Memory Deficits after Resection from Left or Right Anterior Temporal Lobe in Humans: A Meta‐Analytic Review
Bibliographic record
Abstract
PURPOSE: Memory deficits in epileptic patients have been found in some, but not all studies assessing the effects of side of seizures and resection from a temporal lobe on cognitive performance. The purpose of this study was to provide a quantitative review of previous studies on this issue. METHODS: Based on conventional meta-analytic procedures, we identified 33 studies that assessed verbal and nonverbal memory performance before and after anterior temporal lobectomy. The Logical Memory and Visual Reproduction subtests from the Wechsler Memory Scale were used. These studies were then subjected to two levels of analyses: (a) vote-counting procedure, and (b) effect-size calculations and comparisons. RESULTS: Overall, the data confirmed previous findings that verbal memory tasks are sensitive to left hemisphere dysfunction. The efficacy of a "nonverbal" task for tapping function in the nondominant (right) hemisphere was not confirmed, although a trend supporting this speculation was observed. With regard to the comparison of changes in verbal and nonverbal memory before and after resection from a temporal lobe, a clear trend was observed for decline in verbal memory function after resection from the left, especially significant for immediate verbal recall. A trend for contralateral improvement on nonverbal memory also was observed. The pattern of memory change after resection from the right temporal lobe was less clear. CONCLUSIONS: The findings of this study suggest that side of epileptic seizure and surgical resection from a temporal lobe affect verbal memory functions. The relations between the laterality of epileptic seizure, surgical resection from the temporal lobe, and nonverbal memory are to be verified by further research.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.015 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".