Effective tactile noise can decrease luminance modulated thresholds
Bibliographic record
Abstract
The multisensory FULCRUM principle describes a ubiquitous phenomenon in humans [1,2]. This principle can be interpreted within an energy and frequency model of multisensory neurons' spontaneous activity. In this context, the sensitivity transitions represent the change from spontaneous activity to a firing activity in multisensory neurons. Initially the energy and frequency content of the multisensory neurons' activity (supplied by a weak signal) is not enough to be detected but when the facilitation signal (for example auditory noise or another deterministic signal) enters the brain, it generates a general activation among multisensory neurons of different regions, modifying their original activity. The result is an integrated activation that promotes sensitivity transitions and the signals are then perceived. For instance, by using psychophysical techniques we demonstrate that auditory or tactile noise can enhance the sensitivity of visual system responses to weak signals. Specifically, we show that the effective tactile noise significantly decreased luminance modulated visual thresholds. Because this multisensory facilitation process appears universal and a fundamental property of sensory/perceptual systems, we will call it the multisensory FULCRUM principle. A fulcrum is one that supplies capability for action and we believe that this best describes the fundamental principle at work in these multisensory interactions. [1] Lugo E, Doti R, Faubert J (2008) Ubiquitous Crossmodal Stochastic Resonance in Humans: Auditory Noise Noise Facilitates Tactile, Visual and Proprioceptive Sensations. PLoS ONE 3(8): e2860. doi:10.1371/journal.pone.0002860 [2] Lugo J E, Doti R, Wittich W, Faubert J (2008) Multisensory Integration: Central processing modifies perypheral systems. Psychological Science 19 (10): 989-999.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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".