New analysis method for functional brain imaging: White noise removed T₂* variation mapping using multi-echo EPI

Area of Science:

• Neuroimaging
• Functional Magnetic Resonance Imaging (fMRI)

Background:

• Standard fMRI analysis relies on independent component analysis (ICA) for resting-state and general linear model (GLM) for task-related mapping.
• These conventional methods are typically applied independently, limiting their combined utility.

Purpose of the Study:

• To develop a novel fMRI analysis method that integrates both task-related activation mapping and resting-state imaging.
• To address the limitations of conventional fMRI analyses by offering a unified approach.

Main Methods:

• A new white noise-removed T2*-variation mapping technique was developed using multi-echo EPI (ME-EPI) data.
• This method utilizes signal-coherence and slope analyses to remove S0 (initial signal intensity) and white noise components from the EPI signal variation.

Main Results:

• The proposed T2*-variation mapping successfully generated reliable activation maps for visual tasks and identified typical default mode network regions during resting-state imaging.
• Crucially, the method effectively removed white noise and S0 components, enhancing map clarity.

Conclusions:

• White noise-removed true T2*-variation-based mapping offers a unified approach for fMRI analysis, applicable to both activation and resting-state paradigms.
• This integrated method is expected to facilitate studies where the relationship between task timing and brain activity is complex, such as in emotion and awareness research.