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Record W4306871265 · doi:10.1038/s41598-022-22133-z

Tactile facilitation during actual and mere expectation of object reception

2022· article· en· W4306871265 on OpenAlexafffund
Damian M. Manzone, Luc Tremblay, Romeo Chua

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of British ColumbiaFord Motor Company (Canada)University of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsObject (grammar)PerceptionStimulus (psychology)FacilitationTactile perceptionComputer scienceComputer visionHaptic technologyAnticipation (artificial intelligence)CommunicationPsychologyArtificial intelligenceCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

During reaching and grasping movements tactile processing is typically suppressed. However, during a reception or catching task, the object can still be acquired but without suppressive processes related to movement execution. Rather, tactile information may be facilitated as the object approaches in anticipation of object contact and the utilization of tactile feedback. Therefore, the current study investigated tactile processing during a reception task. Participants sat with their upper limb still as an object travelled to and contacted their fingers. At different points along the object's trajectory and prior to contact, participants were asked to detect tactile stimuli delivered to their index finger. To understand if the expectation of object contact contributed to any modulation in tactile processing, the object stopped prematurely on 20% of trials. Compared to a pre-object movement baseline, relative perceptual thresholds were decreased throughout the object's trajectory, and even when the object stopped prematurely. Further, there was no evidence for modulation when the stimulus was presented shortly before object contact. The former results suggest that tactile processing is facilitated as an object approaches an individual's hand. As well, we purport that the expectation of tactile feedback drives this modulation. Finally, the latter results suggest that peripheral masking may have reduced/abolished any facilitation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.023
GPT teacher head0.245
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2022
Admission routes2
Has abstractyes

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