Evidence for Somatosensory Facilitation during Object Reception and Action Observation
Bibliographic record
Abstract
Previous research on somatosensory and tactile processing related to movement has focused on somatosensory and tactile suppression as well as the modulating factors that contribute to this suppression. However, there is a large discrepancy between the understanding of the factors that influence somatosensory and tactile suppression vs. the factors that influence somatosensory and tactile facilitation. Therefore, the aim of the dissertation was to unravel some of the factors related to the facilitation of somatosensory and tactile processing. Study 1 specifically addressed whether the expectation of tactile feedback utilization would lead to tactile facilitation during an object reception task. The results showed that tactile perception was improved as the object approached an individual’s hand and even when the individual only had the expectation of contact (i.e., when the object unexpectedly stopped short of the hand). Study 2 specifically addressed whether observed moment speed influenced tactile processing during action observation. The results showed that tactile perception was improved when observing slow reaching and grasping movements but not when observing higher movement speeds. Study 3 specifically addressed whether somatosensory processing was influenced by the speed of observed social touch interactions. The results showed that the difference in the speed of the interaction led to a greater change in somatosensory processing when observing ball-to-hand vs. ball-to-leaf-contact. Overall, the dissertation provides novel evidence for the facilitation of somatosensory and tactile processing in anticipation of tactile feedback utilization, with kinematics as a modulating factor when observing action and social touch interactions.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".