SNR data export

[laopenti]

Hi, Biafra~

Lately, I've been working on a two-photon .tiff file through computeManualSortSignals on MatLab 2020b, win10. Normally, all things pretty good so far. Thank you for the update version2.5.1, it's amazing.

Could you please concretely enlighten a handy approach or code to help me to export the SNR value of every identified cell while or finishing the computeManualSortSignals part. I could only read it from the interface like below on-by-one.

If there is no misunderstanding on SNR here in CIAtah v2.5.1, that is Signals Noise Ratio, an important parameter I would use someday. So, hope you would help me with that.

And, one more thing, have you ever considered uploading a teaching video on the Internet about the rest of the operation after computeManualSortSignals?

Best Wishes to you!

Benson
from SheepMountain, NJ

[bahanonu]

hey Benson, great to hear things are working out for you. To grab the SNR you can load in the already processed data then compute SNR as below:

% Load data
[inputImages,inputSignals,infoStruct,algorithmStr] = ciapkg.io.loadSignalExtraction('path_to_file.mat');

% Compute SNR
inputSnr = computeSignalSnr(inputSignals,'detectMethod','raw','numStdsForThresh',2);

re: after computeManualSortSignals, are there specific steps or analyses you are referring to? We'll have a book chapter out soon that covers some later steps, e.g. comparing neural activity to behavior/stimuli.

[laopenti]

Hi, Biafra

Thanks for the reply so quickly.

• The grabbing is smoothly with your code demonstrated above, which is significant for my job-to-do.

• Frankly speaking, I am a novice on CalciumImagingAnalysis and NeuralScience. There are so many analysis jobs I should- and would- do. Such as time-frequency analysis within a single neuron or a given population, classified neuron spatial correlation analysis. Each of them seems worthy yet intricacy to handling. I have to learn some other knowledge and Matlab skills to accomplish the later steps.

• So, it is terrific to acknowledge that the new book chapter comes out soon which covers some later steps.

• We will follow your great algorithm persistently and looking forward to other more powerful processing approaches.

Benson
From SheepMountain, NJ