2025
Charting the path in rodent functional neuroimaging
Gozzi A, Stuefer A, Alvino F, Bedin V, Cover C, Kang C, Galbusera A, Gil R, Gini S, de Guzman E, Desrosiers-Grégoire G, Gutierrez-Barragan D, Mandino F, Mariani J, Micotti E, Reimann H, Pagani M, Pepe C, Sastre-Yagüe D, Urosevic M, Valente M, Vertullo R, Canese R, Devor A, Grandjean J, Kahn I, Keiholz S, Lake E, Li N, Shemesh N, Shih Y, Zerbi V, Zhang N. Charting the path in rodent functional neuroimaging. Imaging Neuroscience 2025, 3: imag.a.12. PMID: 40800991, PMCID: PMC12319733, DOI: 10.1162/imag.a.12.Peer-Reviewed Original Research
2024
What N Is N-ough for MRI-Based Animal Neuroimaging?
Grandjean J, Lake E, Pagani M, Mandino F. What N Is N-ough for MRI-Based Animal Neuroimaging? ENeuro 2024, 11: eneuro.0531-23.2024. PMID: 38499355, PMCID: PMC10950324, DOI: 10.1523/eneuro.0531-23.2024.Peer-Reviewed Original ResearchConceptsBrain-wide association studiesScientific progressNeuroimaging communityNeuroimagingAssociation studiesSize extremesDecentralized Mixed Effects Modeling in COINSTAC
Basodi S, Raja R, Gazula H, Romero J, Panta S, Maullin-Sapey T, Nichols T, Calhoun V. Decentralized Mixed Effects Modeling in COINSTAC. Neuroinformatics 2024, 22: 163-175. PMID: 38424371, PMCID: PMC12002420, DOI: 10.1007/s12021-024-09657-7.Peer-Reviewed Original ResearchLarge-scale analysis of dataDecentralized platformLow bandwidthData transferMemory requirementsData sharingSubstantial overheadsCOINSTACStructural magnetic resonance imagingNeuroimaging communityDataData poolNeuroimaging analysisOverheadsPrivacyLarge-scale analysisImagesMagnetic resonance imagingGray matter reductionsMedial frontal regionsDimensionalityLinear mixed-effectsModeling approachBandwidthResearch groups
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