14 patients. Correlation values were significantly lower in NCS than CS (p = 0.0005, δ = 0.58), with\u003c/p\u003e\n\u003cp\u003eViolin plots represent kernel density estimates with overlaid boxplots indicating medians and interquartile ranges. All statistical comparisons used non-parametric tests with Bonferroni correction applied where appropriate and with Cliff’s delta for effect size. Effect sizes were classified as negligible (|δ| \u0026lt; 0.147), small (0.147–0.33), medium (0.33–0.474), or large (≥0.474).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/7b3551bcbbbce844fd880076.jpg"},{"id":89995633,"identity":"0823a72c-ea8d-44f5-9ff4-7cabbf4caf9c","added_by":"auto","created_at":"2025-08-27 07:56:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1782358,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative Cases of Pulvinar–Temporal Spectral Synchrony in Patients with Pulvinar SEEG Coverage showing pulvinar–Temporal Spectral Correlation Across Seizure Types and Onset Regions\u003c/p\u003e\n\u003cp\u003e4A–B: Patient-level examples illustrating thalamic involvement differences in seizure times series followed by corresponding time frequency analysis of the same series illustrated in the SEEG time series between two seizure types (clinical and nonclinical seizures) in the same patients.\u003c/p\u003e\n\u003cp\u003e4A) In a patient with mesial temporal lobe epilepsy (with Engel 1A outcome with 51 months follow up after temporal lobectomy), the pulvinar exhibits strong thalamo–temporal spectral correlation (with focus time series of the pulvinar SEEG contact U’1-2) during a clinical seizure (left panel) compared to the nonclinical seizure (right panel), closely mirroring hippocampal seizure onset dynamics seen in the clinical seizure but not in the nonclinical seizures even with fast onset in cortical regions.\u003c/p\u003e\n\u003cp\u003e4B) In a patient with lateral temporal epilepsy (with Engel 1D outcome with 51 months follow up after temporal lobe epilepsy), the nonclinical seizure (right panel) shows minimal pulvinar involvement, despite a broader cortical onset. In contrast, the clinical seizure (left panel) displays strong pulvinar engagement (with focus time series of the pulvinar SEEG contact U1-2), with time–frequency patterns that closely align with cortical seizure onset dynamics.\u003c/p\u003e\n\u003cp\u003eTime zero indicates seizure onset and highlighted with red solid line.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/f1a43e5c76b9d32a75e9baeb.jpg"},{"id":89994171,"identity":"bcc4e5c9-2cd0-4d35-be95-091121888322","added_by":"auto","created_at":"2025-08-27 07:48:03","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1737353,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative Cases of Thalamo–Temporal Spectral Synchrony in Patients with Both Pulvinar and ATG SEEG Coverage showing Time–frequency correlation analysis from two patients with SEEG contacts in both the pulvinar (Pul) and anterior thalamic group (ATG), illustrating distinct thalamo-cortical synchrony patterns during clinical seizures.\u003c/p\u003e\n\u003cp\u003e(A) Patient with mesial temporal lobe epilepsy showing strong thalamo–temporal spectral synchrony in both Pul and ATG during a clinical seizure. The hippocampus exhibits low-voltage fast activity at seizure onset (time 0), with near-perfect correlation between hippocampal SOZ contacts and both thalamic regions.\u003c/p\u003e\n\u003cp\u003e(B) Patient with lateral temporal lobe epilepsy demonstrating weaker thalamo–temporal correlation during a nonclinical seizure. Seizure activity begins with fast intrusion in the temporal pole around 5 seconds, evolving into rhythmic delta/theta activity by 13 seconds, with delayed involvement of Pul and ATG.\u003c/p\u003e\n\u003cp\u003e(C) Three representative patients with mesial temporal lobe epilepsy (mTLE) and clinical seizures. Time–frequency analysis shows that pulvinar SEEG contacts display spectral patterns that closely track and align with cortical seizure onset activity, indicating temporally and spectrally coordinated thalamo-cortical involvement.\u003c/p\u003e\n\u003cp\u003eTime zero indicates seizure onset and highlighted with red solid line.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/d2d3985dc1773faab69c90e7.jpg"},{"id":89997177,"identity":"f107ee32-210b-479a-b22b-5b7c706c8a21","added_by":"auto","created_at":"2025-08-27 08:12:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7575185,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/07e0ab46-4723-4bff-a79b-534350986828.pdf"},{"id":89994162,"identity":"b1c2b105-4bd0-48fa-94d2-c62d5b62a398","added_by":"auto","created_at":"2025-08-27 07:48:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":34381,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 1\u003c/p\u003e","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/0556fd6de879358b61bd27c2.docx"},{"id":89995630,"identity":"4221dbdb-50ad-43ff-963f-7406aedffef1","added_by":"auto","created_at":"2025-08-27 07:56:03","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":25428,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 2\u003c/p\u003e","description":"","filename":"SupplementaryTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/ab11576126e4a1ce3ae211c6.docx"},{"id":89994163,"identity":"7e7a355a-524c-40c8-aa8e-19a81774ff60","added_by":"auto","created_at":"2025-08-27 07:48:03","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":28287,"visible":true,"origin":"","legend":"Supplementary Table 3","description":"","filename":"SupplementaryTable3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/9de187093a83754044f1ebd7.docx"},{"id":89994170,"identity":"adccbfad-3086-4619-8a35-fa190cd6ccfe","added_by":"auto","created_at":"2025-08-27 07:48:03","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":829966,"visible":true,"origin":"","legend":"Supplementary Figure 1","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7419263/v1/cf9cb0077faa457b69e20e79.tif"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Thalamo-cortical Synchrony Shapes Seizure Expression in Human Temporal Lobe Epilepsy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTemporal lobe epilepsy (TLE), the most common form of focal drug-resistant epilepsy (DRE), is frequently treated with anterior temporal lobectomy, particularly in mesial temporal sclerosis (MTS)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. However, despite comprehensive presurgical evaluation, 20\u0026ndash;40% of patients, including those with MTS, experience recurrent seizures postoperatively\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. This limitation has shifted the field toward viewing epilepsy as a disorder of distributed brain networks rather than an isolated cortical phenomenon\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Stereo-electroencephalography (SEEG) has been instrumental in this shift, revealing that subcortical structures, particularly the pulvinar (Pul), and the anterior thalamic nuclei, are active participants in seizure generation and modulation in TLE\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12 CR13 CR14\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThalamo-cortical interactions are not unique to epilepsy and across neurological disorders, they shape the expression of symptoms, from motor network dysregulation in movement disorders to functional deficits following stroke\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Although debate over the relative roles of the thalamus and cortex in seizure pathogenesis dates back to the 1800s\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, evidence from imaging and SEEG neurophysiology studies highlights that the thalamus is not a passive relay but an active hub influencing seizure propagation, termination, and clinical manifestation, and may contribute to surgical failure\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Increasingly, the thalamus is recognized as a critical therapeutic target, particularly for patients with bilateral seizure onset or unresectable networks, where neuromodulation offers the next step beyond resection\u003csup\u003e22\u0026ndash;2425\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn DR-TLE, clinical seizures (CS), epileptic discharges with overt subjective or observable objective clinical manifestations, are associated with reduced quality of life. With widespread SEEG use, nonclinical seizures (NCS), electrographic seizures without observable symptoms, are increasingly recognized alongside clinical seizures\u003csup\u003e\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Although CS and NCS may originate from the same epileptogenic zone (EZ) in a given patient, the mechanisms underlying their divergent clinical expression remain poorly understood. Experimental studies suggest that differences in neuronal recruitment, synchrony, and propagation may account for this variability\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. However, these hypotheses have not been systematically tested in humans, particularly regarding thalamic dynamics. Prior reports have described intra-subject variability in thalamic recruitment based on ictal frequency and spatial extent (broad vs. focal), but have not directly compared CS and NCS\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Furthermore, no study has comprehensively examined how thalamo\u0026ndash;temporal dynamics differ across clinical subtypes, focal preserved consciousness (FPC), focal impaired consciousness (FIC), and focal to bilateral tonic\u0026ndash;clonic (FBTC), or how these patterns relate to postoperative seizure outcomes. Understanding why some seizures produce symptoms while others remain silent remains a central challenge, hindered by the lack of a reproducible network-level biomarker. Addressing this gap is essential for advancing mechanistic understanding of seizure semiology and for guiding neuromodulatory strategies for nonresectable DR-TLE.