Long‐term neuroplasticity in language networks after anterior temporal lobe resection
Bibliographic record
Abstract
OBJECTIVE: Anterior temporal lobe resection (ATLR) is an effective treatment for drug-resistant temporal lobe epilepsy (TLE), although language deficits may occur after both left and right ATLR. Functional reorganization of the language network has been observed in the ipsilateral and contralateral hemispheres within 12 months after ATLR, but little is known of longer-term plasticity effects. Our aim was to examine the plasticity of language functions up to a decade after ATLR, in relation to cognitive profiles. METHODS: We examined 24 TLE patients (12 left [LTLE]) and 10 controls across four time points: pre-surgery, 4 months, 12 months, and ~9 years post-ATLR. Participants underwent standard neuropsychological assessments (naming, phonemic, and categorical fluency tests) and a verbal fluency functional magnetic resonance imaging (fMRI) task. Using a flexible factorial design, we analyzed longitudinal fMRI activations from 12 months to ~9 years post-ATLR, relative to controls, with separate analyses for people with hippocampal sclerosis (HS). Change in cognitive profiles was correlated with the long-term change in fMRI activations to determine the "efficiency" of reorganized networks. RESULTS: LTLE patients had increased long-term engagement of the left extra-temporal and contralateral temporal regions, with better language performance linked to bilateral activation. Those with HS exhibited more widespread bilateral activations. RTLE patients showed plasticity in the left extra-temporal regions, with better language outcomes associated with these areas. Both groups of patients achieved cognitive stability over 9 years, with more than 50% of LTLE patients improving. Older age, longer epilepsy duration, and lower pre-operative cognitive reserve negatively affected long-term language performance. SIGNIFICANCE: Neuroplasticity continues for up to ~9 years post-epilepsy surgery in LTLE and RTLE, with effective language recovery linked to bilateral engagement of temporal and extra-temporal regions. This adaptive reorganization is associated with improved cognitive outcomes, challenging the traditional view of localized surgery effects. These findings emphasize the need for early intervention, tailored pre-operative counseling, and the potential for continued cognitive gains with extended post-ATLR rehabilitation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".