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Record W2313204103 · doi:10.1152/jn.00793.2013

Decoupling the actions of the eyes from the hand alters beta and gamma synchrony within SPL

2014· article· en· W2313204103 on OpenAlexafffund
Patricia F. Sayegh, Kara M. Hawkins, Bogdan Neagu, J. Douglas Crawford, Kari L. Hoffman, Lauren E. Sergio

Bibliographic record

VenueJournal of Neurophysiology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsCanadians Living with HIVUniversity of TorontoYork University
FundersYork University
KeywordsEye–hand coordinationLocal field potentialEye movementGazeNeuroscienceDecoupling (probability)Motor planningBETA (programming language)PhysicsPsychologyCommunicationComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Eye-hand coordination is crucial for our ability to interact with the world around us. However, much of the visually guided reaches that we perform require a spatial decoupling between gaze direction and hand orientation. These complex decoupled reaching movements are in contrast to more standard eye and hand reaching movements in which the eyes and the hand are coupled. The superior parietal lobule (SPL) receives converging eye and hand signals; however, what is yet to be understood is how the activity within this region is modulated during decoupled eye and hand reaches. To address this, we recorded local field potentials within SPL from two rhesus macaques during coupled vs. decoupled eye and hand movements. Overall we observed a distinct separation in synchrony within the lower 10- to 20-Hz beta range from that in the higher 30- to 40-Hz gamma range. Specifically, within the early planning phase, beta synchrony dominated; however, the onset of this sustained beta oscillation occurred later during eye-hand decoupled vs. coupled reaches. As the task progressed, there was a switch to low-frequency and gamma-dominated responses, specifically for decoupled reaches. More importantly, we observed local field potential activity to be a stronger task (coupled vs. decoupled) and state (planning vs. execution) predictor than that of single units alone. Our results provide further insight into the computations of SPL for visuomotor transformations and highlight the necessity of accounting for the decoupled eye-hand nature of a motor task when interpreting movement control research data.

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)0.001
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 score0.929
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.031
GPT teacher head0.253
Teacher spread0.223 · 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

Citations26
Published2014
Admission routes2
Has abstractyes

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