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Figure_1.m

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+%% Figure 1
+load('Total Unit Information.mat');
+
+%% Firugre 1D
+% % ****** Flag of finding # of cells for specific condition ****** % %
+MeanFR=0.25;
+iHP = DepthFromCortex_iHP < 5.5;
+vHP = DepthFromCortex_iHP >= 5.5;
+
+main_dHP_exp = strcmp(SessionType_dHP,'SS') | strcmp(SessionType_dHP,'SSCH1') | strcmp(SessionType_dHP,'SSCH2') | strcmp(SessionType_dHP,'FRCH1') |...
+    strcmp(SessionType_dHP,'FRCH2') | strcmp(SessionType_dHP,'SSFR1') | strcmp(SessionType_dHP,'SSFR2') | strcmp(SessionType_dHP,'T-SSCH1') |...
+    strcmp(SessionType_dHP,'T-SSCH2') | strcmp(SessionType_dHP,'T-Quantity1') | strcmp(SessionType_dHP,'T-Quantity2');
+main_iHP_exp = strcmp(SessionType_iHP,'SS') | strcmp(SessionType_iHP,'SSCH1') | strcmp(SessionType_iHP,'SSCH2') | strcmp(SessionType_iHP,'FRCH1') |...
+    strcmp(SessionType_iHP,'FRCH2') | strcmp(SessionType_iHP,'SSFR1') | strcmp(SessionType_iHP,'SSFR2') | strcmp(SessionType_iHP,'T-SSCH1') |...
+    strcmp(SessionType_iHP,'T-SSCH2') | strcmp(SessionType_iHP,'T-Quantity1') | strcmp(SessionType_iHP,'T-Quantity2');
+%
+mask_dHP_LowIsolationQuality=(Assessment_dHP < 2);
+mask_dHP_HighIsolationQuality = ~mask_dHP_LowIsolationQuality;
+mask_dHP_LowStability=(NumberOfSpike_dHP(:,1)==0 | NumberOfSpike_dHP(:,4)==0) & mask_dHP_HighIsolationQuality;
+mask_dHP_HighStability = ~mask_dHP_LowStability;
+mask_dHP_GoodCluster=mask_dHP_HighStability & mask_dHP_HighIsolationQuality;
+mask_dHP_Interneuron = strcmp(Celltype_dHP,'Interneruon') & mask_dHP_HighStability & mask_dHP_HighIsolationQuality;
+mask_dHP_Pyramidal = strcmp(Celltype_dHP,'Pyramidal') & mask_dHP_HighStability & mask_dHP_HighIsolationQuality;
+mask_dHP_NonResponsive=(AvgFr_dHP(:,1) < MeanFR & AvgFr_dHP(:,2) < MeanFR & mask_dHP_HighIsolationQuality & mask_dHP_HighStability & mask_dHP_Pyramidal);
+mask_dHP_Responsive_Both=((AvgFr_dHP(:,1) >= MeanFR & AvgFr_dHP(:,2) >= MeanFR) & mask_dHP_HighIsolationQuality & mask_dHP_HighStability & mask_dHP_Pyramidal);
+mask_dHP_Responsive_OpenField=((AvgFr_dHP(:,1) >= MeanFR) & mask_dHP_HighIsolationQuality & mask_dHP_HighStability & mask_dHP_Pyramidal);
+mask_dHP_Responsive_RadialMaze=((AvgFr_dHP(:,2) >= MeanFR) & mask_dHP_HighIsolationQuality & mask_dHP_HighStability & mask_dHP_Pyramidal);
+LowScoreCLST.dHP=(Assessment_dHP(main_dHP_exp & mask_dHP_LowIsolationQuality));
+LowStabilityCLST.dHP=(Assessment_dHP(main_dHP_exp & mask_dHP_LowStability));
