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Matlab scripts/accuplot_mini.m

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+function [G,fAxis,showFreqs]=accuplot_mini(EEG, ch1, fs)
+% function for creating the Accusleep function
+% calls createSpectrogram.m, standardizeSR.m and processEMG.m (from Accusleep source code)
+EEGr=EEG';
+
+%% Accusleep
+epochLen=1;
+G = struct; % holds everything
+
+G.originalSR = fs; % EEG/EMG sampling rate
+G.SR = 128; % sampling rate used when calculating spectrogram and processed EMG
+G.epochLen  = epochLen; % length of one epoch (spectrogram column) in seconds
+
+G.EEG=EEGr(ch1,:);
+
+% create spectrogram and process EMG at a standard SR (128)
+[spec, tAxis, fAxis] = createSpectrogram(standardizeSR(G.EEG, G.originalSR, G.SR), G.SR, G.epochLen);
+
+G.nbins = length(tAxis); % total number of time bins in the recording
+
+% get spectrogram and time axes
+showFreqs = find(fAxis <= 30); % only show frequencies under 30 Hz
+G.specTs = (1:G.nbins)*G.epochLen - G.epochLen/2; % spectrogram time axis, in seconds
+G.specTh = G.specTs./3600; % spectrogram time axis, in hours
+G.spectrogram = spec(:,showFreqs); % our EEG spectrogram
+end

Matlab scripts/preproc_frequency_spectra_pfe.m

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+%% Load Ind mat files
+% calls accuplot_mini requiring the Accusleep from Zeke Barger
+% each mat file contains four animals channels 1-4 -> first animal channels 5-8 -> second animal etc.
+% ch 1 = visual cortex right side, ch 2 = superior colliculus right side
+% ch 3 = superior colliculus left side, ch 4 = visual cortex left side
+
+base_dir=uigetdir(pwd); % point to directory of matfiles
+mat=dir(fullfile(base_dir,'*.mat')); % list of files
+nfiles=length(mat);
+%%
+% initiates arrays for visual cortex (VC) and superior colliculus (SC)
+VC=[];
+SC=[];
+
+for thisF=1:nfiles
+    in_mat=fullfile(base_dir,mat(thisF).name); 
+    data=load(in_mat);
+    EEG=data.d; % d1,d2,d3,d4 (four animals per file)  EEG=data x chan
+    spectra=[];
+    %loop for channels 1:4
+    %accuplot function ==> G.spectrogram for each channel
+    for ii=1:4
+        [G,fAxis,showFreqs]=accuplot_mini(EEG, ii, 1000); %takes EEG, ch, fs
+        % spektrum
+        spe=mean(G.spectrogram,1);
+        m=mean(spe);
+        normSpe=spe/m; % normalisation to mean power
+        %plot(fAxis(showFreqs),normSpe) 
+        spectra=cat(1,spectra,normSpe);
+    end
+    % division into VC and SC
+    VC=cat(3,VC,spectra([1,4],:));
+    SC=cat(3,SC,spectra([2,3],:));
+end
+
+%%
+% dividing each file into group_treatment
+KO_veh=[1,5,9,26,30,34,37,41,45,39,43,47,15,19,23,51,55,59,52,56,60,62,66,70,64,68,72,...
+    90,94,98,100,104,108,103,107,111,137,141,145,161,165,169,163,167,171];
+KO_pfe=[3,7,11,13,17,21,16,20,24,50,54,58,74,78,82,76,80,84,...
+    88,92,96,113,117,121,124,128,132,126,130,134,102,106,110,138,142,146,139,143,147,149,153,157,151,155,159];
+WT_veh=[28,32,36,38,42,46,14,18,22,49,53,57,61,65,69,...
+    89,93,97,91,95,99,112,116,120,114,118,122,127,131,135,150,154,158,160,164,168,162,166,170,172:174];
+WT_pfe=[2,6,10,4,8,12,25,29,33,27,31,35,40,44,48,63,67,71,73,77,81,75,79,83,85:87,...
+    115,119,123,125,129,133,101,105,109,136,140,144,148,152,156];
+
+%% Mean and figures
+mKOve_vc=mean(VC(:,:,KO_veh),3);
+mKOpf_vc=mean(VC(:,:,KO_pfe),3);
+mWTve_vc=mean(VC(:,:,WT_veh),3);
+mWTpf_vc=mean(VC(:,:,WT_pfe),3);
+
+figure(1)
+subplot(211)
+hold on
+plot(fAxis(showFreqs),mWTve_vc','k')
+plot(fAxis(showFreqs),mWTpf_vc','b')
+subplot(212)
+hold on
+plot(fAxis(showFreqs),mKOve_vc','k')
+plot(fAxis(showFreqs),mKOpf_vc','b')
+
+
+mKOve_sc=mean(SC(:,:,KO_veh),3);
+mKOpf_sc=mean(SC(:,:,KO_pfe),3);
+mWTve_sc=mean(SC(:,:,WT_veh),3);
+mWTpf_sc=mean(SC(:,:,WT_pfe),3);
+
+
+figure(2)
+subplot(211)
+hold on
+plot(fAxis(showFreqs),mWTve_sc','k')
+plot(fAxis(showFreqs),mWTpf_sc','b')
+subplot(212)
+hold on
+plot(fAxis(showFreqs),mKOve_sc','k')
+plot(fAxis(showFreqs),mKOpf_sc','b')
+% average of spectra
+
+%% save spectrum for each group
+s.VCko=VC(:,:,KO_veh);
+s.VCwt=VC(:,:,WT_veh);
+s.SCko=SC(:,:,KO_veh);
+s.SCwt=SC(:,:,WT_veh);
+s.VCkoP=VC(:,:,KO_pfe);
+s.VCwtP=VC(:,:,WT_pfe);
+s.SCkoP=SC(:,:,KO_pfe);
+s.SCwtP=SC(:,:,WT_pfe);
+
+path1='C:\Users\...'; % path to output
+IDs=strcat(path1,'\SSVEPspectra.mat'); % name of output file
+save(IDs, 's');