A multimodal fusion framework reveals the heterogeneity of basal ganglia atrophy and its molecular mechanisms in temporal lobe epilepsy.

Individual 18F-FDG PET and arterial spin labeling coupling based on simultaneous PET/MRI predicting anti-seizure medication response in temporal lobe epilepsy patients.

Epilepsy patients face significantly elevated cardiovascular risks, with cardiac arrhythmias occurring 2-3 times more frequently than in the general population. Current knowledge of brain-heart functional coupling abnormalities in epilepsy, particularly during interictal periods, remains limited. We investigated brain-heart interplay characteristics in temporal lobe epilepsy through synchronized electroencephalographic-electrocardiographic analysis using a synthetic data generation model and microstate analysis. We enrolled 52 patients with temporal lobe epilepsy (mean age = 33.4 ± 12.7 years) and 42 age-matched healthy controls (mean age = 31.95 ± 11.03 years). Twenty-minute artifact-free electroencephalographic segments were analyzed during resting states. Four directional brain-heart coupling sequences were extracted: CBrain→HF, CBrain→LF, CHF→Brain, and CLF→Brain, representing bidirectional interactions between brain activity and cardiac components. Six microstate topologies were consistently identified across all brain-heart interplay sequences, with temporal lobe epilepsy patients demonstrating significantly more complex and unstable topological characteristics compared to healthy controls. For CBrain→HF coupling, patients exhibited significantly reduced mean duration of microstate 3 (.34 ± .09 s vs. .38 ± .07 s, p = .02), increased occurrence rates of microstates 3 and 4 (both p < .001), and altered temporal coverage patterns. Similar abnormalities were observed across all sequences, with patients showing shortened microstate durations, altered occurrence rates, and disrupted temporal coverage. Spatial dissimilarity analysis revealed significant topological abnormalities across all microstates. A logistic regression model incorporating microstate parameters achieved 94.7% diagnostic accuracy for temporal lobe epilepsy, with an F1 score of .952 and an area under the curve of .932. Temporal lobe epilepsy is characterized by profound disruptions in brain-heart functional coupling during interictal periods, manifesting as altered microstate topographies and temporal dynamics. These findings establish microstate-based analysis as a promising framework for characterizing brain-heart axis dysfunction in epilepsy.

Validation and Normative Data of a Modified Autobiographical Interview for Use in Taiwanese Patients with Temporal Lobe Epilepsy: A Preliminary Study.

Previous PET studies with [18F]FCWAY were modeled with a 120-min kinetic analysis, using arterial input function with corrections for uptake of the metabolite [18F]fluorocyclohexanecarboxylic acid ([18F]FC) and vascular activity. We evaluated whether logistically less demanding analysis approaches can be used as alternatives to the full analysis. Dynamic frames were acquired for 120-min in 13 temporal lobe epilepsy (TLE) patients and 10 controls, and modeled with a simplified 3-parameter 2-tissue compartment. The gold standard binding index was BPF. Images were also generated with a 90-min (BPF_90) and 60-min (BPF_60) data analysis interval, without correction for [18F]FC (BPF_NOFC) and without neither [18F]FC correction nor vascular correction (BPND_NOFCVA). fP was significantly higher in patients than in controls. BPF_NOFC had very similar statistical power as BPF, except in the raphe where the effect size of BPF_NOFC was about 40% lower than that of BPF. BPND_NOFCVA had poorest performance. Negligible loss of statistical significance in detected differences occurred in the cortex with both BPF_90 and BPF_60, but BPF_60 was associated with some time instability in the raphe. PET scans can be reduced to 90-min in future, arterial line-based, TLE studies. Lack of correction for [18F]FC mildly reduced the statistical power only in the raphe.

Optimization of memory neurofeedback system utilizing intracranial electroencephalogram of the hippocampus.

Outcomes of surgically and non-surgically managed temporal encephalocoeles in the context of drug-resistant temporal lobe epilepsy: A retrospective single-centre case series.

