added code for re-extracting spikes from raw data

extract_spikes_from_raw.m

@@ -0,0 +1,167 @@
+
+
+%% load raw data
+
+set(0,'DefaultFigureWindowStyle','docked'); % fix matlab's figure positioning bug
+
+% raw data available on
+% https://drive.google.com/drive/folders/1CwFcErgp3F3D6I2TB_hTtW1JAQB21TAC?usp=sharing
+%
+datapath='/home/jvoigts/Desktop/TT13_continuous_3/'
+
+out_dir='/home/jvoigts/Desktop/TT13_continuous_3/';
+out_name = 'marie_rsc_test.mat';
+
+source_channels=[40 40 38 36];
+
+data_raw=[];
+for ch=source_cahnnels % grab 4 channels of raw data from one tetrode
+    fname=sprintf('100_CH%d.continuous',ch)
+    [data, timestamps, info]=load_open_ephys_data_faster(fullfile(datapath,fname));
+    data_raw(:,end+1) = data;
+end;
+
+data_raw=data_raw.*info.header.bitVolts;
+fs = info.header.sampleRate;
+
+%data_raw=data_raw(1:30000,:); % cut away some data for faster testing
+
+%% plot
+
+plotlim=50000;
+figure(1);
+clf;
+hold on;
+plot(data_raw(1:plotlim,:));
+
+
+%% filter
+
+clf; hold on;
+[b,a] = butter(3, [300 3000]/(fs/2)); % choose filter (normalize bp freq. to nyquist freq.)
+
+data_bp=filtfilt(b,a,data_raw); %use zero phase filter
+
+%% plot filtered
+offset=plotlim*0;
+clf;
+plot(data_bp([1:plotlim]+offset,:));
+hold on;
+
+%% find treshold crossings
+treshold=-6;
+crossed= min(data_bp,[],2)<-treshold; % trigger if _any_ channel crosses in neg. direction
+
+spike_onsets=find(diff(crossed)==1);
+
+length_sec=size(data,1)/fs;
+fprintf('got %d candidate events in %dmin of data, ~%.2f Hz\n',numel(spike_onsets),round(length_sec/60),numel(spike_onsets)/length_sec);
+
+%% plot some spike onsets 
+for i=1:100%numel(spike_onsets)
+    if(spike_onsets(i)<plotlim)
+        plot([1 1].*spike_onsets(i),[-1 1].*treshold*2,'k--')
+    end;
+end;
+
+
+%% extract spike waveforms and make some features
+
+spike_window=[1:32]-5; % grab some pre-treshold crossign samples
+
+spikes=[];
+spikes.waveforms=zeros(numel(spike_onsets),4*numel(spike_window)); % pre-allocate memory
+spikes.peakamps=zeros(numel(spike_onsets),4);
+spikes.times = spike_onsets/(fs/1000);
+
+for i=1:numel(spike_onsets)
+    this_spike=(data_bp(spike_onsets(i)+spike_window,:));
+
+    spikes.waveforms(i,:)= this_spike(:);% grab entire waveform
+    spikes.peakamps(i,:)=min(this_spike); % grab 4 peak amplitudes
+end;
+
+%% make into and save as simpleclust compatible file
+mua=[];
+mua.waveforms=spikes.waveforms;
+mua.sourcechannel = source_channels;
+mua.ts = spike_onsets/info.header.sampleRate;
+mua.ts_spike=([1:size(spikes.waveforms,2)]-1)./info.header.sampleRate;
+mua.ncontacts=4;
+
+save(fullfile(out_dir,[out_name,'.mat']),'mua');
+
+
+%% BELOW HERE IS A VERY MINIMAL SPIKE SORTER
+
+%% plot peak to peak amplitudes
+clf; hold on;
+plot(spikes.peakamps(:,2),spikes.peakamps(:,4),'.');
+daspect([1 1 1]);
+
+%% initialize all cluster assignments to 1
+spikes.cluster=ones(numel(spike_onsets),1);
+
+%% manual spike sorter
+% cluster 0 shall be the noise cluster (dont plot this one)
