Unlocking sleep-wake secrets with dual brain signal analysis

Background

Understanding the dynamic neural mechanisms of sleep-wake cycles is a major challenge in sleep science and neuroengineering. Sleep, essential for maintaining brain homeostasis and cognitive function, relies on the intricate coordination between neuronal electrical activity and neurochemical signals in specific brain regions. The nucleus accumbens, a key node in the reward and motivation circuit, has been identified as critical for regulating sleep-stage transitions through dopamine dynamics and neuronal firing patterns.

However, existing neural sensing technologies face significant limitations in achieving simultaneous in-situ detection of electrophysiological and neurochemical signals. Although some studies have integrated electrochemical functions into microelectrode arrays, current systems suffer from two main bottlenecks: reliance on externally implanted reference electrodes, which cause significant tissue damage and poor long-term stability, and traditional coating methods that lead to signal crosstalk between functional sites, compromising both sensitivity and fidelity.

Research progress

A breakthrough in neural sensing technology has been achieved through collaboration between Professor Cai Xinxia's team from the National Key Laboratory of Sensor Technology at the Aerospace Information Research Institute, Chinese Academy of Sciences, and Professor Yu Yanqin's team from Zhejiang University. They have successfully developed a novel triple-electrode integrated multi-channel microelectrode array that enables simultaneous monitoring of neurochemical and electrophysiological signals in freely behaving animals.

The research team implemented an innovative targeted modification strategy, creating specialized functional sites within the integrated triple-electrode system. The dopamine-sensing working electrode was enhanced with PtNPs/PEDOT:PSS/Nafion composite to achieve superior selectivity and sensitivity. For electrophysiological recording, electrodes were modified with PtNPs/PEDOT:PSS to significantly reduce impedance and optimize signal quality. Meanwhile, the reference electrode was coated with IrOx to ensure exceptional long-term stability during in vivo applications. This sophisticated design enables high-performance electrochemical detection and electrophysiological recording within a single, compact probe.

Scanning electron microscopy confirmed the distinct morphological characteristics of each functional site, with no cross-contamination between coatings. The electrochemical site featured a Nafion layer, while adjacent recording sites remained clean, demonstrating precise spatial control at the microscale. The reference electrode exhibited a porous IrOx structure, ideal for stable potential response.

In vivo experiments in freely moving mice captured dynamic dopamine release and neural activity across sleep-wake stages. Dopamine levels peaked during wakefulness, dropped to their lowest during non-rapid eye movement (NREM) sleep, and surged most significantly during transitions from REM sleep to wakefulness, highlighting dopamine's role in sleep-state transitions.

Further analysis identified three distinct neuronal populations: REM-inactive neurons (RINs), REM-stable neurons (RSNs), and REM-rhythmic neurons (RRNs). RSNs and RRNs showed the highest firing rates during wakefulness and the lowest during NREM sleep. Notably, their firing dynamics synchronized closely with dopamine fluctuations, providing direct evidence of dopaminergic modulation in sleep-wake regulation.

Future prospects

This triple-electrode integrated microelectrode array establishes an innovative dual-modal sensing platform for synchronized monitoring of electrophysiological and neurochemical activities in deep brain regions. The platform's modular design allows for functional expansion by adjusting targeted modification strategies, enabling specific detection of other neurotransmitters like glutamate and serotonin. This integrated sensing approach opens new avenues for real-time decoding of deep brain circuits, optimizing brain-computer interfaces, and precise evaluation of neuromodulation therapies, with broad implications for basic neuroscience and clinical applications.