+AnalyzableCLST.dHP_INT=(Assessment_dHP(main_dHP_exp & mask_dHP_Interneuron));
+AnalyzableCLST.dHP_PYR=(Assessment_dHP(main_dHP_exp & mask_dHP_Pyramidal));
+AnalyzableCLST.dHP_PYR_NonResp=(Assessment_dHP(main_dHP_exp & mask_dHP_NonResponsive));
+AnalyzableCLST.dHP_PYR_Resp_Both=(Assessment_dHP(main_dHP_exp & mask_dHP_Responsive_Both));
+AnalyzableCLST.dHP_PYR_Resp_OpenField=(Assessment_dHP(main_dHP_exp & mask_dHP_Responsive_OpenField));
+AnalyzableCLST.dHP_PYR_Resp_RadialMaze=(Assessment_dHP(main_dHP_exp & mask_dHP_Responsive_RadialMaze));
+
+%
+mask_iHP_LowIsolationQuality=(Assessment_iHP < 2);
+mask_iHP_HighIsolationQuality = ~mask_iHP_LowIsolationQuality;
+mask_iHP_LowStability=(NumberOfSpike_iHP(:,1)==0 | NumberOfSpike_iHP(:,4)==0) & mask_iHP_HighIsolationQuality;
+mask_iHP_HighStability = ~mask_iHP_LowStability;
+mask_iHP_GoodCluster=mask_iHP_HighStability & mask_iHP_HighIsolationQuality;
+mask_iHP_Interneuron = strcmp(Celltype_iHP,'Interneruon') & mask_iHP_HighStability & mask_iHP_HighIsolationQuality;
+mask_iHP_Pyramidal = strcmp(Celltype_iHP,'Pyramidal') & mask_iHP_HighStability & mask_iHP_HighIsolationQuality;
+mask_iHP_NonResponsive=(AvgFr_iHP(:,1) < MeanFR & AvgFr_iHP(:,2) < MeanFR & mask_iHP_HighIsolationQuality & mask_iHP_HighStability & mask_iHP_Pyramidal);
+mask_iHP_Responsive_Both=((AvgFr_iHP(:,1) >= MeanFR & AvgFr_iHP(:,2) >= MeanFR) & mask_iHP_HighIsolationQuality & mask_iHP_HighStability & mask_iHP_Pyramidal);
+mask_iHP_Responsive_OpenField=((AvgFr_iHP(:,1) >= MeanFR) & mask_iHP_HighIsolationQuality & mask_iHP_HighStability & mask_iHP_Pyramidal);
+mask_iHP_Responsive_RadialMaze=((AvgFr_iHP(:,2) >= MeanFR) & mask_iHP_HighIsolationQuality & mask_iHP_HighStability & mask_iHP_Pyramidal);
+LowScoreCLST.iHP=(Assessment_iHP(iHP' & main_iHP_exp & mask_iHP_LowIsolationQuality));
+LowStabilityCLST.iHP=(Assessment_iHP(iHP' & main_iHP_exp & mask_iHP_LowStability));
+AnalyzableCLST.iHP_INT=(Assessment_iHP(iHP' & main_iHP_exp & mask_iHP_Interneuron));
+AnalyzableCLST.iHP_PYR=(Assessment_iHP(iHP' & main_iHP_exp & mask_iHP_Pyramidal));
+AnalyzableCLST.iHP_PYR_NonResp=(Assessment_iHP(iHP' & main_iHP_exp & mask_iHP_NonResponsive));
+AnalyzableCLST.iHP_PYR_Resp_Both=(Assessment_iHP(iHP' & main_iHP_exp & mask_iHP_Responsive_Both));
+AnalyzableCLST.iHP_PYR_Resp_OpenField=(Assessment_iHP(iHP' & main_iHP_exp & mask_iHP_Responsive_OpenField));
+AnalyzableCLST.iHP_PYR_Resp_RadialMaze=(Assessment_iHP(iHP' & main_iHP_exp & mask_iHP_Responsive_RadialMaze));
+%
+AnalyzableCLST.vHP_INT=(Assessment_iHP(vHP' & main_iHP_exp & mask_iHP_Interneuron));
