Class is one session with an optional Python session earlier in the day:

[optional] Python Boot Camp on Monday, January 20th from 9am-1pm

Neurohacking 101 on Monday, January 20th from 2pm-8pm

Did you know you can learn a lot 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? MRI has revolutionized the way we see the brain and mind, and it is advancing at an incredible speed. This introductory course covers some of the most important techniques used in the analysis of MRI data, and you’ll learn plenty about neuroscience along the way!

We’ll start by going over some of the neuroscience fundamentals, and talk about how they apply to brain networks. You’ll learn to use Python, a powerful general-purpose open-source programming language. You’ll get an introduction to working with powerful Python packages, including Nilearn, Nibabel, and Scikit Learn. You’ll pull brain data from servers, and analyze and visualize the brain networks in these open source data on your own laptop!

About the Optional Python Boot Camp. Python is an incredibly powerful and easy to learn all-purpose programming language. We will be walking step-by-step through DataCamp’s Introduction to Python Course, which is freely available online. This optional boot camp is a great course for people who haven’t programmed at all, or just never in Python. This would also be a great refresher course for people who already have a bit of experience but may feel rusty.

Aki Nikolaidis, PhD, is a research scientist in the Center for the Developing Brain at the Child Mind Institute. His research focuses on using advanced machine learning techniques to map the brains corticostriatal circuits. These circuits play a central role in driving brain plasticity related to learning, addiction, and psychopathology in children and adults. Through a better characterization of these systems, we can develop a better understanding of how our minds change through the interaction between our experiences and patterns of large-scale brain plasticity. Towards these efforts, he has created PyBASC, a powerful open source python platform that leverages advanced machine learning to improve the sensitivity and reliability of mapping the organization of the brain’s corticostriatal circuits.

Dr. Nikolaidis completed his undergraduate studies in psychology at Yale, and subsequently went abroad for research positions in Bern and Taipei. While completing his graduate studies at the University of Illinois, Aki investigated how brain networks, metabolism, and structure contribute to individual differences in executive function, intelligence, and learning. His work has also focused on understanding how interventions drive brain plasticity and improvements in cognition. In addition to a National Science Foundation Graduate Fellowship, Dr. Nikolaidis has received multiple awards and fellowships from the Yale University and the University of Illinois for his work using techniques from machine learning in neuroscience. In 2018, Dr. Nikolaidis was given the NARSAD Young Investigator Award from the Brain and Behavior Research Foundation.