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Record W1971012026 · doi:10.1152/jn.00110.2006

Nonuniform Distribution of Reach-Related and Torque-Related Activity in Upper Arm Muscles and Neurons of Primary Motor Cortex

2006· article· en· W1971012026 on OpenAlexaff
Isaac Kurtzer, Troy M. Herter, Stephen H. Scott

Bibliographic record

VenueJournal of Neurophysiology · 2006
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsQueen's University
Fundersnot available
KeywordsElbowPrimary motor cortexTorqueMotor cortexPhysical medicine and rehabilitationNeuroscienceAnatomyPsychologyPhysicsMedicineStimulation

Abstract

fetched live from OpenAlex

The present study examined the activity of primate shoulder and elbow muscles using a novel reaching task. We enforced similar patterns of center-out movement while the animals countered viscous loads at their shoulder, elbow, both joints, or neither joint. Accordingly, we could examine reach-related activity during the unloaded condition and torque-related activity by comparing activity across load conditions. During unloaded reaching the upper arm muscles exhibited a bimodal distribution of preferred hand direction. Maximal reach-related activity occurred with hand movements mostly toward or away from the body. Arm muscles also exhibited a bimodal distribution of their preferred torque direction. Maximal torque-related activity typically occurred with shoulder-extension/elbow-flexion torque or shoulder-flexion/elbow-extension torque. Similar biases in reach-related and torque-related activity could be reproduced by optimizing a global measure of muscle activity. These biases were also observed in the neural activity of primary motor cortex (M1). The parallels between M1 and muscular activity demonstrate another link between motor cortical processing and the motor periphery and may reflect an optimization process performed by the sensorimotor system.

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 score0.986
Threshold uncertainty score0.371

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 head0.012
GPT teacher head0.218
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".

Quick stats

Citations49
Published2006
Admission routes1
Has abstractyes

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