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Record W2017611522 · doi:10.1167/12.9.644

Increment threshold functions for radial frequency motion trajectories exhibit a dipper function above threshold

2012· article· en· W2017611522 on OpenAlexaff
Marwan Daar, Charles C.-F. Or, H. Wilson

Bibliographic record

VenueJournal of Vision · 2012
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
Fundersnot available
KeywordsAmplitudeDetection thresholdPhysicsMathematicsTrajectoryMathematical analysisOpticsQuantum mechanicsComputer science

Abstract

fetched live from OpenAlex

Radial frequency (RF) trajectories are a new class of stimuli that have been developed to study the visual perception of periodic motion (Or, Thabet, Wilkinson, and Wilson, 2011). These stimuli are described by a moving dot that traverses a circular path through space with periodic radial deformations whose frequency, amplitude, and phase can be independently specified. Here, we show how the discrimination of RF amplitude varies across different reference amplitudes in a 2 alternative forced choice task. Using an RF3 trajectory (a pattern with three cycles of deformation along its trajectory), increment thresholds for seven observers were measured at four different reference amplitudes: Detection (discriminating a circular motion from RF3), 1X (discriminating a pair of RF3 patterns, with the amplitude of one member of this pair set to (1X) threshold obtained from the detection condition), 2.5X, and 5X. Data show that thresholds for detecting changes in amplitude show an approximately two-fold decrease at 1X and 2.5X, relative to detection threshold, and then recover to detection threshold levels at 5X. Mean thresholds (± standard errors) for detection, 1X, 2.5X, and 5X (in minutes of arc): 2.30 ± 0.31, 1.21 ± 0.18, 1.06 ± 0.12, 2.31 ± 0.42, respectively. A repeated measures ANOVA showed a main effect of base increment: F(1,6) = 95.80, p<0.0001 ); paired sample t-tests showed a significant difference between detection and 1X, T(6) = 3.59 (p<0.05); detection and 2.5X, T(6) = 4.28 (p<0.01); and no difference between detection and 5X, T(6) = -0.03 (p = 0.98). Observers were also tested using an RF5 trajectory, and the same pattern was found. As a control, this effect was measured using different angular speeds of the RF trajectory. We conclude that the discrimination of RF trajectories along different base amplitudes points to a sigmoidal neural response function for deviations from circular trajectories. Meeting abstract presented at VSS 2012

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.063
GPT teacher head0.332
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2012
Admission routes1
Has abstractyes

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