Detection of Sounds in the Auditory Stream: Event-Related fMRI Evidence for Differential Activation to Speech and Nonspeech
Bibliographic record
Abstract
The detection of speech in an auditory stream is a requisite first step in processing spoken language. In this study, we used event-related fMRI to investigate the neural substrates mediating detection of speech compared with that of nonspeech auditory stimuli. Unlike previous studies addressing this issue, we contrasted speech with nonspeech analogues that were matched along key temporal and spectral dimensions. In an oddball detection task, listeners heard nonsense speech sounds, matched sine wave analogues (complex nonspeech), or single tones (simple nonspeech). Speech stimuli elicited significantly greater activation than both complex and simple nonspeech stimuli in classic receptive language areas, namely the middle temporal gyri bilaterally and in a locus lateralized to the left posterior superior temporal gyrus. In addition, speech activated a small cluster of the right inferior frontal gyrus. The activation of these areas in a simple detection task, which requires neither identification nor linguistic analysis, suggests they play a fundamental role in speech processing.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".