As the number of neuronal images in the Brain Research Center’s database increases dramatically, two fundamental questions need to be answered. First, how do we analyze neuronal images using the techniques of big data? Second, how to transform these images into a working model of the brain. To overcome this challenge, we are pursuing three directions.
(1) To grasp the whole picture of how signals are transmitted in the brain, we aim to analyze fly brain images, and construct a high-resolution fly connectome database. We then can use our connectome database to investigate features of the brain’s network architecture using deep learning and other heuristic algorithms.
(2) To investigate how a fly brain computes, we use fly connectomic data to simulate the dynamics of the fly brain.
(3) To inspire a new generation of novel and efficient machine learning and AI algorithms, we examine the structure and dynamics of realistic fly neural networks. Here we hope to uncover how evolution, has addressed the same or similar problems.
To achieve the aforementioned goals, we recruit researchers across all disciplines, including neurobiology, physics, and informatics. In addition to the development of image analysis techniques, we also have constructed the first whole fly brain network model. Moreover, we cooperate with other international research groups who curate other fly brain databases.
Investigate the fundamental principles of neural computing and implement neural computing principles to advance AI research. Furthermore, we also assist other divisions performing big data analysis.