Single Image-Based Vignetting Correction for Improving the Consistency of Neural Activity Analysis in 2-Photon Functional Microscopy

doi:10.3389/fninf.2021.674439

	Single Image-Based Vignetting Correction for Improving the Consistency of Neural Activity Analysis in 2-Photon Functional Microscopy
	Li, Dong 1; Wang, Guangyu 2; Werner, Rene 1,3; Xie, Hong 4,5; Guan, Ji-Song2,6 ; Hilgetag, Claus C.1,3,7
	2022-01-05
发表期刊	FRONTIERS IN NEUROINFORMATICS (IF:2.5[JCR-2023],3.8[5-Year])
EISSN	1662-5196
卷号	15
发表状态	已发表
DOI	10.3389/fninf.2021.674439
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.
关键词	vignetting correction functional microscopic imaging neural activity image analysis imaging artifacts
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收录类别	SCI ; SCIE
语种	英语
资助项目	National Natural Science Foundation of China["DFG TRR-169/NSFC (61621136008)","DFG SPP2041","HBP/SGA2","DFG SFB-936-A1"] ; NSFC[31970903] ; Shanghai Ministry of Science and Technology[19ZR1477400] ; DFG["SFB-1328-A2",335447717]
WOS研究方向	Mathematical & Computational Biology ; Neurosciences & Neurology
WOS类目	Mathematical & Computational Biology ; Neurosciences
WOS记录号	WOS:000745810400001
出版者	FRONTIERS MEDIA SA
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/153545
专题	生命科学与技术学院_PI研究组_管吉松组
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.
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.
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).