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Record W2140284391 · doi:10.1152/jn.00418.2003

Kinematic Rules for Upper and Lower Arm Contributions to Grasp Orientation

2003· article· en· W2140284391 on OpenAlexaff
Jonathan J. Marotta, W. Pieter Medendorp, J. Douglas Crawford

Bibliographic record

VenueJournal of Neurophysiology · 2003
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsYork UniversityCanadian Institutes of Health Research
Fundersnot available
KeywordsKinematicsGRASPOrientation (vector space)Computer scienceCommunicationPsychologyMathematicsPhysicsGeometryClassical mechanics

Abstract

fetched live from OpenAlex

The purpose of the current study was to investigate the contribution of upper and lower arm torsion to grasp orientation during a reaching and grasping movement. In particular, we examined how the visuomotor system deals with the conflicting demands of coordinating upper and lower arm torsion and maintaining Donders' Law of the upper arm (a behavioral restriction of the axes of arm rotation to a two-dimensional "surface"). In experiment 1, subjects reached out and grasped a target block that was presented in one of 19 orientations (5 degrees clockwise increments from horizontal to vertical) at one position in a vertical presentation board. In experiment 2, target blocks were presented in one of three orientations (horizontal, three-quarter, and vertical) at nine different positions in the presentation board. If reach and grasp commands control the proximal and distal arms separately, then one would only expect the lower arm to contribute to grasp orientations and that Donders' Law would hold for the upper arm-independent of grasp orientations. Instead, as the required grasp orientation increased from horizontal to vertical, there was a significant clockwise torsional rotation in the upper arm, which accounted for 9% of the final vertical grasp orientation, and the lower arm, which accounted for 42%. A linear relationship existed between the torsional rotations of the upper and lower arm, which indicates that the components of the arm rotate in coordination with one another. The location-dependent aspects of upper and lower arm torsion remained invariant, however, yielding consistently shaped Donders' "surfaces" (with different torsional offsets) for different grasp orientations. These observations suggest that the entire arm-hand system contributes to grasp orientation, and therefore, the reach/grasp distinction is not directly reflected in proximal-distal kinematics but is better reflected in the distinction between these coordinated orienting rules and the location-dependent kinematic rules for the upper arm that result in Donders' Law for one given grasp orientation.

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)0.002
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 score0.807
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.021
GPT teacher head0.291
Teacher spread0.270 · 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".

Quick stats

Citations50
Published2003
Admission routes1
Has abstractyes

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