+AnalyzableCLST.vHP_PYR=(Assessment_iHP(vHP' & main_iHP_exp & mask_iHP_Pyramidal));
+AnalyzableCLST.vHP_PYR_NonResp=(Assessment_iHP(vHP' & main_iHP_exp & mask_iHP_NonResponsive));
+AnalyzableCLST.vHP_PYR_Resp_Both=(Assessment_iHP(vHP' & main_iHP_exp & mask_iHP_Responsive_Both));
+AnalyzableCLST.vHP_PYR_Resp_OpenField=(Assessment_iHP(vHP' & main_iHP_exp & mask_iHP_Responsive_OpenField));
+AnalyzableCLST.vHP_PYR_Resp_RadialMaze=(Assessment_iHP(vHP' & main_iHP_exp & mask_iHP_Responsive_RadialMaze));
+
+% % ****** Calculate the number of cells in Figure 1D ****** % %
+celltype.dHP_Total=length(Assessment_dHP);
+celltype.dHP_Both=length(AnalyzableCLST.dHP_PYR_Resp_Both);
+celltype.dHP_OpenField=length(AnalyzableCLST.dHP_PYR_Resp_OpenField)-celltype.dHP_Both;
+celltype.dHP_RadialMaze=length(AnalyzableCLST.dHP_PYR_Resp_RadialMaze)-celltype.dHP_Both;
+celltype.dHP_NonResp=length(AnalyzableCLST.dHP_PYR_NonResp);
+
+celltype.iHP_Total=length(iHP' & Assessment_iHP);
+celltype.iHP_Both=length(AnalyzableCLST.iHP_PYR_Resp_Both);
+celltype.iHP_OpenField=length(AnalyzableCLST.iHP_PYR_Resp_OpenField)-celltype.iHP_Both;
+celltype.iHP_RadialMaze=length(AnalyzableCLST.iHP_PYR_Resp_RadialMaze)-celltype.iHP_Both;
+celltype.iHP_NonResp=length(AnalyzableCLST.iHP_PYR_NonResp);
+
+celltype.vHP_Total=length(vHP' & Assessment_iHP);
+celltype.vHP_Both=length(AnalyzableCLST.vHP_PYR_Resp_Both);
+celltype.vHP_OpenField=length(AnalyzableCLST.vHP_PYR_Resp_OpenField)-celltype.vHP_Both;
+celltype.vHP_RadialMaze=length(AnalyzableCLST.vHP_PYR_Resp_RadialMaze)-celltype.vHP_Both;
+celltype.vHP_NonResp=length(AnalyzableCLST.vHP_PYR_NonResp);
+
+x=[celltype.dHP_Both celltype.dHP_OpenField celltype.dHP_RadialMaze celltype.dHP_NonResp];
+y=[celltype.iHP_Both celltype.iHP_OpenField celltype.iHP_RadialMaze celltype.iHP_NonResp];
+z=[celltype.vHP_Both celltype.vHP_OpenField celltype.vHP_RadialMaze celltype.vHP_NonResp];
+
+% % ****** Plotting the pie chart ****** % %
+sum(x)
+fig=figure;
+pie(x)
+SaveRoot=['E:\Ongoing Project\Project - Value-based RW Navigation (dHP-vHP)\Analysis Data\BasicProperties'];
+FileName=['PYR ratio_dHP'];
+SaveFigure(gcf,SaveRoot, FileName);
+
+sum(y)
+fig=figure;
+pie(y)
+SaveRoot=['E:\Ongoing Project\Project - Value-based RW Navigation (dHP-vHP)\Analysis Data\BasicProperties'];
+FileName=['PYR ratio_iHP'];
+SaveFigure(gcf,SaveRoot, FileName);
+
+sum(z)
+fig=figure;
+pie(z)
+SaveRoot=['E:\Ongoing Project\Project - Value-based RW Navigation (dHP-vHP)\Analysis Data\BasicProperties'];
+FileName=['PYR ratio_vHP'];
+SaveFigure(gcf,SaveRoot, FileName);
