Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility.

Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC (The Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation) is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration, and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.

Enhancing Collaborative Neuroimaging Research: Introducing COINSTAC Vaults for Federated Analysis and Reproducibility.

Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.

Epilepsy after congenital zika virus infection: EEG and neuroimaging features.

PURPOSE: To describe epilepsy after congenital Zika virus infection (ZIKV) and its relationship with structural neuroimaging findings. METHODS: This was a cross-sectional study in children (aged 13-42 months) who were born with microcephaly due to ZIKV infection between 2015-2017. Patients underwent a brain imaging scan (magnetic resonance) and a video-EEG study. RESULTS: Among the patients (n = 43), 55.8 % were male, 88.4 % were born at term, mean head circumference at the birth was 29.7 ± 1.8 cm, and 44.8 % were infected in the first trimester of pregnancy. Neuroimaging was moderately abnormal in 30.2 % and severely abnormal in 46.5 % of patients. Early seizures (<6 months of age) were observed in 41.9 %. EEG background was abnormal when asleep or awake in 72.1 % and during sleep in 62.8 %. The interictal epileptogenic activity was recorded on 41/43 of the EEGs and was predominantly multifocal (62.8 %). An ictal EEG was obtained in 22 patients and 31.8 % had more than one seizure type. Sleep EEG (background) patterns, interictal epileptogenic activity (p = 0.046), interictal discharge localization (p = 0.015), type of ictal epileptogenic activity (p = 0.002), and localization of ictal discharge (p = 0.024) were significantly different between neuroimaging groups. The mild neuroimaging group had a higher chance of having more frequently normal sleep EEG patterns, no interictal epileptogenic activity and a further increase in the probability of walking without limitations, and less neurodevelopment delay. CONCLUSION: In patients with congenital Zika virus syndrome, epilepsy tended to be early and refractory. EEG features correlated with degree of neuroimaging abnormalities.