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.
