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Related Experiment Video

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Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
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CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics.

Ariosky Areces-Gonzalez1,2, Deirel Paz-Linares1,3, Usama Riaz1

  • 1The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.

Frontiers in Neuroscience
|April 29, 2024
PubMed
Summary
This summary is machine-generated.

CiftiStorm is a new electrophysiological source imaging pipeline that enhances forward and inverse solutions for better brain activity mapping. It produces standardized outputs compatible with major neuroimaging datasets, improving data analysis across various resolutions.

Keywords:
BrainstormCiftifyHIGGSSSSBLVARETAforward modelhuman connectome projectmegconnectome

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience

Background:

  • Electrophysiological source imaging (ESI) is crucial for localizing brain activity.
  • Existing ESI pipelines face challenges with forward and inverse solution accuracy.
  • Standardization across different data resolutions and acquisition protocols is needed.

Purpose of the Study:

  • To introduce CiftiStorm, an advanced ESI pipeline.
  • To improve the accuracy of forward and inverse solutions in ESI.
  • To ensure compatibility with Human Connectome Project (HCP) and megconnectome standards.

Main Methods:

  • Incorporates novel methods for forward and inverse solutions.
  • Includes numerical quality control and geometrical corrections for forward modeling.
  • Employs Bayesian estimation with multiple priors for inverse modeling.

Main Results:

  • CiftiStorm generates HCP and megconnectome-compliant outputs.
  • The pipeline accommodates varying spatial resolutions and data densities (EEG/MEG, with or without sMRI).
  • ESI is facilitated in high-resolution T1w/FSAverage32k space.

Conclusions:

  • CiftiStorm offers an improved ESI pipeline with enhanced accuracy.
  • The pipeline demonstrates flexibility with diverse input data.
  • Validation using historical data confirms its robust performance.