MRI datasets typically result in high-resolution three-dimensional images representing anatomical structures. These images are often stored in formats such as DICOM (Digital Imaging and Communications in Medicine) or NIfTI (Neuroimaging Informatics Technology Initiative). fMRI datasets produce time-series data representing changes in brain activity over time. These data are often stored in formats compatible with neuroimaging software packages, such as NIfTI, Analyze, or MINC (Medical Imaging NetCDF). fMRI data can be conceptualized and analyzed both as images and time-series. The choice of representation depends on the specific research question and analysis techniques being employed. For many analyses, researchers will use both approaches, leveraging the spatial information provided by the image-like representation and the temporal dynamics captured in the time-series data.

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