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figures/Figure5/Code/Create_Connectivity_Matrix_From_Data.m

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+function Create_Connectivity_Matrix_From_Data(PyrCell,FSCell)
+% Create_Connectivity_Matrix_From_Data(’L5MouseR1’, ‘BasektR1’)
+
+
+yaml_file='par.yaml';
+y_str = ReadYaml(yaml_file);
+
+ne=y_str.ne;ni=y_str.ni;ke=y_str.ke;ki=y_str.ki;
+gee=y_str.gee;gei=y_str.gei;gie=y_str.gie;gii=y_str.gii;tee=y_str.tee;tei=y_str.tei;tie=y_str.tie;tii=y_str.tii;
+
+g_S=y_str.g_S;
+Cvk=y_str.Cvk;
+
+
+JEE=gee/sqrt(ke)/tee;JEI=gei/sqrt(ki)/tei;JIE=gie/sqrt(ke)/tie;JII=gii/sqrt(ki)/tii;
+
+
+%%%%% Create Balance matrix J%%%%%%%%%%%%%%
+[J_EE]=make_sparse_normalInDeg(ne,ne,ke,JEE,Cvk);
+
+[J_IE]=make_sparse_normalInDeg(ni,ne,ke,JIE,Cvk);
+
+[J_EI]=make_sparse_normalInDeg(ne,ni,ki,JEI,Cvk);
+
+[J_II]=make_sparse_normalInDeg(ni,ni,ki,JII,Cvk);
+
+J_B=[[J_EE,J_EI];[J_IE, J_II]];
+
+%%%%% Create Specific matrix J%%%%%%%%%%%%%%
+
+[J_EE_S]=zeros(ne,ne);
+[J_IE_S]=zeros(ni,ne);
+
+[J_EI_S_LR]=make_sparse_mat(ne/2,ni/2,sqrt(ki),g_S*JEI);
+[J_EI_S_RL]=make_sparse_mat(ne/2,ni/2,sqrt(ki),g_S*JEI);
+[J_II_S_LR]=make_sparse_mat(ni/2,ni/2,sqrt(ki),g_S*JII);
+[J_II_S_RL]=make_sparse_mat(ni/2,ni/2,sqrt(ki),g_S*JII);
+
+
+J_EI_S=[[zeros(ne/2,ni/2),J_EI_S_LR];[J_EI_S_RL, zeros(ne/2,ni/2)]];
+J_II_S=[[zeros(ni/2,ni/2),J_II_S_LR];[J_II_S_RL, zeros(ni/2,ni/2)]];
+
+J_S=[[J_EE_S,J_EI_S];[J_IE_S, J_II_S]];
+
+J=J_B+J_S;
+J=J-diag(diag(J));
+zIndeg=J(1,:)>0;
+zIndeg(1:10)
+
+zOutdeg=J(:,1)>0;
+zOutdeg(1:10)
+
+%%%%%%%%%%%%%%%%% Save Out Deg %%%%%%%%%%%%%%%%%%
+[ind_i,ind_j,val] = find(J);
+ind_i=ind_i-1; %C++ format 0 to n-1
+ind_j=ind_j-1; %C++ format 0 to n-1
+J_transpose=[ind_j,ind_i,val];
+dlmwrite('connectivityOutDeg.txt',J_transpose,'delimiter','\t');
+
+%%%%%%%%%%%%%%%%% Save In Deg  %%%%%%%%%%%%%%%%%%
+% [s_ind_i,sort_ind]=sort(ind_i);
+% s_ind_j=ind_j(sort_ind); %C++ format 0 to n-1
+% s_val=val(sort_ind); %C++ format 0 to n-1
+[ind_i,ind_j,val] = find(J');
+ind_i=ind_i-1; %C++ format 0 to n-1
+ind_j=ind_j-1; %C++ format 0 to n-1
+
+% Generate rho,alpha for E neurons
+Total_E_neruons_in_list=find(ind_j==ne,1)-1;
+% Layer 5 Rat
+if strcmp(PyrCell,'L5RatR1')
+z= readtable('Rm4000_Rin23_norm.csv');
+end
+
+
+% Layer 4 Spiny
+if strcmp(PyrCell,'SpinyR1')
+z= readtable('Rm1000_Rin45_norm.csv');
+end
+
+
+if strcmp(FSCell,'BasketR1')
+z= readtable('/home/ran/Dropbox (HHMI)/VoltageWholeCellProject-2018/MultiCompProject/rhos/NMO_130658/Rm3000_Rin36_norm.csv');
+end
+% Generate rho,alpha for I neurons
+
+[rhoE,alphaE]=ChooseAlphaRhoFromDataEI(z,Total_E_neruons_in_list);
+disp(['Exc alpha: ' num2str(mean(alphaE)) ' rho: ' num2str(mean(rhoE))] )
+
+Total_I_neruons_in_list=length(val)-Total_E_neruons_in_list;
+[rhoI,alphaI]=ChooseAlphaRhoFromDataEI(z,Total_I_neruons_in_list);
+disp(['Inh alpha: ' num2str(mean(alphaI)) ' rho: ' num2str(mean(rhoI))] )
+
+rho=[rhoE;rhoI];
+alpha=[alphaE;alphaI];
+figure(50)
+subplot(2,1,1)
+hist(rhoE,100)
+subplot(2,1,2)
+hist(rhoI,100)
+
+% rho=ones(size(val));
+% alpha=ones(size(val));
+% J=[s_ind_i,s_ind_j,s_val,rho,alpha];
+J_direct=[ind_j,ind_i,val,rho,alpha];
+
+dlmwrite('connectivityInDeg.txt',J_direct,'delimiter','\t');
+
+
+    function [J]=make_sparse_mat(N1,N2,K,J_0)
+%         plotpplo
+        % Create Balance matrix J      
+        J=rand(N1,N2);
+        J(J>=K/N2)=0;
+        J=ceil(J);
+        J=J_0.*J;
+        J        = sparse(J);
+
+    end
+
+
+
+    function [J]=make_sparse_normalInDeg(N1,N2,K,J_0,Cvk)
+        J=zeros(N1,N2);
+        if Cvk==100
+            Cvk=sqrt(K)/K
+        end
+        tmpvec=(1+Cvk*randn(N1,1));
+        kindeg=round((    tmpvec.* (tmpvec>0   ) ).*K); % truncate by 0
+        kindeg(kindeg>N2)=N2; %Truncate by maximal indegree
+        figure;hist(kindeg,100)
+        % Create Balance matrix J     
+        for nn1=1:N1
+            J(nn1,randperm(N2,kindeg(nn1)))=J_0;
+        end
+        J=sparse(J);
+
+    end
+
+
+end

figures/Figure5/Code/Generate_Input.m

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+function [Input]=Generate_Input
+
+addpath(genpath('/home/ran/C-projects/YAML-MATLAB'))
+yaml_file='par.yaml';
+y_str = ReadYaml(yaml_file);
+
+time_sim  = y_str.time_sim;  dt=y_str.dt;
+steps_tot = round(time_sim / dt);
+
+Tstart   = y_str.Tstart;
+Tend     = y_str.Tend;
+AmpInp   = y_str.AmpInp;
+
+Input    = zeros(steps_tot,1);
+Input(round(Tstart/dt):round(Tend/dt))=AmpInp;
+
+
+
+
+dlmwrite('Input.txt',Input,'delimiter','\t');