Indexing in for loop

1 vue (au cours des 30 derniers jours)
Mary Hemler
Mary Hemler le 1 Juin 2020
I would like to create a new variable, cells_high_MI, that corresponds to the cellspikes index of the cells that have a high MISpikeTotal value. Here is my code for the MISpikeTotal calculation (towards the bottom of the code):
for i = 1:n_cells
spikes = cellspikes{i}; % access cellspikes
spikes = spikes./1000; % ms to secs
spikes = spikes(spikes>startTime&spikes<stopTime);
edgesT = linspace(startTime,stopTime,numel(trackingtimes)+1);
binnedSpikes = histcounts(spikes,edgesT);% sorts spikes into bins
% also bin headangle data
n_bins_angle = 60;
edgesHD = linspace(min(headangle), max(headangle), n_bins_angle +1);
[occupancy,~,angle_inds] = histcounts(headangle,edgesHD);
for iBin = 1:n_bins_angle
spikesPerAngle(iBin) = sum(binnedSpikes(angle_inds == iBin));
end
SPA(1,i)={spikesPerAngle};
% compute average firing rate for each HD angle
firing_rate = spikesPerAngle./(occupancy.*deltaT); %this vector is a TUNING CURVE!
FR(1,i) = {firing_rate};
% now compute individual pieces needed to compute mutual info
probability_density = occupancy./sum(occupancy); %proportion of time spent at each HD angle per total occupancy at all angles
PD(1,i)={probability_density};
% compute average firing rate across all HD angles
mean_rate = numel(spikes)./(stopTime-startTime);
MR(1,i) = mean_rate;
% compute mutual info between firing rate and HD
mutualInfo = sum(firing_rate .* log2(firing_rate./mean_rate) .* probability_density,'omitnan');
MIperspike = mutualInfo./(mean_rate);
%store mutual info for each cell into a matrix
mutualInfoTotal(1,i) = mutualInfo; %in bits per second
MISpikeTotal(1,i) = MIperspike;
idx = mutualInfoTotal >= 5;
highMI_sec = mutualInfoTotal(idx);
end
So, I have those values of highMI_sec that contain the mutual information values for the cells with MI values of at least 5. But what I actually want are the index numbers of the cells with at least MI values of 5, because I want to use these index numbers in the following calculations:
j=1;
for c=1:n_cells
spikes = cellspikes{c};
spikes = spikes(spikes > startTime & spikes < stopTime);
if length(spikes) >= 1000
edgesT = linspace(startTime,stopTime,numel(trackingtimes)+1);
binnedSpikes = histcounts(spikes,edgesT);
binnedSpikes = smoothdata(binnedSpikes,2,'gaussian',50);
pcaBinnedSpikes(j,:) = zscore(binnedSpikes);
j = j+1;
end
end
So I would like to use only the cellspikes that correspond to cells with an MI of at least 5 by using the indexes of the values in mutualInfoTotal.
Thanks! :)

Réponse acceptée

Rafael S.T. Vieira
Rafael S.T. Vieira le 2 Juin 2020
Why don't you use idx as a vector?
for i = 1:n_cells
...
idx(i) = mutualInfoTotal >= 5;
highMI_sec = mutualInfoTotal(idx(i));
end
Then, later you can skip 0 values using:
for c=1:n_cells
if ~idx(c)
continue
end
spikes = cellspikes{c};
...
end
  2 commentaires
Mary Hemler
Mary Hemler le 2 Juin 2020
I tried this, but I'm getting this error: Unable to perform assignment because the left and right sides have a different number of elements.
Here is the code:
for i = 1:n_cells
spikes = cellspikes{i}; % access cellspikes
spikes = spikes./1000; % ms to secs
spikes = spikes(spikes>startTime&spikes<stopTime);
edgesT = linspace(startTime,stopTime,numel(trackingtimes)+1);
binnedSpikes = histcounts(spikes,edgesT);% sorts spikes into bins
% also bin headangle data
n_bins_angle = 60;
edgesHD = linspace(min(headangle), max(headangle), n_bins_angle +1);
[occupancy,~,angle_inds] = histcounts(headangle,edgesHD);
for iBin = 1:n_bins_angle
spikesPerAngle(iBin) = sum(binnedSpikes(angle_inds == iBin));
end
SPA(1,i)={spikesPerAngle};
% compute average firing rate for each HD angle
firing_rate = spikesPerAngle./(occupancy.*deltaT); %this vector is a TUNING CURVE!
FR(1,i) = {firing_rate};
% now compute individual pieces needed to compute mutual info
probability_density = occupancy./sum(occupancy); %proportion of time spent at each HD angle per total occupancy at all angles
PD(1,i)={probability_density};
% compute average firing rate across all HD angles
mean_rate = numel(spikes)./(stopTime-startTime);
MR(1,i) = mean_rate;
% compute mutual info between firing rate and HD
mutualInfo = sum(firing_rate .* log2(firing_rate./mean_rate) .* probability_density,'omitnan');
MIperspike = mutualInfo./(mean_rate);
%store mutual info for each cell into a matrix
mutualInfoTotal(1,i) = mutualInfo; %in bits per second
MISpikeTotal(1,i) = MIperspike;
idx(i) = mutualInfoTotal >= 5;
highMI_sec = mutualInfoTotal(idx(i));
end
Rafael S.T. Vieira
Rafael S.T. Vieira le 2 Juin 2020
Modifié(e) : Rafael S.T. Vieira le 2 Juin 2020
Sorry, I didn't see mutualInfoTotal was already a vector, which makes idx also a vector. In such case, If you want the indexes, we can find it with
pos=find(mutualInfoTotal >= 5);
which will give the indexes that you seek.

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