The field of neuroscience is undergoing a rapid transformation, and within the next decade, it may become possible to capture data from millions of individual neurons at the same time. Such a technological advancement would allow scientists to record and analyze a significant fraction of the brain's neural network at unprecedented spatial and time resolutions. The goal of this research project is to advance our understanding of brain activity through the integration of bioengineering, systems neuroscience and data science and their application to the study of networks of neurons. The research team will engineer new sensors designed to image the activity of individual neurons within a large network and then apply this method to the study of functioning neural systems. The team will also develop computational methods to extract information from the resulting, extremely large datasets. This research will have broader impact through training STEM students in a convergent science area and through deepening our understanding of the science underlying neurological disease and thereby improving mental health treatment.
This research project aims to create novel protein sensors to acquire single-neuron-resolution imaging data. This methodology could serve as the basis for ultra-large-scale neural network imaging. The researchers will establish the architectural principles and fundamental limits for fluorescence imaging systems and inference algorithms that extract underlying neural activity. They will then develop machine learning techniques to extract network-level phenomena from high-dimensional neural data. Finally, the researchers will study large networks of neurons during behavior and learning via carefully-designed experiments and machine learning techniques. The technologies developed in this work, to acquire and to analyze, single-neuron-resolution imaging data, will facilitate the understanding of brain's neural network computation at an ultra-large scale, directly confronting challenging societal problems related to the human brain. The project participants will also educate the next generation of engineers and scientists in the convergent area of neuroscience with data science.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
