Feel sounds with your hands: Exploring tactile frequency-following response
Bibliographic record
Abstract
Auditory perception is often influence by other senses. Prior studies have documented that the auditory cortex can respond to vibration, but the nature of this neural response remains unclear. The frequency-following response (FFR) is a non-invasive evoked brain response that can be used to study the fidelity of periodicity encoding of complex sounds. The main goal of this study was to investigate if tactile processing of sounds retains periodicity information as measured by the FFR. We acquired electroencephalography while participants were presented with repetitions of a synthesized speech syllable /da/ under three conditions (Auditory, Tactile, and both). A technology developed within our laboratory (Multichannel Vibrotactile Glove) was used to present sounds to all fingers. Results reveal that it is possible to measure a tactile FFR using vibrotactile stimulation, which is similar to the auditory FFR, but exhibits somewhat different characteristics as compared to unimodal auditory FFR, including lower amplitude and no sensitivity to harmonics. These findings suggest that these modalities interact, opening up questions about the origins and pathways responsible for the phenomena and introduces potential uses of tactile perception to mitigate the effect of hearing loss in speech and music perception.
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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 | 0.000 |
| 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 | 0.000 |
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".