Association of Normative and Non-Normative Brain Networks With Cognitive Function in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: Despite their temporal lobe pathology, a significant subgroup of patients with temporal lobe epilepsy (TLE) is able to maintain normative cognitive functioning. In this study, we identify patients with TLE with intact vs impaired neurocognitive profiles and interrogate for the presence of both normative and highly individual intrinsic connectivity networks (ICNs)-all toward understanding the transition from impaired to intact neurocognitive status. METHODS: This retrospective cross-sectional study included patients with TLE and matched healthy controls (HCs) from the Thomas Jefferson Comprehensive Epilepsy Center. Functional MRI data were decomposed using independent component analysis to obtain individualized ICNs. In this article, we calculated the degree of match between individualized ICNs and canonical ICNs (e.g., 17 resting-state networks by Yeo et al.) and divided each participant's ICNs into normative or non-normative status based on the degree of match. RESULTS: 100 patients with TLE (mean age 42.0 [SD: 13.7] years, 47 women) and 92 HCs were included in this study. We found that the individualized networks matched to the canonical networks less well in the cognitively impaired (n = 24) compared with the cognitively intact (n = 63) patients with TLE by 2-way mixed-measures analysis of variance (impaired vs intact mean difference [MD] -0.165 [-0.317, -0.013], p = 0.028). The cognitively impaired patients showed significant abnormalities in the profiles of both normative (impaired vs intact MD -0.537 [-0.998, -0.076], p = 0.017, intact vs HC MD -0.221 [-0.536, 0.924], p = 0.220, and impaired vs HC MD -0.759 [-1.200, -0.319], p < 0.001) and non-normative networks (impaired vs intact MD 0.484 [0.030, 0.937], p = 0.033, intact vs HC MD 0.369 [0.059, 0.678], p = 0.014, and impaired vs HC MD 0.853 [0.419, 1.286], p < 0.001) while the intact patients showed abnormalities only in non-normative networks. At the same time, we found that normative networks held a strong, positive association with the neuropsychological measures, with this association negative in non-normative networks. DISCUSSION: Our data demonstrated that significant cognitive deficits are associated with the status of both canonical and highly individual ICNs, making clear that the transition from intact to impaired cognitive status is not simply the result of disruption to normative brain networks.

Dynamic evolution of frontal-temporal network connectivity in temporal lobe epilepsy: A magnetoencephalography study.

Temporal lobe epilepsy (TLE) frequently involves an intricate, extensive epileptic frontal-temporal network. This study aimed to investigate the interactions between temporal and frontal regions and the dynamic patterns of the frontal-temporal network in TLE patients with different disease durations. The magnetoencephalography data of 36 postoperative seizure-free patients with long-term follow-up of at least 1 year, and 21 age- and sex-matched healthy subjects were included in this study. Patients were initially divided into LONG-TERM (n = 18, DURATION >10 years) and SHORT-TERM (n = 18, DURATION ≤10 years) groups based on 10-year disease duration. For reliability, supplementary analyses were conducted with alternative cutoffs, creating three groups: 0 < DURATION ≤7 years (n = 11), 7 < DURATION ≤14 years (n = 11), and DURATION >14 years (n = 14). This study examined the intraregional phase-amplitude coupling (PAC) between theta phase and alpha amplitude across the whole brain. The interregional directed phase transfer entropy (dPTE) between frontal and temporal regions in the alpha and theta bands, and the interregional cross-frequency directionality (CFD) between temporal and frontal regions from the theta phase to the alpha amplitude were further computed and compared among groups. Partial correlation analysis was conducted to investigate correlations between intraregional PAC, interregional dPTE connectivity, interregional CFD, and disease duration. Whole-brain intraregional PAC analyses revealed enhanced theta phase-alpha amplitude coupling within the ipsilateral temporal and frontal regions in TLE patients, and the ipsilateral temporal PAC was positively correlated with disease duration (r = 0.38, p <.05). Interregional dPTE analyses demonstrated a gradual increase in frontal-to-temporal connectivity within the alpha band, while the direction of theta-band connectivity reversed from frontal-to-temporal to temporal-to-frontal as the disease duration increased. Interregional CFD analyses revealed that the inhibitory effect of frontal regions on temporal regions gradually increased with prolonged disease duration (r = -0.36, p <.05). This study clarified the intrinsic reciprocal connectivity between temporal and frontal regions with TLE duration. We propose a dynamically reorganized triple-stage network that transitions from balanced networks to constrained networks and further develops into imbalanced networks as the disease duration increases.

