FunMaps: a toolbox for parcellating functional brain networks using resting-state functional MRI data

التفاصيل البيبلوغرافية
العنوان: FunMaps: a toolbox for parcellating functional brain networks using resting-state functional MRI data
المؤلفون: Shao, Jiayu, Gotts, Stephen J, Martin, Alex, Persichetti, Andrew
بيانات النشر: Center for Open Science
سنة النشر: 2024
الوصف: 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 toolbox: 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 toolbox is publicly available on GitHub (https://github.com/persichetti-lab/FunMaps). It includes source code for running the parcellation and auxiliary code for preparing data, evaluating the parcellation, and displaying the results.
نوع الوثيقة: other/unknown material
اللغة: unknown
DOI: 10.31234/osf.io/49k6a
الاتاحة: http://dx.doi.org/10.31234/osf.io/49k6a
Rights: https://creativecommons.org/publicdomain/zero/1.0/legalcode
رقم الانضمام: edsbas.E732F09A
قاعدة البيانات: BASE