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Record W2171558232 · doi:10.1093/cercor/bhs250

Impairment of Online Control of Hand and Eye Movements in a Monkey Model of Optic Ataxia

2012· article· en· W2171558232 on OpenAlexafffund
Alexandra Battaglia‐Mayer, Simone Ferrari-Toniolo, Federica Visco‐Comandini, Philippe S. Archambault, Sohrab Saberi-Moghadam, Roberto Caminiti

Bibliographic record

VenueCerebral Cortex · 2012
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsEye movementNeuroscienceMovement (music)PsychologySuperior parietal lobuleParietal lobeAtaxiaPhysical medicine and rehabilitationComputer scienceMedicinePhysicsFunctional magnetic resonance imaging

Abstract

fetched live from OpenAlex

The parietal mechanisms for online control of hand trajectory were studied by combining single-cell recording and reversible inactivation of superior parietal area 5 (PE/PEc; SPL) of monkeys while these made reaches and saccades to visual targets, when the target position changed unexpectedly. Neural activity was modulated by hand position, speed, and movement direction, and by pre- and/or postsaccadic signals. After bilateral muscimol injection, an increase in the hand reaction- and movement-time toward both the first and second targets was observed. This caused an increase in the time necessary for the trajectory correction, and therefore an elongation of the hand-path toward the first target location. Furthermore, hand trajectories were different in shape than control ones. An elongation of the eye reaction time to both first and second targets was also observed, which could partially explain the deficit of planning and correction of hand movement. These results identify the superior parietal lobule as a crucial node in the online control of hand and eye movement and highlight the role of the eye impairment in the emergence of the reaching disorder so far regarded as the hallmark of optic ataxia.

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 score0.897
Threshold uncertainty score0.294

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 head0.027
GPT teacher head0.261
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

Citations64
Published2012
Admission routes2
Has abstractyes

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