脑深部电刺激(DBS)是治疗与电路相关的神经和精神疾病以及帕金森病和强迫症等疾病的有力工具,以及扰乱神经回路和探索神经假体的关键研究工具。电介导的DBS,然而,受到刺激电流扩散到与疾病病程和治疗无关的组织的限制,可能导致患者不良副作用。在这项工作中,我们利用红外神经刺激(INS),一种光学神经调制技术,使用近中红外光来驱动神经和神经元的分级兴奋性和抑制性反应,以促进光学和空间约束的DBS范例。INS已被证明在皮质神经元中提供空间约束的响应,与其他光学技术不同,不需要对神经目标进行遗传修饰。我们证明INS产生分级,在大鼠丘脑皮质回路中具有强大信息传递的生物物理相关的单单元响应。重要的是,我们表明,与传统的电刺激相比,来自丘脑INS的激活的皮质扩散产生了更多的空间约束反应曲线。由于观测到的INS的空间精度,我们使用深度强化学习(RL)对丘脑皮质回路进行闭环控制,创建刺激反应动态的实时表示,同时驱动皮层神经元精确的放电模式。我们的数据表明,INS可以作为开环和闭环DBS的有针对性的动态刺激范例。
Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson\'s disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprostheses. Electrically mediated DBS, however, is limited by the spread of stimulus currents into tissue unrelated to disease course and treatment, potentially causing undesirable patient side effects. In this work, we utilize infrared neural stimulation (INS), an optical neuromodulation technique that uses near to midinfrared light to drive graded excitatory and inhibitory responses in nerves and neurons, to facilitate an optical and spatially constrained DBS paradigm. INS has been shown to provide spatially constrained responses in cortical neurons and, unlike other optical techniques, does not require genetic modification of the neural target. We show that INS produces graded, biophysically relevant single-unit responses with robust information transfer in rat thalamocortical circuits. Importantly, we show that cortical spread of activation from thalamic INS produces more spatially constrained response profiles than conventional electrical stimulation. Owing to observed spatial precision of INS, we used deep reinforcement learning (RL) for closed-loop control of thalamocortical circuits, creating real-time representations of stimulus-response dynamics while driving cortical neurons to precise firing patterns. Our data suggest that INS can serve as a targeted and dynamic stimulation paradigm for both open and closed-loop DBS.