Somatosensory Integration and Masking of Complex Tactile Information: Peripheral and Cortical Contributions
Bibliographic record
Abstract
Nerve paresthesia is a sensory impairment experienced in clinical conditions such as diabetes. Paresthesia may "mask" or "compete" with meaningful tactile information in the patient's sensory environment. The two objectives of the present study were: (1) to determine if radiating paresthesia produces a peripheral mask, a central mask, or a combination; (2) to determine if a response competition experimental design reveals changes in somatosensory integration similar to a masking design. Experiment 1 assessed the degree of masking caused by induced radiating ulnar nerve paresthesia (a concurrent non-target stimulus) on a vibrotactile Morse code letter acquisition task using both behavioral and neurophysiological measures. Experiment 2 used a response competition design by moving the radiating paresthesia to the median nerve. This move shifted the concurrent non-target stimulus to a location spatially removed from the target stimuli. The task, behavioral and neurophysiological measures remained consistent. The induced paresthesia impacted letter acquisition differentially depending on the relative location of meaningful and non-meaningful stimulation. Paresthesia acted as a peripheral mask when presented to overlapping anatomical stimulation areas, and a central mask when presented at separate anatomical areas. These findings are discussed as they relate to masking, subcortical, and centripetal gating.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".