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Record W2169697493 · doi:10.3389/fpsyg.2014.00971

Limits to the usability of iconic memory

2014· article· en· W2169697493 on OpenAlexafffund
Ronald A. Rensink

Bibliographic record

VenueFrontiers in Psychology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNissan Motor Company
KeywordsIconic memoryStimulus (psychology)Sensory memoryPsychologyCognitive psychologyComputer scienceVisual memoryVisual short-term memoryCognitive scienceCognitionNeuroscienceWorking memory

Abstract

fetched live from OpenAlex

Human vision briefly retains a trace of a stimulus after it disappears. This trace-iconic memory-is often believed to be a surrogate for the original stimulus, a representational structure that can be used as if the original stimulus were still present. To investigate its nature, a flicker-search paradigm was developed that relied upon a full scan (rather than partial report) of its contents. Results show that for visual search it can indeed act as a surrogate, with little cost for alternating between visible and iconic representations. However, the duration over which it can be used depends on the type of task: some tasks can use iconic memory for at least 240 ms, others for only about 190 ms, while others for no more than about 120 ms. The existence of these different limits suggests that iconic memory may have multiple layers, each corresponding to a particular level of the visual hierarchy. In this view, the inability to use a layer of iconic memory may reflect an inability to maintain feedback connections to the corresponding representation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.059
GPT teacher head0.364
Teacher spread0.305 · 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 designOther design
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

Citations33
Published2014
Admission routes2
Has abstractyes

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