Association Between Postsurgical Functional Connectivity and Seizure Outcome in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: Despite the success of presurgical network connectivity studies in predicting short-term (1-year) seizure outcomes, later seizure recurrence occurs in some patients with temporal lobe epilepsy (TLE). To uncover contributors to this recurrence, we investigated the relationship between functional connectivity and seizure outcomes at different time points after surgery in these patients. METHODS: Patients included were clinically diagnosed with unilateral mesial TLE after a standard clinical evaluation and underwent selective amygdalohippocampectomy. Healthy controls had no history of seizures or head injury. Using resting-state fMRI, we assessed the postsurgical functional connectivity node strength, computed as the node's total strength to all other nodes, between seizure-free (Engel Ia-Ib) and nonseizure-free (Engel Ic-IV) acquisitions. The change over time after surgery in different outcome groups in these nodes was also characterized. RESULTS: Patients with TLE (n = 32, mean age: 43.1 ± 11.9 years; 46.8% female) and 85 healthy controls (mean age: 37.7 ± 13.5 years; 48.2% female) were included. Resting fMRI was acquired before surgery and at least once after surgery in each patient (range 1-4 scans, 5-60 months). Differences between patients with (n = 30) and without (n = 18) seizure freedom were detected in the posterior insula ipsilateral to the resection (I-PIns: 95% CI -154.8 to -50.1, p = 2.8 × 10-4) and the bilateral central operculum (I-CO: 95% CI -163.2 to -65.1, p = 2.6 × 10-5, C-CO: 95% CI -172.7 to -55.8, p = 2.8 × 10-4). In these nodes, only those who were seizure-free had increased node strength after surgery that increased linearly over time (I-CO: 95% CI 1.0-5.2, p = 4.2 × 10-3, C-CO: 95% CI 1.0-5.2, p = 5.5 × 10-3, I-PIns: 95% CI 1.6-5.5, p = 0.9 × 10-3). Different outcome groups were not distinguished by node strength before surgery. DISCUSSION: The findings suggest that network evolution in the first 5 years after selective amygdalohippocampectomy surgery is related to seizure outcomes in TLE. This highlights the need to identify presurgical and surgical conditions that lead to disparate postsurgical trajectories between seizure-free and nonseizure-free patients to identify potential contributors to long-term seizure outcomes. However, the lack of including other surgical approaches may affect the generalizability of the results.

Delineating structural and metabolic abnormalities in amygdala and hippocampal subfields for different seizure-onset patterns via stereotactic electroencephalography.

AIMS: We aimed to investigate mesial temporal lobe abnormalities in mesial temporal lobe epilepsy (MTLE) patients with hypersynchronous (HYP) and low-voltage fast rhythms (LVF) onset identified by stereotactic electroencephalography (SEEG) and evaluate their diagnostic and prognostic value. METHODS: Fifty-one MTLE patients were categorized as HYP or LVF by SEEG. High-resolution MRI volume-based analysis and 18F-FDG-PET standard uptake values of hippocampal and amygdala subfields were quantified and compared with 57 matched controls. Further analyses were conducted to delineate the distinct pathological characteristics differentiating the two groups. Diagnostic and prognostic prediction performance of these biomarkers were assessed using receiver operating characteristic curves. RESULTS: LVF-onset individuals demonstrated ipsilateral amygdala enlargement (p = 0.048) and contralateral hippocampus hypermetabolism (p = 0.042), pathological results often accompany abnormalities in the temporal lobe cortex, while HYP-onset subjects had significant atrophy (p < 0.001) and hypometabolism (p = 0.013) in ipsilateral hippocampus and its subfields, as well as amygdala atrophy (p < 0.001), pathological results are highly correlated with hippocampal sclerosis. Severe fimbria atrophy was observed in cases of HYP-onset MTLE with poor prognosis (AUC = 0.874). CONCLUSION: Individuals with different seizure-onset patterns display specific morphological and metabolic abnormalities in the amygdala and hippocampus. Identifying these subfield abnormalities can improve diagnostic and prognostic precision, guiding surgical strategies for MTLE.

[Construction and analysis of brain metabolic network in temporal lobe epilepsy patients based on 18F-FDG PET].

