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Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
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High Reconstructability of Degree-Heterogeneous Networks

Jia-Jie Qin1, Gang Yan1

  • 1Tongji University, Tongji University, Shanghai Research Institute for Intelligent Autonomous Systems, and School of Physical Science and Engineering, Shanghai 200092, People's Republic of China and National Key Laboratory of Autonomous Intelligent Unmanned Systems, MOE Frontiers Science Center for Intelligent Autonomous Systems, and MOE Key Laboratory of Advanced Micro-Structured Materials, Shanghai 200092, People's Republic of China.

Physical Review Letters
|April 18, 2025
PubMed
Summary

Network reconstruction accuracy improves with greater degree heterogeneity in scale-free networks. This finding holds true for empirical networks, suggesting network structure impacts data-driven reconstruction success.

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