Long-term memory plasticity in a decade-long connectivity study post anterior temporal lobe resection
Bibliographic record
Abstract
Approximately 40% of individuals undergoing anterior temporal lobe resection for temporal lobe epilepsy experience episodic memory decline. There has been a focus on early memory network changes; longer-term plasticity and its impact on memory function are unclear. Our study investigates neural mechanisms of memory recovery and network plasticity over nearly a decade post-surgery. We assess memory network changes, from 3-12 months to 10 years postoperatively, in 25 patients (12 left-sided resections) relative to 10 healthy matched controls, using longitudinal task-based functional MRI and standard neuropsychology assessments. We observe key adaptive changes in memory networks of a predominantly seizure-free cohort. Ongoing neuroplasticity in posterior medial temporal regions and contralesional cingulum or pallidum contribute to long-term verbal and visual memory recovery. Here, we show the potential for sustained cognitive improvement and importance of strategic approaches in epilepsy treatment, advocating for conservative surgeries and long-term use of cognitive rehabilitation for ongoing recovery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".