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Imitating and exploring the human brain's resting and task-performing states via brain computing: scaling and architecture

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National Science Review 2024年第5期11卷 17-28页

作者： Wenlian Lu Longbin Zeng Jiexiang Wang Shitong Xiang Yang Qi Qibao Zheng Ningsheng Xu Jianfeng Feng dtb consortium Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence(Fudan University) Ministry of Education Fudan University Shanghai Center for Mathematical Sciences Fudan University Department of Computer Science University of Warwick Zhangjiang Fudan International Innovation Center Fudan University

A computational human brain model with the voxel-wise assimilation method was established based on individual structural and functional imaging data. We found that the more similar the brain model is to the biological counterpart in both scale and architecture, the more similarity was found between the assimilated model and the biological brain both in resting states and during tasks by quantitative metrics. The hypothesis that resting state activity reflects internal body states was validated by the interoceptive circuit's capability to enhance the similarity between the simulation model and the biological brain. We identified that the removal of connections from the primary visual cortex(V1) to downstream visual pathways significantly decreased the similarity at the hippocampus between the model and its biological counterpart,despite a slight influence on the whole brain. In conclusion, the model and methodology present a solid quantitative framework for a digital twin brain for discovering the relationship between brain architecture and functions, and for digitally trying and testing diverse cognitive, medical and lesioning approaches that would otherwise be unfeasible in real subjects.

关键词： digital twin brain computational cortico-subcortical model fMRI data assimilation interoceptive circuit

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