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Updated: Mar 15, 2026

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

Optimal slice timing correction and its interaction with fMRI parameters and artifacts.

David Parker¹, Xueqing Liu¹, Qolamreza R Razlighi²

¹Biomedical Engineering Department, 500W, 120th St, 351 Engineering Terrace, New York, NY 10027, United States.

Medical Image Analysis

|September 3, 2016

Summary

Slice timing correction (STC) realigns fMRI data acquired at different times. A new Filter-Shift method outperforms existing techniques in simulations and real data, improving fMRI analysis.

Keywords:

EPI Interleaved acquisition Interpolation Slice timing correction fMRI

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Area of Science:

Neuroimaging
Signal Processing
Biomedical Engineering

Background:

fMRI acquisition involves temporal misalignment between slices.
Slice timing correction (STC) is crucial for preprocessing fMRI data.
Existing STC methods lack comprehensive evaluation.

Purpose of the Study:

To propose and evaluate an optimal STC method.
To compare the proposed Filter-Shift method against existing techniques (SPM, FSL).
To assess STC effectiveness under various fMRI acquisition conditions.

Main Methods:

Developed a novel Filter-Shift STC method based on sampling theory.
Evaluated STC methods using 338 simulated and 30 real fMRI datasets.
Compared performance across different motion levels, interleave sequences, and scanner parameters.

Main Results:

Demonstrated the general effectiveness of STC for fMRI data.
The proposed Filter-Shift method showed superiority over SPM and FSL.
Performance varied based on scan conditions, highlighting the importance of method selection.

Conclusions:

The Filter-Shift method offers an improved approach to STC.
Optimal STC is essential for accurate fMRI analysis.
Further research into STC optimization under diverse conditions is warranted.