This lesson is still being designed and assembled (Pre-Alpha version)

Structural MRI (Pre)processing and Neuroimaging Analysis: Glossary

Key Points

sMRI Acquisition and Modalities
  • Different acquisition techniques will offer better quantification of specific brain tissues

sMRI Clean-up
  • Presence of artifacts can lead to flawed analysis and incorrect findings

sMRI Spatial Normalization
  • Reference coordinate spaces and spatial normalization offer a way to map and compare brain anatomy across modalities, individuals, and studies

sMRI Segmentation and Parcellation
  • Brain segmentation and parcellation is a key step towards further analysis

  • The brain can be represented via different data format (volume, surface)

  • Multiple python libraries are particularly useful to manipulate brain data

sMRI Quality Control
  • Image processing failures happen! It is important to perform systematic quality control to minimize biases

sMRI Statistical Analysis
  • Multiple volumetric and surface metrics exist to characterize brain structure morphology

  • Both conventional statistical models and specific neuroimaging approaches can be used

  • Caution should be exercised at both data inspection and model interpretation levels

sMRI Analysis: Reproducibility Considerations
  • It is crucial to assess biological vs methodological variation in your findings to avoid reproducibility crisis.