+
+% % ****** Statistical testing ****** % %
+x=[celltype.dHP_OpenField celltype.dHP_Total-celltype.dHP_OpenField];
+y=[celltype.dHP_RadialMaze celltype.dHP_Total-celltype.dHP_RadialMaze];
+[~,p,stat]=chi2cont([x;y]);
+
+x=[celltype.iHP_OpenField celltype.iHP_Total-celltype.iHP_OpenField];
+y=[celltype.iHP_RadialMaze celltype.iHP_Total-celltype.iHP_RadialMaze];
+[~,p,stat]=chi2cont([x;y]);
+
+x=[celltype.vHP_OpenField celltype.vHP_Total-celltype.vHP_OpenField];
+y=[celltype.vHP_RadialMaze celltype.vHP_Total-celltype.vHP_RadialMaze];
+[~,p,stat]=chi2cont([x;y]);
+
+
+%% Figure 1E, Mean firing rate
+clear all
+load('Analyzable Unit Information.mat');
+main_dHP_exp = strcmp(SessionType_dHP,'SS') | strcmp(SessionType_dHP,'SSCH1') | strcmp(SessionType_dHP,'SSCH2') | strcmp(SessionType_dHP,'FRCH1') |...
+    strcmp(SessionType_dHP,'FRCH2') | strcmp(SessionType_dHP,'SSFR1') | strcmp(SessionType_dHP,'SSFR2') | strcmp(SessionType_dHP,'T-SSCH1') |...
+    strcmp(SessionType_dHP,'T-SSCH2') | strcmp(SessionType_dHP,'T-Quantity1') | strcmp(SessionType_dHP,'T-Quantity2');
+main_iHP_exp = strcmp(SessionType_iHP,'SS') | strcmp(SessionType_iHP,'SSCH1') | strcmp(SessionType_iHP,'SSCH2') | strcmp(SessionType_iHP,'FRCH1') |...
+    strcmp(SessionType_iHP,'FRCH2') | strcmp(SessionType_iHP,'SSFR1') | strcmp(SessionType_iHP,'SSFR2') | strcmp(SessionType_iHP,'T-SSCH1') |...
+    strcmp(SessionType_iHP,'T-SSCH2') | strcmp(SessionType_iHP,'T-Quantity1') | strcmp(SessionType_iHP,'T-Quantity2');
+iHP = DepthFromCortex_iHP < 5.5;
+vHP = DepthFromCortex_iHP >= 5.5;
+
+mask_dHP_LowIsolationQuality=(Assessment_dHP < 2);
+mask_dHP_HighIsolationQuality = ~mask_dHP_LowIsolationQuality;
+mask_dHP_LowStability=(NumberOfSpike_dHP(:,1)==0 | NumberOfSpike_dHP(:,4)==0) & mask_dHP_HighIsolationQuality;
+mask_dHP_HighStability = ~mask_dHP_LowStability;
+mask_dHP_GoodCluster=mask_dHP_HighStability & mask_dHP_HighIsolationQuality;
+
+%
+mask_iHP_LowIsolationQuality=(Assessment_iHP < 2);
+mask_iHP_HighIsolationQuality = ~mask_iHP_LowIsolationQuality;
+mask_iHP_LowStability=(NumberOfSpike_iHP(:,1)==0 | NumberOfSpike_iHP(:,4)==0) & mask_iHP_HighIsolationQuality;
+mask_iHP_HighStability = ~mask_iHP_LowStability;
+mask_iHP_GoodCluster=mask_iHP_HighStability & mask_iHP_HighIsolationQuality;
+
+clear PopulationAvgFr
+a=1; b=1;
+for cl=1:length(Celltype_dHP)
+    if isequal(Celltype_dHP{cl},'Pyramidal') && mask_dHP_GoodCluster(cl)==1 && main_dHP_exp(cl)==1    
+        PopulationAvgFr.Pre_dHP_PYR(a)=PreSleepRate_dHP(cl);   
