Evidence map›Paper›PMID 37968121›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2024

Category Learning Selectively Enhances Representations of Boundary-Adjacent Exemplars in Early Visual Cortex.

Sean R O'Bryan, Shinyoung Jung, Anto J Mohan, Miranda Scolari

Abstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

4 authors.

Sean R O'BryanDepartment of Psychological Sciences, Texas Tech University, Lubbock, Texas 79409 sean_obryan@brown.edu.
Shinyoung JungDepartment of Psychological Sciences, Texas Tech University, Lubbock, Texas 79409.
Anto J MohanDepartment of Psychological Sciences, Texas Tech University, Lubbock, Texas 79409.
Miranda ScolariDepartment of Psychological Sciences, Texas Tech University, Lubbock, Texas 79409.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Category learning and visual perception are fundamentally interactive processes, such that successful categorization often depends on the ability to make fine visual discriminations between stimuli that vary on continuously valued dimensions. Research suggests that category learning can improve perceptual discrimination along the stimulus dimensions that predict category membership and that these perceptual enhancements are a byproduct of functional plasticity in the visual system. However, the precise mechanisms underlying learning-dependent sensory modulation in categorization are not well understood. We hypothesized that category learning leads to a representational sharpening of underlying sensory populations tuned to values at or near the category boundary. Furthermore, such sharpening should occur largely during active learning of new categories. These hypotheses were tested using fMRI and a theoretically constrained model of vision to quantify changes in the shape of orientation representations while human adult subjects learned to categorize physically identical stimuli based on either an orientation rule (

Indexed as

Brain MappingVisual CortexAdultDiscrimination, PsychologicalHumansMagnetic Resonance ImagingVisual Perceptioncategory learningearly visual cortexfMRIhuman

Identifiers

PMID37968121
PMCPMC10860654

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.