Micro-Electronics for autonomous neural implants

可植入的神经接口可用于将人脑连接到人造电子电路，例如通过思想控制计算机或治疗各种伤害和疾病。这样的一个例子是通过绕过受损的神经连接并允许控制假肢来治疗脊髓损伤的可能性。这是通过将电极插入连接到仪器电路的神经组织中来实现的，仪器电路记录由活跃神经元产生的电子电位并解码其含义。虽然过去的解决方案通常依赖于记录单个神经元产生的细胞外动作电位（EAP），也称为神经尖峰，但本项目的目的是专注于局部场电位（LFP）的获取和处理。这是因为EAP记录植入物通常受到有限寿命的阻碍，这是由于宿主的异物反应导致疤痕组织生长充当空间和频率低通滤波器，因此限制了记录的高频EAP的保真度。LFP的低频特性可以显著降低疤痕组织生长对记录的影响。一些涉及的挑战包括电极材料的选择。这必须确保当与脑脊液接触时，在LFP的频带内增加的热噪声最小，同时是化学惰性和医学无害的。初步结果表明，铌（Nb）是一种有前途的材料，适用于这种记录，因为已知它是生物惰性的，通常用于例如牙科植入物。其极化性导致LFP频带中的噪声功率密度通常小于常用的铂和钨，使其成为神经记录的合适候选材料。另一个挑战是采集电子学的发展，这在很大程度上受到神经组织散热安全极限（80 mW/cm ^2）的限制。允许减少所用能量的技术之一是无时钟信号采集，也称为连续时间（CT）信号采集。这种方法导致依赖于活动的电路，仅当在其输入端检测到活动时才使用能量。该项目的目的之一是调查此类电路用于获取LFP的适用性和可能的优势。由于这种采集和采样过程的特性在很大程度上仍然未知，因此使用数学模拟进行调查。这是由集成电路的设计和实际测量验证理论模型所产生的假设的补充。这已经导致制定了一个最低要求，以满足，以防止类似的奈奎斯特定理，适用于普通采样混叠。此外，提出了一种新的方法，允许减少闪烁噪声在CT采样已提出和理论验证。设计、制造和测试验证这一理论的集成电路。这项工作是ENGINI项目的一部分，旨在设计下一代神经植入物，通过完全无线、尺寸最小、针对LFP记录并允许形成分布式植入网络来实现上级慢性化。该研究与以下EPSRC研究领域保持一致：辅助技术、康复和肌肉骨骼生物力学;微电子器件技术

Implantable neural interfaces can be used to connect human brains to artificial electronic circuits allowing e.g. control of computers by thoughts or treatment of various injuries and illnesses. An example of such is the possibility of treating spinal cord injuries by bypassing the damaged neural connection and allowing control of artificial limbs. This is achieved by inserting electrodes into neural tissue connected to instrumentation circuits recording electronic potentials generated by active neurons and decoding their meaning. While past solutions typically relied on recording of extracellular action potentials (EAPs), also known as neural spikes, generated by single neurons, the aim of this project is to focus on acquisition and processing of local field potentials (LFPs). This is as EAP-recording implants are typically hindered by limited lifetime due to the host body's foreign body response leading to scar tissue growth acting as a spatial and frequential low-pass filter, hence limiting the fidelity of recorded high-frequency EAPs. The low-frequency nature of LFPs allows for a significant reduction of the effect scar-tissue growth has on the recording.Some of the involved challenges include selection of electrode material. This has to ensure minimal added thermal noise within the frequency band of LFPs when in contact with cerebrospinal fluid while at the same time being chemically inert and medically harmless. Preliminary results have shown Niobium (Nb) as a promising material suitable for such a recording as it is known to be biologically inert and is commonly used e.g. in dental implants. Its polarizability leads to generally smaller noise power densities in LFP frequency bands than commonly used platinum and tungsten making it a suitable candidate material for neural recordings. This is to be investigated by direct noise measurements in electrolytes and subsequently verified by direct in-vivo measurements.Another challenge lies in the development of acquisition electronics which is greatly constrained by limits imposed on their power consumption governed by safety limits of heat dissipation in neural tissue on the order of 80 mW/cm^2. One of the techniques allowing reduction of used energy is clock-less, also known as continuous-time (CT), acquisition of signals. This approach leads to activity-dependent circuits that only use energy when activity is detected at their input. One of the aims of this project is to investigate the suitability and possible advantages of such circuits for acquisition of LFPs. As properties of such acquisition and sampling processes remain to a large extent unknown, mathematical simulations are used for their investigation. This is complemented by design of integrated circuits and practical measurements verifying hypotheses arising from theoretical models. This has already led to formulation of a minimal requirement to be satisfied in order to prevent aliasing similar to the Nyquist theorem which applies to ordinary sampling. In addition a novel method allowing reduction of flicker noise in CT sampling has been proposed and theoretically validated. An integrated circuit verifying this theory is to be designed, manufactured and tested.This work is part of the ENGINI project with an aim to design the next generation of neural implants that achieve superior chronicity by being completely wireless, minimal in size, targeting LFP recordings and allowing formation of distributed implant networks.The research aligns with the following EPSRC Research Areas: Assistive technology, rehabilitation and musculoskeletal biomechanics; Microelectronic device technology