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Neural mechanisms of resource allocation in working memory

Psychology

Neural mechanisms of resource allocation in working memory

H. Li, T. C. Sprague, et al.

This study by Hsin-Hung Li, Thomas C. Sprague, Aspen H. Yoo, Wei Ji Ma, and Clayton E. Curtis used computational neuroimaging to decode prioritized working-memory items, showing that frontal cortex feedback boosts visual-cortex gain to sharpen high-priority representations and link neural gain to behavioral precision.

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~3 min • Beginner • English
Abstract
To mitigate capacity limits of working memory, people allocate resources according to an item's relevance. However, the neural mechanisms supporting such a critical operation remain unknown. Here, we developed computational neuroimaging methods to decode and demix neural responses associated with multiple items in working memory with different priorities. In striate and extrastriate cortex, the gain of neural responses tracked the priority of memoranda. We decoded higher-priority memoranda with smaller error and lower uncertainty. Moreover, these neural differences predicted behavioral differences in memory prioritization between and within participants. Trial-wise variability in the magnitude of delay activity in the frontal cortex predicted differences in decoded precision between low- and high-priority items in visual cortex. These results support a model in which feedback signals broadcast from frontal cortex sculpt the gain of memory representations in the visual cortex according to behavioral relevance, thus identifying a neural mechanism for resource allocation.
Publisher
Science Advances
Published On
Apr 09, 2025
Authors
Hsin-Hung Li, Thomas C. Sprague, Aspen H. Yoo, Wei Ji Ma, Clayton E. Curtis
Tags
working memory
neural gain
priority-based resource allocation
visual cortex decoding
frontal cortex feedback
decoded precision
computational neuroimaging
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