Using fMRI Representations of Single Objects to Predict Multiple Objects in Working Memory in Human Occipitotemporal and Posterior Parietal Cortices

Research in visual perception has shown that in sensory areas, neural responses to a pair of objects presented together can be approximated by the linear average of the responses of each object shown alone. In this study, we ask if such an averaging relationship is unique to perceptual representations or if it also applies to representations maintained in visual working memory (VWM). By examining fMRI response pattern averaging across two experiments in both male and female human participants, we found that after properly accounting for task factors such as load, an averaging relationship also applies to representations formed in VWM. Specifically, VWM representations for two items can be approximated by the linear average of the VWM representations of each component item in both human occipitotemporal cortex (including early visual areas) and posterior parietal cortex. Although response averaging was originally proposed as a mechanism to combat distortion in representation due to neuronal response saturation in perception, the present study shows that even when response amplitudes were much lower in VWM compared with those in visual perception, an averaging relationship is still present for neural representations formed in VWM. This likely stems from the need to reduce interference among the concurrently stored items in VWM to maintain their representational independence. As an experimental method, response averaging may constitute an efficient yet simple tool to probe response independence in the human brain beyond perception and VWM.

Authors

Institutions

Publication Details

Journal
Journal of Neuroscience
Published
2025-11-14
DOI
https://doi.org/10.1523/jneurosci.1637-25.2025
Primary Topic
Neural and Behavioral Psychology Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using fMRI Representations of Single Objects to Predict Multiple Objects in Working Memory in Human Occipitotemporal and Posterior Parietal Cortices

Marvin M. Chun, Yaoda Xu
Journal of Neuroscience
Neural and Behavioral Psychology Studies
article

Using fMRI Representations of Single Objects to Predict Multiple Objects in Working Memory in Human Occipitotemporal and Posterior Parietal Cortices

Marvin M. Chun, Yaoda Xu
article en

Abstract

Research in visual perception has shown that in sensory areas, neural responses to a pair of objects presented together can be approximated by the linear average of the responses of each object shown alone. In this study, we ask if such an averaging relationship is unique to perceptual representations or if it also applies to representations maintained in visual working memory (VWM). By examining fMRI response pattern averaging across two experiments in both male and female human participants, we found that after properly accounting for task factors such as load, an averaging relationship also applies to representations formed in VWM. Specifically, VWM representations for two items can be approximated by the linear average of the VWM representations of each component item in both human occipitotemporal cortex (including early visual areas) and posterior parietal cortex. Although response averaging was originally proposed as a mechanism to combat distortion in representation due to neuronal response saturation in perception, the present study shows that even when response amplitudes were much lower in VWM compared with those in visual perception, an averaging relationship is still present for neural representations formed in VWM. This likely stems from the need to reduce interference among the concurrently stored items in VWM to maintain their representational independence. As an experimental method, response averaging may constitute an efficient yet simple tool to probe response independence in the human brain beyond perception and VWM.

Journal of NeuroscienceVol. 46(1)
Yale University (US)
Openalex Percentile: Top 66%
Neural and Behavioral Psychology Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.