+        PopulationAvgFr.Main_dHP_PYR(a)=AvgFr_dHP(cl,2);  a=a+1;
+    elseif isequal(Celltype_dHP{cl},'Interneruon') && mask_dHP_GoodCluster(cl)==1 && main_dHP_exp(cl)==1     
+        PopulationAvgFr.Pre_dHP_INT(b)=PreSleepRate_dHP(cl);
+        PopulationAvgFr.Main_dHP_INT(b)=AvgFr_dHP(cl,2);  b=b+1;
+    end
+end
+
+PopulationAvgFr_Rat.Pre_dHP_PYR{1}=[];
+PopulationAvgFr_Rat.Pre_dHP_PYR{2}=[];
+PopulationAvgFr_Rat.Pre_dHP_PYR{3}=[];
+PopulationAvgFr_Rat.Pre_dHP_PYR{4}=[];
+PopulationAvgFr_Rat.Pre_dHP_PYR{5}=[];
+PopulationAvgFr_Rat.Pre_dHP_PYR{6}=[];
+PopulationAvgFr_Rat.Main_dHP_PYR{1}=[];
+PopulationAvgFr_Rat.Main_dHP_PYR{2}=[];
+PopulationAvgFr_Rat.Main_dHP_PYR{3}=[];
+PopulationAvgFr_Rat.Main_dHP_PYR{4}=[];
+PopulationAvgFr_Rat.Main_dHP_PYR{5}=[];
+PopulationAvgFr_Rat.Main_dHP_PYR{6}=[];
+
+for cl=1:length(Celltype_dHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_dHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_dHP{cl},'Pyramidal') && mask_dHP_GoodCluster(cl)==1 && main_dHP_exp(cl)==1
+        switch Rat
+            case 448
+                PopulationAvgFr_Rat.Pre_dHP_PYR{1}(end+1)=PreSleepRate_dHP(cl);   
+                PopulationAvgFr_Rat.Main_dHP_PYR{1}(end+1)=AvgFr_dHP(cl,2); 
+            case 459
+                PopulationAvgFr_Rat.Pre_dHP_PYR{2}(end+1)=PreSleepRate_dHP(cl);   
+                PopulationAvgFr_Rat.Main_dHP_PYR{2}(end+1)=AvgFr_dHP(cl,2); 
+            case 463
+                PopulationAvgFr_Rat.Pre_dHP_PYR{3}(end+1)=PreSleepRate_dHP(cl);   
+                PopulationAvgFr_Rat.Main_dHP_PYR{3}(end+1)=AvgFr_dHP(cl,2); 
+            case 473
+                PopulationAvgFr_Rat.Pre_dHP_PYR{4}(end+1)=PreSleepRate_dHP(cl);   
+                PopulationAvgFr_Rat.Main_dHP_PYR{4}(end+1)=AvgFr_dHP(cl,2); 
+            case 488
+                PopulationAvgFr_Rat.Pre_dHP_PYR{5}(end+1)=PreSleepRate_dHP(cl);   
+                PopulationAvgFr_Rat.Main_dHP_PYR{5}(end+1)=AvgFr_dHP(cl,2); 
+            case 509
+                PopulationAvgFr_Rat.Pre_dHP_PYR{6}(end+1)=PreSleepRate_dHP(cl);   
+                PopulationAvgFr_Rat.Main_dHP_PYR{6}(end+1)=AvgFr_dHP(cl,2); 
+        end
+    end
+end
+
+% iHP
+a=1; b=1;
+for cl=1:length(Celltype_iHP)
+    if iHP(cl) == 1
+        if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1         
+            PopulationAvgFr.Pre_iHP_PYR(a)=PreSleepRate_iHP(cl);
+            PopulationAvgFr.Main_iHP_PYR(a)=AvgFr_iHP(cl,2);
+            PopulationDepth.iHP_PYR(a)=DepthFromCortex_iHP(cl); a=a+1;
