1
|
Ocklenburg S, Guo ZV. Cross-hemispheric communication: Insights on lateralized brain functions. Neuron 2024; 112:1222-1234. [PMID: 38458199 DOI: 10.1016/j.neuron.2024.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 12/13/2023] [Accepted: 02/12/2024] [Indexed: 03/10/2024]
Abstract
On the surface, the two hemispheres of vertebrate brains look almost perfectly symmetrical, but several motor, sensory, and cognitive systems show a deeply lateralized organization. Importantly, the two hemispheres are connected by various commissures, white matter tracts that cross the brain's midline and enable cross-hemispheric communication. Cross-hemispheric communication has been suggested to play an important role in the emergence of lateralized brain functions. Here, we review current advances in understanding cross-hemispheric communication that have been made using modern neuroscientific tools in rodents and other model species, such as genetic labeling, large-scale recordings of neuronal activity, spatiotemporally precise perturbation, and quantitative behavior analyses. These findings suggest that the emergence of lateralized brain functions cannot be fully explained by largely static factors such as genetic variation and differences in structural brain asymmetries. In addition, learning-dependent asymmetric interactions between the left and right hemispheres shape lateralized brain functions.
Collapse
Affiliation(s)
- Sebastian Ocklenburg
- Department of Psychology, MSH Medical School Hamburg, Hamburg, Germany; ICAN Institute for Cognitive and Affective Neuroscience, MSH Medical School Hamburg, Hamburg, Germany; Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany.
| | - Zengcai V Guo
- School of Medicine, Tsinghua University, Beijing 100084, China; Tsinghua-Peking Joint Center for Life Sciences, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China.
| |
Collapse
|
2
|
Jiang T, Gong H, Yuan J. Whole-brain Optical Imaging: A Powerful Tool for Precise Brain Mapping at the Mesoscopic Level. Neurosci Bull 2023; 39:1840-1858. [PMID: 37715920 PMCID: PMC10661546 DOI: 10.1007/s12264-023-01112-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/08/2023] [Indexed: 09/18/2023] Open
Abstract
The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons. Precise dissection of neural circuits at the mesoscopic level can provide important structural information for understanding the brain. Optical approaches can achieve submicron lateral resolution and achieve "optical sectioning" by a variety of means, which has the natural advantage of allowing the observation of neural circuits at the mesoscopic level. Automated whole-brain optical imaging methods based on tissue clearing or histological sectioning surpass the limitation of optical imaging depth in biological tissues and can provide delicate structural information in a large volume of tissues. Combined with various fluorescent labeling techniques, whole-brain optical imaging methods have shown great potential in the brain-wide quantitative profiling of cells, circuits, and blood vessels. In this review, we summarize the principles and implementations of various whole-brain optical imaging methods and provide some concepts regarding their future development.
Collapse
Affiliation(s)
- Tao Jiang
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China
| | - Hui Gong
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Jing Yuan
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China.
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.
| |
Collapse
|
3
|
Wang M, Yu X. Experience-dependent structural plasticity of pyramidal neurons in the developing sensory cortices. Curr Opin Neurobiol 2023; 81:102724. [PMID: 37068383 DOI: 10.1016/j.conb.2023.102724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 04/19/2023]
Abstract
Sensory experience regulates the structural and functional wiring of neuronal circuits, during development and throughout adulthood. Here, we review current knowledge of how experience affects structural plasticity of pyramidal neurons in the sensory cortices. We discuss the pros and cons of existing labeling approaches, as well as what structural parameters are most plastic. We further discuss how recent advances in sparse labeling of specific neuronal subtypes, as well as development of techniques that allow fast, high resolution imaging in large fields, would enable future studies to address currently unanswered questions in the field of structural plasticity.
Collapse
Affiliation(s)
- Miao Wang
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, and PKU-IDG/McGovern Institute, Peking University, Beijing 100871, China.
| | - Xiang Yu
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, and PKU-IDG/McGovern Institute, Peking University, Beijing 100871, China; Autism Research Center of Peking University Health Science Center, Beijing 100191, China; Chinese Institute for Brain Research, Beijing 102206, China.