Temporal lobe epilepsy (TLE) is the most common pharmacoresistant epilepsy in adults, yet few patients receive curative surgery due to diagnostic and prognostic uncertainty. In a multicenter cohort, we analyzed multimodal MRI and clinical data from 282 TLE patients, 298 healthy controls, and 45 disease controls. Patient-specific deviations from typical lifespan trajectories of intrinsic brain function were mapped using normative modeling. Regional functional alterations were heterogeneous but overlapped most in the mesiotemporal cortex. Connectome-based simulations revealed abnormality spread followed structural network architecture, highlighting the hippocampus as well as paralimbic and medial default-mode regions as epicenters. Multimodal integration implicated superficial white-matter microstructural alterations as a key contributor. Supervised models achieved AUCs of 0.77 for distinguishing TLE from disease controls, 0.74 for lateralizing seizure focus, and 0.64 for predicting postsurgical seizure freedom; greater contralateral temporal deviations predicted poorer outcomes. These findings support individualized functional biomarkers for precision presurgical care in focal epilepsy.

About 30% of temporal lobe epilepsy (TLE) cases are negative on MRI, so quantitative diagnosis based on clinical symptoms becomes challenging. There is an urgent need for an accurate and reliable method to differentiate patients with MRI-negative TLE from healthy individuals. This study aimed to explore the use of machine learning methods to diagnose MRI-negative TLE patients based on single and combined resting-state fMRI (rs-fMRI) metrics. This study investigates the diagnostic implications of using both singular and composite resting-state fMRI (rs-fMRI) indices in patients with MRI-negative TLE. We carried out a retrospective analysis of the clinical data and rs-fMRI data of 90 patients with MRI-negative TLE and 90 healthy controls (HCs). Next, the participants were divided into a training set and a test set at 8:2. Functional indices extracted from each brain region included degree centrality (DC), voxel-mirrored homotopic connectivity (VMHC), regional homogeneity (ReHo), fractional amplitude of low-frequency fluctuations (fALFF), and amplitude of low-frequency fluctuations (ALFF). A two-sample t-test was utilized to select significant voxels. After this, classification models based on individual rs-fMRI indices and combined rs-fMRI indices were constructed using ML algorithms such as support vector machines (SVM), random forests (RF), and logistic regression (LR) on the training set. Model performance was evaluated using metrics such as specificity, the area under the receiver operating characteristic curve (AUC), sensitivity, and accuracy, and validations were performed on the test set. Lastly, the feature contribution was assessed using Shapley Additive explanations (SHAP) values. The SVM model employing a combination of rs-fMRI functional indices had optimal performance. On the test set, this model achieved an AUC of 0.89, with an accuracy rate of 82%, where the ALFF values from the cerebellum contributed most significantly to the model. In contrast, ML models based on individual rs-fMRI indices demonstrated inferior classification performance, whereas the RF model using the DC index had the lowest accuracy of 47% on the test set. The SVM model combining the fMRI indices has the greatest potential to distinguish between MRI-negative temporal lobe epilepsy patients and healthy individuals, suggesting a complementary role for the classification of resting-state fMRI indices.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-18146-z.

One third of epilepsy patients do not achieve sufficient seizure freedom with current standard anti-seizure medications. Better understanding of the pathological mechanisms contributing to epileptogenesis is thus necessary to improve current therapies. SUR1-TRPM4 is a depolarizing ion channel minimally expressed in healthy brain that is upregulated de novo in neurons and glia after epileptogenic CNS injuries such as traumatic brain injury and stroke. However, its role in epilepsy is not well understood. Here, we demonstrate using immunofluorescent microscopy that SUR1-TRPM4 expression is elevated in neurons within electrographically sorted human epileptic brain compared to non-epileptic brain obtained after resection from six drug-resistant temporal lobe epilepsy patients. Additionally, we utilized immunofluorescence and co-immunoprecipitation to observe that SUR1-TRPM4 is upregulated within the hippocampus and temporal cortex in mice after PTZ kindling, a chronic model of rodent epilepsy. Pharmacologic inhibition of SUR1-TRPM4 using either the FDA-approved drug glyburide or 9-phenanthrol, as well as either constitutive or neuron-specific knock-out of this channel, attenuated chronic seizure development in this model. Exogenous overexpression of SUR1-TRPM4 by plasmid transfection in neurons in vitro increased neuronal hyperexcitability in response to low Mg2+ stimulation, while pharmacologic inhibition of endogenous TRPM4 attenuated neuronal population hyperexcitation. Collectively, our results reveal that elevated SUR1-TRPM4 expression found in human and rodent epileptic neurons promotes chronic seizures by increasing neuronal excitation. These findings directly support clinical investigation of SUR1-TRPM4 inhibitors as potential anti-seizure therapies in epilepsy patients and suggest further investigations into the contribution of SUR1-TRPM4 to seizures induced by specific epileptogenic insults, such as TBI, are warranted.

