Author

Chonghe Hao

Chinese Academy of Sciences

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Organism:mouse· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Tielin ZhangiD· 2 shared Wangzi YaoiD· 2 shared X S CheniD· 2 shared Bo XuiD· 1 shared Jian ZhangiD· 1 shared Junhua ZhangiD· 1 shared Mu‐ming PooiD· 1 shared Shuncheng JiaiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersNeuroscience

Tielin ZhangORCID

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2 papers

Recent·Most cited

Incorporation of single-neuron projectome-based connectivity motifs enhances the cortex-specific performance of artificial neural networks

Yue Sun, Wangzi Yao, Jian Zhang, W Song, Xuanle Zhao, Chonghe Hao, X S Chen, Shuxin Zeng, Shuncheng Jia, Yi Yang, Xiong Xiao, Mu‐ming Poo, Yangang Sun, Bo Xu, Tielin Zhang

This paper develops a connectome-informed neural network algorithm that improves RNN and LLM performance by incorporating natural cortical connectivity motifs.

bioRxiv · Jun 17, 2026 · PreprintNeuroscience

DigiMus: a connectome-informed spiking framework for multi-region mouse neural-behavior modeling

Yantong Liu, Xinhe Zhang, X S Chen, Chonghe Hao, Wangzi Yao, Junhua Zhang, Y W Sun, Tielin Zhang

DigiMus integrates connectome-derived structural priors into a spiking neural network framework for mouse neural-behavior modeling, showing improved performance in complex tasks.

bioRxiv · Jun 11, 2026 · PreprintNeuroscience