Make artwork representing your brain with the Muse EEG headband, and learn about neurotech in the process!
Lecturing is boring! Instead, we want pairs of students to work towards the final brain-art project. Pairs will go through each week's notebook, and fill in the code and run it. Mentors will be available to help the pairs debug or understand the overall concepts better.
This is going to be a cross of our workshops from 2017-2018 and our initial Prezi workshops, but with less emphasis on hardware and more emphasis on sofware techniques and the brain.
NOTE: This course is extensive! We're teaching a lot of material, and some can be quite advanced... But we are here to guide you throughout the entire process, so if you feel lost at any point don't worry! Just come to HackTernoons or office hours and we'll learn it together :)
NOTE 2: We're trying to introduce you to a lot of crazy things in the span of 2 semesters! This means we have to rely on readings to prep you for each week's workshop. Please make sure to do the mandatory readings and any mandatory prep noted before you come to the workshop, as it will make understanding the material infinitely easier :)
There is no official textbook for this course; however Week 10 will rely on Analyzing Neural Time Series Data by Mike Cohen. You can find the book through the UofT Library system.
https://www.sitepoint.com/quick-tip-sync-your-fork-with-the-original-without-the-cli/
As you go through the workshop, you'll essentially be working on a mini-project and these milestones will give you a way to judge how far along you've come:
Milestone 1: Make an app printing out raw data from the Muse in real-time
Milestone 2: Filter data from the Muse in your app in real-time
Milestone 3: Design, implement, and verify EEG interpretation algorithm on pre-collected data in Python
Milestone 4: Implement and verify real-time EEG interpretation algorithm in Angular
(For details, scroll down to "Weekly Details")
Absolute basics of programming
Some programming, problem solving practice
How to load data from CSVs (or FIFs), graphing data with MatPlotLib, filtering noise, and an introduction to the Fast Fourier Transform.
Front-end programming with Angular, signal acquisition from the Muse using MuseJs, BrainArt architecture, complete BrainArt Milestone 1.
History, how neurons work (brief intro), neuroanatomy review, Rall's cable theory, membrane potential (Nernst, GHK, HH equations).
Lecture about convolution, Discrete Fourier Transform.
Convolution, impulse responses, signal types, continuous vs discrete, aliasing, Nyquist's Theorem, FIR vs IIR, different types of filters, filter order.
Scenario-based practice of DSP I concepts, complete BrainArt Milestone 2.
What exactly is EEG, physics of EEG, oscillatory processes vs ERPs, power spectral analysis for EEG power bands.
Advanced Git, OOP, General Best Practices.
Dev session for BrainArt (offline data), complete BrainArt Milestone 3.
Dev session for BrainArt (online with Muse), complete BrainArt Milestone 4.
Present brain art piece to NeurotechUofT faculty advisors, prizes, and fun!!
Absolute basics of programming
Materials:
- learn Python! http://bit.ly/ntuoft-workshop-2
Some programming, problem solving practice
Preparation:
- Wait But Why: Neuralink - The Human Colossus
- Practice Python (30 mins per day): https://codecombat.com/
https://docs.google.com/document/d/1_VC2Wxz-Qt1g_5Hoh6R5Z6Ln_moHM4Nn7CvTpkcmmS8/edit