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Updated: Feb 13, 2026

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI
Published on: March 19, 2021
Connectomes across temporal scales with simultaneous wide-field optical imaging and resting-state functional MRI
Wen-Ju Pan1, Lauren Daley1, Lisa Meyer-Baese1
1Wallace H. Coulter Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA.
Resting-state functional MRI (rs-fMRI) captures time-averaged brain activity well. Simultaneous wide-field optical imaging (WOI) and rs-fMRI reveal preserved spatial structures across timescales, aiding dynamic brain activity analysis.
Area of Science:
- Neuroscience
- Biophysics
Background:
- Resting-state functional MRI (rs-fMRI) is crucial for brain research.
- Its interpretation is challenging due to the slow hemodynamic response, which can obscure neural activity at faster timescales.
Purpose of the Study:
- To directly investigate the relationship between neural and hemodynamic functional connectomes across different timescales.
- To compare the reliability of time-resolved rs-fMRI and hemodynamic wide-field optical imaging (WOI) signals against neural activity.
Main Methods:
- Simultaneous wide-field optical imaging (WOI) and rs-fMRI were employed.
- Analysis focused on comparing functional connectivity across modalities and timescales.
Main Results:
- Large-scale spatial structure is largely preserved across modalities (WOI and rs-fMRI), timescales, and frequencies.
- rs-fMRI effectively captures time-averaged neural activity, but time-resolved estimates show higher variability.
- Hemodynamic WOI signals show greater similarity to neural activity than rs-fMRI, especially at lower frequencies.
Conclusions:
- The time-averaged spatial structure of neural activity is reliably represented by both hemodynamics and rs-fMRI.
- Findings offer insights into the reliability of time-resolved rs-fMRI across temporal scales.
- A multimodal framework is established for validating dynamic brain activity features.
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