Anton Arkhipov, Nuno da Costa, Saskia de Vries, Trygve Bakken, Corbett Bennett, Amy Bernard, Jim Berg, Michael Buice, Forrest Collman, Tanya Daigle, Marina Garrett, Nathan Gouwens, Peter A. Groblewski, Julie Harris, Michael Hawrylycz, Rebecca Hodge, Tim Jarsky, Brian Kalmbach, Jerome Lecoq, Brian Lee, Ed Lein, Boaz Levi, Stefan Mihalas, Lydia Ng, Shawn Olsen, Clay Reid, Joshua H. Siegle, Staci Sorensen, Bosiljka Tasic, Carol Thompson, Jonathan T. Ting, Cindy van Velthoven, Shenqin Yao, Zizhen Yao, Christof Koch, Hongkui Zeng
{"title":"Integrating multimodal data to understand cortical circuit architecture and function","authors":"Anton Arkhipov, Nuno da Costa, Saskia de Vries, Trygve Bakken, Corbett Bennett, Amy Bernard, Jim Berg, Michael Buice, Forrest Collman, Tanya Daigle, Marina Garrett, Nathan Gouwens, Peter A. Groblewski, Julie Harris, Michael Hawrylycz, Rebecca Hodge, Tim Jarsky, Brian Kalmbach, Jerome Lecoq, Brian Lee, Ed Lein, Boaz Levi, Stefan Mihalas, Lydia Ng, Shawn Olsen, Clay Reid, Joshua H. Siegle, Staci Sorensen, Bosiljka Tasic, Carol Thompson, Jonathan T. Ting, Cindy van Velthoven, Shenqin Yao, Zizhen Yao, Christof Koch, Hongkui Zeng","doi":"10.1038/s41593-025-01904-7","DOIUrl":null,"url":null,"abstract":"<p>In recent years there has been a tremendous growth in new technologies that allow large-scale investigation of different characteristics of the nervous system at an unprecedented level of detail. There is a growing trend to use combinations of these new techniques to determine direct links between different modalities. In this Perspective, we focus on the mouse visual cortex, as this is one of the model systems in which much progress has been made in the integration of multimodal data to advance understanding. We review several approaches that allow integration of data regarding various properties of cortical cell types, connectivity at the level of brain areas, cell types and individual cells, and functional neural activity in vivo. The increasingly crucial contributions of computation and theory in analyzing and systematically modeling data are also highlighted. Together with open sharing of data, tools and models, integrative approaches are essential tools in modern neuroscience for improving our understanding of the brain architecture, mechanisms and function.</p>","PeriodicalId":19076,"journal":{"name":"Nature neuroscience","volume":"93 1","pages":""},"PeriodicalIF":21.2000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41593-025-01904-7","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years there has been a tremendous growth in new technologies that allow large-scale investigation of different characteristics of the nervous system at an unprecedented level of detail. There is a growing trend to use combinations of these new techniques to determine direct links between different modalities. In this Perspective, we focus on the mouse visual cortex, as this is one of the model systems in which much progress has been made in the integration of multimodal data to advance understanding. We review several approaches that allow integration of data regarding various properties of cortical cell types, connectivity at the level of brain areas, cell types and individual cells, and functional neural activity in vivo. The increasingly crucial contributions of computation and theory in analyzing and systematically modeling data are also highlighted. Together with open sharing of data, tools and models, integrative approaches are essential tools in modern neuroscience for improving our understanding of the brain architecture, mechanisms and function.
期刊介绍:
Nature Neuroscience, a multidisciplinary journal, publishes papers of the utmost quality and significance across all realms of neuroscience. The editors welcome contributions spanning molecular, cellular, systems, and cognitive neuroscience, along with psychophysics, computational modeling, and nervous system disorders. While no area is off-limits, studies offering fundamental insights into nervous system function receive priority.
The journal offers high visibility to both readers and authors, fostering interdisciplinary communication and accessibility to a broad audience. It maintains high standards of copy editing and production, rigorous peer review, rapid publication, and operates independently from academic societies and other vested interests.
In addition to primary research, Nature Neuroscience features news and views, reviews, editorials, commentaries, perspectives, book reviews, and correspondence, aiming to serve as the voice of the global neuroscience community.