中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Single Image-Based Vignetting Correction for Improving the Consistency of Neural Activity Analysis in 2-Photon Functional Microscopy

文献类型:期刊论文

作者Li, Dong1; Wang, Guangyu2; Werner, Rene1,3; Xie, Hong4,5; Guan, Ji-Song2,6; Hilgetag, Claus C.1,3,7
刊名FRONTIERS IN NEUROINFORMATICS
出版日期2022-01-05
卷号15页码:10
通讯作者邮箱d.li@uke.de (dong li )
关键词vignetting correction functional microscopic imaging neural activity image analysis imaging artifacts
DOI10.3389/fninf.2021.674439
产权排序6
文献子类综述
英文摘要

High-resolution functional 2-photon microscopy of neural activity is a cornerstone technique in current neuroscience, enabling, for instance, the image-based analysis of relations of the organization of local neuron populations and their temporal neural activity patterns. Interpreting local image intensity as a direct quantitative measure of neural activity presumes, however, a consistent within- and across-image relationship between the image intensity and neural activity, which may be subject to interference by illumination artifacts. In particular, the so-called vignetting artifact-the decrease of image intensity toward the edges of an image-is, at the moment, widely neglected in the context of functional microscopy analyses of neural activity, but potentially introduces a substantial center-periphery bias of derived functional measures. In the present report, we propose a straightforward protocol for single image-based vignetting correction. Using immediate-early gene-based 2-photon microscopic neural image data of the mouse brain, we show the necessity of correcting both image brightness and contrast to improve within- and across-image intensity consistency and demonstrate the plausibility of the resulting functional data.

收录类别SCI
WOS关键词ILLUMINATION-CORRECTION ; CIRCUITS ; REVEALS
资助项目German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) ; National Natural Science Foundation of China[DFG TRR-169/NSFC (61621136008)] ; National Natural Science Foundation of China[DFG SPP2041] ; National Natural Science Foundation of China[HBP/SGA2] ; National Natural Science Foundation of China[DFG SFB-936-A1] ; NSFC[31970903] ; Shanghai Ministry of Science and Technology[19ZR1477400] ; DFG[SFB-1328-A2] ; DFG[335447717]
WOS研究方向Mathematical & Computational Biology ; Neurosciences & Neurology
出版者FRONTIERS MEDIA SA
WOS记录号WOS:000745810400001
资助机构German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) ; National Natural Science Foundation of China ; NSFC ; Shanghai Ministry of Science and Technology ; DFG
源URL[http://ir.psych.ac.cn/handle/311026/41836]  
专题心理研究所_认知与发展心理学研究室
通讯作者Li, Dong
作者单位1.Univ Med Ctr Hamburg Eppendorf, Inst Computat Neurosci, Hamburg, Germany
2.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai, Peoples R China
3.Univ Med Ctr Hamburg Eppendorf, Ctr Biomed Artificial Intelligence bAIome, Hamburg, Germany
4.Univ Shanghai Sci & Technol, Inst Photon Chips, Shanghai, Peoples R China
5.Univ Shanghai Sci & Technol, Sch Hlth Sci & Engn, Shanghai, Peoples R China
6.Chinese Acad Sci, Inst Psychol, Beijing, Peoples R China
7.Boston Univ, Dept Hlth Sci, Boston, MA 02215 USA
推荐引用方式
GB/T 7714
Li, Dong,Wang, Guangyu,Werner, Rene,et al. Single Image-Based Vignetting Correction for Improving the Consistency of Neural Activity Analysis in 2-Photon Functional Microscopy[J]. FRONTIERS IN NEUROINFORMATICS,2022,15:10.
APA Li, Dong,Wang, Guangyu,Werner, Rene,Xie, Hong,Guan, Ji-Song,&Hilgetag, Claus C..(2022).Single Image-Based Vignetting Correction for Improving the Consistency of Neural Activity Analysis in 2-Photon Functional Microscopy.FRONTIERS IN NEUROINFORMATICS,15,10.
MLA Li, Dong,et al."Single Image-Based Vignetting Correction for Improving the Consistency of Neural Activity Analysis in 2-Photon Functional Microscopy".FRONTIERS IN NEUROINFORMATICS 15(2022):10.

入库方式: OAI收割

来源:心理研究所

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