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Record W2001067448 · doi:10.1167/14.1.11

Neural correlates of radial frequency trajectory perception in the human brain

2014· article· en· W2001067448 on OpenAlexafffund
Diana J. Gorbet, F. Wilkinson, H. R. Wilson

Bibliographic record

VenueJournal of Vision · 2014
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaYork University
KeywordsPerceptTrajectoryNeural correlates of consciousnessMotion perceptionNeurosciencePsychologyPerceptionBrain activity and meditationStimulus (psychology)Neural activityArtificial intelligenceCommunicationComputer visionPhysicsComputer scienceElectroencephalographyCognitive psychologyCognition

Abstract

fetched live from OpenAlex

Radial frequency (RF) motion trajectories are visual stimuli that consist of a difference of Gaussians moving along a closed trajectory defined by a sinusoidal variation of the radius relative to a circular path. In the current study, multivoxel fMRI analyses demonstrated that spatial patterns of activity in visual regions V2, V3, and MT can predict RF motion trajectory shape regardless of whether an observer can behaviorally identify the shape or not. This result suggests that processing in these regions is concerned with local properties of the trajectories and not directly linked with a conscious percept of global trajectory shape. Whole-brain analyses show that RF motion trajectories also evoke premotor and posterior parietal cortical activity that may be a neural correlate of shape recognizability. Further, comparisons with activity evoked by static versions of the RF shapes reveal cue-invariant processing in regions of the posterior parietal and occipitotemporal cortices. Interestingly, the RF motion trajectories evoke patterns of dorsal visual stream cortical activity typical of visually guided movement preparation or action observation, suggesting that these stimuli may be processed as potential motor actions rather than as purely visual experiences.

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)0.001
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 score0.955
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.043
GPT teacher head0.344
Teacher spread0.302 · 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

Citations13
Published2014
Admission routes2
Has abstractyes

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