mayadeh-kooti/ohbm2022

Companion repository for my OHBM 2022 Educational Course

OHBM2022

This repository is a companion for Noah C. Benson's OHBM 2022 Educational Course. The course introduces a number of software tools that are useful in the analysis of structure and function in neuroimaging work. The tutorials and resources documented below context and instructions on using these tools.

Introductory Resources

These resources are not necessarily related to the OHBM talk, but they provide useful introductory context for those who are newly learning the neuroimaging software environment.

• Software Carpentry. The Carpentries is a not-for-profit organization that creates introductory data science tutorials on a variety of topics. Their lessons (linked) include an introduction to the UNIX/POSIX shell, using git and GitHub, Python, and R. For those who are new to the shell, git, or Python, these tutorials are a recommended starting place. The setup instructions for the Python lesson provide information on installing Python and JupyterLab, which can be used to view the notebook tutorials (files with .ipynb endings, usually). Note that recordings of many of these tutorials are available on YouTube (search for "software carpentry").
• The Python Datascience Handbook. This book by Jake VanderPlas is an excellent resource for learning valuable and useful data science techniques in Python. Anyone who is new to Python or who is new to data science should strongly consider this book, which is freely available online as a set of Jupyter notebooks on GitHub.
• MRI Geometry. This tutorial is slightly out-dated, but it is still very useful for understanding the basics of cortical geometry and how neuroscience software tends to represent the structural data from MRI scans.
• Retinotopic Maps. Each visual area has a retinotopic map: that is, a mapping of the retina (or, equivalently, the visual field) onto the cortical surface of that visual area. Retinotopic maps are determined by solving what is called a "population receptive field" (pRF) model for each voxel in the visual cortex. The pRF model explains the BOLD respons in terms of the visual stimulus during an fMRI experiment. These resources are related to retinotopic maps and may be useful for understanding them.
  • VistaSoft PRF Tutorial. This tutorial on the VistaSoft suite (for Matlab) to solve pRF models and to analyze retinotopic maps.
  • mrTools PRF Tutorial. This tutorial is similar to the above tutorial, but is for the mrTools suite (also for Matlab).
  • popeye. Popeye is a Python tool for solving retinotopic maps; although this link is not a tutorial, it is a useful start page for this tool and includes links to documentation.
• Andy's Brain Book. This collection of tutorials (including videos for most) by Andy Jahn is incredibly valuable and is referenced frequently below.

Resources Related to the OHBM 2022 Talk

These resources explain the various tools discussed in the OHBM talk specifically.

• Data Processing
  • fMRIprep. I recommend the fMRIprep sequence of tutorials from Andy's Brain Book. These tutorials are comprehensive and include example data and videos. This tutorial by Gelana Tostaeva walks through a different analysis scenario and may also be useful.
  • FreeSurfer. Once again, the FreeSurfer tutorial from Andy's Brain Book is an excellent starting place for learning how to use FreeSurfer. Additionally, FreeSurfer has its own comprehensive collection of tutorials, which can be found here.
• Data Sharing
  • Brain Imagine Data Structure (BIDS). The BIDS tutorial from the Stanford Center for Reproducible Neuroscience along with the BIDS Starter Kit are probably the best places to start learning about BIDS.
  • OpenNeuro.org. I recommend the OpenNeuro user guide for learning about this website and how to use it. Additionally, the INCF Training Space tutorials may be useful for learning about how to upload data to OpenNeuro.
• Data Access and Manipulation
  • DataLad. An comprehensive registry of DataLad tutorials can be found at the GitHub repository datalad/tutorials.
  • Neuropythy. A variety of tutorials for Neuropythy can be found in the GitHub repository noahbenson/neuropythy-tutorials.

Additional Resources

• NeuroStars is a question-and-answer forum where one can post neuroscience questions that aren't covered in these resources!