Step1_Generate_convergence_connections.m

% Generate connection from source layer to target layer with three convergence structures
% Gaussian-Gaussian(GG) model, Uniform-Constant (UC), and Uniform-Exponential (UE) models
% Please refer to the text for description of each structure
%%
clc
close all
clear all

%% Heterogeneity testing
HETEROGENEITY = true; % Randomize source cells activity or not
%%
PROP_SPEED = 1000 ; % [um/ms] speed of axonal propagation < 1 m/s >
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Cell position
layer1locTxt = 'Cells_position_source_layer1'; % layer 1 (source layer)
layer2locTxt = 'Cells_position_target_layer2'; % layer 2 (target layer)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Download cell position
[L1pos, L1Distmat, L1nnDist]= GetCellsDistInfo(layer1locTxt, 0); %Source Cell
[L2pos, L2Distmat, L2nnDist]= GetCellsDistInfo(layer2locTxt, 0); %Target Cell
DistMat = pdist2(L1pos,L2pos);

dirFile ='Input/'; % The location to save the connection
mkdir(dirFile)

%%

N_TRIAL = 10; % Any N
for TRIAL = 1:N_TRIAL
rng(TRIAL)
PLOT_FIG = 0;

W_SCALE = 0.00001; % Multiplication of weighting factor (because the exact weight value is really small)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Convergence Conditions
W_LST = [50:10:100]; %List of connection strength parameters
Range_LST = [50:10:100]; %List of connection range parameters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

saveConn_g = cell(  length(Range_LST),  length(W_LST));     saveConn_u = cell(  length(Range_LST),  length(W_LST));     saveConn_e = cell(  length(Range_LST),  length(W_LST)); %Saved connection info
rw_NumCon_g = zeros(  length(Range_LST),  length(W_LST));     rw_NumCon_s = zeros(  length(Range_LST),  length(W_LST));    % Average number of Connection 
rw_sumW_g = zeros(  length(Range_LST),  length(W_LST));     rw_sumW_u = zeros(  length(Range_LST),  length(W_LST));     rw_sumW_e = zeros(  length(Range_LST),  length(W_LST)); %average summation of connection strength per target cell



for rr = 1 : length(Range_LST)
    for ww = 1 : length(W_LST)
    tt = tic();
    range = Range_LST(rr);
    weight_factor = W_LST(ww);

    %%
    gConnMat = DistMat.*0;  uConnMat = DistMat.*0;  eConnMat = DistMat.*0;
    gW_Mat = DistMat.*0;    uW_Mat = DistMat.*0;    eW_Mat = DistMat.*0;
    gDelay_Mat = DistMat.*0;    uDelay_Mat = DistMat.*0;    eDelay_Mat = DistMat.*0;
    Pmax = 0.85;

    SumConnectivity_g =  zeros( length(L2pos), 1);
    NumConnection_g = zeros( length(L2pos), 1);

    SumConnectivity_s =  zeros( length(L2pos), 1);
    NumConnection_s = zeros( length(L2pos), 1);

    SumTotalConnStrength_g =  zeros( length(L2pos), 1);
    SumTotalConnStrength_u =  zeros( length(L2pos), 1);
    SumTotalConnStrength_e =  zeros( length(L2pos), 1);

    SumConnStrength_g =  zeros( length(L2pos), 1);
    SumConnStrength_u =  zeros( length(L2pos), 1);
    SumConnStrength_e =  zeros( length(L2pos), 1);

    % Note : For Volume comparison , take summation values of all the cells
    % within range before make connection. This way, it's the closest to the
    % real volumn

    for l2_ID = 1 : length(L2pos) % for each cell in layer 2 (target layer)
        %%% only the cells within range
        potentialLayer1 = find(DistMat(:,l2_ID) <= range*3 ); % Cells that located within range

        %%% Convergent Connection Rule 1
    %     disp('--------------------- G-G ---------------------');
        % ############## Connectivity : Gaussian Distribution
        pp = func_gauss(Pmax, DistMat(potentialLayer1,l2_ID),range);
        xx = rand(size(pp));
        tmpVec_g =  xx < pp; sumProb = sum(pp); 
        tmpConnID = potentialLayer1(tmpVec_g);
        if isempty(tmpConnID) % check the case that there is no connection(xx > pp)
            continue
        end
        nCon_of_g = length(tmpConnID); 

