Auditory noise can facilitate low-level visual processing
Bibliographic record
Abstract
It has been shown that the Stochastic Resonance (SR) phenomenon occurs in different macro, micro and nano systems. From the cyclic recurrence of ice ages, bistable ring lasers, electronic circuits, superconducting quantum interference devices and neurophysiological systems such as receptors in animals. It has been extended to human sensory systems such as auditory, visual, proprioceptive and tactile mechanisms. Regardless of the demonstration of its presence in human sensory systems, there have been no direct demonstrations of cross-modal SR-based interactions in the human cortex. Here we report evidence of cortically based cross-modal effects of stochastically induced transitions. In previous experiments we demonstrated that introducing auditory noise significantly improved tactile sensations of the finger and EMG recordings of the leg muscles and the sweep area of stabilograms during posture maintenance. In the present experiments we presented different levels of auditory broadband noise while observers discriminated between vertical or horizontal luminance and contrast defined sinusoidal gratings. As in our previous auditory-tactile or auditory-proprioceptive experiments, the visual sensitivity profiles of the observers varied as a function of the different auditory noise levels demonstrating a typical SR function with zones of sensitivity values significantly different from baseline (no auditory noise condition). Our results show clear evidence that a stochastic synchronization-like phenomenon is present in the human cortex and that the added signals act upon the multi-sensory integration system creating a state that enhances functionality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".