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Peer-reviewedCC BYCurrent Biology

Flexible working memory in the human peripheral nervous system

  • Sihan Yang1
  • Yueying Dong2
  • Anastasia Kiyonaga3
  1. 1Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA. Electronic address: [email protected]
  2. 2Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA
  3. 3Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA. Electronic address: [email protected]
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Abstract

SUMMARY Working memory (WM) representations that are distributed across the brain can be flexibly recruited to best guide behavior 1–4 . For instance, information may be represented relatively more strongly in visual cortex when a WM task requires fine visual detail, or more strongly in motor cortex when a specific response can be prepared 5–10 . If WM drives goal-oriented actions, we might also expect such task-dependent signals to propagate to the peripheral effectors that realize WM commands. Accordingly, oculomotor signatures like gaze biases can track simple visuo-spatial WM features 11,12 , but their functional flexibility is unclear. Here, we test the idea that WM content is adaptively distributed across the nervous system according to behavioral demands. We ask whether patterns in both eye and hand movements can express visual WM stimulus features, and whether the distribution of such activity shifts with the task context. In a delayed recall task, we manipulated how human participants reported their memory: they would either draw a line or adjust a visible response wheel to match a remembered orientation. Via continuous eye- and stylus-tracking, we found that remembered orientations were decodable from small inflections in both gaze and hand movements during the WM maintenance period. Moreover, this decoding strength varied by response format. Gaze patterns tracked memorized features relatively better in the wheel condition (vs. draw ), while hand movements were better in the draw condition (vs. wheel ). Therefore, visually encoded WM contents may be adaptively allocated to task-relevant motor effectors, balancing WM representations across peripheral activity according to behavioral needs.

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Cite

BibTeXRIS
BibTeX
@article{yang2026flexible,
  title = {{Flexible working memory in the human peripheral nervous system}},
  author = {Sihan Yang and Yueying Dong and Anastasia Kiyonaga},
  journal = {Current Biology},
  year = {2026},
  month = jun,
  doi = {10.1016/j.cub.2026.05.027},
  url = {https://doi.org/10.1016/j.cub.2026.05.027},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Flexible working memory in the human peripheral nervous system
AU  - Sihan Yang
AU  - Yueying Dong
AU  - Anastasia Kiyonaga
PY  - 2026
DA  - 2026/06/01
JO  - Current Biology
DO  - 10.1016/j.cub.2026.05.027
UR  - https://doi.org/10.1016/j.cub.2026.05.027
AB  - SUMMARY Working memory (WM) representations that are distributed across the brain can be flexibly recruited to best guide behavior 1–4 . For instance, information may be represented relatively more strongly in visual cortex when a WM task requires fine visual detail, or more strongly in motor cortex when a specific response can be prepared 5–10 . If WM drives goal-oriented actions, we might also expect such task-dependent signals to propagate to the peripheral effectors that realize WM commands. Accordingly, oculomotor signatures like gaze biases can track simple visuo-spatial WM features 11,12 , but their functional flexibility is unclear. Here, we test the idea that WM content is adaptively distributed across the nervous system according to behavioral demands. We ask whether patterns in both eye and hand movements can express visual WM stimulus features, and whether the distribution of such activity shifts with the task context. In a delayed recall task, we manipulated how human participants reported their memory: they would either draw a line or adjust a visible response wheel to match a remembered orientation. Via continuous eye- and stylus-tracking, we found that remembered orientations were decodable from small inflections in both gaze and hand movements during the WM maintenance period. Moreover, this decoding strength varied by response format. Gaze patterns tracked memorized features relatively better in the wheel condition (vs. draw ), while hand movements were better in the draw condition (vs. wheel ). Therefore, visually encoded WM contents may be adaptively allocated to task-relevant motor effectors, balancing WM representations across peripheral activity according to behavioral needs.
SN  - 0960-9822
SN  - 1879-0445
ER  -