NCS-FO: Super resolution Mapping of Multi-scale Neuronal circuits Using Flexible Transparent Arrays

NCS-FO：使用灵活透明阵列的多尺度神经元电路的超分辨率映射

• 批准号: 1734940
• 负责人: Piya Pal
• 金额: $ 50万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734940&HistoricalAwards=false
• 关键词: NCS; FO; Super; resolution; Mapping

Understanding the structural and functional components of the brain that underlie perception, cognition and action, is crucial for developing next generation neural prostheses, brain machine interfaces, and discovering preventive measures against neurological disorders. Optical technologies have enabled us to record and infer neural activity with single-cell resolution. However, they are limited by low temporal resolution, and often fail to accurately capture the neural dynamics at the milli-second time scales. Electrophysiology, on the other hand, provides higher temporal resolution, but single-cell electrophysiology usually suffers from low throughput, and recordings that cover larger spatial scales suffer from poor spatial resolution, making it difficult to decipher neural activity at cellular scale from large areas. Realizing that micro-scale optical imaging and macro-scale electrophysiological recording possess complementary strengths in terms of spatial and temporal resolution, this multidisciplinary project will combine the two recording modalities using innovations in neural engineering, multi-modal imaging and signal processing, to understand neural activity at previously unattained temporal and spatial resolution. Such a capability will lead to new discoveries on information processing in the brain and circuit dysfunctions for neurological disorders (epilepsy, depression, memory disorders, etc.), affecting one billion people worldwide. Recording and resolving neural activity with enhanced resolution can drive the development of next-generation of brain computer interfaces for restoring vision, hearing, and movement. The outcomes of this project will also be integrated into developing interdisciplinary educational materials for training the next generation of neuroengineers, neuroscientists and signal processing experts. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).The project has three main technical components that consist of development of novel electrode arrays, careful design of multi-modal imaging experiments, and advanced signal processing techniques for solving ill-posed inverse problems. Simultaneous multiphoton imaging and electrophysiology experiments enabled by novel electrode arrays will generate brand new datasets which will be processed by new data-driven super-resolution algorithms that judiciously exploit the complementary strengths of the two imaging modalities. The key idea is to cast the fusion problem within the mathematical framework of bilinear problems, and exploit sparsity of the underlying neural activity as a key ingredient in solving the inverse problem by fusing the datasets obtained from optical and electrophysiological recordings. The mathematical principles and algorithms used for creating super-resolution images by fusing signals with complementary attributes have broader applicability beyond neural imaging, and can be used for developing more efficient solutions for ill-posed inverse problems that arise in diverse imaging applications.

了解大脑的结构和功能组成部分是感知，认知和行动的基础，对于开发下一代神经假体，脑机接口以及发现预防神经系统疾病的措施至关重要。光学技术使我们能够以单细胞分辨率记录和推断神经活动。然而，它们受到低时间分辨率的限制，并且通常无法准确地捕获毫秒时间尺度上的神经动力学。另一方面，电生理学提供了更高的时间分辨率，但单细胞电生理学通常具有低通量，并且覆盖较大空间尺度的记录具有较差的空间分辨率，使得难以从大面积上破译细胞尺度上的神经活动。认识到微观尺度的光学成像和宏观尺度的电生理记录具有互补的优势，在空间和时间分辨率方面，这个多学科的项目将联合收割机的两个记录模式，使用创新的神经工程，多模态成像和信号处理，了解神经活动在以前没有达到的时间和空间分辨率。这种能力将导致对大脑中的信息处理和神经系统疾病（癫痫、抑郁、记忆障碍等）的电路功能障碍的新发现，影响着全球10亿人以更高的分辨率记录和解析神经活动可以推动下一代脑机接口的发展，以恢复视觉，听觉和运动。该项目的成果也将被纳入开发跨学科的教育材料，用于培训下一代神经工程师，神经科学家和信号处理专家。该项目由理解神经和认知系统的综合策略（NSF-NCS）资助，这是一个由计算机和信息科学与工程（CISE），教育和人力资源（EHR），工程（ENG）以及社会，行为和经济科学（SBE）董事会联合支持的多学科计划。该项目有三个主要技术组成部分，包括新型电极阵列的开发，多模态成像实验的精心设计，以及用于解决不适定逆问题的先进信号处理技术。由新型电极阵列实现的同步多光子成像和电生理学实验将生成全新的数据集，这些数据集将由新的数据驱动的超分辨率算法处理，这些算法明智地利用了两种成像模式的互补优势。其关键思想是将融合问题置于双线性问题的数学框架内，并通过融合从光学和电生理记录中获得的数据集，将底层神经活动的稀疏性作为解决逆问题的关键成分。用于通过融合具有互补属性的信号来创建超分辨率图像的数学原理和算法具有超出神经成像的更广泛的适用性，并且可以用于为在各种成像应用中出现的不适定逆问题开发更有效的解决方案。

项目成果

Decoding ECoG High Gamma Power from Cellular Calcium Response using Transparent Graphene Microelectrodes

使用透明石墨烯微电极从细胞钙响应中解码 ECoG 高伽玛功率

• DOI: 10.1109/ner.2019.8717147
• 发表时间: 2019
• 期刊: 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER
• 作者: Liu, Xin;Ren, Chi;Lu, Yichen;Hattori, Ryoma;Shi, Yuhan;Zhao, Ruoyu;Ding, David;Komiyama, Takaki;Kuzum, Duygu
• 通讯作者: Kuzum, Duygu

Multimodal neural recordings with Neuro-FITM uncover diverse patterns of cortical-hippocampal interactions.

• DOI: 10.1038/s41593-021-00841-5
• 发表时间: 2021-06
• 期刊: Nature neuroscience
• 影响因子: 25
• 作者: Liu X;Ren C;Lu Y;Liu Y;Kim JH;Leutgeb S;Komiyama T;Kuzum D
• 通讯作者: Kuzum D