All-optical electrophysiology: probing real-time dynamics of neural circuits

全光学电生理学：探测神经回路的实时动态

• 批准号: BB/W010623/1
• 负责人: Jacques Carolan
• 金额: $ 51.8万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FW010623%2F1
• 关键词: optical; electrophysiology; probing; real; time

Understanding how patterns of electrical signals within the brain give rise to complex behaviour --- the 'neural code' --- is critical for not only discovering the neural basis of fundamental processes such as learning, decision making and cognition; but also for treating neuropsychiatric pathologies and motor impairments. The challenge is that unlike a computer, the neurons in the brain are highly recurrent, nonlinear and have long range interactions that vary across very short (millisecond) and very long (years) times-scales. The overall aim of this fellowship is to develop a tool that can dynamically interact with the brain at sufficient scale and resolution to reverse-engineer the neural circuitry. Much like how self driving cars build a model of the world (e.g. other cars, road geometry, road surface) by dynamically interacting with it (accelerating, braking, imaging); the systems proposed here will dynamically interrogate populations of neurons --- at cellular-level resolution and with temporal dynamics comparable to individual action potentials --- to generate models of key neural processes and 'reverse engineer' the neural circuitry. Such a system would not only have radical implications for our understanding of basic processes such neural representation; but also could be used to 'drive' neuronal circuits, which would enable new frontiers in brain machine interfaces for neuropsychiatric prosthetics and clinical applications such as seizure prevention.The gold-standard for interrogating electrical signals from individual neurons are electrophysiology techniques. However these require bulky electrical probes to be inserted into the brain, making it impossible to access large populations of neurons. Instead, I will address neuronal circuits using an entirely different modality: light. Nature has provided us with light sensitive proteins that can either optically report electrical changes with variations in fluorescence or generate an electrical signal under optical excitation. By engineering these proteins into neurons, it is possible to optically readout and control electrical activity in the brain. This fellowship will perfect a new type of reporter called a 'voltage indicator' that directly reports action potentials rather than proxies for voltage change, such as calcium variations. Calcium changes happen two orders of magnitude slower than a typical action potential, meaning that critical timing information is lost. In contrast, voltage indicators observe action potentials in real-time, which is critical for dynamically interacting with the brain --- a self-driving car with a camera delay would quickly crash! To keep pace with these rapid dynamics, I will develop ultra-fast optical hardware to readout and control electrical signals all within the time it takes an action potential to propagate, and at sufficient scale to access neuronal circuits. Moreover, by closing the loop between readout and control, it will be possible to trigger a neuron to spike, then 'track' the neurons that respond, thus determining the wiring diagram. This 'all-optical' approach enables high-throughput cellular resolution connectomics (i.e. functional connection mapping of circuits) in vivo, and would be transformative to our understanding of the structure of the nervous system, e.g. for identifying circuit defects in neuropsychiatric disorders.This fellowship, hosted at the Wolfson Institute for Biomedical Research at UCL, builds tools to ask entirely new questions about the function and structure of the brain, which are not possible using existing technology. It would have wide ranging applications in neuroscience and beyond (including cardiac, renal, and hepatic physiology). The proposed fellowship is therefore very well aligned with the BBSRC priority area 'biosciences for health' under the 'technology development for the biosciences' responsive mode priority.

了解大脑内电信号的模式如何产生复杂的行为 - “神经代码” - 不仅对于发现诸如学习，决策和认知等基本过程的神经基础至关重要；而且还用于治疗神经精神科病理和运动障碍。面临的挑战是，与计算机不同，大脑中的神经元是高度复发的，非线性的，并且在很短的（毫秒）和很长的时间（年度时间）中，它们的远距离相互作用会有所不同。该奖学金的总体目的是开发一种可以以足够的尺度和分辨率动态与大脑相互作用的工具，以逆转神经回路。就像自动驾驶汽车如何通过动态相互作用（加速，制动，成像）来建立世界模型（例如其他汽车，道路几何，道路表面）；此处提出的系统将在细胞级分辨率上动态询问神经元的种群，并且具有与个体动作电位相当的时间动力学 - 以生成关键神经过程的模型和“反向工程师”神经回路的模型。这样的系统不仅对我们对这种神经表示的基本过程的理解具有根本的影响。但也可以用于“驱动”神经元电路，这将使脑机界面中的新边界用于神经精神肢体的假体和临床应用，例如预防癫痫发作。但是，这些要求将笨重的电探针插入大脑中，从而无法进入大量神经元。相反，我将使用完全不同的方式来解决神经元电路：光。大自然为我们提供了光敏蛋白质，可以通过光学地报告荧光变化的电动变化，或者在光激发下产生电信号。通过将这些蛋白质设计到神经元中，可以在大脑中光学读数和控制电活动。该奖学金将完善一种称为“电压指标”的新类型的记者，该记者直接报告动作电位，而不是电压变化的代理，例如钙变化。钙变化发生了两个数量级的速度比典型的动作电位慢，这意味着关键的时机信息丢失了。相比之下，电压指示器可实时观察动作电位，这对于与大脑动态互动至关重要---带有相机延迟的自动驾驶汽车会迅速崩溃！为了跟上这些快速动力学的步伐，我将开发超快速的光学硬件，以读取和控制电信号，这些电信在需要传播的动作潜力的时间内，并以足够的规模访问神经元电路。此外，通过关闭读数和控制之间的循环，可以触发神经元尖峰，然后“跟踪”响应的神经元，从而确定接线图。这种“全光”方法可以使高通量细胞分辨率连接（即电路的功能连接映射）体内，并且可以转化为我们对神经系统结构的理解，例如为了确定神经精神疾病的电路缺陷。该奖学金在UCL的沃尔夫森生物医学研究所主持，建立了工具，以提出有关大脑功能和结构的全新问题，而这些问题是不可能使用现有技术的。它将在神经科学及其他地区（包括心脏，肾脏和肝生理学）中具有广泛的应用。因此，拟议的奖学金与“生物科学技术开发”响应模式优先级的BBSRC优先领域的“健康生物科学”非常一致。