| |
Collapse
|
4
|
Zhou W, Ke S, Li W, Yuan J, Li X, Jin R, Jia X, Jiang T, Dai Z, He G, Fang Z, Shi L, Zhang Q, Gong H, Luo Q, Sun W, Li A, Li P. Mapping the Function of Whole-Brain Projection at the Single Neuron Level. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2202553. [PMID: 36228099 PMCID: PMC9685445 DOI: 10.1002/advs.202202553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 09/18/2022] [Indexed: 06/16/2023]
Abstract
Axonal projection conveys neural information. The divergent and diverse projections of individual neurons imply the complexity of information flow. It is necessary to investigate the relationship between the projection and functional information at the single neuron level for understanding the rules of neural circuit assembly, but a gap remains due to a lack of methods to map the function to whole-brain projection. Here an approach is developed to bridge two-photon calcium imaging in vivo with high-resolution whole-brain imaging based on sparse labeling with the genetically encoded calcium indicator GCaMP6. Reliable whole-brain projections are captured by the high-definition fluorescent micro-optical sectioning tomography (HD-fMOST). A cross-modality cell matching is performed and the functional annotation of whole-brain projection at the single-neuron level (FAWPS) is obtained. Applying it to the layer 2/3 (L2/3) neurons in mouse visual cortex, the relationship is investigated between functional preferences and axonal projection features. The functional preference of projection motifs and the correlation between axonal length in MOs and neuronal orientation selectivity, suggest that projection motif-defined neurons form a functionally specific information flow, and the projection strength in specific targets relates to the information clarity. This pipeline provides a new way to understand the principle of neuronal information transmission.
Collapse
Affiliation(s)
- Wei Zhou
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Shanshan Ke
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Wenwei Li
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Jing Yuan
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Xiangning Li
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Rui Jin
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Xueyan Jia
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Tao Jiang
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Zimin Dai
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Guannan He
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Zhiwei Fang
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Liang Shi
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Qi Zhang
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
| | - Hui Gong
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Qingming Luo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical EngineeringHainan UniversityHaikou570228China
| | - Wenzhi Sun
- Chinese Institute for Brain ResearchBeijing102206China
- School of Basic Medical SciencesCapital Medical UniversityBeijing100069China
| | - Anan Li
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Pengcheng Li
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| |
Collapse
|
5
|
Munck S, Cawthorne C, Escamilla‐Ayala A, Kerstens A, Gabarre S, Wesencraft K, Battistella E, Craig R, Reynaud EG, Swoger J, McConnell G. Challenges and advances in optical 3D mesoscale imaging. J Microsc 2022; 286:201-219. [PMID: 35460574 PMCID: PMC9325079 DOI: 10.1111/jmi.13109] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 03/02/2022] [Accepted: 04/14/2022] [Indexed: 12/14/2022]
Abstract
Optical mesoscale imaging is a rapidly developing field that allows the visualisation of larger samples than is possible with standard light microscopy, and fills a gap between cell and organism resolution. It spans from advanced fluorescence imaging of micrometric cell clusters to centimetre-size complete organisms. However, with larger volume specimens, new problems arise. Imaging deeper into tissues at high resolution poses challenges ranging from optical distortions to shadowing from opaque structures. This manuscript discusses the latest developments in mesoscale imaging and highlights limitations, namely labelling, clearing, absorption, scattering, and also sample handling. We then focus on approaches that seek to turn mesoscale imaging into a more quantitative technique, analogous to quantitative tomography in medical imaging, highlighting a future role for digital and physical phantoms as well as artificial intelligence.
Collapse
Affiliation(s)
- Sebastian Munck
- VIB‐KU Leuven Center for Brain & Disease ResearchLight Microscopy Expertise Unit & VIB BioImaging CoreLeuvenBelgium
- KU Leuven Department of NeurosciencesLeuven Brain InstituteLeuvenBelgium
| | | | - Abril Escamilla‐Ayala
- VIB‐KU Leuven Center for Brain & Disease ResearchLight Microscopy Expertise Unit & VIB BioImaging CoreLeuvenBelgium
- KU Leuven Department of NeurosciencesLeuven Brain InstituteLeuvenBelgium
| | - Axelle Kerstens
- VIB‐KU Leuven Center for Brain & Disease ResearchLight Microscopy Expertise Unit & VIB BioImaging CoreLeuvenBelgium
- KU Leuven Department of NeurosciencesLeuven Brain InstituteLeuvenBelgium
| | - Sergio Gabarre
- VIB‐KU Leuven Center for Brain & Disease ResearchLight Microscopy Expertise Unit & VIB BioImaging CoreLeuvenBelgium
- KU Leuven Department of NeurosciencesLeuven Brain InstituteLeuvenBelgium
| | | | | | - Rebecca Craig