\u003c/p\u003e\u003cp\u003eWe hypothesized that thalamo-cortical synchrony, particularly involving the Pul and anterior thalamic group (ATG), contributes to clinical seizure expression in DR-TLE. Specifically, we predicted that CS would exhibit stronger thalamo-temporal coupling than NCS. We further examined whether this coupling differs across seizure subtypes (FPC, FIC, FBTC) and whether it relates to post-surgical outcomes. Using SEEG-based time\u0026ndash;frequency (TF) analysis in a multicenter cohort with targeted thalamic coverage, we quantified thalamo\u0026ndash;temporal spectral correlation to examine its association with seizure semiology and surgical prognosis.\u003c/p\u003e"},{"header":"Materials and Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePatient selection, demographic data and seizure selection\u003c/h2\u003e\u003cp\u003e The study was approved by the institutional review board at the University of Pittsburgh (January 2020 to June 2025) and the Duke University Hospital (June 2023 to June 2025). Consecutive patients (\u0026ge;\u0026thinsp;16 years) with focal DR-TLE from both centers were included if intracranial exploration covered temporal and thalamic regions with at least one SEEG electrode contact in ATG, Pul, or both. Only patients who experienced at least one spontaneous habitual seizure during SEEG monitoring were eligible. Patients whose EZ extended beyond the temporal lobe were excluded (\u003cem\u003eSupplementary Fig.\u0026nbsp;1\u003c/em\u003e). Demographic and clinical data (age, sex, epilepsy onset, duration, MRI findings, SOZ, electrode placement, outcome, and follow-up duration) were collected from medical records.\u003c/p\u003e\u003cp\u003eAnatomical and electrophysiological data on each patient's SOZ were obtained from the multidisciplinary patient management conferences held after SEEG evaluation. Two experienced epileptologists (T.A., T.T.) independently reviewed and confirmed the SOZ localization. Additionally, all recorded seizures were retrospectively reviewed and classified as clinical or nonclinical by the same two epileptologists (T.A., T.T.). In cases of disagreement, seizures were jointly re-reviewed, and if consensus could not be reached, those seizures were excluded. Seizures that were untested or unclear on video review were also excluded. Seizures were classified as \u003cem\u003enon-clinical\u003c/em\u003e when patients, tested during the event, exhibited no observable clinical signs or reported symptoms, with such events defined as self-limited, broadly synchronized paroxysmal epileptiform discharges unaccompanied by behavioral manifestations. Seizures were clinical if patients reported subjective symptoms, or observable signs were present and further categorized using the updated ILAE classification\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e as FPC, FIC, or FTBC. FPC was defined as seizures with retained awareness and responsiveness; FIC as seizures with altered awareness or responsiveness; and FBTC as focal seizures that secondarily generalized to bilateral tonic\u0026ndash;clonic activity. A maximum of four seizures per category (FPC, FIC, FBTC, and nonclinical) were analyzed per patient. For patients exhibiting multiple seizure types, up to four seizures from each type were included. Epilepsy subtypes were classified based on seizure onset zone. Mesial temporal lobe epilepsy (mTLE) was defined as seizures arising from the mesial limbic network, including the hippocampus, amygdala, entorhinal cortex, and mesial temporal pole. Mesio-lateral TLE involved both mesial and lateral temporal regions, while lateral TLE was defined as seizures originating exclusively from the lateral temporal neocortex, without evidence of mesial involvement\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. For patients who underwent resective surgery or neurostimulation, follow-up duration was calculated from the date of surgery to the most recent clinic visit. Seizure outcomes were classified using the Engel system\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, with only patients achieving Engel Class 1A and at least one year of follow-up considered seizure-free (SF).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eElectrode localization\u003c/h3\u003e\n\u003cp\u003eElectrode contacts were localized by co-registering post-implantation thin-sliced CT with preoperative 1 mm T1-weighted MRI using SPM12\u003csup\u003e37\u003c/sup\u003e (Fig.\u0026nbsp;1). Electrode positions were mapped in subject space using a 0.4 mm radius sphere and the Automated Anatomical Labeling atlas 3 (AAL3)\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. T1 MRIs were then nonlinearly registered to the ICBM2023b MNI template\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e to obtain MNI coordinates. Pulvinar group contacts included any subnucleus within the pulvinar complex (e.g., PuA, PuM, PuL, PuI). ATG contacts included those labeled as ventral anterior (VA), anteroventral (AV), or ventral lateral anterior (VLa) per AAL3 (\u003cem\u003eSupplementary Table\u0026nbsp;1\u003c/em\u003e). Figure\u0026nbsp;1B shows electrode trajectories from all patients overlaid on the ICBM2023b cortical surfaces, with pulvinar and ATG contacts visualized using AAL3 surface-rendered thalamic segmentation (Fig.\u0026nbsp;1C) and ultra-high resolution 7 Tesla ex vivo brain scans in MNI space (Fig.\u0026nbsp;1D)\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eData selection, time-frequency decomposition, synchrony correlation analysis and epileptogenicity index\u003c/h3\u003e\n\u003cp\u003eSEEG signals were sampled at 2048 Hz at both institutions. For each seizure, 40 seconds (s) of SEEG data were extracted, comprising 20s before and 20s after seizure onset (Fig.\u0026nbsp;1A). Additionally, a 40-second baseline epoch was obtained at least two minutes prior to seizure onset. Data were preprocessed in Brainstorm\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e and imported to the Epileptogenic Zone Fingerprint software\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e for the following TF analyses. Both ictal and baseline TF decomposition was performed using the Morlet wavelets (1\u0026ndash;200 Hz, 1 Hz steps; 3-s time resolution). Seizure TF maps (including grey and white matter electrode contacts) were normalized against the corresponding baseline maps across all frequencies, following our previously published methodology\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. All analyses were performed using bipolar montages.\u003c/p\u003e\u003cp\u003eTo reduce artifacts, a complex independent component analysis was applied to the TF plots to identify and remove artifacts common across channels (e.g., muscle activity). Channels with channel-specific artifacts, including those located outside the brain or within the ventricular system, were excluded. Seizures with artifacts in SOZ or thalamic contacts were excluded. In patients with bilateral thalamic implantation, only ipsilateral thalamic contacts and ipsilateral mesial temporal SOZ electrodes were analyzed. Thalamic contacts were localized using subject-specific anatomical labels from the AAL3 atlas, and multiple bipolar pairs within the SOZ were selected.\u003c/p\u003e\u003cp\u003eA Spectral Synchrony Correlation was applied to quantify frequency-specific thalamo-cortical SOZ coupling, i.e., thalamo-cortical synchrony. TF decomposition was performed using a continuous wavelet transform, and Pearson correlation coefficients were calculated between normalized power envelopes across sliding windows, generating frequency\u0026ndash;correlation profiles. For each seizure, the median correlation value across all SOZ\u0026ndash;thalamus pairs was used for statistical analysis (Fig.\u0026nbsp;1).\u003c/p\u003e\u003cp\u003eIn patients who underwent resection, one habitual stereotypic seizure, prefer clinical, per patient was additionally used to compute the epileptogenicity index (EI) following Bartolomei et al.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, using a 20-second window from ictal onset, to assess thalamic involvement in seizure initiation. By measuring the abruptness and magnitude of ictal power changes relative to interictal baseline, EI offers a standardized, quantitative assessment of a structure\u0026rsquo;s role in the early propagation of epileptic activity. Applying an EI threshold of \u0026gt;\u0026thinsp;0.3\u003csup\u003e14\u003c/sup\u003e, as previously suggested for the pulvinar, allowed classification of patients into high- and low-EI groups, enabling direct comparison with postoperative seizure outcomes.