The establishment of brain metabolic network is based on 18fluoro-deoxyglucose positron emission computed tomography ( 18F-FDG PET) analysis, which reflect the brain functional network connectivity in normal physiological state or disease state. It is now applied to basic and clinical brain functional network research. In this paper, we constructed a metabolic network for the cerebral cortex firstly according to 18F-FDG PET image data from patients with temporal lobe epilepsy (TLE).Then, a statistical analysis to the network properties of patients with left or right TLE and controls was performed. It is shown that the connectivity of the brain metabolic network is weakened in patients with TLE, the topology of the network is changed and the transmission efficiency of the network is reduced, which means the brain metabolic network connectivity is extensively impaired in patients with TLE. It is confirmed that the brain metabolic network analysis based on 18F-FDG PET can provide a new perspective for the diagnose and therapy of epilepsy by utilizing PET images.

Pattern of abnormalities on gray matter in patients with medial temporal lobe epilepsy and hippocampal sclerosis: An updated meta-analysis.

Temporal lobe epilepsy (TLE) is a prevalent form of epilepsy originating in the temporal lobes. A common pathological feature is hippocampal sclerosis (HS), characterized by the loss of neuronal cells, which is associated with the typical temporal mesial lobe epilepsy (MTLE). In this study, we aimed to analyze gray matter alterations in patients with MTLE with right and left hemisphere HS using voxel-based morphometry and compare them with control groups. A meta-analysis was performed based on the guidelines contained in the Protocol Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), using the MEDLINE database, with the keywords: "gray matter" AND "temporal lobe epilepsy " AND ("hippocampal sclerosis" OR "hippocampal abnormalities") AND ("voxel-based morphometry" OR "VBM" OR "voxel-wise"). Of the 14 articles included in the review, 8 were added by the method, in which the meta-analysis was performed. Our results indicate that in the right hemisphere, the hippocampus, caudate nucleus, parahippocampal gyrus, thalamus, dorsalis medial nucleus, insula, and right claustrum were most commonly implicated. In the left hemisphere, a significant pattern of gray matter loss was observed in the putamen, lentiform nucleus, uncus, Brodmann areas 20 and 23, cingulate gyrus, caudate nucleus, cerebellum, and cuneus compared to healthy controls.Our study highlights distinct patterns of gray matter alteration in MLTE-HS and suggests that these regions may contribute to changes in verbal memory and visuospatial impairment based on their anatomical and hemispheric locations. Our findings can be potentially helpful for future diagnostic markers, therapeutic targets, and insights into disease progression, better understanding of these findings.

Characterizing white matter connectome abnormalities in patients with temporal lobe epilepsy using threshold-free network-based statistics.

INTRODUCTION: Emerging evidence illustrates that temporal lobe epilepsy (TLE) involves network disruptions represented by hyperexcitability and other seizure-related neural plasticity. However, these associations are not well-characterized. Our study characterizes the whole brain white matter connectome abnormalities in TLE patients compared to healthy controls (HCs) from the prospective Epilepsy Connectome Project study. Furthermore, we assessed whether aberrant white matter connections are differentially related to cognitive impairment and a history of focal-to-bilateral tonic-clonic (FBTC) seizures. METHODS: Multi-shell connectome MRI data were preprocessed using the DESIGNER guidelines. The IIT Destrieux gray matter atlas was used to derive the 162 × 162 structural connectivity matrices (SCMs) using MRTrix3. ComBat data harmonization was applied to harmonize the SCMs from pre- and post-scanner upgrade acquisitions. Threshold-free network-based statistics were used for statistical analysis of the harmonized SCMs. Cognitive impairment status and FBTC seizure status were then correlated with these findings. RESULTS: We employed connectome measurements from 142 subjects, including 92 patients with TLE (36 males, mean age = 40.1 ± 11.7 years) and 50 HCs (25 males, mean age = 32.6 ± 10.2 years). Our analysis revealed overall significant decreases in cross-sectional area (CSA) of the white matter tract in TLE group compared to controls, indicating decreased white matter tract integrity and connectivity abnormalities in addition to apparent differences in graph theoretic measures of connectivity and network-based statistics. Focal and generalized cognitive impaired TLE patients showcased higher trend-level abnormalities in the white matter connectome via decreased CSA than those with no cognitive impairment. Patients with a positive FBTC seizure history also showed trend-level findings of association via decreased CSA. CONCLUSIONS: Widespread global aberrant white matter connectome changes were observed in TLE patients and characterized by seizure history and cognitive impairment, laying a foundation for future studies to expand on and validate the novel biomarkers and further elucidate TLE's impact on brain plasticity.

