Onset timing of letter processing in auditory and visual sensory cortices
Bibliographic record
Abstract
Here, we report onset latencies for multisensory processing of letters in the primary auditory and visual sensory cortices. Healthy adults were presented with 300-ms visual and/or auditory letters (uppercase Roman alphabet and the corresponding auditory letter names in English). Magnetoencephalography (MEG) evoked response generators were extracted from the auditory and visual sensory cortices for both within-modality and cross-sensory activations; these locations were mainly consistent with functional magnetic resonance imaging (fMRI) results in the same subjects. In the primary auditory cortices (Heschl's gyri) activity to auditory stimuli commenced at 25 ms and to visual stimuli at 65 ms (median values). In the primary visual cortex (Calcarine fissure) the activations started at 48 ms to visual and at 62 ms to auditory stimuli. This timing pattern suggests that the origins of the cross-sensory activations may be in the primary sensory cortices of the opposite modality, with conduction delays (from one sensory cortex to another) of 17-37 ms. Audiovisual interactions for letters started at 125 ms in the auditory and at 133 ms in the visual cortex (60-71 ms after inputs from both modalities converged). Multivariate pattern analysis suggested similar latency differences between the sensory cortices. Combined with our earlier findings for simpler stimuli (noise bursts and checkerboards), these results suggest that primary sensory cortices participate in early cross-modal and interaction processes similarly for different stimulus materials, but previously learned audiovisual associations and stimulus complexity may delay the start of the audiovisual interaction stage.
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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) | 0.003 | 0.001 |
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".