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eDue to non-normal distribution of thalamo\u0026ndash;temporal correlation values, non-parametric tests were used. CS vs. NCS and SF (Engel IA) vs. NSF (Engel IB\u0026ndash;IV) were compared using Mann\u0026ndash;Whitney U tests (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For seizure subtypes (FPC, FIC, FBTC), the Kruskal\u0026ndash;Wallis H test was followed by Bonferroni-adjusted pairwise tests (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0167). For combined outcome/semiology groups (SF-CS, SF-NCS, NSF-CS, NSF-NCS), six comparisons were tested with a threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.0083. The same threshold was applied to intra-subject comparisons involving thalamic region and seizure type (Pul-CS, ATG-CS, Pul-NCS, ATG-NCS) and stratified intra-subject outcome/semiology groups (SF-CS, SF-NCS, NSF-CS, NSF-NCS). Effect size was estimated using Cliff\u0026rsquo;s delta (δ). Effect sizes were classified as negligible (|δ| \u0026lt; 0.147), small (0.147\u0026ndash;0.33), medium (0.33\u0026ndash;0.474), or large (\u0026ge;\u0026thinsp;0.474).\u003c/p\u003e\u003cp\u003eTo assess independent predictors of thalamo\u0026ndash;temporal coupling, multiple linear regression was performed with seizure type (CS vs. NCS) as the primary variable. Covariates included thalamic region (Pul vs. ATG), seizure outcome (SF vs. NSF), and TLE subtype (mesial, lateral, mesiolateral), selected based on clinical relevance and univariate findings. Model fit was assessed via R\u0026sup2;, F-statistics, and p-values. Analyses were conducted in MATLAB (The MathWorks Inc., Natick, MA) and Stata (StataCorp, College Station, TX).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePatient Demographics\u003c/h2\u003e\u003cp\u003eA total of 62 consecutive patients with DR-TLE (286 seizures: 224 clinical seizures (CS), 62 nonclinical seizures (NCS)) were included. The average seizure duration was 158 seconds for CS and 67 seconds for NCS. The median age at SEEG evaluation was 37\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6 years (range: 16\u0026ndash;68), and median epilepsy duration was 11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2 years (range: 1\u0026ndash;43.5). Most were right-handed males with non-lesional MRI; 10 had prior resective surgery or laser ablation (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During SEEG monitoring, 66.1% of the patients (n\u0026thinsp;=\u0026thinsp;41) had only CS, 32.3% (n\u0026thinsp;=\u0026thinsp;20) had both CS and NCS, and 1.6% (n\u0026thinsp;=\u0026thinsp;1) had only NCS (1.6%). mTLE was diagnosed in 51.5% (n\u0026thinsp;=\u0026thinsp;32), including five with bilateral onset. Thalamic coverage included Pul only (n\u0026thinsp;=\u0026thinsp;48), both Pul and ATG (n\u0026thinsp;=\u0026thinsp;11), and ATG only (n\u0026thinsp;=\u0026thinsp;3). Surgical intervention was performed in 77.4% (n\u0026thinsp;=\u0026thinsp;48, 46 surgical resections, 2 laser ablations). Of the 46 patients who underwent resection, 38 (178 seizures: 138 CS, 40 NCS) had\u0026thinsp;\u0026ge;\u0026thinsp;1 year of follow-up (mean: 21.4 months; range: 12\u0026ndash;63), with 50% (n\u0026thinsp;=\u0026thinsp;19) achieving seizure freedom (Engel IA). Among them, 30 had Pul-only coverage, 6 had both Pul and ATG, and 2 had ATG only.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDetailed demographics and clinical information of the patient population\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal patient\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;62 patients)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge at the time of SEEG recording (median, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (range) (y)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37.0, 38.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6 (16\u0026ndash;68)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge at time of seizure onset (median, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (range) (y)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.0, 24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;15.0 (0\u0026ndash;65)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of epilepsy (median, mean \u0026plusmn; SD) (range) (y)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.5, 13.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2 (1-43.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHandedness\u003c/p\u003e\u003cp\u003e- Right\u003c/p\u003e\u003cp\u003e- Left\u003c/p\u003e\u003cp\u003e- Ambidextrous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53 (85.5%)\u003c/p\u003e\u003cp\u003e8 (12.9%)\u003c/p\u003e\u003cp\u003e1 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39 (62.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMRI finding\u003c/p\u003e\u003cp\u003e- None\u003c/p\u003e\u003cp\u003e- Prior resection or laser ablation\u003c/p\u003e\u003cp\u003e- Mesial temporal sclerosis\u003c/p\u003e\u003cp\u003e- Temporal lobe encephalomalacia and temporal encephalocele\u003c/p\u003e\u003cp\u003e- Nonspecific changes (cortical flair changes)\u003c/p\u003e\u003cp\u003e- Cavernoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (48.4%)\u003c/p\u003e\u003cp\u003e10 (16.1%)\u003c/p\u003e\u003cp\u003e8 (12.9%)\u003c/p\u003e\u003cp\u003e7 (11.3%)\u003c/p\u003e\u003cp\u003e5 (8.1%)\u003c/p\u003e\u003cp\u003e2 (3.25)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSEEG implantation scheme\u003c/p\u003e\u003cp\u003e- Unilateral\u003c/p\u003e\u003cp\u003eo Left\u003c/p\u003e\u003cp\u003eo Right\u003c/p\u003e\u003cp\u003e- Bilateral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 (69.4%)\u003c/p\u003e\u003cp\u003e33/43\u003c/p\u003e\u003cp\u003e10/43\u003c/p\u003e\u003cp\u003e19 (30.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThalamus Implantation\u003c/p\u003e\u003cp\u003e- Only Pulvinar\u003c/p\u003e\u003cp\u003e- Only Anterior thalamus Group\u003c/p\u003e\u003cp\u003e- Both Pulvinar and Anterior thalamus Group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48 (77.4%)\u003c/p\u003e\u003cp\u003e3 (4.8%)\u003c/p\u003e\u003cp\u003e11 (17.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeizure semiology captured during SEEG evaluation\u003c/p\u003e\u003cp\u003e- Only Clinical (FPC, FIC and FTBC) seizures\u003c/p\u003e\u003cp\u003e- Only Nonclinical seizures\u003c/p\u003e\u003cp\u003e- Both Clinical Nonclinical Seizures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41 (64.5%)\u003c/p\u003e\u003cp\u003e1 (1.6%)\u003c/p\u003e\u003cp\u003e20 (33.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocation of the confirmed epileptogenic zone\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e- Mesial temporal\u003c/p\u003e\u003cp\u003eo Unilateral\u003c/p\u003e\u003cp\u003eo Bilateral \u003csup\u003e\u0026amp;\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e- Mesial and lateral temporal\u003c/p\u003e\u003cp\u003eo Unilateral\u003c/p\u003e\u003cp\u003eo Bilateral\u003c/p\u003e\u003cp\u003e- Lateral temporal\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (51.6%)\u003c/p\u003e\u003cp\u003e30/32\u003c/p\u003e\u003cp\u003e5/32\u003c/p\u003e\u003cp\u003e11 (17.7%)\u003c/p\u003e\u003cp\u003e10/11\u003c/p\u003e\u003cp\u003e1/11\u003c/p\u003e\u003cp\u003e19 (30.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgical Intervention\u003c/p\u003e\u003cp\u003e- Resection\u003c/p\u003e\u003cp\u003eo Corticectomy\u003c/p\u003e\u003cp\u003eo Temporal lobectomy\u003c/p\u003e\u003cp\u003e- Laser ablation\u003c/p\u003e\u003cp\u003e- RNS\u003c/p\u003e\u003cp\u003e- No intervention or waiting for surgical intervention*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (74.2%)\u003c/p\u003e\u003cp\u003e9\u003c/p\u003e\u003cp\u003e37\u003c/p\u003e\u003cp\u003e2 (3.2%)\u003c/p\u003e\u003cp\u003e6 (9.7%)\u003c/p\u003e\u003cp\u003e8 (12.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;38 patients)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThe outcome of 38 patients who underwent resective or laser ablation surgery with at least 1 year follow-up\u003c/p\u003e\u003cp\u003e- Engel IA outcome\u003c/p\u003e\u003cp\u003e- Other Engel 1 outcome\u003c/p\u003e\u003cp\u003e- Engel II-IV outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (50%)\u003c/p\u003e\u003cp\u003e6 (15.8%)\u003c/p\u003e\u003cp\u003e13 (34.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollow-up duration of all 38 patients who underwent resective surgery (median, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (range) (m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32, 32.4\u0026thinsp;\u0026plusmn;\u0026thinsp;17.4 (12\u0026ndash;63)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathology\u003c/p\u003e\u003cp\u003e- Reactive gliosis\u003c/p\u003e\u003cp\u003e- Hippocampal sclerosis\u003c/p\u003e\u003cp\u003e- FCD type IIB, and III\u003c/p\u003e\u003cp\u003e- No pathology due to laser ablation\u003c/p\u003e\u003cp\u003e- Lesion (cavernoma, AVM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (68.4%)\u003c/p\u003e\u003cp\u003e5 (13.1%)\u003c/p\u003e\u003cp\u003e3 (7.9%)\u003c/p\u003e\u003cp\u003e2 (5.3%)\u003c/p\u003e\u003cp\u003e2 (5.