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Epilepsy, Temporal Lobe

Epilepsy, Temporal Lobe: explore 2 source-linked works published from 2026 to 2026, with original documents and citations.

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Granger connectivity and graph-theoretical analysis of scalp EEG across the preictal to ictal transition for presurgical evaluation.

OBJECTIVE: To assess the feasibility of estimating lateralization and localization of the epileptogenic zone (EZ) in temporal and extratemporal lobe epilepsy by combining Electric Source Imaging (ESI) with functional connectivity analysis of high-density EEG from the preictal to the ictal phase. METHODS: Adults with drug-resistant focal epilepsy and at least one recorded seizure during 40- or 64 channels EEG monitoring were retrospectively included. Granger causality and hubness centrality were computed over the 10-s preictal interval and the first 5 s of the ictal period, with ictal onset defined as the first EEG change identified by experienced epileptologists. The reference standard for EZ localization was based on resective surgical outcome or stereo-EEG findings. RESULTS: Thirteen patients (7 females; median age 35 years) were included. Connectivity analyses showed higher concordance with clinical findings during the preictal phase than during the ictal phase for both lateralization (91% vs 46%) and localization (73% vs 27%). Performance was highest in temporal (7/7 lateralization; 6/7 localization) and frontal lobe epilepsy (2/2 for both), and lower in parieto-occipital epilepsy (1/2 and 0/2, respectively). In two cases with poor surgical outcome or no surgical indication, connectivity findings were discordant with clinical estimates. CONCLUSIONS: Connectivity analysis across the preictal to ictal transition provides relevant lateralizing and localizing information, particularly in temporal and frontal lobe epilepsy, and may reveal clinically meaningful discordance. SIGNIFICANCE: Integrating high-density EEG, ESI, and functional connectivity during the phase preceding the first EEG change may support non-invasive presurgical evaluation.

Humans

Cognitive-metabolic relationship in temporal lobe epilepsy: A systematic review.

OBJECTIVE: To summarize the current literature on neurometabolic dysfunction identified through brain imaging and its cognitive correlates in temporal lobe epilepsy (TLE). BACKGROUND: Cognitive decline contributes to chronic disability in TLE. The pathophysiology of cognitive decline in TLE is poorly understood, limiting therapeutic advances. Characterizing metabolic changes in patients with TLE and cognitive impairment may identify biomarkers and inform new treatment strategies. DESIGN/METHODS: We conducted a systematic review of five major databases, gathering studies published through December 2024, in accordance with PRISMA guidelines. We included all observational studies describing associations between metabolic imaging findings and cognitive measures in TLE. RESULTS: Of 1449 reports, 38 met the inclusion criteria, encompassing 1161 patients with TLE aged 5-66 years. Twenty-two studies applied fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) to assess interictal brain glucose metabolism. Two studies utilized PET with other tracers to assess more specific metabolic aspects. Fourteen studies used proton magnetic resonance spectroscopy (1H-MRS) to quantify local concentrations of brain metabolites. Impairment of verbal memory was consistently associated with left temporal lobe metabolite changes. Non-memory cognitive impairments correlated with changes in glucose metabolism, N-acetylaspartate, and gamma-aminobutyrate in both temporal and extratemporal areas. CONCLUSION: 18F-FDG PET remains the most widely used imaging modality to assess cognitive-metabolic correlates in TLE, while other PET tracers and 1H-MRS are potentially underexplored. Verbal memory impairment correlates robustly with left temporal dysmetabolism. Cognitive impairment in TLE is multifaceted and correlates with measurable changes in metabolism in both temporal and extratemporal regions. While our synthesis was restricted by some methodological limitations, these neurometabolic signatures may hold promise as potential biomarkers for identifying risk of cognitive decline and highlight avenues for future research.

Humans
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