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Record W2043852225 · doi:10.1007/s00221-015-4197-9

No effect of delay on the spatial representation of serial reach targets

2015· article· en· W2043852225 on OpenAlexaff
Immo Schütz, Denise Y. P. Henriques, Katja Fiehler

Bibliographic record

VenueExperimental Brain Research · 2015
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsYork University
FundersDeutsche Forschungsgemeinschaft
KeywordsGazeReference framePsychologyFrame of referenceCoding (social sciences)CommunicationRapid serial visual presentationCognitive psychologyArtificial intelligenceComputer scienceComputer visionCognitionFrame (networking)NeuroscienceMathematics

Abstract

fetched live from OpenAlex

When reaching for remembered target locations, it has been argued that the brain primarily relies on egocentric metrics and especially target position relative to gaze when reaches are immediate, but that the visuo-motor system relies stronger on allocentric (i.e., object-centered) metrics when a reach is delayed. However, previous reports from our group have shown that reaches to single remembered targets are represented relative to gaze, even when static visual landmarks are available and reaches are delayed by up to 12 s. Based on previous findings which showed a stronger contribution of allocentric coding in serial reach planning, the present study aimed to determine whether delay influences the use of a gaze-dependent reference frame when reaching to two remembered targets in a sequence after a delay of 0, 5 or 12 s. Gaze was varied relative to the first and second target and shifted away from the target before each reach. We found that participants used egocentric and allocentric reference frames in combination with a stronger reliance on allocentric information regardless of whether reaches were executed immediately or after a delay. Our results suggest that the relative contributions of egocentric and allocentric reference frames for spatial coding and updating of sequential reach targets do not change with a memory delay between target presentation and reaching.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.013
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
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 head0.122
GPT teacher head0.411
Teacher spread0.289 · 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

Citations12
Published2015
Admission routes1
Has abstractyes

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