function []=my_analyzeremap2_individualneurons
stimulatednodes=[2 7 10 26 31 34 39 42 47 50 55 58]; %18 excluded b/c there was an error in loading the file
for i=stimulatednodes
    disp(sprintf('Loading and filtering remap2pin%d . . . ',i))
    my_filter_individualneurons(sprintf('remap2pin%d',i));
end

%creates list of neurons at each electrode. Assumes that there is at most one neuron of a given type at a given electrode.
numneurons=[]; %list of all neurons, first column is location, second colum is shape
neurons=cell{64,1}
for i=stimulatednodes
    load(sprintf('remap2pin%d_spikesindivneurons.mat',i));
    for j=1:length(spikes)
        temp=neurons(spikes(2,j),1);
        temp=temp{:,1};
        flag=0;
        for k=1:length(temp}
            if temp(k,1)==spikes(1,j)
                flag=1;
            end
        end    
        if flag==0
            temp=[temp; spikes(1,j)];
            neurons(spikes(2,j),1)=temp;
            numneurons=[numneurons; spikes(2,j) spikes(1,j)];
        end
    end
    clear spikes;
end

%sort neurons (first by location, then by shape)
numneurons=sort(numneurons, [1 2]);

%determines which neurons were stimulated
for i=1:length(numneurons)
    for j=1:length(stimulatenodes)
        if stimulatednodes(j)==numneurons(i,1)
           stimulatedneurons=[stimulatedneurons; i];
       end
   end
end

time_conversion=20000;
connectionsfound=zeros(length(numneurons));

for i=stimulatedneurons
    load(sprintf('remap2pin%d_spikesindivneurons.mat',i));
    disp(sprintf('   Smearing neuron %d . . .', i))

    %determine which neuron was stimulated
    networksize=size(spikes);
    networksize=networksize(1,2);
    for j=1:networksize
        if numneurons(i)==spikes(1:2,j)'
            stim=j;
        end
    end
    
    %smear appropriately 
    spikes=[spikes(1:2,:); my_smearspikes(spikes(3:end,:),stim)];
    disp(sprintf('   Analyzing simulation of neuron %d stimulation . . .', i))
    maxdelay=round(.05*time_conversion);
    
    %set connectionsfound correctly
    holder=my_analyzenetwork(spikes(3:end,:),stim, maxdelay);
    for j=1:length(holder)
        for l=1:length(numneurons)
            if numneurons(l,:)==spikes(1:2,j)'
               connectionsfound(i,l)=holder(j);
           end
       end
   end
end

my_graph_connections(connectionsfound); %note my_graph_connections2 will not produce a spatially meaningful result for this analysis of individual neurons.
save('remap2_connectionsfound.mat','connectionsfound');