{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["18"],"submitter":["Areces-Gonzalez A"],"pubmed_abstract":["We present CiftiStorm, an electrophysiological source imaging (ESI) pipeline incorporating recently developed methods to improve forward and inverse solutions. The CiftiStorm pipeline produces Human Connectome Project (HCP) and megconnectome-compliant outputs from dataset inputs with varying degrees of spatial resolution. The input data can range from low-sensor-density electroencephalogram (EEG) or magnetoencephalogram (MEG) recordings without structural magnetic resonance imaging (sMRI) to high-density EEG/MEG recordings with an HCP multimodal sMRI compliant protocol. CiftiStorm introduces a numerical quality control of the lead field and geometrical corrections to the head and source models for forward modeling. For the inverse modeling, we present a Bayesian estimation of the cross-spectrum of sources based on multiple priors. We facilitate ESI in the T1w/FSAverage32k high-resolution space obtained from individual sMRI. We validate this feature by comparing CiftiStorm outputs for EEG and MRI data from the Cuban Human Brain Mapping Project (CHBMP) acquired with technologies a decade before the HCP MEG and MRI standardized dataset."],"journal":["Frontiers in neuroscience"],"pagination":["1237245"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11047451"],"repository":["biostudies-literature"],"pubmed_title":["CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics."],"pmcid":["PMC11047451"],"pubmed_authors":["Lifespan Brain Chart Consortium (LBCC)","Valdes-Sosa PA","Martinez-Montes E","Riaz U","Galan-Garcia L","Cuban Human Brain Mapping Project (CHBMP)","Ontivero-Ortega M","Paz-Linares D","Li M","Global Brain Consortium (GBC)","Areces-Gonzalez A","Razzaq FA","Gonzalez-Moreira E","Bringas-Vega ML","Minati L","Wang Y","Valdes-Sosa MJ","Bosch-Bayard JF"],"additional_accession":[]},"is_claimable":false,"name":"CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics.","description":"We present CiftiStorm, an electrophysiological source imaging (ESI) pipeline incorporating recently developed methods to improve forward and inverse solutions. The CiftiStorm pipeline produces Human Connectome Project (HCP) and megconnectome-compliant outputs from dataset inputs with varying degrees of spatial resolution. The input data can range from low-sensor-density electroencephalogram (EEG) or magnetoencephalogram (MEG) recordings without structural magnetic resonance imaging (sMRI) to high-density EEG/MEG recordings with an HCP multimodal sMRI compliant protocol. CiftiStorm introduces a numerical quality control of the lead field and geometrical corrections to the head and source models for forward modeling. For the inverse modeling, we present a Bayesian estimation of the cross-spectrum of sources based on multiple priors. We facilitate ESI in the T1w/FSAverage32k high-resolution space obtained from individual sMRI. We validate this feature by comparing CiftiStorm outputs for EEG and MRI data from the Cuban Human Brain Mapping Project (CHBMP) acquired with technologies a decade before the HCP MEG and MRI standardized dataset.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024","modification":"2026-06-27T03:21:19.483Z","creation":"2026-06-27T03:17:17.545Z"},"accession":"S-EPMC11047451","cross_references":{"pubmed":["38680452"],"doi":["10.3389/fnins.2024.1237245"]}}