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. 2022 Jul 21;12:12023. doi: 10.1038/s41598-022-15539-2

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© The Author(s) 2022

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Top 10% FNC for patients computed using most 5% of the salient data as thresholded using feature attribution maps (saliency maps) for different disorders (created in programs MNE 1.1.dev0, https://mne.tools/dev/ and Inkscape 1.1.2, http://inkscape.org/release/inkscape-1.1.2). Apart from the high predictive capacity of the salient data, we observed some intriguing differences among these connectograms. The autism spectrum disorder exhibits the lowest between-domain FNC. However, salient data in autism disorder highlights domain changes in specific cerebellum, sensorimotor, and subcortical domains. The model-identified salient data reflects the most widespread pattern for schizophrenia and is consistent with the literature showing cerebellum interaction across multiple domains and sensorimotor changes. The predictive features for Alzheimer’s disease mainly concentrate on visual and cognitive interactions.