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Qu L, Li Y, Xie P, et al. Cross-modal coherent registration of whole mouse brains. Nat Methods. 2021;19(1):111-118doi: 10.1038/s41592-021-01334-w.
Qu, L., Li, Y., Xie, P., Liu, L., Wang, Y., Wu, J., Liu, Y., Wang, T., Li, L., Guo, K., Wan, W., Ouyang, L., Xiong, F., Kolstad, A. C., Wu, Z., Xu, F., Zheng, Y., Gong, H., Luo, Q., Bi, G., Dong, H., Hawrylycz, M., Zeng, H., & Peng, H. (2022). Cross-modal coherent registration of whole mouse brains. Nature methods, 19(1), 111-118. https://doi.org/10.1038/s41592-021-01334-w
Qu, Lei, et al. "Cross-modal coherent registration of whole mouse brains." Nature methods vol. 19,1 (2022): 111-118. doi: https://doi.org/10.1038/s41592-021-01334-w
Qu L, Li Y, Xie P, Liu L, Wang Y, Wu J, Liu Y, Wang T, Li L, Guo K, Wan W, Ouyang L, Xiong F, Kolstad AC, Wu Z, Xu F, Zheng Y, Gong H, Luo Q, Bi G, Dong H, Hawrylycz M, Zeng H, Peng H. Cross-modal coherent registration of whole mouse brains. Nat Methods. 2022 Jan;19(1):111-118. doi: 10.1038/s41592-021-01334-w. Epub 2021 Dec 09. PMID: 34887551.
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Nat Methods. 2022 Jan;19(1):111-118. doi: 10.1038/s41592-021-01334-w. Epub 2021 Dec 09.

Cross-modal coherent registration of whole mouse brains.

Nature methods

Lei Qu, Yuanyuan Li, Peng Xie, Lijuan Liu, Yimin Wang, Jun Wu, Yu Liu, Tao Wang, Longfei Li, Kaixuan Guo, Wan Wan, Lei Ouyang, Feng Xiong, Anna C Kolstad, Zhuhao Wu, Fang Xu, Yefeng Zheng, Hui Gong, Qingming Luo, Guoqiang Bi, Hongwei Dong, Michael Hawrylycz, Hongkui Zeng, Hanchuan Peng

Affiliations

  1. Ministry of Education Key Laboratory of Intelligent Computation & Signal Processing, Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Electronics and Information Engineering, Anhui University, Hefei, China.
  2. SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China.
  3. Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
  4. Ministry of Education Key Laboratory of Developmental Genes and Human Disease, School of Life Science and Technology, Southeast University, Nanjing, China.
  5. School of Computer Engineering and Science, Shanghai University, Shanghai, China.
  6. Department of Cell, Developmental & Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  7. Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  8. CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China.
  9. Tencent Jarvis Lab, Shenzhen, Guangdong, China.
  10. Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China.
  11. HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China.
  12. CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai, China.
  13. School of Biomedical Engineering, Hainan University, Haikou, China.
  14. Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, China.
  15. Center for Integrative Connectomics, Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  16. Allen Institute for Brain Science, Seattle, WA, USA.
  17. SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China. [email protected].
  18. Allen Institute for Brain Science, Seattle, WA, USA. [email protected].

PMID: 34887551 DOI: 10.1038/s41592-021-01334-w

Abstract

Recent whole-brain mapping projects are collecting large-scale three-dimensional images using modalities such as serial two-photon tomography, fluorescence micro-optical sectioning tomography, light-sheet fluorescence microscopy, volumetric imaging with synchronous on-the-fly scan and readout or magnetic resonance imaging. Registration of these multi-dimensional whole-brain images onto a standard atlas is essential for characterizing neuron types and constructing brain wiring diagrams. However, cross-modal image registration is challenging due to intrinsic variations of brain anatomy and artifacts resulting from different sample preparation methods and imaging modalities. We introduce a cross-modal registration method, mBrainAligner, which uses coherent landmark mapping and deep neural networks to align whole mouse brain images to the standard Allen Common Coordinate Framework atlas. We build a brain atlas for the fluorescence micro-optical sectioning tomography modality to facilitate single-cell mapping, and used our method to generate a whole-brain map of three-dimensional single-neuron morphology and neuron cell types.

© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.

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