Evidence map›Paper›PMID 34887551›Full record

ArticleNature methods2022

Cross-modal coherent registration of whole mouse brains.

Lei Qu, Yuanyuan Li, Peng Xie, Lijuan Liu, Yimin Wang, Jun Wu, Yu Liu, Tao Wang, Longfei Li, Kaixuan Guo and 14 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
16.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 85 citations in OpenAlex.

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  18. BIFROST: A method for registering diverse imaging datasets of theProceedings of the National Academy of Sciences of the United States of America · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors at 11 institutions in 2 countries.

Lei Qu *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.ORCID http://orcid.org/0000-0002-2129-5253
Yuanyuan Li *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.
Peng XieSEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China.
Lijuan LiuSEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China.
Yimin WangSEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China.ORCID http://orcid.org/0000-0003-2515-6602
Jun WuMinistry 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.
Yu LiuMinistry 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.
Tao WangMinistry 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.
Longfei LiMinistry 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.
Kaixuan GuoMinistry 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.
Wan WanMinistry 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.
Lei OuyangMinistry 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.
Feng XiongSEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China.
Anna C KolstadDepartment of Cell, Developmental & Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0003-2256-3739
Zhuhao WuDepartment of Cell, Developmental & Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Fang XuCAS 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.
Yefeng ZhengTencent Jarvis Lab, Shenzhen, Guangdong, China.ORCID http://orcid.org/0000-0003-2195-2847
Hui GongBritton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China.
Qingming LuoBritton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China.ORCID http://orcid.org/0000-0002-6725-9311
Guoqiang BiInstitute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
Hongwei DongCenter for Integrative Connectomics, Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Michael HawrylyczAllen Institute for Brain Science, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-5741-8024
Hongkui ZengAllen Institute for Brain Science, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-0326-5878
Hanchuan PengSEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China. h@braintell.org.ORCID http://orcid.org/0000-0002-3478-3942
Anhui University · CNAllen Institute for Brain Science · USSoutheast University · CNIcahn School of Medicine at Mount Sinai · USCenter for Excellence in Brain Science and Intelligence Technology · CNHainan University · CNShanghai University of Engineering Science · CNShenzhen Institutes of Advanced Technology · CNTencent (China) · CNUniversity of California, Los Angeles · USUniversity of Science and Technology of China · CN

Funding

Generation of novel cell type specific mouse genetic toolsU19MH114830 · NIMH · ALLEN INSTITUTE · PI NGAI, JOHN J. · 2017 to 2021
$64.7M
6 · The paper itself

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.

Indexed as

AlgorithmsAnimalsBrainDeep LearningImaging, Three-DimensionalMagnetic Resonance ImagingMaleMiceMice, Inbred C57BLWorkflow

Identifiers

PMID34887551
OpenAlexW4200271479

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.