        % Volume Comparison
        SumConnectivity_g(l2_ID) =  sumProb;
        NumConnection_g(l2_ID) = nCon_of_g;

        % Recorded Connection
        gConnMat(tmpConnID,l2_ID) = 1; % 1 = connection exist, 0 = no connection;    
        gDelay_Mat(tmpConnID,l2_ID) = DistMat(tmpConnID, l2_ID)./PROP_SPEED;

        % ############## Connection Strength : Gaussian Distribution
        tmpW = func_gauss(weight_factor*W_SCALE, DistMat(potentialLayer1, l2_ID),range); %for all possible connection within range 
        WforConnectedCells =  tmpW(tmpVec_g);    

        %Volume Comparison
        SumTotalConnStrength_g(l2_ID) = sum(tmpW);
        SumConnStrength_g(l2_ID) =  sum(WforConnectedCells);

        % Recorded Connection Strength
        gW_Mat(tmpConnID,l2_ID) = WforConnectedCells;


    %     disp('--------------------- Uniform Connectivity in U-C and U-E ---------------------');
        %%% Convergent Connection Rule 2 and 3 use the same kind of
        %%% connectivity = Uniform connection from uniform distribution (constant connection)  ----> Make Connectivity first

        % ############## Connectivity : Uniform Distribution
        pGauss = sumProb; % From Gaussian
        pp_s = ones(size(potentialLayer1)).*(pGauss / length(potentialLayer1)); % Average weight per one L1 cell
        xx = rand(size(pp_s));  sumProb_s = sum(pp_s); 
        tmpVec_s =  xx < pp_s;  
        tmpConnID_s = potentialLayer1(tmpVec_s);   
        nCon_of_s = length(tmpConnID_s); 

        % Volume Comparison
        SumConnectivity_s(l2_ID) =  sumProb_s;
        NumConnection_s(l2_ID) = nCon_of_s;

        % Recorded Connection
        % U-C
        uConnMat(tmpConnID_s,l2_ID) = 1; % 1 = connection exist, 0 = no connection;    
        uDelay_Mat(tmpConnID_s,l2_ID) = DistMat(tmpConnID_s, l2_ID)./PROP_SPEED;
        % U-E
        eConnMat(tmpConnID_s,l2_ID) = 1; % 1 = connection exist, 0 = no connection;    
        eDelay_Mat(tmpConnID_s,l2_ID) = DistMat(tmpConnID_s, l2_ID)./PROP_SPEED;


        %%% Convergent Connection Rule 2 : Connectivity - Uniform , Strength - Uniform
    %     disp('-----------------------U-C ---------------------');

        % ############## Connection Strength : Uniform Distribution
        % (Constant)
        wGauss = SumConnStrength_g(l2_ID);% The possible weight in Gaussian 
        avgW = wGauss ./ length(tmpConnID_s); 
        tmpW = ones(size(tmpConnID_s)).*avgW;
        WforConnectedCells_u = tmpW; %  % For Uniform distribution

        %Volume Comparison
        SumTotalConnStrength_u(l2_ID) = sum(tmpW);
        SumConnStrength_u(l2_ID) =  sum(WforConnectedCells_u);

        % Recorded Connection Strength
        uW_Mat(tmpConnID_s,l2_ID) = WforConnectedCells_u;

        %%% Convergent Connection Rule 3 : Connectivity - Uniform , Strength -
        %%% Negative Exponential
    %     disp('-----------------------U-E ---------------------');

        % ############## Connection Strength : Exponential Distribution
        wGauss = SumConnStrength_g(l2_ID);% The possible weight in Gaussian 
        avgW = wGauss./ length(tmpConnID_s); 
        tmpW = exprnd(avgW, size(tmpConnID_s));

        % control sum W to be same 
        tmpW = tmpW.* wGauss./ sum(tmpW); % already checked that distribution of tmpW is same before and after normalized
        WforConnectedCells_e = tmpW;%( tmpVec_s);  % For Exponential distribution
            
