Hemispheric decoupling of awareness-related activity in human auditory cortex under informational masking and divided attention
Bibliographic record
Abstract
Whether unattended sound streams reach perceptual awareness, and the extent to which they are represented in the central auditory system, are fundamental questions of modern hearing science. We examined these questions utilizing M/EEG, multi-tone masking, and a dual-task dichotic listening paradigm. Listeners performed a demanding primary task in one ear—detecting isochronous target-tone streams embedded in random multi-tone backgrounds and counting within-target-stream deviants—and retrospectively reported their awareness of similar masker-embedded targets in the other ear. Irrespective of attention or stimulation ear, left-AC activity strongly covaried with target-stream detection starting as early as 50 ms post-stimulus. In contrast, right-AC activity, while highly sensitive to stimulation ear, was unmodulated by detection until later, and then only weakly. Thus, under certain conditions, human ACs can functionally decouple, such that one—here, right—is automatic and stimulus-driven while the other—here, left—supports perceptual and/or task demands, including basic perceptual awareness of nonverbal sounds both within and outside the focus of top-down selective attention.
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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 | 0.001 |
| 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".