Region-specific MRI predictors of surgical outcome in temporal lobe epilepsy.

OBJECTIVE: In drug-resistant temporal lobe epilepsy (TLE), it is not well-established in how far surgery should target morphological anomalies to achieve seizure freedom. Here, we assessed interactions between structural brain compromise and surgery to identify region-specific predictors of seizure outcome. METHODS: We obtained pre- and post-operative 3D T1-weighted MRI in 55 TLE patients who underwent selective amygdalo-hippocampectomy (SAH) or anterior temporal lobectomy (ATL) and 40 age and sex-matched healthy subjects. We measured surface-based morphological alterations of the mesiotemporal lobe structures (hippocampus, amygdala, entorhinal and piriform cortices), the neocortex and the thalamus on both pre- and post-operative MRI. Using precise co-registration, in each patient we mapped the surgical cavity onto the MRI acquired before surgery, thereby quantifying the amount of pathological tissue resected; these features, together with the preoperative morphometric data, served as input to a supervised classification algorithm for postsurgical outcome prediction. RESULTS: On pre-operative MRI, patients who became seizure-free (TLE-SF) presented with severe ipsilateral amygdalar and hippocampal atrophy, while not seizure-free patients (TLE-NSF) displayed amygdalar hypertrophy. Stratifying patients based on the surgical approach, post-operative MRI showed similar patterns of mesiotemporal and thalamic changes, but divergent neocortical thinning affecting the parieto-temporo-occipital regions following ATL and the frontal lobes after SAH. Irrespective of the surgical approach, hippocampal atrophy on pre-operative MRI and its extent of resection were the most predictive features of seizure-freedom in 89% of patients (selected 100% across validations). SIGNIFICANCE: Our study indicates a critical role of the extent of resection of MRI-derived hippocampal morphological anomalies on seizure outcome. Precise pre-operative quantification of the mesiotemporal lobe provides non-invasive prognostics for individualized surgery.

Dynamic functional connectivity and gene expression correlates in temporal lobe epilepsy: insights from hidden markov models.

BACKGROUD: Temporal lobe epilepsy (TLE) is associated with abnormal dynamic functional connectivity patterns, but the dynamic changes in brain activity at each time point remain unclear, as does the potential molecular mechanisms associated with the dynamic temporal characteristics of TLE. METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired for 84 TLE patients and 35 healthy controls (HCs). The data was then used to conduct HMM analysis on rs-fMRI data from TLE patients and an HC group in order to explore the intricate temporal dynamics of brain activity in TLE patients with cognitive impairment (TLE-CI). Additionally, we aim to examine the gene expression profiles associated with the dynamic modular characteristics in TLE patients using the Allen Human Brain Atlas (AHBA) database. RESULTS: Five HMM states were identified in this study. Compared with HCs, TLE and TLE-CI patients exhibited distinct changes in dynamics, including fractional occupancy, lifetimes, mean dwell time and switch rate. Furthermore, transition probability across HMM states were significantly different between TLE and TLE-CI patients (p < 0.05). The temporal reconfiguration of states in TLE and TLE-CI patients was associated with several brain networks (including the high-order default mode network (DMN), subcortical network (SCN), and cerebellum network (CN). Furthermore, a total of 1580 genes were revealed to be significantly associated with dynamic brain states of TLE, mainly enriched in neuronal signaling and synaptic function. CONCLUSIONS: This study provides new insights into characterizing dynamic neural activity in TLE. The brain network dynamics defined by HMM analysis may deepen our understanding of the neurobiological underpinnings of TLE and TLE-CI, indicating a linkage between neural configuration and gene expression in TLE.

White matter brain-age in diverse forms of epilepsy and interictal psychosis.

