Dynamic prioritization reshapes neural geometries for action in human working memory
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Prior work has shown that control brain regions encode upcoming novel instructed actions. Similarly, visual working memory (WM) representations can reflect different priority states. However, it remains unknown whether the priority status of WM-guided novel actions similarly modulates their neural coding format, and how such dynamics unfold over time. We addressed these questions using EEG while human participants performed two consecutive choice reaction tasks. At the start of each trial, participants encoded two novel stimulus-response (S-R) mappings. A cue then indicated whether these mappings would be relevant immediately (“current” condition), later after an intervening task (“prospective”), or after a free delay (“delayed”). Using multivariate pattern analysis, we found that the S-R category was decodable in all conditions during relevant time windows. Critically, pattern similarity analyses revealed that while mere maintenance demands allow for temporary preservation of neural codes (i.e., between current and delayed trials), shielding from interference (i.e., prospective trials) induced significant alterations to the neural code. Further exploration of the representational geometry revealed that priority status gained prominence dynamically over S-R category coding when preparing for such shielding demands. Importantly, some of these changes emerged anticipatorily, prior to target onset. Overall, our results show that, similar to visual WM, the priority of intended actions dynamically and anticipatorily reshapes their neural format. They further reveal how different demands induce content geometries compatible with previously proposed coding schemes, and that such representational changes can be implemented flexibly in time.
Significance statement
Successfully translating visuomotor plans into action relies not only on maintaining such plans but also on prioritizing relevant information at the right time. While prior work has shown that working memory representations adapt to prioritize visual content, it remains unknown whether similar mechanisms apply to action-guiding content. Using EEG and multivariate analyses, we show that priority states—whether immediate, delayed, or prospectively relevant—modulate the representational geometry of novel stimulus-response mappings. Notably, the anticipation of interference compared to mere maintenance leads to greater alterations in the neural code during a retention interval. These results demonstrate that neural representations of novel instructed actions are shaped by their priority state and upcoming demands and reveal how goal- relevant information is restructured over time.