Evidence map›Paper›PMID 35524011›Full record

ArticlePsychonomic bulletin & review2022

Long-term priors constrain category learning in the context of short-term statistical regularities.

Casey L Roark, Lori L Holt

Abstract read
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In one paragraph

Article in Psychonomic bulletin & review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  5. Article
  6. The nature of non-native speech sound representations.The Journal of the Acoustical Society of America · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Casey L RoarkDepartment of Psychology, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA. casey.l.roark@gmail.com.ORCID http://orcid.org/0000-0001-5642-8784
Lori L HoltDepartment of Psychology, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA.

Funding

Predoctoral Training Program in Behavioral Brain ResearchT32GM081760 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FIEZ, JULIE A, HOLT, LORI L · 2007 to 2021
$4.3M
Shared and specific mechanisms of auditory and visual category learningF32DC018979 · NIDCD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ROARK, CASEY L · 2020 to 2021
$131k
Division of Behavioral and Cognitive Sciences BCS1950054NIDCD NIH HHS F32DC018979NIGMS NIH HHS T32-GM0081760
6 · The paper itself

Abstract

Cognitive systems face a constant tension of maintaining existing representations that have been fine-tuned to long-term input regularities and adapting representations to meet the needs of short-term input that may deviate from long-term norms. Systems must balance the stability of long-term representations with plasticity to accommodate novel contexts. We investigated the interaction between perceptual biases or priors acquired across the long-term and sensitivity to statistical regularities introduced in the short-term. Participants were first passively exposed to short-term acoustic regularities and then learned categories in a supervised training task that either conflicted or aligned with long-term perceptual priors. We found that the long-term priors had robust and pervasive impact on categorization behavior. In contrast, behavior was not influenced by the nature of the short-term passive exposure. These results demonstrate that perceptual priors place strong constraints on the course of learning and that short-term passive exposure to acoustic regularities has limited impact on directing subsequent category learning.

Indexed as

LearningHumansAuditionCategory learningPerceptual priorsStatistical learning

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.