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Record W4308174569 · doi:10.1101/2022.11.04.515184

Seeing our hand or a tool during visually-guided actions: different effects on the somatosensory and visual cortices

2022· preprint· en· W4308174569 on OpenAlexaff
Benjamin Mathieu, Antonin Abillama, Simon Moré, Catherine Mercier, Martin Simoneau, Jérémy Danna, Laurence Mouchnino, Jean Blouin

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre for Interdisciplinary Research in RehabilitationUniversité LavalCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean
Fundersnot available
KeywordsSomatosensory systemTracingPsychologyStylusSensory systemContext (archaeology)ProprioceptionNeuroscienceCommunicationAudiologyCognitive psychologyComputer visionComputer scienceMedicineBiology

Abstract

fetched live from OpenAlex

Abstract The processing of proprioceptive information in the context of a conflict between visual and somatosensory feedbacks deteriorates motor performance. Previous studies have shown that seeing one’s hand increases the weighting assigned to arm somatosensory inputs. In this light, we hypothesized that the sensory conflict, when tracing the contour of a shape with mirror-reversed vision, will be greater for participants who trace with a stylus seen in their hand (Hand group, n=17) than for participants who trace with the tip of rod without seen their hand (Tool group, n=15). Based on this hypothesis, we predicted that the tracing performance with mirror vision will be more deteriorated for the Hand group than for the Tool group, and we predicted a greater gating of somatosensory information for the Hand group to reduce the sensory conflict. The participants of both groups followed the outline of a shape in two visual conditions. Direct vision: the participants saw the hand or portion of a light 40 cm rod directly. Mirror Vision: the hand or the rod was seen through a mirror. We measured tracing performance using a digitizing tablet and the cortical activity with electroencephalography. Behavioral analyses revealed that the tracing performance of both groups was similarly impaired by mirror vision. However, contrasting the spectral content of the cortical oscillatory activity between the Mirror and Direct conditions, we observed that tracing with mirror vision resulted in significantly larger alpha (8-12 Hz) and beta (15-25 Hz) powers in the somatosensory cortex for participants of the Hand group. The somatosensory alpha and beta powers did not significantly differ between Mirror and Direct vision conditions for the Tool group. For both groups, tracing with mirror vision altered the activity of the visual cortex: decreased alpha power for the Hand group, decreased alpha and beta power for the Tool group. Overall, these results suggest that seeing the hand enhanced the sensory conflict when tracing with mirror vision and that the increase of alpha and beta powers in the somatosensory cortex served to reduce the weight assigned to somatosensory information. The increased activity of the visual cortex observed for both groups in the mirror vision condition suggests greater visual processing with increased task difficulty. Finally, the fact that the participants of the Tool group did not show better tracing performance than those of the Hand group suggests that tracing deterioration resulted from a sensorimotor conflict (as opposed to a visuo-proprioceptive conflict).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.000
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 head0.037
GPT teacher head0.272
Teacher spread0.235 · 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 designObservational
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

Citations0
Published2022
Admission routes1
Has abstractyes

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