This study aimed to investigate the diagnostic value of combined glutamate chemical exchange saturation transfer (GluCEST) imaging and γ-aminobutyric acid (GABA)-edited proton magnetic resonance spectroscopy (1H-MRS) in localizing epileptogenic foci and differentiating drug-resistant epilepsy (DR) from drug-responsive epilepsy (DRES) in temporal lobe epilepsy (TLE) using 5T MRI.Twenty-four TLE patients (13 left, 11 right) and 25 age-/gender-matched healthy controls (HCs) underwent GluCEST and MEGA-PRESS MRS at 5T MRI. Directional asymmetry indices (DAIglu_H for hippocampus, DAIglu_A for amygdala) and a novel composite biomarker (DAIglu_GABA) integrating GluCEST asymmetry and GABA/Cr ratios were analyzed. Another asymmetry metric was employed to discriminate the left and right TLE groups [DAIglu_H(epi) for hippocampus, DAIglu_A(epi) for amygdala]. Subgroup comparisons (HC vs. DR vs. DRES) and receiver-operating characteristic (ROC) analyses were performed.ResultsGluCEST-derived hippocampal asymmetry [DAIglu_H(epi)] effectively lateralized epileptogenic foci (AUC = 0.86). The DRES patients exhibited elevated DAIglu_H (adjusted p < 0.001) and reduced GABA/Cr (adjusted p = 0.015) compared to HCs. The DAIglu_GABA index increased in the DRES subgroup compared to HCs (adjusted p < 0.001). Moreover, DAIglu_GABA levels were found to be significantly lower in the DR subgroup in comparison to the DRES subgroup (adjusted p = 0.009).ConclusionMultimodal 5T MRI integrating GluCEST and GABA-MRS provides a clinically feasible tool for lateralizing epileptogenic foci and stratifying drug resistance in TLE. The observed excitatory-inhibitory imbalance dynamics suggest distinct neurometabolic profiles underlying DR and DRES, advancing personalized therapeutic strategies.

SCN1A rs3812718 polymorphism modulates structural and functional brain networks in TLE: A multimodal imaging-genomics study.

Facial emotion recognition in focal epilepsy: localization is not the main factor.

Language impairment in temporal lobe epilepsy: insights from a meta-analysis of fMRI studies.

A pilot study of inter-regional phase amplitude coupling as comorbid depression biomarker in temporal lobe epilepsy.

Isolated hippocampal sclerosis and focal dysplasia type IIIa: Comparative study of anatomo-electro-clinical profile and seizure outcome.

Alternations in static and dynamic functional connectivity density in temporal lobe epilepsy with and without hippocampal sclerosis.

