Abstract

Info

Author(s):: XU Longchun1; ZHANG Minfeng1; ZHANG Gang2; ZOU Yue2; ZHAO Wenbo2; HE Lemin3; ZHOU Huijing3; YAN Shumin3; ZHANG Guangyu3; 1. Department of Medical Imaging, the Second Affiliated Hospital of Shandong First Medical University (Shandong Academy of Medical Sciences), Tai’an 271000, China; 2. Department of Otorhinolaryngology, the Second Affiliated Hospital of Shandong First Medical University (Shandong Academy of Medical Sciences), Tai’an 271000, China; 3. Department of Radiology, Shandong First Medical University (Shandong Academy of Medical Sciences), Tai’an 271016, China

Keywords:: Keywords: virtual digital brain; brain science; brain-inspired artificial intelligence; causal connectivity network; functional magnetic resonance imaging

Abstract:: Abstract: Objective To provide a software research platform for brain science and brain-inspired artificial intelligence. Methods Firstly, a causal connection network was constructed on the basis of preprocessed resting-state functional magnetic resonance imaging data by a causal connectivity method. The regression coefficients of a nodal neural activity prediction model were obtained by the least-mean-square error algorithm. Then, the virtual digital brain was constructed based on the causal connection network and the prediction model. Finally, a software package which can implement all functions of virtual digital brain was developed by C/C++ programming language in the VC++12.0 development environment. Results Compared with the European virtual brain software platform, the proposed software package was easy to operate and could be applied to the researches on brain science and brain-inspired artificial intelligence. Conclusion The results of preliminary practices confirm the validity and application value of the software in the research on brain science.