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eAbbreviations:\u0026nbsp;N: number, SD: standard deviation, y: year, m: month, %: percentage, FPC: focal preserved consciousness, FIC: focal impaired consciousness, FTBC: Focal to bilateral tonic clonic seizure.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e(*including recent SEEG waiting for intervention)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e(\u003csup\u003e#\u003c/sup\u003e Out of 18 patients, one patient had ipsilateral lateral temporal lobe epilepsy and contralateral mesial temporal lobe epilepsy in relation to the SEEG thalamus electrode analyzed)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e(\u003csup\u003e\u0026amp;\u003c/sup\u003e Out of 5 patients, one patient had ipsilateral mesial temporal and contralateral lateral temporal epilepsy in relation to the SEEG thalamus electrode analyzed)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eThalamo-Temporal Spectral Synchrony Correlation Analysis\u003c/h3\u003e\n\u003cp\u003eDescriptive statistics (median, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, IQR) and subgroup comparisons are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among the 62 patients analyzed, 11 had SEEG coverage of both the Pul and ATG. For these patients, 50 seizures (40 CS, 10 NCS) were analyzed twice, once per thalamic nucleus, resulting in a total of 347 seizure entries. Additionally, 20 patients with both CS and NCS contributed 82 paired within-subject comparisons.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThalamo\u0026ndash;Temporal Spectral Correlation Analysis: Comparisons by Thalamic Group With Stratification by Seizure Semiology and Post-Surgical Outcome (with significant p-value in Bold)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo. of patients (No. of seizures analyzed)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThalamo-Temporal Correlation\u003c/p\u003e\u003cp\u003eMedian (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), IQR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value / *type of analysis (Bold as significant)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCliff\u0026rsquo;s delta/ effect size\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eA) Both Pulvinar and ATG group: seizure analysis (N\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ei) Clinical versus Nonclinical seizures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.63/ large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical seizure group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61 (275)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.19 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23), 0.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical seizure group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06 (0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14), 0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eii) Clinical Seizure Subtypes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.4266**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFocal preserved conscious (FPC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.19 (0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21), 0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFocal impaired conscious (FIC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 (140)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.20 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22), 0.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFocal to bilateral clonic (FTBC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26), 0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFPC vs FIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.932***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.04/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFIC vs FTBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.437***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12/small\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFPC vs FTBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.905***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06/ negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eiii) Types of temporal lobe epilepsy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ea) Mesial temporal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.67/ large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31 (155)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21 (0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24), 0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06 (0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10), 0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eb) Lateral temporal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;=\u0026thinsp;0.0003*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.60/ large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.11 (0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18), 0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02 (0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25), 0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ec) Mesio-lateral temporal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;=\u0026thinsp;0.0031\u003c/b\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.66/ large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.20 (0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21). 0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05 (0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07), 0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eB) Both Pulvinar and ATG group: Post-surgical Resection Patients with one year outcome (N\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ei) Clinical vs Nonclinical: Post-surgical Resection Patients with one year outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.72/ large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical seizure group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37 (162)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.20 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20), 0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical seizure group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05 (0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16), 0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eii) Seizure freedom status: Post-surgical Resection Patients with one year outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.7514*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeizure free (SF) group (Engel 1A)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (105)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16 (0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18), 0.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonseizure free (NSF) group (Engel other than 1A)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16 (0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22), 0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eiii) Post-surgical Resection Patients with one year outcome (Seizure and SF groups)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSF Clinical seizure (SF-CS) group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.19 (0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18), 0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSF Nonclinical seizure (SF-NCS) group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04 (0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05), 0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNSF Clinical seizure (NSF-CS) group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.22 (0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22). 0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNSF Nonclinical seizure (NSF-NCS) group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06 (0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22), 0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eSF-CS vs SF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.64/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eNSF-CS vs NSF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.0007\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37/medium\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eNSF-CS vs SF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.52/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eNSF-NC vs SF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.391\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.10/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eSF-CS vs NSF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.46/ medium\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eSF-CS vs NSF-CS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.0003\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.32/ medium\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eC) Intrasubject analysis in patients who had both clinical and nonclinical seizures (N\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ei) Clinical versus Nonclinical seizures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;=\u0026thinsp;0.0003\u003c/b\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.37/medium\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.12 (0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09), 0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06 (0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15), 0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eii) Post-surgical Resection Patients with one year outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.52/ large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13 (0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08), 0.