How do I calculate the duration of a peak event for a cell activity signal?

Question

Esther 2024-2-15

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2082668-how-do-i-calculate-the-duration-of-a-peak-event-for-a-cell-activity-signal

编辑： Vinay 2024-9-3，11:15

I have a set of cell activity data plotted over time. I used the findpeaks function to detect peak "events" (in orange circles in screenshot below) which is measured as "dFF." I want to calculate how long each detected peak lasts for. Specifically, I want the code to take the time point of the lowest valley/point of the signal 2 seconds before and after the peak is detected and to subtract those time points to calculate the duration of the peak event. How would I be able to accomplish this?

Example code for the image below:

for i = 1:ncells % loops through each cell 
    fig_title = strcat('DFF, Cell # ', num2str(i));
    [pks, locs] = findpeaks(z_dff(i,:), MinPeakProminence=2, MinPeakDistance=10); % detects peaks in cell activity
    plot(timeSec, z_dff(i,:), timeSec(locs), pks, "o")
    title(fig_title)
                                                                                                                                                                                                                                                                                                                                                                                          
    xlim([1, maxTime])
    ylim ([(min(z_dff, [], "all")-2) (max(z_dff,[],"all"))])
    xlabel('Time');
    ylabel('dFF');
    pause;
end

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Mathieu NOE 2024-3-12

hello

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Answer 1

Vinay 2024-9-3，11:14

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https://ww2.mathworks.cn/matlabcentral/answers/2082668-how-do-i-calculate-the-duration-of-a-peak-event-for-a-cell-activity-signal#answer_1509889

编辑：Vinay 2024-9-3，11:15

在 MATLAB Online 中打开

Hii Esther,

As per my understanding you want to calculate the duration of the peak, which is defined as the time difference between the lowest valley before and after 2 seconds of the peak time.

The approach involves identifying the indices of the data points within the intervals [peakTime - 2, peakTime] and [peakTime, peakTime + 2], and then calculating the minimum values of "dff" within these intervals.

time = 0:0.1:10; % Example time vector
dFF = sin(time) + 1*randn(size(time)); % Example dFF signal with noise
% Find peaks
[peakValues, peakLocs] = findpeaks(dFF, time, MinPeakProminence=0.5, MinPeakDistance=2);
% Initialize array to store durations
peakDurations = zeros(length(peakLocs), 1);
% Loop through each peak to calculate duration
for i = 1:length(peakLocs)
    peakTime = peakLocs(i);
    
    % Find indices within the intervals
    preIntervalIdx = find(time >= peakTime - 2 & time <= peakTime);
    postIntervalIdx = find(time >= peakTime & time <= peakTime + 2);
    
    % Ensure intervals are valid
    if ~isempty(preIntervalIdx) && ~isempty(postIntervalIdx)
        % Find minimum valley values in each interval
        preValleyValue = min(dFF(preIntervalIdx));
        postValleyValue = min(dFF(postIntervalIdx));
        
        % Find corresponding times for these minimum values
        preValleyTime = time(preIntervalIdx(dFF(preIntervalIdx) == preValleyValue));
        postValleyTime = time(postIntervalIdx(dFF(postIntervalIdx) == postValleyValue));
        
        % Calculate duration
        peakDurations(i) = postValleyTime - preValleyTime;
    else
        % If no valid valleys are found, set duration to NaN
        peakDurations(i) = NaN;
    end
end
% Display results
disp('Peak Durations:');
disp(peakDurations);
% Plot results
figure;
plot(time, dFF);
hold on;
plot(peakLocs, peakValues, 'ro'); % Peaks
for i = 1:length(peakLocs)
    if ~isnan(peakDurations(i))
        plot([preValleyTime, postValleyTime], [preValleyValue, postValleyValue], 'go'); % Valleys
    end
end
title('Peaks and Minimum Valleys');
xlabel('Time');
ylabel('dFF');
legend('Signal', 'Peaks', 'Valleys');