Analyzing Neural Time Series Data Theory And Practice Pdf !link! Download Today

: Principal Components Analysis (PCA), surface Laplacian spatial filters, and cross-frequency coupling.

The author provides all MATLAB code and sample data for free on his personal website. : Principal Components Analysis (PCA)

Beyond basic oscillations, the field is moving toward even more sophisticated metrics: surface Laplacian spatial filters

Some key analysis techniques for neural time series data include: ICA (Independent Component Analysis)

Deconstructing complex neural oscillations into their component frequencies.

Covers artifact rejection, ICA (Independent Component Analysis), referencing, and epoching.