ObjectiveThis study aims to evaluate the glymphatic system (GS) in different temporal lobe epilepsy (TLE) subtypes using diffusion tensor imaging analysis along the perivascular space (DTI‐ALPS) and to explore its correlation with clinical factors and memory performance.MethodsThe study encompassed 112 TLE patients with hippocampal sclerosis (TLE‐HS), 73 TLE patients with no lesions on magnetic resonance imaging (TLE‐NL), and 55 healthy controls. The DTI‐ALPS index was calculated based on 3.0T diffusion tensor image sequences, and the memory performance was assessed using the Wechsler Memory Scale‐Revised. The DTI‐ALPS index was compared among the three groups, and its relationships with clinical characteristics and memory performance were explored.ResultsTLE‐HS group showed a significantly lower DTI‐ALPS index compared with healthy controls in both hemispheres (ipsilateral: p < 0.001; contralateral: p = 0.002). By contrast, TLE‐NL group exhibited a reduced DTI‐ALPS index solely in the ipsilateral hemisphere (p < 0.001). Within TLE‐NL cohort, those with a history of focal to bilateral tonic–clonic seizures showed reduced DTI‐ALPS indices in both hemispheres (ipsilateral: p = 0.037; contralateral: p = 0.004). In the TLE‐HS group, DTI‐ALPS index positively correlated with memory performance (ps < 0.05). A multiple regression analysis indicated that the average DTI‐ALPS index was significantly associated with memory quotient (β = 0.309, p < 0.001; R2 = 0.226), independent of the ipsilateral hippocampal volume.SignificanceThe patterns of reduced DTI‐ALPS index differed between TLE‐HS and TLE‐NL patients. The extent of GS impairment in TLE‐HS patients correlated with memory decline, suggesting its potential as a therapeutic target for memory enhancement.Plain Language SummaryThis study employed the DTI‐ALPS index, a neuroimaging marker, to assess glymphatic system function in distinct subtypes of temporal lobe epilepsy (TLE). Glymphatic impairment was observed in both TLE with hippocampal sclerosis (TLE‐HS) and nonlesional TLE (TLE‐NL), exhibiting distinct patterns. Notably, this dysfunction was associated with memory deficits, suggesting that targeting glymphatic clearance may represent a novel therapeutic strategy for memory improvement in epilepsy.

Developmental epileptic encephalopathies (DEEs) are epilepsy conditions characterized by significant severity and treatment challenges. Spectral components of the encephalogram (EEG) may provide a valuable biomarker of epileptic severity. Features of this signal include alterations in power spectral density, interictal epileptiform discharges, and high-frequency oscillations (HFOs). These findings largely derive from temporal lobe epilepsy patients and rodent models. Evidence for altered spectral EEG components in preclinical DEE models is rare. Here, we analyzed electrophysiology data from zebrafish genetically engineered to mimic human DEE conditions. Local field potential (LFP) recordings from six zebrafish mutant lines (arxa, gabrb3, grin1b, pnpo, scn1lab, and strada) with recurrent ictal-like epileptiform discharges were analyzed. HFOs were identified using an automated MATLAB program (RippleLab). Fast Fourier transformations and analysis of interictal epileptiform discharges (IEDs) were also performed using MATLAB software. Fast Fourier transform analysis of LFP signals revealed increased power in the delta frequency band (0.5-3.5 Hz) for scn1lab, grin1b, and gabrb3 mutant lines. We also report the consistent presence of HFO events (>250 Hz) and altered IED dynamics in arxa, gabrb3, grin1b, pnpo, scn1lab, and strada mutant lines. This study provides compelling evidence that spectral signatures of abnormal brain activity commonly observed in humans can be recapitulated in larval zebrafish. These electrical events in zebrafish could serve as important biomarkers. These observations not only reinforce the value of zebrafish as an important preclinical animal model for epilepsy research but also suggest new avenues for deconstruction of pathological epileptic networks in an experimental setting.

Temporal lobe epilepsy (TLE) is a common and often drug-resistant neurological disorder, presenting a major clinical challenge due to the limited effectiveness of current therapies. There is a pressing need to identify novel molecular targets to improve treatment outcomes. This study focuses on Pyk2, a calcium-sensitive non-receptor tyrosine kinase implicated in neuronal signalling and excitability. Given its abundant neural expression and synaptic role, the research investigates Pyk2's spatio-temporal activity and phosphorylation in mesial TLE (MTLE) patients and in a lithium-pilocarpine rat model across acute and chronic stages. Using techniques such as western blotting, qRT-PCR, kinase assays, and FACS, the study also explores the impact of PF-4,618,433, a pharmacological Pyk2 inhibitor. Elevated phosphorylation of Pyk2 at Tyr402 was observed in MTLE patient hippocampi and temporal lobes, correlating with increased intracellular calcium. In rats, Pyk2 activation displayed stage- and region-specific changes, notably extending to cortical areas in chronic TLE. Inhibition of Pyk2 reduced its activity, significantly lowering seizure frequency and intensity. These findings suggest that calcium-driven, temporally regulated Pyk2 activation contributes to TLE pathology. Targeting Pyk2 may represent a promising therapeutic strategy, offering potential for seizure mitigation and network remodeling. Further research is needed to assess long-term effects and refine clinical applications.