{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:21:03Z","timestamp":1787026863028,"version":"build-2736575974"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T00:00:00Z","timestamp":1727136000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Hum. Neurosci."],"abstract":"<jats:p>\n                    Parcellations of resting-state functional magnetic resonance imaging (rs-fMRI) data are widely used to create topographical maps of functional networks in the human brain. While such network maps are highly useful for studying brain organization and function, they usually require large sample sizes to make them, thus creating practical limitations for researchers that would like to carry out parcellations on data collected in their labs. Furthermore, it can be difficult to quantitatively evaluate the results of a parcellation since networks are usually identified using a clustering algorithm, like principal components analysis, on the results of a single group-averaged connectivity map. To address these challenges, we developed the FunMaps method: a parcellation routine that intrinsically incorporates stability and replicability of the parcellation by keeping only network distinctions that agree across halves of the data over multiple random iterations. Here, we demonstrate the efficacy and flexibility of FunMaps, while describing step-by-step instructions for running the program. The FunMaps method is publicly available on GitHub (\n                    <jats:ext-link>https:\/\/github.com\/persichetti-lab\/FunMaps<\/jats:ext-link>\n                    ). It includes source code for running the parcellation and auxiliary code for preparing data, evaluating the parcellation, and displaying the results.\n                  <\/jats:p>","DOI":"10.3389\/fnhum.2024.1461590","type":"journal-article","created":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T00:20:06Z","timestamp":1727137206000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["FunMaps: a method for parcellating functional brain networks using resting-state functional MRI data"],"prefix":"10.3389","volume":"18","author":[{"given":"Jiayu","family":"Shao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen J.","family":"Gotts","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taylor L.","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Martin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew S.","family":"Persichetti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,9,24]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.neuroimage.2007.04.042","article-title":"A component based noise correction method (CompCor) for BOLD and perfusion based fMRI","volume":"37","author":"Behzadi","year":"2007","journal-title":"NeuroImage"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1016\/j.neuroimage.2007.11.059","article-title":"The respiration response function: the temporal dynamics of fMRI signal fluctuations related to changes in respiration","volume":"40","author":"Birn","year":"2008","journal-title":"NeuroImage"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"117461","DOI":"10.1016\/j.neuroimage.2020.117461","article-title":"Improved resting state functional connectivity sensitivity and reproducibility using a multiband multi-echo acquisition","volume":"225","author":"Cohen","year":"2021","journal-title":"NeuroImage"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1006\/cbmr.1996.0014","article-title":"AFNI: software for analysis and visualization of functional magnetic resonance neuroimages","volume":"29","author":"Cox","year":"1996","journal-title":"Comput. 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