An EEG–MEG Dissociation between Online Syntactic Comprehension and Post Hoc Reanalysis
Bibliographic record
Abstract
Successful comprehension of syntactically complex sentences depends on online language comprehension mechanisms as well as reanalysis in working memory. To differentiate the neural substrates of these processes, we recorded electroencephalography and magnetoencephalography (MEG) during sentence-picture-matching in healthy subjects, assessing the effects of two difficulty factors: syntactic complexity (object-embedded vs. subject-embedded relative clauses) and semantic reversibility on neuronal oscillations during sentence presentation, and during a subsequent memory delay prior to picture onset. Synthetic Aperture magnetometry analysis of MEG showed that semantic reversibility induced left lateralized perisylvian power decreases in a broad frequency range, approximately 8-30 Hz. This effect followed the relative clause presentation and persisted throughout the remainder of the sentence and the subsequent memory delay period, shifting to a more frontal distribution during the delay. In contrast, syntactic complexity induced enhanced power decreases only during the delay period, in bilateral frontal and anterior temporal regions. These results indicate that detailed syntactic parsing of auditory language input may be augmented in the absence of alternative cues for thematic role assignment, as reflected by selective perisylvian engagement for reversible sentences, compared with irreversible sentences in which world knowledge constrains possible thematic roles. Furthermore, comprehension of complex syntax appears to depend on post hoc reanalysis in working memory implemented by frontal regions in both hemispheres.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".