Evidence map›Paper›PMID 42344997›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Interactive shape and color representation in visual working memory for colored objects in the human occipitotemporal cortex.

Yaoda Xu, Benjamin Swinchoski, JohnMark Taylor, Marvin Chun

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yaoda XuYale University, New Haven, CT, United States.ORCID https://orcid.org/0000-0002-8697-314X
Benjamin SwinchoskiYale University, New Haven, CT, United States.
JohnMark TaylorColumbia University, New York, NY, United States.
Marvin ChunYale University, New Haven, CT, United States.

Funding

Adaptive visual representation in human posterior parietal cortexR01EY030854 · NEI · YALE UNIVERSITY · PI YAODA XU · 2020 to 2026
$3.1M
NEI NIH HHS R01 EY030854
6 · The paper itself

Abstract

Two defining visual features of a real-world object are its shape and color. While previous fMRI pattern decoding studies showed that these features are represented in a largely orthogonal and independent manner in the human occipitotemporal cortex (OTC) during visual perception, how they are coded together in visual working memory (VWM) remains unknown. Here, we asked human participants to retain a real-world object's shape and color together in VWM. Using fMRI pattern decoding, we trained a linear classifier to decode two object shapes in one color to then decode the same two object shapes either in the same color (within-decoding) or in a different color (cross-decoding). During VWM encoding, replicating prior findings, we found significant cross-decoding and no drop in cross-decoding compared to within-decoding across OTC, indicating orthogonal and independent shape and color coding. During VWM delay, we again found significant cross-decoding, but more critically, a significant cross-decoding drop in OTC shape-selective areas and ventral color areas, indicating interactive shape and color coding in these areas in VWM. To our knowledge, this is the first time that interactive shape and color representations are reported in VWM in the human brain using fMRI pattern decoding. Sensory representations of an object's shape and color are thus transformed during VWM delay, likely tracking the demand of VWM to enable more efficient information storage.

Indexed as

fMRIoccipitotemporal cortexposterior parietal cortexvisionvisual object representationvisual short-term memoryvisual working memory

Identifiers

PMID42344997
PMCPMC13288494

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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.