Review: Neurodegenerative processes in temporal lobe epilepsy with hippocampal sclerosis: Clinical, pathological and neuroimaging evidence
Bibliographic record
Abstract
Cognitive decline is increasingly described as a co-morbidity of temporal lobe epilepsy (TLE). Mechanisms underlying cognitive impairment are not fully understood despite examining clinical factors, such as seizure frequency, and cellular mechanisms of excitotoxicity. We review the neuropsychometry evidence for progressive cognitive decline and examine the pathology and neuroimaging evidence supporting a neurodegenerative process in hippocampal sclerosis (HS)-related TLE. Accelerated cognitive decline is described in groups of adult HS-related TLE patients. Large childhood studies show early onset of seizures result in poor development of verbal memory and a hindrance in achieving cognitive potential. We discuss HS classification according to different patterns of neuronal loss and correlation to post-temporal lobectomy cognitive outcomes in refractory TLE patients. Factors such as lateralization of HS pathology, neuronal density and subtype have correlated to cognitive outcomes with varying significance between different studies. Furthermore, alterations in neuronal maturity, regenerative capacity and aberrant connectivity appear to affect cognitive performance post-operatively suggesting a complex multifactorial process. More recent studies have identified tau pathology being present in HS-related TLE and correlated to post-operative cognitive decline in some patients. A traumatic head injury-related or novel tauopathy has been hypothesized as an underlying process. We discuss the value of prospective and cross-sectional imaging in assessing cognition and review volumetric magnetic resonance studies with progressive ipsilateral hippocampal atrophy identified to correlate with seizure frequency. Finally, we consider the use of positron emission tomography biomarkers, such as tau tracers, and connectivity studies that may examine in vivo pathways and further explore cognitive decline in TLE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".