MEG correlates of speech planning in simple vs. interactive picture naming in children and adults
Bibliographic record
Abstract
The picture naming task is common both as a clinical task and as a method to study the neural bases of speech production in the healthy brain. However, this task is not reflective of most naturally occurring productions, which tend to happen within a context, typically in dialogue in response to someone else's production. How the brain basis of the classic "confrontation picture naming" task compares to the planning of utterances in dialogue is not known. Here we used magnetoencephalography (MEG) to measure neural activity associated with language production using the classic picture naming task as well as a minimal variant of the task, intended as more interactive or dialogue-like. We assessed how neural activity is affected by the interactive context in children, teenagers, and adults. The general pattern was that in adults, the interactive task elicited a robust sustained increase of activity in frontal and temporal cortices bilaterally, as compared to simple picture naming. This increase was present only in the left hemisphere in teenagers and was absent in children, who, in fact, showed the reverse effect. Thus our findings suggest a robustly bilateral neural basis for the coordination of interaction and a very slow developmental timeline for this network.
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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 | 0.002 |
| 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".