        %Volume Comparison
        SumTotalConnStrength_e(l2_ID) = sum(tmpW);
        SumConnStrength_e(l2_ID) =  sum(WforConnectedCells_e);

        % Recorded Connection Strength
        eW_Mat(tmpConnID_s,l2_ID) = WforConnectedCells_e;  


    if(l2_ID == 1)&&(PLOT_FIG) %plot
        figure; set(gcf,'position',[  350         380        1369         420]);
        subplot(131); hist(WforConnectedCells); title(['Gaussian, sum W =' num2str(sum(WforConnectedCells)) ]);
        subplot(132); hist(WforConnectedCells_u); title(['Uniform, sum W =' num2str(sum(WforConnectedCells_u)) ]);
        subplot(133); hist(WforConnectedCells_e); title(['Exponential, sum W =' num2str(sum(WforConnectedCells_e)) ]);
        suptitle('Distribution of weight in one layer2 cell (one cell example)');
    end

    end

    if(PLOT_FIG)
    % Connectivity
    figure; set(gcf,'position',[   657   384   712   420]);
    subplot(121); hist(SumConnectivity_g); title(['Gaussian, mean =' num2str(mean(SumConnectivity_g)) ]); 
    subplot(122); hist(SumConnectivity_s); title(['Uniform, mean =' num2str(mean(SumConnectivity_s)) ]); 
    suptitle('Average sum of connectivity of all cells within range (= Volume of Connectivity)');


    figure; set(gcf,'position',[  657   384   712   420]);
    subplot(121); hist(NumConnection_g); title(['Gaussian, mean =' num2str(mean(NumConnection_g)) ]); 
    subplot(122); hist(NumConnection_s); title(['Uniform, mean =' num2str(mean(NumConnection_s)) ]); 
    suptitle('Average Number of Connection');

    %Connection Strength
    figure; set(gcf,'position',[  350         380        1369         420]);
    subplot(131); hist(SumTotalConnStrength_g); title(['Gaussian, mean =' num2str(mean(SumTotalConnStrength_g)) ]); 
    subplot(132); hist(SumTotalConnStrength_u); title(['Uniform, mean =' num2str(mean(SumTotalConnStrength_u)) ]); 
    subplot(133); hist(SumTotalConnStrength_e); title(['Exponential, mean =' num2str(mean(SumTotalConnStrength_e)) ]); 
    suptitle('Average Total W of all possible connection within range (= Volume of Connection Strength)');

    figure; set(gcf,'position',[  350         380        1369         420]);
    subplot(131); hist(SumConnStrength_g); title(['Gaussian, mean =' num2str(mean(SumConnStrength_g)) ]); 
    subplot(132); hist(SumConnStrength_u); title(['Uniform, mean =' num2str(mean(SumConnStrength_u)) ]); 
    subplot(133); hist(SumConnStrength_e); title(['Exponential, mean =' num2str(mean(SumConnStrength_e)) ]); 
    suptitle('Average summation of effective strength ( strength of connected cells)');
    end

    %save
    tmpStruct.Conn_Mat = sparse(gConnMat);   tmpStruct.W_Mat = sparse(gW_Mat);  tmpStruct.Delay_Mat = sparse(gDelay_Mat); 
    saveConn_g{rr,ww} = tmpStruct;

    tmpStruct.Conn_Mat = sparse(uConnMat);   tmpStruct.W_Mat = sparse(uW_Mat);  tmpStruct.Delay_Mat = sparse(uDelay_Mat); 
    saveConn_u{rr,ww} = tmpStruct;

    tmpStruct.Conn_Mat = sparse(eConnMat);   tmpStruct.W_Mat = sparse(eW_Mat);  tmpStruct.Delay_Mat = sparse(eDelay_Mat); 
    saveConn_e{rr,ww} = tmpStruct;

    % G-G
    [i,j,val] = find(gConnMat);
    conn_list = zeros(length(val), 4);
    cnt = 0;
    for  m = 1: length(i)
            cnt = cnt + 1; 
            conn_list(cnt,:) =[i(m)-1 j(m)-1 gW_Mat(i(m),j(m)) gDelay_Mat(i(m),j(m))];
    end
        