Abnormal brain aging is suggested in epilepsy. Given the brain network dysfunction in epilepsy, the white matter tracts, which primarily interconnect brain regions, could be of special importance. We focused on white matter brain aging in diverse forms of epilepsy and comorbid psychosis. We obtained brain diffusion tensor imaging (DTI) data at 3 T-MRI in 257 patients with epilepsy and 429 healthy subjects. The tract-based fractional anisotropy values of the healthy subjects were used to build a brain-age prediction model, and we calculated the brain-predicted age difference (brain-PAD: predicted age-chronological age) of all subjects. As a result, almost all epilepsy categories showed significantly increased brain-PAD (p < 0.001), including temporal lobe epilepsy (TLE) with no MRI-lesion (+ 4.2 yr), TLE with hippocampal sclerosis (+ 9.1 yr), extratemporal focal epilepsy (+ 5.1 yr), epileptic encephalopathy or progressive myoclonus epilepsy (+ 18.4 yr), except for idiopathic generalized epilepsy (IGE). Patients with psychogenic non-epileptic seizures also presented increased brain-PAD. In TLE, interictal psychosis significantly raised brain-PAD by 8.7 years. In conclusion, we observed increased brain aging in most types of epilepsy, which was generally consistent with brain morphological aging results in previous studies. Psychosis may accelerate brain aging in TLE. These findings may suggest abnormal aging mechanisms in epilepsy and comorbid psychotic symptoms.

Mechanical pain sensitivity is associated with hippocampal structural integrity.

ABSTRACT: Rodents and human studies indicate that the hippocampus, a brain region necessary for memory processing, responds to noxious stimuli. However, the hippocampus has yet to be considered a key brain region directly involved in the human pain experience. One approach to answer this question is to perform quantitative sensory testing on patients with hippocampal damage-ie, medial temporal lobe epilepsy. Some case studies and case series have performed such tests in a handful of patients with various types of epilepsy and have reported mixed results. Here, we aimed to determine whether mechanical pain sensitivity was altered in patients diagnosed with temporal lobe epilepsy. We first investigated whether mechanical pain sensitivity in patients with temporal lobe epilepsy differs from that of healthy individuals. Next, in patients with temporal lobe epilepsy, we evaluated whether the degree of pain sensitivity is associated with the degree of hippocampal integrity. Structural integrity was based on hippocampal volume, and functional integrity was based on verbal and visuospatial memory scores. Our findings show that patients with temporal lobe epilepsy have lower mechanical pain sensitivity than healthy individuals. Only left hippocampal volume was positively associated with mechanical pain sensitivity-the greater the hippocampal damage, the lower the sensitivity to mechanical pain. Hippocampal measures of functional integrity were not significantly associated with mechanical pain sensitivity, suggesting that the mechanisms of hippocampal pain processing may be different than its memory functions. Future studies are necessary to determine the mechanisms of pain processing in the hippocampus.

MRI-Derived Modeling of Disease Progression Patterns in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: Temporal lobe epilepsy (TLE) is assumed to follow a steady course that is similar across patients. To date, phenotypic and temporal diversities of TLE evolution remain unknown. In this study, we aimed at simultaneously characterizing these sources of variability based on cross-sectional data. METHODS: We studied consecutive patients with TLE referred for evaluation by neurologists to the Montreal Neurological Institute epilepsy clinic, who underwent in-patient video EEG monitoring and multimodal imaging at 3 Tesla, comprising 3D T1 and fluid-attenuated inversion recovery and 2D diffusion-weighted MRI. The cohort included patients with drug-resistant epilepsy and patients with drug-responsive epilepsy. The neuropsychological evaluation included Wechsler Adult Intelligence Scale-III and Leonard tapping task. The control group consisted of participants without TLE recruited through advertisement and who underwent the same MRI acquisition as patients. Based on surface-based analysis of key MRI markers of pathology (gray matter morphology and white matter microstructure), the Subtype and Stage Inference algorithm estimated subtypes and stages of brain pathology to which individual patients were assigned. The number of subtypes was determined by running the algorithm 100 times and estimating mean and SD of disease trajectories and the consistency of patients' assignments based on 1,000 bootstrap samples. Effect of normal aging was subtracted from patients. We examined associations with clinical and cognitive parameters and utility for individualized predictions. RESULTS: We studied 82 patients with TLE (52 female, mean age 35 ± 10 years; 11 drug-responsive) and 41 control participants (23 male, mean age 32 ± 8 years). Among 57 operated, 43/37/20 had Engel-I outcome/hippocampal sclerosis/hippocampal isolated gliosis, respectively. We identified 3 trajectory subtypes: S1 (n = 35), led by ipsilateral hippocampal atrophy and gliosis, followed by white-matter damage; S2 (n = 27), characterized by bilateral neocortical atrophy, followed by ipsilateral hippocampal atrophy and gliosis; and S3 (n = 20), typified by bilateral limbic white-matter damage, followed by bilateral hippocampal gliosis. Patients showed high assignability to their subtypes and stages (>90% bootstrap agreement). S1 had the highest proportions of patients with early disease onset (effect size d = 0.27 vs S2, d = 0.73 vs S3), febrile convulsions (χ2 = 3.70), drug resistance (χ2 = 2.94), a positive MRI (χ2 = 8.42), hippocampal sclerosis (χ2 = 7.57), and Engel-I outcome (χ2 = 1.51), pFDR < 0.05 across all comparisons. S2 and S3 exhibited the intermediate and lowest proportions, respectively. Verbal IQ and digit span were lower in S1 (d = 0.65 and d = 0.50, pFDR < 0.05) and S2 (d = 0.76 and d = 1.09, pFDR < 0.05), compared with S3. We observed progressive decline in sequential motor tapping in S1 and S3 (T = -3.38 and T = -4.94, pFDR = 0.027), compared with S2 (T = 2.14, pFDR = 0.035). S3 showed progressive decline in digit span (T = -5.83, p = 0.021). Supervised classifiers trained on subtype and stage outperformed subtype-only and stage-only models predicting drug response in 73% ± 1.0% (vs 70% ± 1.4% and 63% ± 1.3%) and 76% ± 1.6% for Engel-I outcome (vs 71% ± 0.8% and 72% ± 1.1%), pFDR < 0.05 across all comparisons. DISCUSSION: Cross-sectional MRI-derived models provide reliable prognostic markers of TLE disease evolution, which follows distinct trajectories, each associated with divergent patterns of hippocampal and whole-brain structural alterations, as well as cognitive and clinical profiles.

