{"authors":[{"id":null,"fullName":"Bey, Patrik","name":"Patrik","surname":"Bey","rank":1,"pid":null},{"id":null,"fullName":"Dhindsa, Kiret","name":"Kiret","surname":"Dhindsa","rank":2,"pid":null},{"id":null,"fullName":"Kashyap, Amrit","name":"Amrit","surname":"Kashyap","rank":3,"pid":null},{"id":null,"fullName":"Schirner, Michael","name":"Michael","surname":"Schirner","rank":4,"pid":null},{"id":null,"fullName":"Feldheim, Jan","name":"Jan","surname":"Feldheim","rank":5,"pid":null},{"id":null,"fullName":"Bönstrup, Marlene","name":"Marlene","surname":"Bönstrup","rank":6,"pid":null},{"id":null,"fullName":"Schulz, Robert","name":"Robert","surname":"Schulz","rank":7,"pid":null},{"id":null,"fullName":"Cheng, Bastian","name":"Bastian","surname":"Cheng","rank":8,"pid":null},{"id":null,"fullName":"Thomalla, Götz","name":"Götz","surname":"Thomalla","rank":9,"pid":null},{"id":null,"fullName":"Gerloff, Christian","name":"Christian","surname":"Gerloff","rank":10,"pid":null},{"id":null,"fullName":"Ritter, Petra","name":"Petra","surname":"Ritter","rank":11,"pid":null}],"openAccessColor":null,"publiclyFunded":null,"eoscIfGuidelines":null,"type":"dataset","language":{"code":"und","label":"Undetermined"},"countries":null,"subjects":[{"subject":{"scheme":"keyword","value":"Neuroscience"},"provenance":null}],"mainTitle":"Longitudinal UKE multimodal magnetic resonance imaging data for ischemic stroke patients and healthy controls: Simulation (TVB) ready derivatives prepared by CHARITÉ (v1.0)","subTitle":null,"descriptions":["The longitudinal stroke patient multimodal imaging data ([Schlemm et al. 2020](https://doi.org/10.1093/braincomms/fcaa001)) derivatives such as structural connectomes (SC), region-wise BOLD time series, and lesion information ([Bey et al. 2024](https://doi.org/10.1002/hbm.26701)) are ready for personalized simulations with [The Virtual Brain (TVB)](https://www.ebrains.eu/tools/the-virtual-brain) – a service available on EBRAINS ([Schirner et al. 2022](https://doi.org/10.1016/j.neuroimage.2022.118973)). Processing multimodal neuroimaging data in the presence of stroke lesion holds various challenges. To overcome these challenges when creating image derivatives for TVB, the dataset has been processed by the [Lesion Aware automated Processing Pipeline](https://search.kg.ebrains.eu/instances/1a66bca4-2c44-4c42-bfd2-ac546a2ca02c) (LeAPP, [Bey et al. 2024](https://doi.org/10.1002/hbm.26701)). The data set contains longitudinal multimodal magnetic resonance imaging (MRI) data derivatives of 36 ischemic stroke patients at four time points (3-5, 30-40, 85-95 and 340-380 days) post stroke and of 15 healthy controls. The here derivative data are ready for constructing computational brain network models with TVB. The data are organized following the [BIDS](https://bids.neuroimaging.io/) extension proposal for computational modeling ([Schirner and Ritter 2021](https://doi.org/10.5281/zenodo.7962032)). Derivatives have been computed for a total of 383 distinct brain regions-of-interest (ROI) using a combination of the HCP-MMP1 atlas ([Glasser et al. 2016](https://doi.org/10.1038/nature18933)) for cortical areas and FreeSurfer’s subcortical areas ([Fischl 2012](https://doi.org/10.1016/j.neuroimage.2012.01.021)). Functional MRI data have been acquired under task conditions. Tasks onset and offsets are provided."],"publicationDate":"2025-03-16","publisher":"EBRAINS","embargoEndDate":null,"sources":null,"formats":null,"contributors":["Ritter, Petra"],"coverages":null,"bestAccessRight":{"code":"c_abf2","label":"OPEN","scheme":"http://vocabularies.coar-repositories.org/documentation/access_rights/"},"container":null,"documentationUrls":null,"codeRepositoryUrl":null,"programmingLanguage":null,"contactPeople":null,"contactGroups":null,"tools":null,"size":null,"version":"null","geoLocations":null,"id":"doi_dedup___::c277028b31f9eda88fbcb35a1a2ffb6f","originalIds":["50|datacite____::c277028b31f9eda88fbcb35a1a2ffb6f","10.25493/nav3-ejs","50|sygma_______::c277028b31f9eda88fbcb35a1a2ffb6f"],"pids":[{"scheme":"doi","value":"10.25493/nav3-ejs"}],"dateOfCollection":null,"lastUpdateTimeStamp":null,"indicators":{"citationImpact":{"citationCount":0.0,"influence":2.1746283E-9,"popularity":2.2497804E-9,"impulse":0.0,"citationClass":"C5","influenceClass":"C5","impulseClass":"C5","popularityClass":"C5"}},"projects":[{"id":"corda_____he::498fbfce4411571fbc71b892b213bf89","code":"101147319","acronym":"EBRAINS 2.0","title":"EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health","funder":"European Commission","pids":[{"scheme":"doi","value":"10.3030/101147319"}]},{"id":"corda_____he::0076357a1e39d82caa3231904823c86e","code":"101058516","acronym":"eBRAIN-Health","title":"eBRAIN-Health - 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