Extracting different frequency bands (alpha, beta, gamma) from brain activity data I am new to signal processing and despite googling about my question, I still couldn't find the solution.

I have an Electrocorticography (ECoG) dataset. This consists of recording brain activity from many channels. The data is stored in a matrix. Data in each row relates to the brain activity recorded from each channel. Brain activity data was recorded with 10kHz frequency (Therefore, the continues 10,000 elements of each row is the brain activity data of 1s)

Similar to many analysis such as, I need to extract powers of different frequency bands (1-8 hz, etc) from this data and run some regression anlaysis. 

For example, as a sentence from a previous study: 


  A fast Fourier transformation (FFT; EEGLAB v5.03) was performed for each 1-secondsignal to obtain the power of each of the 3 frequency bands(2–8, 8–25, and 80–150Hz) for each electrode


I am still confused how should I apply the fft function of matlab to correctly obtain power of different frequency bands. 

Considering I only have this matrix of dataset (each row: brain activity recorded from each channel) and also the fact that I am not very familiar with methods in signal processing, I appreciate if someone can kindly help me how should I do such an analysis.
MATLAB's fft returns the FFT of the columns of a matrix X, so by transposing your input matrix before feeding it to the algorithm should work fine: F = fft(X.'); and then you will have the FFT for each channel of yours.

The FFT can be used to obtain the power spectrum. Here is a link with examples and explanations.

Once you have your power spectrum, then there are plenty of ways to extract different frequency bands (mostly based on filtering).