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05 (0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17), 0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eD) Intrasubject analysis in patients who had both Pulvinar and ATG (N\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ei) Clinical versus Nonclinical seizures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical in Pulvinar group (Pul-CS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21 (0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23), 0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;=\u0026thinsp;0.0004*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical in Pulvinar group (Pul-NCS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06 (0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10), 0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical in ATG group (ATG-CS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.28 (0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28), 0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical in ATG group (ATG-NCS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07 (0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13), 0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ePul-CS vs ATG CS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.6757\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ePul-NCS vs ATG -NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.6776\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ePul-CS vs ATG-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;=\u0026thinsp;0.0049\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.57/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eATG-CS vs Pul_NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;=\u0026thinsp;0.0023\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.62/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ePul-CS vs Pul-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;=\u0026thinsp;0.0006\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.69/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eATG-CS vs ATG-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.0144\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.49/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eE) Pulvinar Group: seizure analysis (N\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ei) Clinical versus Nonclinical seizures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.64/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58 (216)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.19 (0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22), 0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06 (0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15), 0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eii) Clinical Seizure Subtypes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.3685**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFPC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.22 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20), 0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (111)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.20 (0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20), 0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFTBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28), 0.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFPC vs FIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.63***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFTBC vs FIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.19***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.13/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFPC vs FTBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.27***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eF) Pulvinar Group: Post-resection patients with one year outcome (N\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ei) Clinical vs Nonclinical: Post-surgical Resection Patients with one year outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.69/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35 (133)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21 (0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21), 0.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05 (0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18), 0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eii) Seizure freedom status: Post-surgical Resection Patients with one year outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.6427*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeizure free\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.17 (0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;019), 0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonseizure free\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.18 (0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24), 0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eiii) Post-surgical Resection Patients with one year outcome (Seizure and SF groups)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSF-CS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.19 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19), 0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04 (0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05), 0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNSF-CS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.28 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23), 0.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNSF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13 (0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24), 0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSF-CS vs SF NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.85/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eSF-C vs NSF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.66/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eNSF-CS vs SF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.72/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eNSF-CS vs NSF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eP\u0026thinsp;=\u0026thinsp;0.0003\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.55/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eNSF-CS vs SF-CS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.408\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.08/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eNSF-NCS vs SF-NCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.568\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eG) ATG group: Seizure analysis (N\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ei) Clinical versus Nonclinical seizures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.0005*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.58/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.15 (0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27), 0.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06 (0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11), 0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eii) Clinical Seizure Subtypes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.3571**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFPC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13 (0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24),0.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.20 (0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30), 0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFTBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21 (0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13), 0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFPC vs FIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.1831***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.22/small\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFIC vs FTBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.9477***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.02/negligible\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFTBC vs FPC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.3642***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.25/small\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eH) ATG group: Post-resection patients with one year outcome (N\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ei) Clinical vs Nonclinical: Post-surgical Resection Patients with one year outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.0001*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.94/large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8(29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.15 (0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10), 0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonclinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05 (0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04), 0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eii) Seizure freedom status: Post-surgical Resection Patients with one year outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.8868*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeizure free\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13 (0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11), 0.