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Record W4402911977 · doi:10.1167/jov.24.10.422

Perceptual comparisons are necessary and sufficient for the persistence of memory biases across time

2024· article· en· W4402911977 on OpenAlexaff
Joseph M. Saito, Susanne Ferber, Morgan D. Barense, Keisuke Fukuda

Bibliographic record

VenueJournal of Vision · 2024
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPersistence (discontinuity)Cognitive psychologyPerceptionPsychologyComputer scienceNeuroscienceGeology

Abstract

fetched live from OpenAlex

Interactions between visual memories and percepts have been shown to induce systematic biases in observers’ memory reports. When memories are explicitly compared with percepts, the resulting biases are potent enough to persist long after they are initially reported. However, it remains unclear whether bias persistence is attributable to processes that occur during perceptual comparisons themselves or those that occur when the bias is read out during initial memory reporting. To test this, we asked observers to encode colored object silhouettes into their long-term memory in anticipation of memory testing that occurred immediately after the encoding phase and 24 hours later. At each test, observers were cued to recall a target object from memory by presenting the uncolored target silhouette. Following recognition, the probe silhouette was then re-presented in a color that was sampled proximal to the encoded target color and observers were instructed to either ignore this colored probe or to judge its similarity to the remembered target. Observers then completed the trial by either reporting the remembered target color from a continuous wheel or by completing a search for an uncolored letter. Critically, all objects tested during the immediate test were tested again during the delayed test in a report condition where colored probes were omitted. Within each test, observers’ target reports showed attractive biases towards the colored probes, with larger biases following comparisons than passive viewing. More importantly, comparison-induced biases persisted into the delayed test with comparable magnitude across reported and unreported targets, while biases induced by passively viewing the probe dissipated by the delayed test, even for targets that were initially reported. These findings suggest that processes tied to perceptual comparisons are both necessary and sufficient for the formation of report biases that carry over from one retrieval episode to the next.

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)0.002
metaresearch head score (Gemma)0.015
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.130
GPT teacher head0.391
Teacher spread0.261 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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