Brain states such as sleep, anesthesia, wakefulness, or coma are characterized by specific patterns of cortical activity dynamics, from local circuits to full-brain emergent properties. We previously demonstrated that full-spectrum signals, including the infraslow component (DC, direct current-coupled), can be recorded acutely in multiple sites using flexible arrays of graphene solution-gated field-effect transistors (gSGFETs). Here, we performed chronic implantation of 16-channel gSGFET arrays over the rat cerebral cortex and recorded full-band neuronal activity with two objectives: (1) to test the long-term stability of implanted devices; and (2) to investigate full-band activity during the transition across different levels of anesthesia. First, we demonstrate it is possible to record full-band signals with stability, fidelity, and spatiotemporal resolution for up to 5.5 months using chronic epicortical gSGFET implants. Second, brain states generated by progressive variation of levels of anesthesia could be identified as traditionally using the high-pass filtered (AC, alternating current-coupled) spectrogram: from synchronous slow oscillations in deep anesthesia through to asynchronous activity in the awake state. However, the DC signal introduced a highly significant improvement for brain-state discrimination: the DC band provided an almost linear information prediction of the depth of anesthesia, with about 85% precision, using a trained algorithm. This prediction rose to about 95% precision when the full-band (AC + DC) spectrogram was taken into account. We conclude that recording infraslow activity using gSGFET interfaces is superior for the identification of brain states, and further supports the preclinical and clinical use of graphene neural interfaces for long-term recordings of cortical activity.

中文翻译：

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使用石墨烯微晶体管作为神经接口进行慢性全频带记录，用于区分大脑状态

睡眠、麻醉、清醒或昏迷等大脑状态的特征是皮层活动动态的特定模式，从局部回路到全脑突发特性。我们之前证明，可以使用灵活的石墨烯溶液门控场效应晶体管（gSGFET）阵列在多个位置精确记录全频谱信号，包括次慢分量（DC，直流耦合）。在这里，我们在大鼠大脑皮层上进行了 16 通道 gSGFET 阵列的长期植入，并记录了全带神经元活动，目的有两个：(1) 测试植入装置的长期稳定性；(2) 测试植入装置的稳定性。 (2) 研究不同麻醉水平过渡期间的全带活动。首先，我们证明使用慢性外皮层 gSGFET 植入物可以稳定、保真度和时空分辨率地记录全频带信号长达 5.5 个月。其次，麻醉水平逐渐变化产生的大脑状态可以传统上使用高通滤波（AC，交流电耦合）频谱图来识别：从深度麻醉中的同步缓慢振荡到清醒状态下的异步活动。然而，DC 信号为大脑状态辨别带来了非常显着的改进：DC 频带使用经过训练的算法提供了麻醉深度的几乎线性信息预测，精度约为 85%。当考虑全频段 (AC + DC) 频谱图时，该预测精度上升到约 95%。我们得出的结论是，使用 gSGFET 接口记录次慢活动对于识别大脑状态而言更为优越，并进一步支持石墨烯神经接口在长期记录皮质活动中的临床前和临床使用。