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Record W2328234534 · doi:10.1152/jn.00131.2013

Simultaneous encoding of the direction and orientation of potential targets during reach planning: evidence of multiple competing reach plans

2013· article· en· W2328234534 on OpenAlexafffund
Brandie M. Stewart, Lee A. Baugh, Jason P. Gallivan, J. Randall Flanagan

Bibliographic record

VenueJournal of Neurophysiology · 2013
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsQueen's University
FundersCanadian Institutes of Health Research
KeywordsOrientation (vector space)Computer scienceTask (project management)Control (management)Encoding (memory)Artificial intelligenceMathematicsEngineeringGeometry

Abstract

fetched live from OpenAlex

Reaches performed in many natural situations involve selecting a specific target from a number of alternatives. Recent studies show that before reaching, multiple potential reach targets are encoded in brain regions involved in action control and that, when people are required to initiate the reach before the target is specified, initial hand direction is biased by the spatial distribution of potential targets. These findings have led to the suggestion that the brain, during planning, simultaneously prepares multiple reaches to potential targets. In addition to hand direction, reach planning often involves specifying other parameters such as wrist orientation. For example, when posting a letter in a mail slot, both the location and orientation of the slot must be encoded to control hand direction and orientation. Therefore, if the brain prepares multiple reaches to potential targets and if these targets require the specification of hand direction and orientation, then both of these variables should be biased by the spatial distribution of potential targets. To test this prediction, we examined a task in which participants moved a hand-held rectangular tool toward multiple rectangular targets of varying location and orientation, one of which was selected, with equal probability as the actual target after movement initiation. We found that initial hand direction and orientation were biased by the spatial distributions of potential target locations and orientations, respectively. This result is consistent with the idea that the brain, in cases of target uncertainty, simultaneously plans fully specified reaching movements to all potential targets.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.224

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 head0.026
GPT teacher head0.260
Teacher spread0.234 · 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

Citations54
Published2013
Admission routes2
Has abstractyes

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