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Spatial Abilities and Effect of Working Memory on Pictures of Objects Recognized from Haptic Perception

2018· article· en· W3174148930 on OpenAlexaffabout
J Langlois, Yvan Dagenais, Renald Lemieux, Marc Lecourtois, Jordan Bernick, Christian Bellemare, Elizabeth Yetisir, Germain Bergeron, Stanley J. Hamstra, George A. Wells

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsUniversity of OttawaCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité de SherbrookeCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre Hospitalier Universitaire de Sherbrooke
FundersDepartment of Surgery
KeywordsHaptic technologyHaptic perceptionPerceptionMemorizationPsychologyObject (grammar)StereotaxyWorking memoryMental rotationCognitive psychologyCognitionComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Objective As a basis for an application in anatomy education, vision‐based spatial abilities tests have been correlated with pictures of objects recognized from haptic perception. Decreasing haptic perception while increasing working memory has been found to decrease performance on pictures of objects recognized from haptic perception. The objective of the current study was to correlate spatial abilities to the effect of working memory on pictures of objects recognized from haptic perception. Methods A cohort of 48 medical graduates was enrolled in a prospective study. Ethics committee approval and written informed concent were obtained. Spatial abilities were measured with a redrawn Vandenberg and Kuse Mental Rotations Tests in two (MRTA) and three (MRTC) dimensions and a Surface Development Test (SDT). In a one‐month rotation preparing for residency, the experiment was done within a one‐week drawing course before a one‐week applied anatomy course. Twenty‐five objects constructed from various shaped parts glued together were identified on a picture by participants after haptic perception. In the first exercice, participants could touch the object for up to two minutes while identifying the corresponding picture. In the second exercice, 30 seconds were allowed for haptic perception of the object, 15 seconds to memorize, and up to 75 seconds to identify the corresponding picture without any further haptic access to the object. The maximum score was 24 for each of MRTA and MRTC, 60 for SDT, and 25 for the picture score. Descriptive statistics included median and lower (Q1) and upper (Q3) quartiles. Spearman's correlation coefficient (and associated p‐value) was used to correlate the picture score to MRTA, MRTC and SDT scores. Results Correlations of change in picture score between the first and second exercice [6.5 (3, 10)] with MRTA [14 (9, 17)], MRTC [9.5 (6.5, 12)] and SDT [44.5 (36, 53)] scores were −0.046 (p = 0.7577), 0.126 (p = 0.3945) and 0.149 (p = 0.3133), respectively. Conclusion Haptics is involved in the handling of anatomical structures. Spatial abilities tests were not correlated to the effect of working memory on pictures of objects recognized from haptic perception. Spatial abilities tests have been correlated to the effect of working memory on drawings of objects from haptic perception. These findings may be explained by the 2‐D nature of picture recognition and 3‐D nature of making a perspective drawing of an object. Support or Funding Information This study was supported by an internal grant from the Department of Surgery, Université de Sherbrooke, Sherbrooke, QC, Canada. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.176

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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 teacher head, 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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