Associations of Cerebral Blood Flow Patterns With Gray and White Matter Structure in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: Neuroimaging studies in patients with temporal lobe epilepsy (TLE) show widespread brain network alterations beyond the mesiotemporal lobe. Despite the critical role of the cerebrovascular system in maintaining whole-brain structure and function, changes in cerebral blood flow (CBF) remain incompletely understood in the disease. Here, we studied whole-brain perfusion and vascular network alterations in TLE and assessed its associations with gray and white matter compromises and various clinical variables. METHODS: We included individuals with and without pharmaco-resistant TLE who underwent multimodal 3T MRI, including arterial spin labelling, structural, and diffusion-weighted imaging. Using surface-based MRI mapping, we generated individualized cortico-subcortical profiles of perfusion, morphology, and microstructure. Linear models compared regional CBF in patients with controls and related alterations to morphological and microstructural metrics. We further probed interregional vascular networks in TLE, using graph theoretical CBF covariance analysis. The effects of disease duration were explored to better understand the progressive changes in perfusion. We assessed the utility of perfusion in separating patients with TLE from controls using supervised machine learning. RESULTS: Compared with control participants (n = 38; mean ± SD age 34.8 ± 9.3 years; 20 females), patients with TLE (n = 24; mean ± SD age 35.8 ± 10.6 years; 12 females) showed widespread CBF reductions predominantly in fronto-temporal regions (Cohen d -0.69, 95% CI -1.21 to -0.16), consistent in a subgroup of patients who remained seizure-free after surgical resection of the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partially constrained by gray and white matter changes (8.11% reduction in Cohen d) and topologically segregated from whole-brain perfusion networks (area under the curve -0.17, p < 0.05). Negative effects of progressive disease duration further targeted regional CBF profiles in patients (r = -0.54, 95% CI -0.77 to -0.16). Perfusion-derived classifiers discriminated patients from controls with high accuracy (71% [70%-82%]). Findings were robust when controlling for several methodological confounds. DISCUSSION: Our multimodal findings provide insights into vascular contributions to TLE pathophysiology affecting and extending beyond mesiotemporal structures and highlight their clinical potential in epilepsy diagnosis. As our work was cross-sectional and based on a single site, it motivates future longitudinal studies to confirm progressive effects, ideally in a multicentric setting.

Hippocampal activations obtained during language fMRI tasks: A complementary tool for predicting postoperative memory prognosis.

