During Visual Word Recognition, Phonology Is Accessed within 100 ms and May Be Mediated by a Speech Production Code: Evidence from Magnetoencephalography: Figure 1.
Bibliographic record
Abstract
Debate surrounds the precise cortical location and timing of access to phonological information during visual word recognition. Therefore, using whole-head magnetoencephalography (MEG), we investigated the spatiotemporal pattern of brain responses induced by a masked pseudohomophone priming task. Twenty healthy adults read target words that were preceded by one of three kinds of nonword prime: pseudohomophones (e.g., brein-BRAIN), where four of five letters are shared between prime and target, and the pronunciation is the same; matched orthographic controls (e.g., broin-BRAIN), where the same four of five letters are shared between prime and target but pronunciation differs; and unrelated controls (e.g., lopus-BRAIN), where neither letters nor pronunciation are shared between prime and target. All three priming conditions induced activation in the pars opercularis of the left inferior frontal gyrus (IFGpo) and the left precentral gyrus (PCG) within 100 ms of target word onset. However, for the critical comparison that reveals a processing difference specific to phonology, we found that the induced pseudohomophone priming response was significantly stronger than the orthographic priming response in left IFG/PCG at approximately 100 ms. This spatiotemporal concurrence demonstrates early phonological influences during visual word recognition and is consistent with phonological access being mediated by a speech production code.
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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 | 0.001 |
| 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) | 0.002 | 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".