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Real-world Objects Scaffold Visual Working Memory for Features: Increased Neural Engagement When Colors Are Remembered as Part of Meaningful Objects.

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Title: Real-world Objects Scaffold Visual Working Memory for Features: Increased Neural Engagement When Colors Are Remembered as Part of Meaningful Objects.
Authors: Chung, Yong Hoon1 (AUTHOR) yong.hoon.chung.gr@dartmouth.edu, Brady, Timothy F.2 (AUTHOR), Störmer, Viola S.1 (AUTHOR)
Source: Journal of Cognitive Neuroscience. Jun2026, Vol. 38 Issue 6, p1171-1184. 14p.
Subjects: Visual memory, Electroencephalography, Sensory perception, Electrophysiology
Abstract: Visual working memory is a core cognitive function that allows active storage of task-relevant visual information. Contrary to the common assumption that the capacity of this system is fixed with respect to a single feature dimension, recent research has shown that working memory performance for a simple visual feature—color—is improved when this feature is encoded as part of a real-world object relative to an unrecognizable scrambled object. Using EEG (n = 24), we here demonstrate that this performance benefit is supported by increased neural engagement during the retention period, as indexed by enlarged contralateral delay activity during maintenance. Furthermore, the pattern of neural activity across parietal-occipital electrodes was more stable across time, suggesting that real-world objects may support more robust memory representations. Finally, we report a novel fronto-central ERP that distinguishes between real-world objects and scrambled objects during encoding and maintenance processes. Overall, our results demonstrate that active visual working memory capacity for simple features is not fixed but can expand depending on what context these features are encoded in. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Cognitive Neuroscience is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Cognitive+Neuroscience%22">Journal of Cognitive Neuroscience</searchLink>. Jun2026, Vol. 38 Issue 6, p1171-1184. 14p.
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  Data: Visual working memory is a core cognitive function that allows active storage of task-relevant visual information. Contrary to the common assumption that the capacity of this system is fixed with respect to a single feature dimension, recent research has shown that working memory performance for a simple visual feature—color—is improved when this feature is encoded as part of a real-world object relative to an unrecognizable scrambled object. Using EEG (n = 24), we here demonstrate that this performance benefit is supported by increased neural engagement during the retention period, as indexed by enlarged contralateral delay activity during maintenance. Furthermore, the pattern of neural activity across parietal-occipital electrodes was more stable across time, suggesting that real-world objects may support more robust memory representations. Finally, we report a novel fronto-central ERP that distinguishes between real-world objects and scrambled objects during encoding and maintenance processes. Overall, our results demonstrate that active visual working memory capacity for simple features is not fixed but can expand depending on what context these features are encoded in. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Cognitive Neuroscience is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1162/JOCN.a.2427
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        Text: English
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      – TitleFull: Real-world Objects Scaffold Visual Working Memory for Features: Increased Neural Engagement When Colors Are Remembered as Part of Meaningful Objects.
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              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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