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Estimation of temporal signal-to-noise ratio (tSNR)

MC Matteo Visconti di Oleggio Castello
VC Vassiki Chauhan
GJ Guo Jiahui
MG M. Ida Gobbini
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We first computed tSNR for each preprocessed functional run using data in each subject’s anatomy without template normalization, which would smooth the data spatially and affect tSNR. For each voxel, tSNR was calculated within each separate run as the temporal mean divided by the temporal standard deviation45. A tSNR map was generated for each subject by computing the median tSNR across runs within each voxel. To qualitatively visualize how tSNR varied according to brain areas and generate a group tSNR map, the same analysis was performed with functional data resampled to the fsaverage surface.

Copyright and License information: The Author(s) ©2020
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/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.

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