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DETAILS |
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Class in two sessions:
Saturday, April 28th from 11am-3pm
Sunday, April 29th from 11am-3pm
Did you know you can get a lot of information about the brain from as little as a half hour in an MRI scanner? And that there are tens of thousands of brain scans publicly available on the internet? Functional MRI has revolutionized the way we see the brain & mind, & it is advancing at an incredible speed. This introductory course covers some of the basic techniques used in the cleaning & analysis of fMRI data.
We'll start by going over some of the basic concepts of brain structure, function, & network organization. You'll learn to pull brain data from servers & begin analyzing the data on your own laptop using open source tools in Python, a programming language. Next, we'll introduce some of the statistical tools that we use to study these brains, & you'll learn how to perform them yourself & build your own analysis workflows. After manipulating the data in different ways, you will extract brain networks yourself & visualize them.In the final class, we will introduce the fundamental concepts in machine learning & work together to apply these techniques to MRI data.
No previous experience with Python or data analysis is necessary. If you're new to working with data of any kind, this is a great first course to learn the basics!
Aki Nikolaidis, PhD, is a postdoctoral research fellow in the Center for the Developing Brain at the Child Mind Institute. He uses machine learning techniquesto map out the development of the brain circuits critical for emergence of executive function & attention in children & adolescents. His work also focuses on understanding the neural correlates of intelligence, & more broadly, he is interested in understanding how patterns of large-scale brain plasticity drive the development of generalized higher cognitive skills. Aki received his BA in Psychology from Yale University & PhD in Neuroscience from University of Illinois at Urbana Champaign.
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