143 lines
3.1 KiB
Matlab
143 lines
3.1 KiB
Matlab
% load data into time, voltage and spiketimes
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load( 'extdata' );
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% indices into voltage trace of spike times:
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dt = time( 2) - time(1);
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tinx = round(spiketimes/dt)+1;
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% plot voltage trace with detected spikes:
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figure( 1 );
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clf;
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plot( time, voltage, '-b' )
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hold on
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scatter( time(tinx), voltage(tinx), 'r', 'filled' );
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xlabel( 'time [s]' );
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ylabel( 'voltage' );
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xlim([0.1, 0.4])
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hold off
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% spike waveform snippets:
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w = ceil( 0.005/dt );
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vs = zeros(length(tinx), 2*w);
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for k=1:length(tinx)
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vs(k,:) = voltage(tinx(k)-w:tinx(k)+w-1);
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end
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ts = time(1:size(vs,2));
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ts = ts - ts(floor(length(ts)/2));
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% % plot snippets:
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figure( 2 );
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clf;
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hold on
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for k=1:size(vs,1)
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plot( ts, vs(k,:), '-b' );
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end
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xlabel( 'time [ms]' );
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ylabel( 'voltage' );
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hold off
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% pca:
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cv = cov( vs );
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[ ev , ed ] = eig( cv );
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[d,dinx] = sort( diag(ed), 'descend' );
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figure( 3 );
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clf;
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subplot( 4, 2, 1 );
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imagesc( cv );
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xlabel( 'time bin' );
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ylabel( 'time bin' );
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title( 'covariance matrix' );
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caxis([-0.1 0.1])
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% spectrum of eigenvalues:
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subplot( 4, 2, 2 );
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scatter( 1:length(d), d, 'b', 'filled' );
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xlabel( 'index' );
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ylabel( 'eigenvalue' );
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% features:
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subplot( 4, 2, 5 );
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plot( 1000.0*ts, ev(:,dinx(1)), 'r', 'LineWidth', 2 );
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xlabel( 'time [ms]' );
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ylabel( 'eigenvector 1' );
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subplot( 4, 2, 6 );
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plot( 1000.0*ts, ev(:,dinx(2)), 'g', 'LineWidth', 2 );
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xlabel( 'time [ms]' );
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ylabel( 'eigenvector 2' );
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% project onto eigenvectors:
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nx = vs * ev(:,dinx(1));
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ny = vs * ev(:,dinx(2));
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%scatter( nx, ny, 'b', 'filled', 'MarkerEdgeColor', 'white' );
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% clustering (two clusters):
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%kx = kmeans( [ nx, ny ], 2 );
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% nx smaller or greater a threshold:
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kthresh = 1.6;
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kx = ones( size( nx ) );
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kx(nx<kthresh) = 2;
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subplot( 4, 1, 2 );
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scatter( nx(kx==1), ny(kx==1), 10.0, 'r', 'filled' ); %, 'MarkerEdgeColor', 'white' );
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hold on;
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scatter( nx(kx==2), ny(kx==2), 10.0, 'g', 'filled' ); %, 'MarkerEdgeColor', 'white' );
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hold off;
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xlabel( 'projection onto eigenvector 1' );
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ylabel( 'projection onto eigenvector 2' );
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% show sorted spike waveforms:
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subplot( 4, 2, 7 );
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hold on
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kinx1 = find(kx==1);
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for k=1:length(kinx1)
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plot( 1000.0*ts, vs(kinx1(k),:), '-r' );
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end
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plot( 1000.0*waveformt, waveform2, '-k', 'LineWidth', 2 );
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xlim( [ 1000.0*ts(1) 1000.0*ts(end) ] )
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xlabel( 'time [ms]' );
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ylabel( 'waveform 1' );
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hold off
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subplot( 4, 2, 8 );
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hold on
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kinx2 = find(kx==2);
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for k=1:length(kinx2)
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plot( 1000.0*ts, vs(kinx2(k),:), '-g' );
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end
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plot( 1000.0*waveformt, waveform1, '-k', 'LineWidth', 2 );
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xlim( [ 1000.0*ts(1) 1000.0*ts(end) ] )
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xlabel( 'time [ms]' );
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ylabel( 'waveform 2' );
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hold off
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% spike trains:
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figure( 1 );
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hold on;
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scatter( time(tinx(kinx1)), voltage(tinx(kinx1)), 10.0, 'r', 'filled' );
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scatter( time(tinx(kinx2)), voltage(tinx(kinx2)), 10.0, 'g', 'filled' );
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hold off;
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% ISIs:
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figure(4);
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clf;
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subplot(1, 3, 1)
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allisis = diff(spiketimes);
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hist(allisis, 20);
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title('all spikes')
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xlabel('ISI [ms]')
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subplot(1, 3, 2)
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spikes1 = time(tinx(kinx1));
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isis1 = diff(spikes1);
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hist(isis1, 20);
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title('neuron 1')
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xlabel('ISI [ms]')
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subplot(1, 3, 3)
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spikes2 = time(tinx(kinx2));
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isis2 = diff(spikes2);
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hist(isis2, 20);
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title('neuron 2')
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xlabel('ISI [ms]')
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pause
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