View on GitHub

fmri-for-beginners

A course designed for anyone entering the field of fMRI-based cognitive neuroscience. It covers both the theory behind how we analyze the data and technical skills/knowledge to apply right away. This course is designed for those who are new to the field, but contains useful resources for all skill levels.

Data Management Basics

This is something that I am sure is done differently no matter which lab you are in, but the purpose of it is universal: make sure your data is good and organized. In my experience, this is best done with a spreadsheet where you can have a row for each participant and a column for each scan or other data. Then, some very motivated students can open up each scan in a program like MRIcron or afni, and make notes on any artifacts or missing data. You may be asking yourself, What is an artifact? Not only is something that is described very well in the video below and supplemented by the article linked, and an artifact is any distortion or error in the imaging data that can be obscure or mimic the true signal. In simpler terms, it is when there is a problem with the image.

Principles of fMRI Part 1, Module 9: fMRI Artifacts and Nois e(Video)

[BOLD fMRI and DTI: Artifacts, Tips, and Tricks Radiology Key (Article)](https://radiologykey.com/bold-fmri-and-dti-artifacts-tips-and-tricks/)

At the end of the day, my best piece of advice for finding artifacts is to trust your gut and make sure you are actively paying attention when checking data(which you should be doing regardless, but you need to really be attentive to catch the small things). If something doesn’t look right, it probably isn’t. Your intuition for this will get better with time and experience. Don’t be afraid to annoy your superiors asking if something is an artifact(which they may not appreciate) since trying to identify it yourself is the best practice.

Last Page - (Preprocessing) Next Page - (Statistics)
Home