An analysis approach for high-field fMRI data from awake non-human primates

Area of Science:

• Neuroscience
• Neuroimaging

Background:

• Functional magnetic resonance imaging (fMRI) in awake non-human primates (NHP) is increasingly used.
• Standard human fMRI analysis tools are suboptimal for NHP data, especially at high fields.
• NHP experiments are trial-based, and subject motion causes artifacts.

Purpose of the Study:

• To develop and demonstrate an improved fMRI analysis methodology for awake NHP.
• To address challenges in analyzing high-field NHP fMRI data, including motion artifacts and trial-based designs.
• To provide a semi-automated software solution for NHP fMRI data processing.

Main Methods:

• A six-step processing pipeline including trial-based design, motion control, artifact/motion selection, realignment, interpolation, and filtering.
• Development of the fMRI Sandbox software toolbox for semi-automated processing.
• Integration with SPM software for statistical analysis.

Main Results:

• The proposed methodology significantly improves the analysis of awake monkey fMRI data acquired at high-field.
• The fMRI Sandbox toolbox facilitates semi-automated application of the processing steps.
• The method effectively handles trial-based designs and motion-related artifacts.

Conclusions:

• The developed fMRI analysis approach enhances the quality and reliability of awake NHP fMRI data.
• The fMRI Sandbox toolbox offers a practical solution for researchers working with NHP fMRI.
• This methodology may also benefit clinical fMRI applications requiring motion management.