Optimising light-tissue interaction to enable multiscale imaging of neuronal dynamics deep within the neocortex

优化光组织相互作用以实现新皮质深处神经元动力学的多尺度成像

• 批准号: EP/W024039/1
• 负责人: Robin Silver
• 金额: $ 244.16万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW024039%2F1
• 关键词: Optimising; light; tissue; interaction; enable

The neocortex plays a central role in learning new motor skills, such as typing, driving a car and playing tennis. Neocortical circuits receive subcortical input and are highly interconnected within and across layers, so their activity arises from both extrinsic input and intrinsic sources. The process of learning is thought to involve modification in the strength of synaptic connections between neurons and changes in neuronal excitability. But how principal neocortical neurons combine 'top down' self generated predictions with 'bottom up' extrinsic feedforward inputs to improve task performance during learning is unknown. A key reason for this is that such information is encoded in brief synaptic signals that are distributed across their large 3D dendritic trees, which span both superficial and deep cortical regions, which are inaccessible to current imaging methods. Although synaptic activity can be detected using optical microscopes that measure fluorescence from genetically encoded reporters, no available imaging technology can monitor synaptic activity that is distributed across all neocortical layers at high spatiotemporal resolution, because image quality is degraded by scattering of light as it passes through brain tissue.The major physical factor limiting imaging in deep tissue is scattering of light. Understanding how light interacts with brain tissue and developing strategies to compensate for the optical distortions caused by scattering are necessary for extending the depth at which optical microscopes can operate effectively. Collaboration at the interface between physics and biology is therefore essential for addressing neocortical processing at the synaptic level, since it requires deeper, faster imaging than currently possible. This project will bring together teams of leading physicists, microscope developers and neuroscientists at UCL and Oxford University with expertise in modelling light-tissue interactions, optical wavefront shaping and in vivo imaging. This cross-discipline collaboration will push the frontiers of deep tissue multiphoton imaging by experimentally measuring and simulating light-tissue interactions and developing strategies for correcting the resulting optical distortions. Predictions from models that link light-tissue interactions to circuit structure will inform optimal strategies for monitoring neural activity. Deeper and higher spatiotemporal resolution of 3D multiphoton imaging will be achieved by novel combinations of two- and three photon microscopy, high speed spatial light modulators and acousto-optic lens 3D scanning. This will allow synaptic population dynamics to be mapped at high spatiotemporal resolution across all the layers of the neocortex for the first time.This research will provide fundamental new insights into how the neocortical neurons contribute to motor learning by imaging the synaptic input across the entire dendritic tree of deep pyramidal cells. This will show how extrinsic feedforward information arriving onto the basal dendrites in deep layers is combined with intrinsic information from cortex conveyed by synaptic inputs in more superficial layers.This will reveal the nature of the information available to pyramidal cells during learning, the dendritic computations performed and provide new insight into the 'learning rules' that could be employed to adjust their synaptic weights during learning. Development of novel multiphoton methods for imaging deeper and faster than is currently possible will enable researchers to investigate the properties of brain and other tissues that were previously inaccessible. Extending the amount of information that we can acquire through microscopic observations requires an understanding of tissue properties, optics and neural dynamics. Advancing our understanding of neocortical function therefore requires a fully integrated approach and cannot be answered if the biological and physical aspects are considered separately.

新皮层在学习新的运动技能方面起着核心作用，比如打字、开车和打网球。新皮层回路接收皮层下输入，并且在层内和层间高度互连，因此它们的活动来自外部输入和内在来源。学习过程被认为涉及神经元之间突触连接强度的改变和神经元兴奋性的变化。但是，主要的新皮层神经元如何联合收割机“自上而下”的自我生成的预测与“自下而上”的外部前馈输入，以提高学习过程中的任务性能是未知的。一个关键的原因是，这些信息被编码在简短的突触信号中，这些信号分布在它们的大型3D树突树中，这些树突树跨越表层和深层皮层区域，这些区域是目前成像方法无法访问的。虽然突触活动可以使用光学显微镜检测荧光从基因编码的报告，没有可用的成像技术可以监测突触活动，分布在所有的新皮层层在高时空分辨率，因为图像质量是由光的散射，因为它通过脑组织降级。了解光如何与脑组织相互作用，并制定策略来补偿散射引起的光学失真，对于扩展光学显微镜有效操作的深度是必要的。因此，在物理学和生物学之间的界面上进行合作对于在突触水平上解决新皮层处理至关重要，因为它需要比目前可能的更深，更快的成像。该项目将汇集UCL和牛津大学的领先物理学家，显微镜开发人员和神经科学家团队，他们在建模光组织相互作用，光学波前整形和体内成像方面具有专业知识。这种跨学科的合作将通过实验测量和模拟光-组织相互作用，并开发校正由此产生的光学失真的策略，推动深层组织多光子成像的前沿。将光组织相互作用与电路结构联系起来的模型的预测将为监测神经活动的最佳策略提供信息。将双光子显微镜、三光子显微镜、高速空间光调制器和声光透镜三维扫描技术相结合，将实现三维多光子成像更深、更高的时空分辨率。这将使突触群体动态映射在高时空分辨率的所有层的新皮层的第一次。这项研究将提供新的见解，新皮层神经元如何有助于运动学习通过成像突触输入整个树突状树的深锥体细胞。这将展示到达深层基底树突的外部前馈信息如何与来自皮层的内在信息相结合，这些信息是由更表层的突触输入传递的。这将揭示锥体细胞在学习过程中可用的信息的本质，树突计算的执行，并提供对“学习规则”的新见解，这些规则可以在学习过程中用于调整突触权重。开发新的多光子方法，使成像比目前可能的更深、更快，将使研究人员能够研究以前无法获得的大脑和其他组织的特性。扩大我们可以通过显微镜观察获得的信息量需要对组织特性，光学和神经动力学的理解。因此，推进我们对新皮层功能的理解需要一个完全整合的方法，如果生物学和物理学方面被分开考虑，就无法回答。