+run =1;
+
+projections=[1 2; 1 3; 1 4; 2 3; 2 4; 3 4]; % possible feature projections
+use_projection=1;
+
+cluster_selected=2; spike_selected=1;
+
+while run
+    dat_x=spikes.peakamps(:,projections(use_projection,1));
+    dat_y=spikes.peakamps(:,projections(use_projection,2));
+
+    clf; 
+    subplot(2,3,1); hold on;% plot median waveform
+    plot(quantile(spikes.waveforms(spikes.cluster==cluster_selected,:),.2),'g');
+    plot(quantile(spikes.waveforms(spikes.cluster==cluster_selected,:),.5),'k');
+    plot(quantile(spikes.waveforms(spikes.cluster==cluster_selected,:),.8),'g');
+    plot(spikes.waveforms(spike_selected,:),'r'); % also plot currently selected spike waveform
+
+    title('waveforms from cluster');
+
+    subplot(2,3,4); hold on;% plot isi distribution
+    isi = diff(spikes.times(spikes.cluster==cluster_selected));
+    bins=linspace(0.5,15,20); 
+    h= hist(isi,bins); h(end)=0;
+    stairs(bins,h);
+    title('ISI histogram'); xlabel('isi(ms)');
+
+    ax=subplot(2,3,[2 3 5 6]); hold on; % plot main feature display
+    ii=spikes.cluster>0; % dont plot noise cluster
+    scatter(dat_x(ii),dat_y(ii),(0.5+(spikes.cluster(ii)==cluster_selected))*20,spikes.cluster(ii)*2,'filled');
+    plot(dat_x(spike_selected),dat_y(spike_selected),'ro','markerSize',10);
+    title(sprintf('current cluster %d, projection %d, %d spikes in cluster',cluster_selected,use_projection,sum(spikes.cluster==cluster_selected)));
+
+    [x,y,b]=ginput(1);
+
+    if b>47 & b <58 % number keys, cluster select
+        cluster_selected=b-48;
+    end;
+
+    if b==30; use_projection=mod(use_projection,6)+1; end; % up/down: cycle trough projections
+    if b==31; use_projection=mod(use_projection-2,6)+1; end; % up/down: cycle trough projections
+    if b==27; disp('exited'); run=0; end; % esc: exit
+
+    if b==43 | b==42; % +, add to cluster
+        t= imfreehand(ax,'Closed' ,1);
+        t.setClosed(1);
+        r=t.getPosition;
+        px=r(:,1);py=r(:,2);
+        in = inpolygon(dat_x,dat_y,px,py);
+        if b==43 % +, add
+            spikes.cluster(in)=cluster_selected;
+        else % *. intersect cluster (move all non selected to null cluster)
+            spikes.cluster(~in & spikes.cluster==cluster_selected)=1;
+        end;
+    end;
+
+    if b==1 % left click - select individual waveform to plot
+        [~,spike_selected]=min((dat_x-x).^2 +(dat_y-y).^2);
+    end;
+
+end;

sc_getpolygon.m

@@ -27,7 +27,6 @@
         t= imfreehand(gca,'Closed' ,1);
         t.setClosed(1);
          r=t.getPosition;
-
         px=r(:,1);py=r(:,2);
 
 % remap from screen space to feature space

sc_mua2features.m

@@ -99,7 +99,7 @@
 %% write data
 
 
-features.data=zeros(6,length(mua.ts));
+features.data=zeros(2,length(mua.ts));
 
 lastpercent=0;
 

sc_plotinbox.m

@@ -20,6 +20,10 @@ function sc_plotinbox(x,y,fstr,c,s)
     fstr='k.';
 end;
 
+if min(c==[0 0 1])==1
+    c=[.2 .7 1];
+end;
+
 plot(x,y,fstr,'color',c,'MarkerSize',m)
 
 plot([-1 -1],[-1 1],'k');