1. Neural data-analysis Workshop
Ben-Gurion University of the Negev
Dept. of Brain and Cognitive Sciences
Neural data-analysis Workshop

2. Fourier Analysis
Fourier analysis represents a signal in the frequency domain rather than in the time domain.
The Fourier representation is invertible, so one can recover the original signal.
This representation reveals important information about the signal and is the basis for many subsequent analyses.

3. Fourier Analysis
The general idea is that a signal can be decomposed into a linear combination of sine and cosine wave functions.

4. Fourier Series
Fourier series makes use of the orthogonality relationships of
the sine and cosine functions

5. Examples

6. Power Spectrum
The power spectrum is square of the amplitude at each frequency (the square of the cosine coefficient plus the square of the sine coefficient).
It reflects the contribution of each frequency to the signal.
It ignores the precise temporal structure.

7. Extracting Individual Alpha Frequency