In medial temporal lobe epilepsy (MTLE), the benefits of surgery must be balanced against the risk of post-operative memory decline. Prediction of postoperative outcomes based on functional magnetic resonance imaging (fMRI) tasks is increasingly common but remains uncertain. The aim of this retrospective study was to determine whether hippocampal activations elicited by fMRI language tasks could enhance or refine memory fMRI in MTLE patients candidates to surgery. Forty-six patients were included: 30 right and 16 left MTLE, mostly with hippocampal sclerosis. Preoperative assessment included neuropsychological tests and fMRI with language (syntactic verbal fluency) and memory tasks (encoding, delayed, and immediate recognition of images of objects). Thirty patients underwent surgery and had neuropsychological evaluations one year after surgery. Worsening was defined as a degradation of more than 10 % in postoperative forgetting scores compared to preoperative scores in verbal, non-verbal and global memory. Memory fMRI had the best sensitivity with hippocampal activations obtained in 95 % of patients, versus 65 % with language fMRI. Considering the patients who elicited an hippocampal activation, language fMRI led to 80 %, 65 % and 85 % of correct predictions for respectively global, verbal and non verbal memory (versus 71 %, 64 % and 68 % with memory fMRI). Memory and language fMRI predictions outperformed those made by neuropsychological tests. In summary, language fMRI was less sensitive than memory fMRI to elicit hippocampal activations but when it did, the proportion of correct memory predictions was better. Moreover, it proved to be an independent predictive factor regardless of the side of the epileptic focus. Given the ease of setting up a language task in fMRI, we recommend the systematic combination of memory and language tasks to predict the post-operative memory outcome of MTLE patients undergoing epilepsy surgery.

Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach.

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.

Connectome-based prediction of cognitive performance in patients with temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) patients often exhibit varying degrees of cognitive impairments. This study aims to predict cognitive performance in TLE patients by applying a connectome-based predictive model (CPM) to whole-brain resting-state functional connectivity (RSFC) data. METHODS: A CPM was established and leave-one-out cross-validation was employed to decode the cognitive performance of patients with TLE based on the whole-brain RSFC. RESULTS: Our findings indicate that cognitive performance in TLE can be predicted through the internal and network connections of the parietal lobe, limbic lobe, and cerebellum systems. These systems play crucial roles in cognitive control, emotion processing, and social perception and communication, respectively. In the subgroup analysis, CPM successfully predicted TLE patients with and without focal to bilateral tonic-clonic seizures (FBCTS). Additionally, significant differences were noted between the two TLE patient groups and the normal control group. CONCLUSION: This data-driven approach provides evidence for the potential of predicting brain features based on the inherent resting-state brain network organization. Our study offers an initial step towards an individualized prediction of cognitive performance in TLE patients, which may be beneficial for diagnosis, prognosis, and treatment planning.

Quantitative cellular pathology of the amygdala in temporal lobe epilepsy and correlation with magnetic resonance imaging volumetry, tissue microstructure, and sudden unexpected death in epilepsy risk factors.

OBJECTIVE: Amygdala enlargement can occur in temporal lobe epilepsy, and increased amygdala volume is also reported in sudden unexpected death in epilepsy (SUDEP). Apnea can be induced by amygdala stimulation, and postconvulsive central apnea (PCCA) and generalized seizures are both known SUDEP risk factors. Neurite orientation dispersion and density imaging (NODDI) has recently provided additional information on altered amygdala microstructure in SUDEP. In a series of 24 surgical temporal lobe epilepsy cases, our aim was to quantify amygdala cellular pathology parameters that could predict enlargement, NODDI changes, and ictal respiratory dysfunction. METHODS: Using whole slide scanning automated quantitative image analysis methods, parallel evaluation of myelin, axons, dendrites, oligodendroglia, microglia, astroglia, neurons, serotonergic networks, mTOR-pathway activation (pS6) and phosphorylated tau (pTau; AT8, AT100, PHF) in amygdala, periamygdala cortex, and white matter regions of interest were compared with preoperative magnetic resonance imaging data on amygdala size, and in 13 cases with NODDI and evidence of ictal-associated apnea. RESULTS: We observed significantly higher glial labeling (Iba1, glial fibrillary acidic protein, Olig2) in amygdala regions compared to cortex and a strong positive correlation between Olig2 and Iba1 in the amygdala. Larger amygdala volumes correlated with lower microtubule-associated protein (MAP2), whereas higher NODDI orientation dispersion index correlated with lower Olig2 cell densities. In the three cases with recorded PCCA, higher MAP2 and pS6-235 expression was noted than in those without. pTau did not correlate with SUDEP risk factors, including seizure frequency. SIGNIFICANCE: Histological quantitation of amygdala microstructure can shed light on enlargement and diffusion imaging alterations in epilepsy to explore possible mechanisms of amygdala dysfunction, including mTOR pathway activation, that in turn may increase the risk for SUDEP.