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# Spontaneous oscillatory activity

Spontaneous occipital Alpha rhythm can be induced or suppressed by closing and opening one’s eyes, respectively. In Fig. \ref{fig_spectra} we can see a clear spike in the 10 Hz area in data 1. Compared to the data set 2 no clear spikes it’s pretty safe to assume that data 1 was recorded with eyes closed and data 2 with eyes opened.

The following Matlab script was used for visualization:

 %% Part 1 load('P1_spontaneous_data.mat') Pxx1 = zeros(122, 1025); Pxx2 = zeros(122, 1025); for i = 1:122 [Pxx1(i,:) f] = pwelch(data1(i,:),[],[],2048,sff); [Pxx2(i,:) f] = pwelch(data2(i,:),[],[],2048,sff); i end %% close all plotSpectra(f, Pxx1, Pxx2, 'coils', 'grad2', 'xlimits',[2 30],'Ylimits',[-5e-10 1e-9]); figure semilogy(f,Pxx1(96,:),'b') hold on semilogy(f,Pxx2(96,:),'r') title('Channel 096') xlabel('Frequency [Hz]') ylabel('Power spectral density [T^2/Hz]') legend('Eyes closed', 'Eyes open') 

Here, we used the Welch’s method to estimate the power spectrum. The number of points used for FFT was chosen to be a power of 2 and larger than 4 times the sampling frequency. This corresponds to frequency resolution below 0.5 Hz when Hamming window was used (Full-width half maximum for this window is 2 bins).

\label{fig_spectra} Spectra of all channels. Blue = data1, red = data2