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonseizure free\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.12 (0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12), 0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e* p value calculated using Mann\u0026ndash;Whitney U tests\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e** p value calculated using Kruskal\u0026ndash;Wallis H test\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*** Corrected p value (Bonferroni-adjusted threshold for pair-wise analysis using Mann-Whitney U test) p\u0026thinsp;\u0026lt;\u0026thinsp;0.0165\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e#\u003c/sup\u003e Corrected p value (Bonferroni-adjusted threshold for pair-wise analysis using Mann-Whitney U test)\u0026thinsp;=\u0026thinsp;P\u0026thinsp;\u0026lt;\u0026thinsp;0.0083\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eSignificant p-values are highlighted in bold.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e(Abbreviation: No: number, SF: seizure free, NSF: nonseizure free, CS: clinical seizure, NCS: nonclinical seizure, FPC: focal preserved consciousness seizure, FICL: focal impaired consciousness, FTBC: focal to bilateral tonic clonic seizure, SD: standard deviation, IQR: 25\u0026ndash;75% Interquartile range, Pul: Pulvinar, ATG: Anterior thalamus group, N; Number of patients, NA: not applicable)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAcross all seizures, thalamo\u0026ndash;temporal spectral correlation values were significantly lower in NCS (n\u0026thinsp;=\u0026thinsp;72) compared to CS (n\u0026thinsp;=\u0026thinsp;275) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, δ\u0026thinsp;=\u0026thinsp;0.63; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cem\u003e(i)\u003c/em\u003e). This pattern persisted across temporal epilepsy subtypes: correlations in NCS were significantly lower than in CS for mesial temporal (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, δ\u0026thinsp;=\u0026thinsp;0.67), lateral temporal (p\u0026thinsp;=\u0026thinsp;0.0003, δ\u0026thinsp;=\u0026thinsp;0.60), and mesiolateral subtypes (p\u0026thinsp;=\u0026thinsp;0.0032, δ\u0026thinsp;=\u0026thinsp;0.66) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). When stratifying CS into FPC (n\u0026thinsp;=\u0026thinsp;83), FIC (n\u0026thinsp;=\u0026thinsp;140), and FTBC (n\u0026thinsp;=\u0026thinsp;52), no significant differences were found (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cem\u003e(ii)\u003c/em\u003e), suggesting that awareness level or generalization does not further modulate resonance strength beyond the clinical vs. nonclinical dichotomy. In the subset of 38 patients with \u0026ge;\u0026thinsp;1 year of surgical follow-up (250 seizure entries), CS again demonstrated significantly higher thalamo\u0026ndash;temporal correlation than NCS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, δ\u0026thinsp;=\u0026thinsp;0.72; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA(iii)). No overall difference was observed between SF and NSF groups (p\u0026thinsp;=\u0026thinsp;0.7514); however, when stratified into four subgroups (SF-CS, SF-NCS, NSF-CS, NSF-NCS), significant differences emerged (Kruskal\u0026ndash;Wallis p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA(iv)). Notably, SF-CS showed significantly higher correlation than SF-NCS and NSF-NCS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), while NSF-CS also exceeded NSF-NCS (p\u0026thinsp;=\u0026thinsp;0.0007) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cem\u003e(iv)\u003c/em\u003e).\u003c/p\u003e\u003cp\u003eIn a multiple linear regression model (N\u0026thinsp;=\u0026thinsp;347), seizure type was the only significant predictor of thalamo\u0026ndash;temporal correlation values (F(4, 342)\u0026thinsp;=\u0026thinsp;8.94, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, R\u0026sup2; = 0.095). Nonclinical seizures were associated with significantly lower correlation values compared to clinical seizures (β = \u0026minus;\u0026thinsp;0.166, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Thalamic region, epilepsy subtypes, and seizure freedom status were not significantly associated with correlation values (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.12) (\u003cem\u003eSupplementary Table\u0026nbsp;3\u003c/em\u003e).\u003c/p\u003e\n\u003ch3\u003eWithin-Subject Comparisons\u003c/h3\u003e\n\u003cp\u003eIntra-subject analyses were performed to confirm these findings. In 20 patients with both CS and NCS, correlation remained higher in CS (p\u0026thinsp;=\u0026thinsp;0.0003, δ\u0026thinsp;=\u0026thinsp;0.37; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cem\u003e(i)\u003c/em\u003e), with a stronger difference in the subset with \u0026ge;\u0026thinsp;1 year of outcome data (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, δ\u0026thinsp;=\u0026thinsp;0.52; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cem\u003e(ii)\u003c/em\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates two representative patients with both clinical and nonclinical seizure types, where thalamic involvement was observed only during CS, despite identical EZ.\u003c/p\u003e\u003cp\u003eIn the 11 patients with both Pul and ATG coverage, Pul-CS showed the highest correlation values, significantly exceeding Pul-NCS (p\u0026thinsp;=\u0026thinsp;0.0006) and ATG-NCS (p\u0026thinsp;=\u0026thinsp;0.005). No difference was found between Pul-CS and ATG-CS (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B highlights two patients with mesial and lateral temporal epilepsy showing bilateral thalamic coupling during CS.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eThalamic Subregion Analysis\u003c/h2\u003e\u003cp\u003eThe pulvinar group (273 seizures (216 CS, 57 NCS) from 59 patients) mirrored the global findings: CS had significantly stronger pulvinar\u0026ndash;temporal synchrony than NCS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, δ\u0026thinsp;=\u0026thinsp;0.64; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eD \u003cem\u003e(i)\u003c/em\u003e), regardless of clinical subtype (FPC, FIC and FTBC) or surgical outcome (SF vs NSF). Stratified analysis again showed that SF-CS had higher coupling than all other subgroups (Kruskal\u0026ndash;Wallis p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eD (ii)) and no differences were found in comparisons between SF-C and NSF-C (p\u0026thinsp;=\u0026thinsp;0.408) and between SF-NC and NSF-NC (p\u0026thinsp;=\u0026thinsp;0.568). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eC illustrates three mTLE patients with the Pul involvement during CS.\u003c/p\u003e\u003cp\u003eATG-specific analysis (74 seizures (59 CS, 15 NCS) from 14 patients) similarly showed a higher correlation in CS than NCS (p\u0026thinsp;=\u0026thinsp;0.0005, δ\u0026thinsp;=\u0026thinsp;0.58; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF ), with no differences across FPC, FIC, and FTBC. Eight patients underwent resective surgery (mean follow-up =\u0026thinsp;33.3 months), contributing 36 seizures (29 CS, 7 NCS). NCS again showed lower correlation than CS (p\u0026thinsp;=\u0026thinsp;0.0001, δ\u0026thinsp;=\u0026thinsp;0.94), but no significant difference was observed between SF and NSF groups (p\u0026thinsp;=\u0026thinsp;0.8868).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eEpileptogenicity index and Surgical outcome\u003c/h2\u003e\u003cp\u003eEI values were analyzed in 38 patients with \u0026ge;\u0026thinsp;12 months of postoperative follow-up (\u003cem\u003eSupplementary Table\u0026nbsp;2\u003c/em\u003e). Of these, 37 patients had at least one clinical seizure subtype, and one patient had only NCS. Using a threshold of EI\u0026thinsp;\u0026gt;\u0026thinsp;0.3 based on previously suggested threshold in the Pul, 5.3% (n\u0026thinsp;=\u0026thinsp;2) patients were classified as high EI, one was seizure-free. Of the 36 with EI\u0026thinsp;\u0026le;\u0026thinsp;0.3, 23 (63.9%) achieved SF, suggesting that limited thalamic recruitment at seizure onset may be associated with a higher likelihood of postoperative seizure control.