Pypreclin: An automatic pipeline for macaque functional MRI preprocessing.

Area of Science:

• Neuroscience
• Neuroimaging
• Primate Research

Background:

• Non-human primate functional MRI (fMRI) is crucial for neuroscience research.
• Existing macaque fMRI data analysis lacks standardized preprocessing methods.
• Technical challenges include motion artifacts and intracranial lead interference.

Purpose of the Study:

• To develop a versatile and automatic preprocessing pipeline for macaque fMRI data.
• To address specific challenges in non-human primate fMRI data acquisition and analysis.
• To provide a validated tool for diverse experimental conditions.

Main Methods:

• Developed Pypreclin, a Python module for automatic fMRI data preprocessing.
• Applied Pypreclin to macaque fMRI data under various conditions (awake/anesthetized, contrast agents, coil types, electrodes).
• Validated Pypreclin using resting-state and auditory evoked fMRI, comparing it to existing pipelines and external datasets.

Main Results:

• Pypreclin successfully registered fMRI data to the macaque brain template across all tested conditions.
• Pypreclin demonstrated more accurate localization of auditory evoked activations in awake macaques.
• External validation on ultra-high field data from other institutions confirmed Pypreclin's robustness.

Conclusions:

• Pypreclin is a validated, versatile tool for macaque fMRI preprocessing.
• The pipeline adapts to diverse technical and experimental situations in primate neuroimaging.
• Pypreclin enhances the reliability and accuracy of non-human primate fMRI studies.