Zhang Wei, Guo Lei, Liu Dongzhao
School of Information Engineering, Tianjin University of Commerce, Tianjin, 300134 China.
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin, 300130 China.
Cogn Neurodyn. 2022 Dec;16(6):1409-1425. doi: 10.1007/s11571-022-09792-4. Epub 2022 Feb 28.
Working memory (WM) is a kind of advanced cognitive function, which requires the participation and cooperation of multiple brain regions. Hippocampus and prefrontal cortex are the main responsible brain regions for WM. Exploring information coordination between hippocampus and prefrontal cortex during WM is a frontier problem in cognitive neuroscience. In this paper, an advanced information theory analysis based on bimodal neural electrical signals (local field potentials, LFPs and spikes) was employed to characterize the transcerebral information coordination across the two brain regions. Firstly, LFPs and spikes were recorded simultaneously from rat hippocampus and prefrontal cortex during the WM task by using multi-channel in vivo recording technique. Then, from the perspective of information theory, directional hippocampus-prefrontal cortex networks were constructed by using transfer entropy algorithm based on spectral coherence between LFPs and spikes. Finally, transcerebral coordination of bimodal information at the brain-network level was investigated during acquisition and performance of the WM task. The results show that the transfer entropy in directional hippocampus-prefrontal cortex networks is related to the acquisition and performance of WM. During the acquisition of WM, the information flow, local information transmission ability and information transmission efficiency of the directional hippocampus-prefrontal networks increase over learning days. During the performance of WM, the transfer entropy from the hippocampus to prefrontal cortex plays a leading role for bimodal information coordination across brain regions and hippocampus has a driving effect on prefrontal cortex. Furthermore, bimodal information coordination in the hippocampus → prefrontal cortex network could predict WM during the successful performance of WM.
工作记忆（WM）是一种高级认知功能，需要多个脑区的参与和协作。海马体和前额叶皮层是负责WM的主要脑区。探索工作记忆过程中海马体和前额叶皮层之间的信息协调是认知神经科学中的一个前沿问题。本文采用基于双峰神经电信号（局部场电位，LFPs和尖峰）的先进信息论分析方法，来表征跨两个脑区的经脑信息协调。首先，在工作记忆任务期间，通过多通道体内记录技术同时记录大鼠海马体和前额叶皮层的LFPs和尖峰。然后，从信息论的角度，利用基于LFPs和尖峰之间频谱相干性的转移熵算法构建定向海马体-前额叶皮层网络。最后，在工作记忆任务的获取和执行过程中，研究了脑网络水平上双峰信息的经脑协调。结果表明，定向海马体-前额叶皮层网络中的转移熵与工作记忆的获取和执行有关。在工作记忆的获取过程中，定向海马体-前额叶网络的信息流、局部信息传输能力和信息传输效率随学习天数增加。在工作记忆的执行过程中，从海马体到前额叶皮层的转移熵在跨脑区的双峰信息协调中起主导作用，并且海马体对前额叶皮层有驱动作用。此外，在工作记忆成功执行期间，海马体→前额叶皮层网络中的双峰信息协调可以预测工作记忆。
