Abstract Real-time, in situ monitoring of neurochemical dynamics in intact neural circuits is critical for elucidating brain function. Recent innovations in micro- and nanoelectrode engineering have markedly advanced our ability to detect neurotransmitter and neuromodulator release with high spatiotemporal resolution, while the application of machine learning (ML) has facilitated the development of next-generation electrodes and enhanced signal processing capabilities. Here, we outline a vision for the potential directions for electrode interface design and the deepening integration of ML in in situ neurochemical sensing, illustrating how breakthroughs over the past decade have illuminated these opportunities.
Chen et al. (Thu,) studied this question.