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

• Published in: bioRxiv
• Main Authors: Li, Dong, Wang, Guangyu, Werner, René, Xie, Hong, Ji-Song, Guan, Hilgetag, Claus C
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 02.03.2021; Cold Spring Harbor Laboratory
• Edition: 1.1
• Subjects: Activity patterns; Image processing; Microscopy; Nervous system; Neuroscience; vignetting correction; neural activity; imaging artifacts; image analysis; functional microscopic imaging
• ISSN: 2692-8205; 2692-8205
• DOI: 10.1101/2021.03.01.433412

Abstract 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 towards 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. Competing Interest Statement The authors have declared no competing interest.