Wang Yiding, Yang Chao, Song Yilin, Xiao Guihua, Cao Jiangbei, Mi Weidong, Yang Gucheng, Xu Wei, Dai Yuchuan, Liu Juntao, Dai Zhongquan, Qu Lina, Luo Jinping, Li Yinghui, Cai Xinxia
State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100094, China.
ACS Sens. 2025 Aug 22;10(8):5600-5612. doi: 10.1021/acssensors.5c00310. Epub 2025 Jul 28.
Studying neuronal activity during hibernation's extremely low metabolic state may offer novel solutions for metabolic disorders, stroke treatment, and space travel challenges. To explore hibernation's neural mechanisms, we developed a natural hibernation model using Siberian chipmunks. However, their characteristic weak neuronal discharge and prolonged hibernation periods necessitate electrodes with both enhanced detection sensitivity and exceptional long-term stability. We developed a new nanocomposite platinum nanoparticles/Prussian blue-modified microelectrode arrays (MEAs) aimed at solving the above difficulties. Prussian blue can react with reactive oxygen species to reduce inflammation during the detection process; therefore, MEAs achieved a high signal-to-noise ratio (15.53 ± 6.73) in the detection of individual neurons, even against weak neural activity in dormant states. We discovered that three types of neurons exhibited distinct responses to hibernation and established three-dimensional characteristics to differentiate them through algorithmic processing of the signal. Type 3 neurons discharged in the extremely low metabolic state, indicating that Type 3 neurons are critical for chipmunks to enter and maintain deep hibernation without damaging the brain. The theta frequency band of local field potentials (LFPs) rapidly increased during arousal, representing consciousness arousal, and can be used as a key signal to predict arousal. These results fill part of the research gaps in the characteristics of critical neurons during hibernation and provide a solid foundation for regulating neurons to control the body into a state of low temperature and low metabolism.
研究冬眠期间极低代谢状态下的神经元活动,可能为代谢紊乱、中风治疗和太空旅行挑战提供新的解决方案。为了探索冬眠的神经机制,我们利用西伯利亚花栗鼠建立了一个自然冬眠模型。然而,它们具有神经元放电微弱和冬眠期长的特点,这就需要电极具备更高的检测灵敏度和出色的长期稳定性。我们开发了一种新型纳米复合铂纳米颗粒/普鲁士蓝修饰的微电极阵列(MEA),旨在解决上述难题。普鲁士蓝可与活性氧发生反应,以减少检测过程中的炎症反应;因此,MEA在检测单个神经元时,即使针对休眠状态下微弱的神经活动,也能实现高信噪比(15.53±6.73)。我们发现三种类型的神经元对冬眠表现出不同的反应,并通过对信号进行算法处理建立了三维特征来区分它们。3型神经元在极低代谢状态下放电,这表明3型神经元对于花栗鼠进入并维持深度冬眠而不损伤大脑至关重要。局部场电位(LFP)的θ频段在觉醒过程中迅速增加,代表意识觉醒,可作为预测觉醒的关键信号。这些结果填补了冬眠期间关键神经元特征方面的部分研究空白,并为调节神经元以控制身体进入低温和低代谢状态奠定了坚实基础。