Frequency Analysis
This unit covers fundamental and advanced frequency analysis techniques for neural signal processing. You will master power spectral density estimation using Fourier transforms, Welch’s method, and multitapering approaches through hands-on exercises with both synthetic signals and real LFP data. You will also learn how to do time-resolved frequency analysis using Morlet wavelets for tracking dynamic spectral changes and lastly apply statistical methods to determine the statistical significance of peaks in frequency spectra.
Tools
Sessions
Frequency Analysis Tools and Methods
Study How Fourier Transform, Welch's Method, and Multitapering Work with Toy Data
For Loops and Trial Averaged Frequency Spectra
Apply Fourier Transform, Welch's Method, and Multitapering to LFP and Spike Data
Time-resolved Frequency Analysis
Calculate and Analyze Frequency Spectra over Time with Morlet Wavelets
Statistical Significance of Power Spectra
Evaluate the Statistical Significance of Peaks in Power Spectra