- Department of Physics, SUPAUniversity of StrathclydeGlasgowUK
| | - Emmanuel G. Reynaud
- School of Biomolecular and Biomedical ScienceUniversity College DublinDublinBelfieldIreland
| | - Jim Swoger
- European Molecular Biology Laboratory (EMBL) BarcelonaBarcelonaSpain
| | - Gail McConnell
- Department of Physics, SUPAUniversity of StrathclydeGlasgowUK
| |
Collapse
|
6
|
Guo S, Xue J, Liu J, Ye X, Guo Y, Liu D, Zhao X, Xiong F, Han X, Peng H. Smart imaging to empower brain-wide neuroscience at single-cell levels. Brain Inform 2022; 9:10. [PMID: 35543774 PMCID: PMC9095808 DOI: 10.1186/s40708-022-00158-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 04/12/2022] [Indexed: 11/10/2022] Open
Abstract
A deep understanding of the neuronal connectivity and networks with detailed cell typing across brain regions is necessary to unravel the mechanisms behind the emotional and memorial functions as well as to find the treatment of brain impairment. Brain-wide imaging with single-cell resolution provides unique advantages to access morphological features of a neuron and to investigate the connectivity of neuron networks, which has led to exciting discoveries over the past years based on animal models, such as rodents. Nonetheless, high-throughput systems are in urgent demand to support studies of neural morphologies at larger scale and more detailed level, as well as to enable research on non-human primates (NHP) and human brains. The advances in artificial intelligence (AI) and computational resources bring great opportunity to 'smart' imaging systems, i.e., to automate, speed up, optimize and upgrade the imaging systems with AI and computational strategies. In this light, we review the important computational techniques that can support smart systems in brain-wide imaging at single-cell resolution.
Collapse
Affiliation(s)
- Shuxia Guo
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China.
| | - Jie Xue
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Jian Liu
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Xiangqiao Ye
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Yichen Guo
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Di Liu
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Xuan Zhao
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Feng Xiong
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Xiaofeng Han
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China.
| | - Hanchuan Peng
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| |
Collapse
|
7
|
Zhang Z, Yao X, Yin X, Ding Z, Huang T, Huo Y, Ji R, Peng H, Guo ZV. Multi-Scale Light-Sheet Fluorescence Microscopy for Fast Whole Brain Imaging. Front Neuroanat 2021; 15:732464. [PMID: 34630049 PMCID: PMC8497830 DOI: 10.3389/fnana.2021.732464] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 08/12/2021] [Indexed: 12/23/2022] Open
Abstract
Whole-brain imaging has become an increasingly important approach to investigate neural structures, such as somata distribution, dendritic morphology, and axonal projection patterns. Different structures require whole-brain imaging at different resolutions. Thus, it is highly desirable to perform whole-brain imaging at multiple scales. Imaging a complete mammalian brain at synaptic resolution is especially challenging, as it requires continuous imaging from days to weeks because of the large number of voxels to sample, and it is difficult to acquire a constant quality of imaging because of light scattering during in toto imaging. Here, we reveal that light-sheet microscopy has a unique advantage over wide-field microscopy in multi-scale imaging because of its decoupling of illumination and detection. Based on this observation, we have developed a multi-scale light-sheet microscope that combines tiling of light-sheet, automatic zooming, periodic sectioning, and tissue expansion to achieve a constant quality of brain-wide imaging from cellular (3 μm × 3 μm × 8 μm) to sub-micron (0.3 μm × 0.3 μm × 1 μm) spatial resolution rapidly (all within a few hours). We demonstrated the strength of the system by testing it using mouse brains prepared using different clearing approaches. We were able to track electrode tracks as well as axonal projections at sub-micron resolution to trace the full morphology of single medial prefrontal cortex (mPFC) neurons that have remarkable diversity in long-range projections.
Collapse
Affiliation(s)
- Zhouzhou Zhang
- School of Medicine, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
- School of Life Sciences, Tsinghua University, Beijing, China
| | - Xiao Yao
- School of Medicine, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
- Tsinghua-Peking Joint Center for Life Sciences, Beijing, China
| | - Xinxin Yin
- School of Medicine, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
- Tsinghua-Peking Joint Center for Life Sciences, Beijing, China
| | - Zhangcan Ding
- SEU-Allen Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Tianyi Huang
- School of Medicine, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
| | - Yan Huo
- School of Medicine, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
| | - Runan Ji
- School of Medicine, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
| | - Hanchuan Peng
- SEU-Allen Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- Allen Institute for Brain Science, Seattle, WA, United States
| | - Zengcai V Guo
- School of Medicine, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
- Tsinghua-Peking Joint Center for Life Sciences, Beijing, China
| |
Collapse
|