Centre for Electronics Frontiers, Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, UK.
The Gonda Brain Research Center, Bar-Ilan University, Ramat-Gan 52900, Israel.
Sci Adv. 2024 Sep 6;10(36):eadp7613. doi: 10.1126/sciadv.adp7613. Epub 2024 Sep 4.
Implantable devices hold the potential to address conditions currently lacking effective treatments, such as drug-resistant neural impairments and prosthetic control. Medical devices need to be biologically compatible while providing enhanced performance metrics of low-power consumption, high accuracy, small size, and minimal latency to enable ongoing intervention in brain function. Here, we demonstrate a memristor-based processing system for single-trial detection of behaviorally meaningful brain signals within a timeframe that supports real-time closed-loop intervention. We record neural activity from the reward center of the brain, the ventral tegmental area, in rats trained to associate a musical tone with a reward, and we use the memristors built-in thresholding properties to detect nontrivial biomarkers in local field potentials. This approach yields consistent and accurate detection of biomarkers >98% while maintaining power consumption as low as 4.14 nanowatt per channel. The efficacy of our system's capabilities to process real-time in vivo neural data paves the way for low-power chronic neural activity monitoring and biomedical implants.
植入式设备有望解决目前缺乏有效治疗方法的疾病，例如耐药性神经损伤和假肢控制。医疗设备需要具有生物兼容性，同时提供低功耗、高精度、小尺寸和最小延迟的增强性能指标，以实现对大脑功能的持续干预。在这里，我们展示了一种基于忆阻器的处理系统，用于在支持实时闭环干预的时间范围内对行为相关的大脑信号进行单次检测。我们记录了经过训练以将音乐与奖励相关联的大鼠大脑奖励中心腹侧被盖区的神经活动，并使用忆阻器的内置阈值特性来检测局部场电位中的重要生物标志物。这种方法在保持每个通道低至 4.14 纳瓦功耗的情况下，实现了 >98%的生物标志物的一致和准确检测。我们的系统处理实时体内神经数据的能力为低功耗慢性神经活动监测和生物医学植入物铺平了道路。
