Introduction to fMRI data analysis

How can we understand how the brain works? This course provides an introduction to in vivo neuroimaging in humans using functional magnetic resonance imaging (fMRI). The goal of the class is to introduce: (1) how the scanner generates data, (2) how psychological states can be probed in the scanner, and (3) how this data can be processed and analyzed. Students will be expected to collect and analyze brain imaging data using the opensource Python programming language. We will be using several packages such as numpy, matplotlib, nibabel, nilearn, fmriprep, and nltools. This course will be useful for students working in neuroimaging labs, completing a neuroimaging thesis, or interested in pursuing graduate training in fields related to cognitive neuroscience.

GOALS

  1. Learn the basics of fMRI signals
  2. Introduce standard data preprocessing techniques
  3. Introduce the general linear model
  4. Introduce advanced analysis techniques

Acknowledgements

Dartbrains was created by Luke Chang and supported by an NSF CAREER Award 1848370.

Our jupyterhub server was built and maintained by the Research Computing staff at Dartmouth. Special thanks to Susan Schwarz, William Hamblen, Christian Darabos, and John Hudson.