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eBy leveraging thalamic and temporal SEEG in drug-resistant TLE, we show that thalamo-cortical spectral synchrony is markedly stronger during clinically manifest seizures than during non-clinical seizures, a state-dependent effect that holds across seizure subtypes, temporal onset classes, and thalamic nuclei (pulvinar and anterior group). Within-patient comparisons confirm the phenomenon irrespective of prognosis, and multivariable modeling identifies seizure type as the sole independent predictor of coupling strength. These findings reposition the thalamus from a passive relay to a symptomatogenic hub whose dynamic coupling with cortex governs clinical expression. Conceptually, this resolves prior inconsistencies in thalamic involvement by focusing on synchrony strength rather than onset timing alone. Practically, it defines a quantitative signature that could guide neuromodulation, suggesting that attenuating thalamo-cortical synchrony may suppress symptoms even when resection is not feasible. Beyond epilepsy, the framework generalizes to disorders where thalamo-cortical coupling shapes cognition and behavior, offering a mechanistic bridge from network dynamics to clinical phenomenology. Crucially, our finding raises the therapeutic possibility that targeted disruption of thalamo-cortical synchrony through neuromodulation or focused ablations could suppress clinical symptoms even in the presence of ongoing electrographic seizures. Such an approach could shift the treatment paradigm from seizure elimination to symptom prevention, offering meaningful quality-of-life improvements for patients with DRE. In addition, our results highlight the importance of incorporating seizure semiology, particularly the CS\u0026ndash;NCS distinction, when evaluating thalamo\u0026ndash;temporal network dynamics in both the Pul and ATG in DR-TLE.\u003c/p\u003e\u003cp\u003eOver the past several decades, SEEG has fundamentally reshaped our understanding of epilepsy, shifting the paradigm from a focal disorder localized to discrete cortical regions to a dynamic network disease involving both cortical and subcortical structures, particularly the thalamus\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Although the involvement of subcortical involvement is a known mechanistic process in generalized epilepsy\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, the concept is evolving in the role of focal epilepsy. Within this network-based framework applied to focal epilepsy, increasing attention has concentrated on specific thalamic subregions, such as the Pul and the ANT, both of which have been implicated in TLE pathophysiology \u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Despite its long-term efficacy (up to 70% median seizure reduction), the mechanism of ANT neuromodulation in TLE remains unclear whether through disrupted propagation, altered excitability, or broader network reorganization\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. While ANT has been traditionally selected for TLE due to its anatomical position within the Papez circuitry\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, recent studies highlight the medial pulvinar (PuM) nucleus as a functionally relevant target\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. The PuM exhibits strong reciprocal connectivity with mesial temporal structures, particularly the hippocampus and amygdala, and is engaged in up to 80% of mesial TLE seizures\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Multi-nucleus thalamic recordings reveal variable seizure recruitment patterns across subregions, with visual analysis suggesting that the PuM may engage earlier and more prominently than the ANT\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. However, visual inspection alone has proven insufficient to reliably characterize thalamic involvement, given the complexity and variability of recorded signals, a limitation we also encountered in our dataset. Our findings, using quantitative spectral correlation analysis, extend prior work by demonstrating that indeed thalamo-cortical synchrony during ictal events is not limited to mesial temporal seizures but is also present in seizures originating from lateral and mesiolateral neocortical temporal regions. This broader cortical engagement, coupled with strong thalamic synchrony, suggests that the thalamus participates in a more extensive seizure network than previously appreciated. Our observations of comparable thalamic engagement in both Pul and ATG during clinical seizures support the idea of convergent thalamo-cortical pathways contributing to the emergence of semiology, expanding the current concept of epileptic network and offering scientific insights into the mechanism of action of thalamic neuromodulation by hypothesizing that is by the disruption of thalamo-cortical synchrony through electrical stimulation that the translation of electrographic seizures into clinical symptoms is disrupted..\u003c/p\u003e\u003cp\u003eOur findings complement existing work on thalamic functional connectivity (FC) in seizure dynamic. Soulier et al. reported increased thalamo-cortical FC during seizures, although they found no global differences between ANT and PuM\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. They did, however, identify stronger pulvinar involvement during synchronous seizure termination\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Conversely, Ilyas et al. suggested that ANT may actively facilitate seizure propagation in TLE\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. These findings suggest subregional heterogeneity and emphasize moving beyond static anatomical assumptions when evaluating seizure networks. Although our study did not assess FC via graph theory metrics, our TF correlation approach revealed robust thalamo\u0026ndash;temporal synchrony in both pulvinar and ATG during CS, and significantly reduced synchrony during NCS, suggesting state-dependent thalamo-cortical coupling across both nuclei, reinforcing their consistent engagement during behaviorally expressive seizures.\u003c/p\u003e\u003cp\u003eA recent study by Salami et al. reported that seizures with broader cortical onset or higher-frequency activity (\u0026lt;\u0026thinsp;20 Hz) were more likely to propagate early (within 1\u0026ndash;6 seconds) to the centromedian and pulvinar thalamic nuclei, whereas mesial temporal onset seizures tended to spread earlier to the ANT\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Their findings suggested that seizure onset pattern, whether spatially broad or spectrally fast, may influence thalamic recruitment\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Our results are broadly consistent with these observations but offers an important complementary perspective. In our cohort, both mesial and lateral temporal seizures demonstrated early engagement of the pulvinar and ATG, but this was contingent on seizure semiology, whether the event was clinically manifest. Here, the intrasubject comparisons revealed that, even within the same patient, thalamic recruitment was evident only during clinical seizures and absent or markedly reduced during NCS, even with similar onset patterns or faster mesial temporal onset in NCS. This suggests that thalamic involvement is not solely dictated by onset frequency or spatial spread but is more closely linked to the clinical expression of seizures. In this context, our findings extend Salami et al.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e by highlighting thalamo\u0026ndash;cortical spectral synchrony as a network-level correlate of behavioral expression. These results support the idea that thalamic recruitment is an active epileptogenic mechanism, reflecting the emergence of clinical symptomatology, and not merely passive propagation. It is interesting to note that in our cohort, limited thalamic involvement at seizure onset, reflected by a low EI, was associated with a higher likelihood of postoperative seizure freedom, reflecting the incomplete treatment of a more broader pathological process that goes beyond the cortical treated areas.\u003c/p\u003e\u003cp\u003eOur findings align with and extend prior findings linking thalamic synchrony to semiology. Guye et al. found greater thalamo-cortical synchrony in seizures with impaired consciousness compared to those with preserved awareness, although their cohort did not include FTBC\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Other studies have shown that excessive thalamo\u0026ndash;associative cortical synchronization may underlie impaired awareness and cognitive symptoms in TLE\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Supporting a causal role, a proof-of-concept study showed that stimulation of the medial pulvinar during hippocampal seizures improved consciousness, possibly suggesting that modulation of thalamic activity can alter behavioral outcomes\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Pizarro et al., although not focused on the pulvinar, demonstrated that ictal power changes within the ANT closely paralleled activity in the seizure onset zone (SOZ) and were significantly heightened during seizures that impaired consciousness or secondarily generalized\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Ye et al. further reported that preictal functional connectivity variability within the cortical SOZ was greater for CS than NCS in TLE\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, although their analysis did not include thalamic data. These studies suggest that behavioral expression may depend more on thalamo-cortical dynamics in addition to seizure onset site or frequency, directly supported by our observation that thalamic spectral synchrony consistently distinguished CS from NCS. Importantly, thalamic synchrony was not influenced by seizure subtype, further supporting its role as a state-dependent marker of clinical expression. Altogether, our findings support thalamic spectral correlation as a direct physiological marker of semiology than conventional measures such as cortical onset patterns or EEG morphology.