1. CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics
- Author
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Ariosky Areces-Gonzalez, Deirel Paz-Linares, Usama Riaz, Ying Wang, Min Li, Fuleah A. Razzaq, Jorge F. Bosch-Bayard, Eduardo Gonzalez-Moreira, Lifespan Brain Chart Consortium (LBCC), Global Brain Consortium (GBC), Cuban Human Brain Mapping Project (CHBMP), Marlis Ontivero-Ortega, Lidice Galan-Garcia, Eduardo Martínez-Montes, Ludovico Minati, Mitchell J. Valdes-Sosa, Maria L. Bringas-Vega, and Pedro A. Valdes-Sosa
- Subjects
human connectome project ,megconnectome ,Brainstorm ,Ciftify ,VARETA ,SSSBL ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - 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.
- Published
- 2024
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