    %Save to file
    fname = sprintf('ConvergentInput_GG_Wscale%.5f_W%g_range%g_Trial%g.txt', W_SCALE, weight_factor, range, TRIAL);
    fid = fopen([dirFile fname],'w');
    fprintf( fid,'%d %d \n', size(conn_list,1),  size(gW_Mat,1)); % Total number of Conn , Total number of cells in Layer1 
    fprintf( fid,'%d %d %1.9f %g\n', conn_list' ); % SourceID TargetID Weight Delay
    fclose(fid);

    % U-C
    [i,j,val] = find(uConnMat);
    conn_list = zeros(length(val), 4);
    cnt = 0;
    for  m = 1: length(i)
            cnt = cnt + 1; 
            conn_list(cnt,:) =[i(m)-1 j(m)-1 uW_Mat(i(m),j(m)) uDelay_Mat(i(m),j(m))];
    end

    %Save to file
    fname = sprintf('ConvergentInput_UC_Wscale%.5f_W%g_range%g_Trial%g.txt', W_SCALE, weight_factor, range, TRIAL);
    fid = fopen([dirFile fname],'w');
    fprintf( fid,'%d %d \n', size(conn_list,1),  size(uW_Mat,1)); % Total number of Conn , Total number of cells in Layer1 
    fprintf( fid,'%d %d %1.9f %g\n', conn_list' ); % SourceID TargetID Weight Delay
    fclose(fid);


    % U-E
    [i,j,val] = find(eConnMat);
    conn_list = zeros(length(val), 4);
    cnt = 0;
    for  m = 1: length(i)
            cnt = cnt + 1; 
            conn_list(cnt,:) =[i(m)-1 j(m)-1 eW_Mat(i(m),j(m)) eDelay_Mat(i(m),j(m))];
    end
     
    %Save to file
    fname = sprintf('ConvergentInput_UE_Wscale%.5f_W%g_range%g_Trial%g.txt', W_SCALE, weight_factor, range, TRIAL);
    fid = fopen([dirFile fname],'w');
    fprintf( fid,'%d %d \n', size(conn_list,1),  size(eW_Mat,1)); % Total number of Conn , Total number of cells in Layer1 
    fprintf( fid,'%d %d %1.9f %g\n', conn_list' ); % SourceID TargetID Weight Delay
    fclose(fid);

    rw_NumCon_g(rr,ww) = mean(NumConnection_g);  rw_NumCon_s(rr,ww) = mean(NumConnection_s); 
    rw_sumW_g(rr,ww) = mean(SumConnStrength_g); rw_sumW_u(rr,ww) = mean(SumConnStrength_u);  rw_sumW_e(rr,ww) = mean(SumConnStrength_e); 

    % Report
    disp('==================================================================================================');
    disp(['Done :: range = ' num2str(range) ', weight factor = ' num2str(weight_factor) ])
    disp(['Average Number of Connection::: Gaussian ' num2str(mean(NumConnection_g)) ', Uniform' num2str(mean(NumConnection_s)) ])
    disp(['Average summation of effective strength::: G-G = ' num2str(mean(SumConnStrength_g)) ', U-C = ' num2str(mean(SumConnStrength_u)) ', U-E = ' num2str(mean(SumConnStrength_e))])
    toc(tt)
    disp('==================================================================================================');

    end
end


%% SAVE sim data
save([dirFile 'NewGennConn_r' num2str(Range_LST(1)) '_' num2str(Range_LST(length(Range_LST))) '_w_' num2str(W_LST(1)) '_' num2str(W_LST(length(W_LST)))  '_trial' num2str(TRIAL) '_'  date '.mat'],'saveConn_g','saveConn_u','saveConn_e','W_LST','Range_LST','-v7.3');
disp('Save')
disp(['Trial = ' num2str(TRIAL)]);
end

% If want to test the cases where phase of source cells are random, hence
% non-homogeneous source layer
if (HETEROGENEITY)
    GenPhase_random_cntrl
end