GCR: Synthetic Neurocomputers for Cognitive Information Processing

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The project brings together material scientists and electrical engineers who build synthetic 3D scaffolds with embedded electronic and optoelectronic devices, neuroscientists who culture neural cells on the 3D scaffold to form biological neural networks with precisely defined 3D topology and integrated multimodal information interfaces, chemists and chemical engineers who synthesize functional molecules for controlling the neural cell placement, development, and activity, and computer scientists who operate the neurocomputer prototype and extract its information-coding and processing algorithms with machine-learning methods. The goals of the project are to contribute to the grand challenge of reverse engineering the brain and open up new computing paradigms based on cultured biological neural networks to propel machine learning and artificial intelligence to the next level. The neurocomputer prototype pursued in the project employs biological neuronal circuits engineered into well-defined 3D topologies reminiscent of deep-neural-network models as the information-processing units. Electronic and optoelectronic devices will be integrated with each neural cell to administer and monitor the neuronal and synaptic activities based on electrophysiology, optogenetics, and neurochemistry. The fabricated neurocomputer prototype will then be utilized to perform various learning and computing tasks such as image recognition and space navigation. Neural code and learning algorithms will be extracted using a combination of experiment and simulations based on spike generation models and recurrent neural network models. The results will help reveal how complex living neural networks function and provide a technologically transformative approach to information-processing machines.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.