Speech and lexico-semantic errors during direct cortical stimulation mapping of the language-dominant hemisphere: effects of object and action naming
Bibliographic record
Abstract
OBJECTIVE: In this retrospective study, the authors aimed to establish the stereotactically defined probability distribution for speech (i.e., anarthria, speech arrest) and lexico-semantic errors (i.e., anomia) through direct cortical stimulation (DCS) by using two tasks: action naming and object naming. They also analyzed the patterns of interindividual variability in the localization of the language sites involved, and investigated whether any patient or lesion location factors were associated with greater variability. METHODS: Eighty-one Italian-speaking patients who underwent awake surgery between 2010 and 2021 for low- and high-grade gliomas in eloquent areas of the language-dominant hemisphere were entered in the analyses. The intraoperative DCS protocol included automatic speech tasks, object naming, and action naming. The position of the tags, as depicted on the intraoperative video or photograph, was transposed into Montreal Neurological Institute space. Subsequently, a 2D scatterplot and cluster analysis were performed. Associations between various clinical and radiological characteristics and the quantity of positive stimulated sites were determined by univariate analyses using binary logistic regression. Associated variables (p < 0.2) were included in stepwise multivariate logistic regression with backward elimination (p < 0.05). RESULTS: A total of 1380 cortical sites were stimulated, with a positive response in 511 cases (37%). Most anarthric errors were triggered when stimulating the left precentral gyrus, and most speech arrest errors were elicited when stimulating the left posterior inferior frontal gyrus. Anomias were found in the left inferior frontal gyrus and in the posterior part of the left temporal lobe for object naming. DCS to the left dorsal premotor cortex elicited anomic errors for action naming. Anomias were also elicited during DCS to the left posterior temporal lobe, with both object and action naming. CONCLUSIONS: The distribution of speech and lexico-semantic errors is in line with the current literature. The action-naming results are new and mostly involve the dorsal premotor cortex. These findings stress the importance of maximizing the use of different language tasks during surgery, because even when looking for the same type of errors, different tasks may be better suited to map specific brain regions. DCS with action and object naming identifies more positive sites than object naming alone.
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 | 0.002 |
| 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".