Chapter 10: Big Brain Data

Photo by Robina Weermeijer on Unsplash

As we think and act, the brain is constantly producing Big Data in the firing of its neurons and in the connections that are strengthened and weakened. This chapter discusses how we can study the brain and the Big Data that it creates. First, we discuss how clever behavioral tasks, looking at development and other species, and natural variation across people are our first tools for understanding the brain. Next, we delve into describing several popular brain imaging methods – direct recording, electroencephalography, magnetoencephalography, magnetic resonance imaging, and a few others. We discuss how to interpret the Big Data shown by brain maps, and some Big Data themes like multiple comparisons correction to consider when viewing this data. Finally, we end the chapter discussing the ethical question of whether such neuroimaging allows mindreading.


  • Open neuroimaging repositories
  • Here is a list of repositories making neuroscience data available. I will update this list as I come across more repositories:

  • Neuroscience crowd-sourcing resources
  • Here are some interesting meta-analysis and crowd-sourcing brain imaging resources:
    Braindr is a Tinder-like service for crowd-sourcing quality judgments of brain MRI images. Users swipe left or right depending on the quality of the scan.
    Neurosynth is a tool that synthesizes and visualized MRI results across multiple studies.
    Gallant Lab Brain viewers allows for dynamic navigation of brain imaging results from the lab of Prof. Jack Gallant.

  • Get started working with brain imaging data
  • Andy's Brain Blog by Andrew Jahn is a fantastic resource for learning about analyzing MRI data.
    The AFNI Bootcamp for learning how to use the MRI analysis and preprocessing tool AFNI.
    BrainVoyager's Guide for analyzing fMRI data.