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. 2021 Oct 13;12:5992. doi: 10.1038/s41467-021-26255-2

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 4 — a Automated alignment and segmentation pipeline of the atlas-to-brain approach. The raw GCaMP image was segmented using U-Net, and landmark estimation was done using DLC and then combined together to determine each brain region ROI. b Frontal and lateral view of an experimental set-up involving head-fixed mice with sensory stimulation cranial recording. c Sensory mapping across independent trials (n = 6 mice) shows similar regions of activation resulting from physical stimulation of the tail or whiskers and visual field of the mouse. d Single trials (n = 30 trials) of calcium temporal dynamics around the tail, whisker, and visual stimulations of different brain regions (indicated with the same colour on the brain image, the number of brain region ROIs are automatically output from MesoNet). The black line is the averaged calcium response of all the trials.