Temporal and Spatial Filters

In this unit, you’ll learn how to use spatial and temporal filters to extract specific sources and frequency bands from the EEG signal.

The first lesson will explore spatial filtering with principal component analysis (PCA) and independent component analysis (ICA). Using simulated data, you’ll see how these methods can be used to reduce noise and isolate sources of interest. In the second lesson, you’ll learn how to use finite impulse response (FIR) filters to remove or extract specific frequency bands to preprocess and denoise EEG recordings. Using simulated toy signals, you’ll also explore the different kinds of artifacts that filtering can introduce.