\u003c/p\u003e\u003cp\u003eThalamic involvement has been proposed as a prognostic marker in TLE, with imaging studies linking pulvinar atrophy and disrupted thalamo-temporal connectivity to poor surgical outcomes, even after adequate cortical resection \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Some reports have associated higher thalamic epileptogenicity (EI\u0026thinsp;\u0026gt;\u0026thinsp;0.3)\u003csup\u003e14\u003c/sup\u003e or early thalamic synchronization\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e with poor surgical failure, while others found that delayed thalamic recruitment predicted poor surgical outcomes\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. These discrepancies raise questions about whether thalamic involvement is causative, compensatory, or epiphenomenal. Our findings provide a complementary perspective, showing that thalamic spectral synchrony was strongly associated with seizure semiology but not with surgical outcome. Thalamic recruitment consistently followed or coincided with cortical seizure onset, but coupling strength was significantly higher in clinical than nonclinical seizures, regardless of postoperative seizure freedom. This suggests that thalamo-cortical synchrony governs behavioral expression rather than underlying epileptogenicity. Focusing on synchrony strength, as opposed to timing alone\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, may help reconcile previous discrepancies and better capture the functional relevance of thalamic dynamics in TLE.\u003c/p\u003e\u003cp\u003eIn summary, our findings suggest that thalamo\u0026ndash;temporal spectral synchrony is a robust physiological marker of seizure expression. It reliably tracks clinical symptoms across TLE subtypes and is unrelated to seizure onset zone or surgical outcome. By prioritizing seizure semiology, our work repositions thalamo-cortical dynamics as a key driver of behavioral manifestations and a novel therapeutic target for symptom suppression.\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eLimitations and Future Directions\u003c/h2\u003e\u003cp\u003eAlthough our study offers valuable insights, it has several limitations. First, its post-hoc nature and heterogeneity in electrode coverage, particularly the fact that not all patients had recordings from both the pulvinar and ATG, may limit generalizability, despite inclusion of data from two centers. The small sample size for subgroup analyses, especially for the ATG-only group, also warrants caution. Second, while our time\u0026ndash;frequency correlation approach effectively quantified thalamo-cortical synchrony, it did not assess causal relationships or directional connectivity. Future studies incorporating causality measures (e.g., Granger causality, transfer entropy) or phase\u0026ndash;amplitude coupling could better delineate how different thalamic subregions contribute to seizure generation and propagation. Third, our analysis focused on the first 20 seconds of ictal activity, which may limit interpretation of how clinical semiology evolves or emergent, particularly in motor features or progression to FBTC seizures. Future studies should examine the full duration of seizures, including ictal evolution, to better characterize how thalamo-cortical dynamics shape the emergence and progression of clinical symptoms. This approach may help differentiate synchrony patterns among distinct clinical seizure subtypes, such as FPC, FIC and FTBC. Additionally, thalamic electrode placement varied between patients, and precise subnuclear localization was not always feasible, introducing potential anatomical variability. Standardized implantation strategies and prospective multicenter studies with larger cohorts will be essential for validating and expanding these findings.\u003c/p\u003e\u003cp\u003eDespite these limitations, the robustness of results bring evidence that thalamic-cortical synchrony is marker of a broader symptomatogenic process in focal epilepsies. Our results highlight the need to explore the therapeutic potential of targeting thalamo-cortical pathways. In patients with diffuse, non-localizable, or eloquent cortex-involving epileptogenic zones, the thalamus may serve as a key hub for stabilizing cortical networks. Modulating thalamo-cortical circuits, via deep brain stimulation or closed-loop neuromodulation, could offer a means of suppressing seizure symptoms when resection is not an option. Future studies should evaluate whether thalamic engagement, via closed-loop or open-loop stimulation, or other techniques, can be harnessed to modulate semiology, improve seizure control, and preserve cognitive function in challenging cases of DR-TLE.\u003c/p\u003e\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eanterior thalamus group (ATG), stereo-electroencephalography (SEEG), anterior temporal lobectomy (ATL), mesial temporal sclerosis (MTS), focal preserved consciousness seizure (FPC), focal impaired consciousness seizures (FIC), focal to bilateral tonic-clonic (FBTC), time-frequency (TF), standard deviation (SD), Interquartile range (IQR), Clinical seizure (CS), Nonclinical seizure (NCS), Seizure free (SF), nonseizure free (NSF), Clinical seizure in pulvinar group (Pul-CS), Nonclinical seizure in pulvinar group (Pul-NCS), Clinical seizure in ATG group (ATG-CS), Nonclinical seizure in ATG group (ATG-NCS), drug-resistant temporal lobe epilepsy (DR-TLE), Epileptogenic zone (EZ), Seizure onset zone (SOZ).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting this study are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWiebe S, Blume WT, Girvin JP, Eliasziw MA, Randomized (2001) Controlled Trial of Surgery for Temporal-Lobe Epilepsy. 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Sci Rep 12\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7419263/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7419263/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn drug-resistant temporal lobe epilepsy (DR-TLE), electrographic seizures with clinical symptoms (CS) largely determine quality of life, yet some remain silent (NCS) despite arising from the same seizure-onset zone (SOZ). While surgical resection can be curative in select cases, many patients particularly those with bilateral TLE or unresectable networks are not surgical candidates. For these individuals, clarifying why some seizures produce symptoms while others do not is essential for advancing therapy. We hypothesized that thalamo-cortical network engagement may explain this divergence. 286 seizures from 62 DR-TLE patients, included coverage of the pulvinar and/or anterior thalamic group, were analyzed. Thalamo-cortical synchrony, quantified as the correlation between time\u0026ndash;frequency patterns in thalamic nuclei and the cortical SOZ, was investigated in relation to seizure type, epilepsy subtype, thalamic region, and one-year post-resection surgical outcome. Thalamo-cortical synchrony was stronger during CS than NCS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, δ\u0026thinsp;\u0026gt;\u0026thinsp;0.6), regardless of epilepsy subtype, thalamic region, seizure subtype, or outcome, and confirmed within patients. Multivariate analysis identified seizure type as the only independent predictor (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings establish thalamo-cortical synchrony as a network-level marker of clinical seizure expression and highlight the potential of neuromodulation to modulate seizure expression when resection is not feasible.\u003c/p\u003e","manuscriptTitle":"Thalamo-cortical Synchrony Shapes Seizure Expression in Human Temporal Lobe Epilepsy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-27 07:47:58","doi":"10.21203/rs.3.rs-7419263/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8ef30482-1f19-4150-9257-705ec253953e","owner":[],"postedDate":"August 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":53501181,"name":"Health sciences/Medical research/Translational research"},{"id":53501182,"name":"Health sciences/Biomarkers/Diagnostic markers"}],"tags":[],"updatedAt":"2026-04-28T16:01:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-27 07:47:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7419263","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7419263","identity":"rs-7419263","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}