function [m]=my_filter(filename)
coeffthreshold=10;
time_conversion=20000;
totallength=0;
spikes_sparse=[];

%flags
plot_unfilteredfiltered_comparison=0;
plot_filteredspike_comparison=0;

for numfile=1:1%numfiles
    
    load(sprintf('%s.mat',filename));

    data=[];
    for i=1:length(dataStruct.data)
        temp=dataStruct.data(i);
        temp=temp{:,:};
        data=[data; temp(1001:end,:)];
    end
    
    
    spikes=logical(zeros(size(data)));
    numpoints=length(data);
    f=numpoints; %nyquist frequency
    
    data_fft=zeros(f,1);
    for i=1:64
        
        %%%%%%%%%%%%%%%%%%%%%%%%%
        %filter               %%%
        %%%%%%%%%%%%%%%%%%%%%%%%%
        clear temp;
        temp=detrend(data(:,i));
        data_fft=fft(temp, f);
        data_fft2=data_fft;
        %zero window around frequencies with coefficients above threshold
        for j=1:f
            if abs(data_fft(j,1)) > coeffthreshold
                if j-2<1
                    low=1;
                else low=j-2;
                end
                if j+2>f
                    high=f;
                else high=j+2;
                end
                for k=low:high
                    data_fft(k,1)=0;
                end
            end
            
        end
        
        %zero out frequencies above 5000Hz
        data_fft(round(5000*f/time_conversion+1):f-round(5000*f/time_conversion-1))=0;
        
        %zero out frequencies below 500Hz
        data_fft(1:round(500*f/time_conversion))=0;
        data_fft(f-round(500*f/time_conversion-1):f)=0;
        
        %compute inverse transform
        temp=real(ifft(data_fft,numpoints));
        temp=temp-mean(temp);
        
        if plot_unfilteredfiltered_comparison==1
            subplot(8,8,i);
            plot(dataStruct.timeVec,dataStruct.data(:,i), 'r', dataStruct.timeVec,temp, 'g');
            xlabel('Time (ms)');
            ylabel('Voltage');
            title('Comparison of Filtered and Unfiltered Signals');
        end
        
        
        %%%%%%%%%%%%%%%%%%%%%%%%%
        %extract spikes       %%%
        %%%%%%%%%%%%%%%%%%%%%%%%%
        
        %set threshold to be 3.2 standard deviations above mean
        spikethresh=3.2*std(temp);
        
        %set maximum spike time
        spikemax=2e-7;
        
        %puts spike at maximum of signal
        for j=1:numpoints
            if (temp(j)>spikethresh)|(temp(j)<(-1*spikethresh))
                maxpoint=j;
                for k=j:j+round(spikemax*time_conversion)
                    if temp(k) > temp(j)
                        maxpoint=k;
                    end
                end
                spikes(maxpoint,i)=1;
                j=k+1;
            end
        end
        
        if plot_filteredspike_comparison==1
            subplot(8,8,i)
            plot(dataStruct.timeVec,temp,'g', dataStruct.timeVec, .0005*spikes(1:numpoints,i),'b');
            xlabel('Time (ms)');
            ylabel('Voltage / Spike');
            title('Comparison of Filtered Signal and Extracted Spikes');
        end
    end
    
    %Compress to spare matrix
    spikes_sparse = [spikes_sparse; sparse(spikes)];
    
    totallength=totallength + numpoints;
    clear temp dataStruct spikes;
end

spikes=spikes_sparse;
% save extracted spikes as sparse matrix
save(sprintf('%s_spikes.mat',filename),'spikes');

[m]=spikes;