Signal Generation¶

by Luke Chang

Measuring in-vivo brain activity from humans is an extraordinary feat. How do scanners work? and what exactly are we measuring? In this course, we will be learning how to analyze functional magnetic resonance imaging (fMRI) data. Before we dive in the analysis methods, it’s important to have a basic understanding of what we are measuring. This course primarily focuses on Blood Oxygenated Level Dependent (BOLD) fMRI signals. In this section, we will watch a few short videos by Martin Lindquist and Tor Wager to gain a very high level understanding of (1) magnetic resonance physics, (2) how images are formed from these signals, (3) the relationship between k-space and image space, and (4) BOLD physiology. Gaining a deep understanding of the MR physics and physiological basis for the BOLD fMRI signal is beyond the scope of this course and we refer the interested reader to the excellent Huettel, Song, & McCarthy (2004) Functional magnetic resonance imaging textbook for a more in depth conceptual and quantitative overview.

The lecture for this section can be viewed here.

Basic MR Physics¶

from IPython.display import YouTubeVideo



Image Formation¶

YouTubeVideo('PxqDjhO9FUs')


K-Space¶

YouTubeVideo('FI5frNsRTI4')


fMRI Signal & BOLD Physiology¶

YouTubeVideo('jG2WQpgpnMs')