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spike_processing.asv
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spike_processing.asv
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set(0,'DefaultFigureWindowStyle','docked'); % fix matlab's figure positioning bug
%% or load from MAT file
%{
%load('C:\Users\Jakob Voigts\Downloads\example_ephys\ancalogon_2019-11-13T07_51_08_TT13_100sec.mat');
load('C:\Users\Jakob Voigts\Downloads\example_ephys\ancalogon_2019-11-13T07_51_08_TT13_600sec.mat');
fs = 30000; % 30KHz
v_temp=v_temp';
%}
%% load raw data
% raw data available on
% usb sticks
%
addpath('C:\Users\Jakob Voigts\Documents\GitHub\analysis-tools\');
%datapath='C:\Users\Jakob Voigts\Desktop\pondababa_2021-09-18_09-33-02\Record Node 111\'
datapath='C:\Users\Jakob Voigts\Downloads\example_ephys\2022-06-12_16-24-58\Record Node 117\experiment1\recording1\structure.oebin'
D=load_open_ephys_binary(datapath,'continuous',1,'mmap');
v_temp=D.Data.Data.mapped([0:3]*1),:)';
v_temp=v_temp.*0.195; % go from raw to uV
fs = D.Header.sample_rate;
%%data_raw=data_raw(1:30000,:); % cut away some data for faster testing
% plot raw data
% data_raw=data_raw-repmat(median_all_data',1,4);
% data_raw(50000+[0:2],:)=-80; % add fake spike?
plotlim=200000;
offs=1200000;
figure(1);
clf;
hold on;
plot(v_temp([1:plotlim],:));
%% filter
clf; hold on;
[b,a] = butter(3, [300 3000]/(fs/2)); % choose filter (normalize bp freq. to nyquist freq.)
data_bp=filter(b,a,v_temp); %apply filter in one direction
plot(v_temp(1:plotlim,:),'k:');
plot(data_bp(1:plotlim,:));
% find treshold crossings
treshold=600;
crossed= min(data_bp,[],2)<-treshold; % trigger if _any_ channel crosses in neg. direction
spike_onsets=find(diff(crossed)==1);
length_sec=size(v_temp,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);
for i=1:numel(spike_onsets)
if(spike_onsets(i)<plotlim)
plot([1 1].*spike_onsets(i),[-1 1].*treshold*2,'k--')
end;
end;
disp('done filtering')
%% 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;
%% plot peak to peak amplitudes
clf; hold on;
plot(spikes.peakamps(:,1),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(0.5,25,20);
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, * intersect 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;