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Record W2058151632 · doi:10.1167/12.11.5

An fMRI examination of the neural processing of periodic motion trajectories

2012· article· en· W2058151632 on OpenAlexafffund
Diana J. Gorbet, F. Wilkinson, Hugh R. Wilson

Bibliographic record

VenueJournal of Vision · 2012
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaYork University
KeywordsTrajectoryStimulus (psychology)Biological motionMotion (physics)Artificial intelligenceMotion perceptionENCODEComputer visionPerceptionTranslation (biology)Computer scienceNeurosciencePeriodic functionVisual perceptionCommunicationPhysicsPsychologyMathematicsCognitive psychologyBiologyMathematical analysis

Abstract

fetched live from OpenAlex

Perception of periodic or closed-circuit motion trajectories plays a crucial role in our ability to learn and perform many common skilled actions. For example, periodic trajectories are a key component of many types of biological movements when viewed relative to body translation. In the current fMRI study, we used a novel visual stimulus consisting of a target moving along a closed trajectory defined by a radial frequency (RF) pattern (i.e., a sinusoidal variation of trajectory radius relative to a circular trajectory) to determine which brain regions encode these periodic movement paths. Multivoxel pattern analyses permitted prediction of the shapes of different periodic trajectories within regions V2 and V3 indicating that these regions play a role in the processing of periodic visual motion. In addition, blood oxygen level dependent (BOLD) responses associated with the presentation of targets moving along RF trajectories compared with nonperiodic motion and static RF shapes revealed significantly greater activity in visual areas V1, V2, V3, V3A, and V4. To our knowledge, the results of this study represent the first examination of the functional brain activity underlying periodic motion processing and should inform further study.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.156

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 communication0.0000.001
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 head0.054
GPT teacher head0.350
Teacher spread0.296 · 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

Citations7
Published2012
Admission routes2
Has abstractyes

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