Activity flow under the manipulation of cognitive load and training Article Swipe
Wanyun Zhao
,
Kaiqiang Su
,
Hengcheng Zhu
,
Marcus Kaiser
,
Mingxia Fan
,
Yong Zou
,
Ting Li
,
Dazhi Yin
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.neuroimage.2024.120761
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.neuroimage.2024.120761
Flexible cognitive functions, such as working memory (WM), usually require a balance between localized and distributed information processing. However, it is challenging to uncover how local and distributed processing specifically contributes to task-induced activity in a region. Although the recently proposed activity flow mapping approach revealed the relative contribution of distributed processing, few studies have explored the adaptive and plastic changes that underlie cognitive manipulation. In this study, we recruited 51 healthy volunteers (31 females) and investigated how the activity flow and brain activation of the frontoparietal systems was modulated by WM load and training. While the activation of both executive control network (ECN) and dorsal attention network (DAN) increased linearly with memory load at baseline, the relative contribution of distributed processing showed a linear response only in the DAN, which was prominently attributed to within-network activity flow. Importantly, adaptive training selectively induced an increase in the relative contribution of distributed processing in the ECN and also a linear response to memory load, which were predominantly due to between-network activity flow. Furthermore, we demonstrated a causal effect of activity flow prediction through training manipulation on connectivity and activity. In contrast with classic brain activation estimation, our findings suggest that the relative contribution of distributed processing revealed by activity flow prediction provides unique insights into neural processing of frontoparietal systems under the manipulation of cognitive load and training. This study offers a new methodological framework for exploring information integration versus segregation underlying cognitive processing.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.neuroimage.2024.120761
- OA Status
- gold
- Cited By
- 5
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https://openalex.org/W4401103163Canonical identifier for this work in OpenAlex
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https://doi.org/10.1016/j.neuroimage.2024.120761Digital Object Identifier
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Activity flow under the manipulation of cognitive load and trainingWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
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2024-07-27Full publication date if available
- Authors
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Wanyun Zhao, Kaiqiang Su, Hengcheng Zhu, Marcus Kaiser, Mingxia Fan, Yong Zou, Ting Li, Dazhi YinList of authors in order
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https://doi.org/10.1016/j.neuroimage.2024.120761Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.neuroimage.2024.120761Direct OA link when available
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Cognition, Cognitive load, Working memory, Computer science, Task (project management), Psychology, Information processing, Cognitive psychology, Neuroscience, Economics, ManagementTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2025: 5Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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