I felt that: Do the kinematics of social touch influence somatosensory processing?
Bibliographic record
Abstract
Social touch refers to the sensory processes related to the observation of physical interactions between individuals or between individuals and the environment. Indeed, observing a hand touched by an object or another hand led to increased somatosensory activation compared to observing contactless interactions (Schaefer et al., 2009; Pisoni et al., 2018). However, it is unclear whether the kinematics of the observed interaction modulates such somatosensory activation and whether such modulation is dependent on the moving and contact receiving object. In three experiments, participants observed either a slow- or fast- moving hand or ball at the top of the screen, contact either a hand or leaf at the bottom of the screen. To infer somatosensory activation, participants reacted to an auditory beep at the moment of observed contact. If observed contact led to increased somatosensory activation, response times (RTs) would decrease due to intersensory facilitation (Forster et al., 2002). In Experiment 1, RTs were lower when observing fast compared to slow hand movements, regardless of the target (i.e., hand or leaf). In Experiment 2, RTs were lower when observing fast compared to slow ball movements, but the size of effect was larger when a hand was the target compared to a leaf. In Experiment 3, RTs were lower when observing fast compared to slow movements toward a leaf, regardless of the moving object (i.e., hand or ball). Overall, this study provides evidence that observed movement speed influences somatosensory activation and its influence is dependent on the moving and contact receiving object.Acknowledgments: University of Toronto, Ontario Research Fund, Canadian Foundation for Innovation, National Sciences and Engineering Research Council
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 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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".