Online Signal Averaging Example

Import strobe store gizmo data into MATLAB using SynapseLive during the experiment
Plot the average waveform
Good for Evoked Potential visualization

Download M File

Download Experiment File

Housekeeping

Clear workspace and close existing figures. Add SDK directories to Matlab path.

close all; clc;
[MAINEXAMPLEPATH,name,ext] = fileparts(cd); % \TDTMatlabSDK\Examples
[SDKPATH,name,ext] = fileparts(MAINEXAMPLEPATH); % \TDTMatlabSDK
addpath(genpath(SDKPATH));

Variable Setup

Set up the variables for the data you want to extract. We will extract a single channel from a fixed duration strobed storage gizmo.

EVENT = 'StS1';
CHANNEL = 1;

show the last N waveforms in the plot.

N = 5;

Set KEEPALL to 0 to only show the running average of the last N waveforms. Otherwise, all waveforms in the block are included in the average.

KEEPALL = 0;

Setup SynapseLive

t = SynapseLive('MODE', 'Preview', 'EXPERIMENT', 'OnlineAveragingDemo'); % we will default to 'Preview' mode
t.TYPE = {'snips'}; % we only care about these types of events
t.VERBOSE = false;
first_pass = true;

Connected to TANK: F:\Tanks\OnlineAveragingDemo-220119-151526, BLOCK: TempBlk
Waiting for initial data...............................done

The Main Loop

prevWaves = cell(1,N);
nsweeps = 0;
while 1

    % slow it down a little
    pause(1)

    % get the most recent data, exit loop if the block has stopped
    if isempty(t.update)
        break
    end

    % read the snippet events
    r = t.get_data(EVENT);
    if isstruct(r)
        if ~isnan(r.data)
            % get our channel of data
            chan_data = r.data(r.chan == CHANNEL,:);
            nsize = size(chan_data,1);

            % cache the waveforms in our circular buffer
            prevWaves = circshift(prevWaves, -nsize);
            for i = 1:(min(nsize, N))
                prevWaves{i} = chan_data(end-(i-1),:);
            end

            % find average signal
            cache_ind = ~cellfun('isempty', prevWaves);
            if KEEPALL == 0
                % if we are only keeping the previous N, do average on just those
                avg_data = mean(cell2mat(prevWaves(cache_ind)'), 1);
            else
                if first_pass
                    first_pass = false;
                    nsweeps = nsize;
                    avg_data = new_mean;
                else
                    new_mean = mean(chan_data, 1);
                    % add new average into the old average
                    avg_data = (avg_data .* nsweeps + new_mean * nsize) / (nsweeps + nsize);
                end
            end

            nsweeps = nsweeps + nsize;

            % plot the preview N waves in gray
            t_ms = 1000*(1:numel(avg_data)) / r.fs;
            plot(t_ms, cell2mat(prevWaves(cache_ind)')','Color', [.85 .85 .85]); hold on;

            % plot the average signal in thick blue
            plot(t_ms, avg_data, 'b', 'LineWidth', 3); hold off;

            % finish up plot
            title(sprintf('nsweeps = %d, last %d shown', nsweeps, N));
            xlabel('Time, ms','FontSize',12)
            ylabel('V', 'FontSize', 12)
            temp_axis = axis;
            temp_axis(1) = t_ms(1);
            temp_axis(2) = t_ms(end);
            axis(temp_axis);

            % force the plots to update
            try
                snapnow
            catch
                drawnow
            end

            % for publishing, end early
            if nsweeps > 30
                t.SYN.setModeStr('Idle'); % set to idle mode
                break
            end
        end
    end
end

Runtime Output