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Enregistrement W6962669026 · doi:10.17605/osf.io/s6y5u

Investigating the role of physical and observational experience in visual and kinesthetic imagery

2023· other· en· W6962669026 sur OpenAlexaff

Notice bibliographique

RevueOpen Science Framework · 2023
Typeother
Langueen
Domaine
Thématique
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésKinesthetic learningMotor imageryMental imagePerceptionModality (human–computer interaction)Representation (politics)Mental representationTask (project management)

Résumé

récupéré en direct d'OpenAlex

This process of cognitively generating the perceptual consequences of an action, whether they be visual or kinesthetic, has been termed motor imagery (MI). How imagery ability is developed and the processes underlying it’s use has generated ample debate in the literature (Moran & O’Shea, 2019). MI training has consistently been shown to benefit motor performance in sport, education, music, and medicine (Schuster et al., 2011). However, its utility is dependent on the user’s ability to generate and manipulate mental images (Martin et al., 1999). In current models of MI, it is unclear what components (motor or perceptual) of an internal representation are simulated. How does previous task experience impact the representation used in MI? Do representations created through visual and physical experience differ in how they are used in MI; potentially interacting with MI modality (visual or kinesthetic)? A prevailing theory of MI is that the motor system internally simulates the same representation used for overt action. In using the same processes as overt movement, MI is thought to be functionally equivalent to physical movement (Jeannerod, 2001), with muscle activity inhibited or occurring at a subthreshold level (Hurst & Boe, 2022). Yet, it is not well-understood if sensory and/or motor components are simulated during MI, if this simulation is moderated by the type of experience (physical vs. observational), and what this means for the generation of visual and kinesthetic MI (Hurst & Boe, 2022). MI ability can be measured using mental chronometry, by comparing the difference between actual and imagined movement times (MTs). Based on ideas of functional equivalence, imagined and actual MTs should be approximately the same if they are drawing on the same resources. Larger differences between MTs would signal deficits in MI ability or a low-fidelity action representation. There is evidence that imagined MTs are generally longer than actual movement times, due also to the increased cognitive resources required to generate the mental image (Glover & Baran, 2017). In a recent study, we tested whether visual and kinesthetic MI ability was dependent on the type and amount of physical or observational practice experiences performing novel hand gestures (Peters et al., in prep.). We expected that observational practice would primarily benefit visual imagery and physical practice (in the absence of vision) would primarily benefit kinesthetic imagery. These benefits would be evidenced in smaller differences between actual and imagined movement times and higher subjective ratings of quality and ease of generation for the mental imagery conditions. Although there was some evidence from the subjective ratings that supported our hypotheses, contrary to predictions, the physical practice group had large differences between actual and imagined movement times. These differences were due to long duration imagined movement times for both visual and kinesthetic MI for the physical practice group. The generation of kinesthetic imagery may rely on the presence of a visual representation and potentially explain why the physical practice group that practised without vision had difficulty in both visual and kinesthetic imagery. Indeed, there has been some uncertainty regarding the relationship between visual and kinesthetic MI and their distinctiveness (Klatzky, 1994). While to our knowledge, there is no empirical evidence that the generation of kinesthetic MI relies on the presence of a visual representation, in applied settings, researchers have had success in MI training designs when richer sensory representations are layered upon a basic visual representation of the task (e.g., Williams et al., 2013). In this study by Williams et al., only the group that experienced the ‘layered’ imagery intervention, in comparison to more general instructions that did not cue a rich kinesthetic representation, showed improvements in kinesthetic imagery ability. Therefore, it may be that for kinesthetic imagery to be successfully produced, it requires a basic visual representation of the task to scaffold kinesthetic-related experiences relating to how the movement feels. We are proposing here to further investigate the relationship between practice experiences and imagery modality to determine if a visual representation is necessary to act as a scaffold for the kinesthetic representation to be used in MI. In a mixed, cross-over design, comprising two different groups (Table 1), participants will be given both observational and physical practice with a hand gesture sequence. Dependent on group assignment, one group will first complete physical practice of the task with vision of their hand occluded and the other group will first complete an observation-only practice phase. The conditions will then be switched in a second phase such that both groups practice with both physical and observational practice. MI ability will be measured before and after each phase of practice. As with our previous study, we will compare actual and imagined MTs for visual and kinesthetic MI (i.e., mental chronometry difference scores) and subjective ratings of quality and ease of generation for each type of MI as well as the relative visual versus kinesthetic contribution of their MI.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,120
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,003
Études des sciences et des technologies0,0000,005
Communication savante0,0000,001
Science ouverte0,0020,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,059
Tête enseignante GPT0,384
Écart entre enseignants0,325 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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