Yang Jiayi, Cao Dan, Guo Chunyan, Stieglitz Lennart, Ledergerber Debora, Sarnthein Johannes, Li Jin
School of Psychology, Capital Normal University, Beijing, China.
Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Nat Commun. 2025 Jul 1;16(1):5798. doi: 10.1038/s41467-025-60681-w.
In daily life, we frequently encounter varying demands on working memory (WM), yet how the brain adapts to high WM load remains unclear. To address this question, we recorded intracranial EEG from hippocampus, entorhinal cortex (EC), and lateral temporal cortex (LTC) in humans performing a task with varying WM loads (load 4, 6, and 8). Using multivariate machine learning analysis, we decoded WM load using the power from each region as neural features. The results showed that the EC exhibited both higher decoding accuracy on medium-to-high load and superior cross-regional generalization. Further analysis revealed that removing EC-related information significantly reduced residual decoding accuracy in the hippocampus and LTC. Additionally, we found that WM maintenance was associated with enhanced phase synchronization between the EC and other regions. This inter-regional communication increased as WM load rose. These results suggest that under higher WM load, the brain relies more on the EC, a key connector that links and shares information with the hippocampus and LTC.
在日常生活中，我们经常会遇到对工作记忆（WM）的不同要求，但大脑如何适应高工作记忆负荷仍不清楚。为了解决这个问题，我们在人类执行具有不同工作记忆负荷（负荷4、6和8）的任务时，记录了海马体、内嗅皮层（EC）和颞叶外侧皮层（LTC）的颅内脑电图。使用多变量机器学习分析，我们将来自每个区域的功率作为神经特征来解码工作记忆负荷。结果表明，内嗅皮层在中高负荷下表现出更高的解码准确率和更好的跨区域泛化能力。进一步分析发现，去除与内嗅皮层相关的信息会显著降低海马体和颞叶外侧皮层的残余解码准确率。此外，我们发现工作记忆维持与内嗅皮层和其他区域之间增强的相位同步有关。随着工作记忆负荷的增加，这种区域间通信也会增加。这些结果表明，在更高的工作记忆负荷下，大脑更多地依赖内嗅皮层，它是与海马体和颞叶外侧皮层连接并共享信息的关键连接点。
