Course Details
Week 1
Introduction to Neural Signal Processing
Course and participant introductions
Overview of neural signal recording
Pre-processing: filtering, power spectral density (PSD), beta desynchronization
Feature extraction: thresholding, amplitude-based methods
Python environment setup
Week 2.1
Signal Games & Artifact Handling
Revisit Week 1 concepts through an interactive signal game
Introduction to artifacts using the game
Techniques for artifact removal
Introduction to probability concepts
Week 2.2
Probability & Independent Component Analysis (ICA)
Deeper exploration of probability
Introduction to ICA
Hands-on ICA implementation via signal game
Week 2.1
Signal Games & Artifact Handling
Revisit Week 1 concepts through an interactive signal game
Introduction to artifacts using the game
Techniques for artifact removal
Introduction to probability concepts
Week 2.2
Probability & Independent Component Analysis (ICA)
Deeper exploration of probability
Introduction to ICA
Hands-on ICA implementation via signal game
Week 2.1
Signal Games & Artifact Handling
Revisit Week 1 concepts through an interactive signal game
Introduction to artifacts using the game
Techniques for artifact removal
Introduction to probability concepts
Week 2.2
Probability & Independent Component Analysis (ICA)
Deeper exploration of probability
Introduction to ICA
Hands-on ICA implementation via signal game
Week 2.1
Signal Games & Artifact Handling
Revisit Week 1 concepts through an interactive signal game
Introduction to artifacts using the game
Techniques for artifact removal
Introduction to probability concepts
Week 2.2
Probability & Independent Component Analysis (ICA)
Deeper exploration of probability
Introduction to ICA
Hands-on ICA implementation via signal game
Week 3.1
Guest Lecture and Project Kickoff
Quick review of prior content
Guest lecture by industry specialist
Launch of the final BCI project
Basics of loading datasets and plotting signals with filtering
Week 3.2
Advanced Signal Processing
Noise removal using ICA
Detailed PSD analysis
Filtering signals into frequency bands
Introduction to signal decoding
Week 3.1
Guest Lecture and Project Kickoff
Quick review of prior content
Guest lecture by industry specialist
Launch of the final BCI project
Basics of loading datasets and plotting signals with filtering
Week 3.2
Advanced Signal Processing
Noise removal using ICA
Detailed PSD analysis
Filtering signals into frequency bands
Introduction to signal decoding
Week 3.1
Guest Lecture and Project Kickoff
Quick review of prior content
Guest lecture by industry specialist
Launch of the final BCI project
Basics of loading datasets and plotting signals with filtering
Week 3.2
Advanced Signal Processing
Noise removal using ICA
Detailed PSD analysis
Filtering signals into frequency bands
Introduction to signal decoding
Week 3.1
Guest Lecture and Project Kickoff
Quick review of prior content
Guest lecture by industry specialist
Launch of the final BCI project
Basics of loading datasets and plotting signals with filtering
Week 3.2
Advanced Signal Processing
Noise removal using ICA
Detailed PSD analysis
Filtering signals into frequency bands
Introduction to signal decoding
Week 4.1
Wrap up & Guest Lecturing (Optional)
Open session for discussion, troubleshooting, and final project help
Optional guest lecture or student project showcases
Week 4.1
Guest Lecture and Project Kickoff
Implementing decoding algorithms
Interpreting and presenting final project results
Week 4.1
Wrap up & Guest Lecturing (Optional)
Open session for discussion, troubleshooting, and final project help
Optional guest lecture or student project showcases
Week 4.1
Guest Lecture and Project Kickoff
Implementing decoding algorithms
Interpreting and presenting final project results
Week 4.1
Wrap up & Guest Lecturing (Optional)
Open session for discussion, troubleshooting, and final project help
Optional guest lecture or student project showcases
Week 4.1
Guest Lecture and Project Kickoff
Implementing decoding algorithms
Interpreting and presenting final project results
Week 4.1
Wrap up & Guest Lecturing (Optional)
Open session for discussion, troubleshooting, and final project help
Optional guest lecture or student project showcases
Week 4.1
Guest Lecture and Project Kickoff
Implementing decoding algorithms
Interpreting and presenting final project results