Development of minimally invasive, flexible implants for closed-loop cortical sensing and stimulation

皮层电图（ECoG）是一种神经植入接口，由一系列电极组成，作为传感器记录大脑功能。这种类型的神经植入物放置在皮质表面上的硬膜外或硬膜下，允许神经测量的高空间和时间分辨率，并允许映射大脑的大区域。ECoG阵列中的集成电极测量由大脑皮层中的神经元通过与皮层表面直接接触而产生的平均局部电场电位。ECoG传感阵列目前在临床上用于癫痫外科治疗的诊断工具，指导手术干预。先前针对ECoG传感阵列开发的研究集中在使用柔性生物相容性材料作为基底，因为柔性ECoG阵列设计也用于更好地与皮质表面轮廓匹配，提高测量的信噪比。然而，尽管已经探索了灵活的ECoG设计，但ECoG感测和刺激技术仍然是非常侵入性的，需要在比植入的ECoG阵列更大的区域上进行开颅术。由于手术期间感染风险增加，该手术具有高风险，因此通过使用具有形状适应性材料设计的柔性生物电子器件，可以设计可以通过侵入性较小的手术方法（例如锁孔开颅术）植入的ECoG电极阵列。通过降低柔性ECoG传感器的侵入性，可以降低手术风险和成本，增加这些传感器在临床应用中的可用性。因此，我们的项目的目的是通过生物相容性材料和微流体设计的结合，设计可以通过微创手术技术植入的柔性ECoG神经植入物，同时仍然保持现有ECoG技术的高精度和空间分辨率。我们的目标是生产一种ECoG阵列，可以使用微流体滚动，以减少植入的侵入性。使用可以使用微流体扩张的卷起的装置，可以减小所需的开颅手术的尺寸，从而降低植入的风险。为了实现这些项目目标，我们将评估适合ECoG平台的生物相容性和柔性材料。将评估这些材料在体内条件下的长期稳定性以及将微流体设计整合到基底中的能力。选择合适的材料，我们将研究微流体系统设计，可以创建一个灵活的ECoG平台与皮质表面的适当覆盖，可以使用微流体展开。最初将使用模拟皮质表面评价平台易于植入和取出的性能。将电极集成到柔性平台后，将通过加速老化稳定性测试使用电化学阻抗谱法评价电极阻抗和漏电流。通过开发用于医疗诊断和治疗的微创ECoG阵列，该博士学位与EPSRC的传感器和仪器以及临床技术的研究领域保持一致。

Electrocorticography (ECoG) is a neural implanted interface consisting of an array of electrodes acting as sensors to record brain functionality. This type of neural-implant, placed either epi- or subdurally on the cortical surface, allows for both high spatial and temporal resolution of neural measurements and allows for large areas of the brain to be mapped. The integrated electrodes in the ECoG array measure the averaged local electrical field potentials produced by the neurons in the cerebral cortex through direct contact with the cortical surface. ECoG sensing arrays are currently in clinical use a diagnostic tool in surgical epilepsy treatment, guiding surgical intervention. Previous studies aimed at ECoG sensing array development have focused on the use of flexible, biocompatible materials as the substrate, as flexible ECoG array designs also for better contour matching to the cortical surface, improving the signal to noise ratio of the measurements. However, whilst there has been exploration of flexible ECoG designs, ECoG sensing and stimulating technologies are still very invasive, requiring a craniotomy to be performed on an area larger than the implanted ECoG array. This procedure is high risk due to increased risk of infection during the procedure, therefore by using flexible bioelectronics with shape-adaptive material design, an ECoG electrode array could be designed that could be implanted through less invasive surgical methods, such as a keyhole craniotomy. By reducing the invasiveness of flexible ECoG sensors, it allows for the reduction of both surgical risk and cost, increasing the availability of these sensors for clinical applications.Therefore, our project's aim is to design flexible ECoG neural implants that can be implanted with minimally invasive surgical technique through the combination of bio-compatible materials and microfluidic design, whilst still retaining the high accuracy and spatial resolution of existing ECoG technologies. We aim to produce an ECoG array that can be rolled using microfluidics to reduce the invasiveness of implantation. Using a rolled device which can be expanded using microfluidics, the size of the craniotomy required can be reduced, reducing the risk of implantation. To achieve these project aims, we will be evaluating suitable bio-compatible and flexible materials for the ECoG platform. The materials will be assessed for their long-term stability in in-vivo conditions, and their ability to integrate a microfluidics design into the substrate. With a suitable material chosen, we will investigate microfluidic system designs that can create a flexible ECoG platform with a suitable coverage of the cortical surface that can be unrolled using microfluidics. The performance of the platform's ease of implantation and removal will be evaluated initially using simulated cortical surfaces. After integrating electrodes into the flexible platform, the electrode impedance and leakage current will be evaluated using Electrochemical Impedance Spectroscopy through accelerated aging stability tests. By developing minimally-invasive ECoG arrays for medical diagnosis and treatment, this PhD aligns with the EPSRC's research areas of Sensors and Instrumentation, and Clinical Technologies.