Biomimetic Surface for Neural Implants

描述(申请人提供)：R01：神经植入的仿生表面PI：Tracy Cui用于神经记录和刺激的植入式微电极阵列显示了巨大的研究和临床潜力。脑组织对神经电极阵列的反应研究揭示了局部的小胶质细胞激活，紧随其后的是星形细胞疤痕和神经变性。这些反应被认为是导致神经记录的低产率和长期失败的原因，尽管直接联系还没有得到充分的建立。过去关于中枢神经系统对植入物反应的研究使用了离散时间点的死后组织学。这种方法存在很大的变异性，无法捕捉宿主分子、细胞和血管的动态变化。为了解决这个问题，我们开发了一种实验装置，使用双光子显微镜结合电子记录直接成像活体动物的电极-组织界面。我们以前的工作表明，通过在神经探针表面涂覆神经黏附分子，可以提高装置周围的神经元密度，同时减弱神经胶质反应。同时，神经记录的质量也有了显著的提高。我们假设，促进神经元生长和健康，和/或抑制小胶质细胞激活将导致记录的改善。该项目的具体目标是研究涂层对记录的影响的生物学机制，并在脑机接口(BMI)模型中评估仿生涂层的临床潜力。首先，使用双光子成像和电记录技术，在转基因动物身上进行为期两周的急性神经元和小胶质细胞对包被探针的反应。实时组织特征(如神经元和轴突密度、小胶质细胞密度和形态、血管改变和血脑屏障泄漏)将与记录指标(如单位产量、信噪比、信号和噪声的幅度以及阻抗)相关。几个促进或抑制神经元生长或小胶质细胞激活的生物分子将被固定在BlackRock阵列上，以验证我们的假设。其次，通过在大鼠体内进行6个月的最佳涂层条件的测试，确定涂层在记录中的长期效益。每月将采集外植体以检查涂层的寿命，同时将对界面上的组织进行免疫组织化学和微阵列分析，以表征细胞和分子随时间的变化。第三，评估仿生涂层在临床上的应用潜力 电极将在脑-机-接口(BMI)模型中在恒河猴身上进行测试。记录指标，如信噪比、信号幅度、单位产量和稳定性将在两年内量化，并与未镀膜的阵列进行比较。将开发一种新的功能度量来评估记录信号的功能。BMI性能将基于速度和准确性进行评估。这一建议结合了尖端的实时成像、有效的生物材料策略和最先进的脑机接口技术，以了解神经植入物与宿主组织之间的相互作用。这些发现将指导BMI、视觉和听觉假体、帕金森氏病、抑郁症和癫痫等深部脑刺激等无缝神经接口设备的开发。这一知识也将使其他脑植入物受益，从生化传感和治疗性输送到支架和干细胞移植，用于治疗神经疾病。

DESCRIPTION (provided by applicant): R01:Biomimetic Surface for Neural Implant PI: Tracy Cui Implantable microelectrode arrays for neural recording and stimulation have demonstrated tremendous research and clinical potential. Studies of brain tissue response to neural electrode arrays have revealed localized microglia activation, followed by astrocytic scarring and neural degeneration. These reactions are thought to contribute to the low yield and chronic failure of neural recording, although direct links have not been soundly established. Past studies characterizing the CNS response to implants have used postmortem histology at discrete time points. This approach suffers from a large degree of variability and fails to capture the dynamic molecular, cellular and vascular changes of the host. To address this issue, we have developed an experimental set-up to directly image the electrode-tissue interface in live animals using 2-photon microscopy in conjunction with electrical recording. Our previous work indicates that by coating the surface of neural probes with neural adhesion molecules, neuronal density around the device can be promoted while glial reaction attenuated. Meanwhile, neural recording quality is drastically improved. We hypothesize that promoting neuronal growth and health, and/or inhibiting microglia activation will lead to recording improvement. The specific objectives of thi project are to investigate the biological mechanisms of the coating's effect on recording and to evaluate the clinical potential of biomimetic coating in a brain machine interface (BMI) model. First, the acute neuronal and microglia responses to coated probes will be characterized in transgenic animals using two photon imaging and electrical recording for two weeks. Real time tissue characteristics (such as neuronal and neurite density, microglia density and morphology, vasculature change and BBB leakage) will be correlated to recording metrics(such as unit yield, SNR, amplitude of signal and noise as well as impedance). Several biomolecules that promote or inhibit neuronal growth or microglia activation will be immobilized on the Blackrock arrays to test our hypothesis. Secondly, the long-term benefit of the coatings on recording will be determine by testing the optimum coating conditions in rats for 6 months. Explants will be taken monthly to examine the coating longevity, while immunohistochemistry and microarray analysis of the tissue at the interface will be performed to characterize the cellular and molecular change over time. Thirdly, to assess the potential of biomimetic coating for clinical application, coated electrodes will be tested in rhesus monkeys in a brain-machine-interface (BMI) model. Recording metrics such as SNR, signal amplitude, unit yield and stability will be quantified over 2 years and compared to uncoated arrays. A novel functional metric will be developed to assess functionality of the recorded signals. BMI performance will be evaluated based on speed and accuracy. This proposal combines the cutting edge real-time imaging, effective biomaterial strategies and state of the art brain machine interface technology to understand the interactions between neural implants and host tissue. The findings will guide the development of seamless neural interface devices for BMI, visual and auditory prosthesis, deep brain stimulation for Parkinson's disease, depression and epilepsy, to name a few. The knowledge will also benefit other brain implants from biochemical sensing and therapeutic delivery to scaffold and stem cell transplant for treating neurological disorders.