+        elseif isequal(Celltype_iHP{cl},'Interneruon') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1    
+            PopulationAvgFr.Pre_iHP_INT(b)=PreSleepRate_iHP(cl);
+            PopulationAvgFr.Main_iHP_INT(b)=AvgFr_iHP(cl,2);
+            PopulationDepth.iHP_INT(b)=DepthFromCortex_iHP(cl); b=b+1;
+        end
+    end
+end
+
+PopulationAvgFr_Rat.Pre_iHP_PYR{1}=[];
+PopulationAvgFr_Rat.Pre_iHP_PYR{2}=[];
+PopulationAvgFr_Rat.Pre_iHP_PYR{3}=[];
+PopulationAvgFr_Rat.Pre_iHP_PYR{4}=[];
+PopulationAvgFr_Rat.Pre_iHP_PYR{5}=[];
+PopulationAvgFr_Rat.Pre_iHP_PYR{6}=[];
+PopulationAvgFr_Rat.Main_iHP_PYR{1}=[];
+PopulationAvgFr_Rat.Main_iHP_PYR{2}=[];
+PopulationAvgFr_Rat.Main_iHP_PYR{3}=[];
+PopulationAvgFr_Rat.Main_iHP_PYR{4}=[];
+PopulationAvgFr_Rat.Main_iHP_PYR{5}=[];
+PopulationAvgFr_Rat.Main_iHP_PYR{6}=[];
+
+for cl=1:length(Celltype_iHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_iHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && iHP(cl) == 1
+        switch Rat
+            case 448
+                PopulationAvgFr_Rat.Pre_iHP_PYR{1}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_iHP_PYR{1}(end+1)=AvgFr_iHP(cl,2); 
+            case 459
+                PopulationAvgFr_Rat.Pre_iHP_PYR{2}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_iHP_PYR{2}(end+1)=AvgFr_iHP(cl,2); 
+            case 463
+                PopulationAvgFr_Rat.Pre_iHP_PYR{3}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_iHP_PYR{3}(end+1)=AvgFr_iHP(cl,2); 
+            case 473
+                PopulationAvgFr_Rat.Pre_iHP_PYR{4}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_iHP_PYR{4}(end+1)=AvgFr_iHP(cl,2); 
+            case 488
+                PopulationAvgFr_Rat.Pre_iHP_PYR{5}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_iHP_PYR{5}(end+1)=AvgFr_iHP(cl,2); 
+            case 509
+                PopulationAvgFr_Rat.Pre_iHP_PYR{6}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_iHP_PYR{6}(end+1)=AvgFr_iHP(cl,2); 
+        end
+    end
+end
+
+% vHP
+a=1; b=1;
+for cl=1:length(Celltype_iHP)
+    if vHP(cl) == 1
+        if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1        
+            PopulationAvgFr.Pre_vHP_PYR(a)=PreSleepRate_iHP(cl);
+            PopulationAvgFr.Main_vHP_PYR(a)=AvgFr_iHP(cl,2);a=a+1;
+        elseif isequal(Celltype_iHP{cl},'Interneruon') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1    
+            PopulationAvgFr.Pre_iHP_INT(b)=PreSleepRate_iHP(cl);
+            PopulationAvgFr.Main_vHP_INT(b)=AvgFr_iHP(cl,2);b=b+1;
+        end
+    end
+end
+
+PopulationAvgFr_Rat.Pre_vHP_PYR{1}=[];
+PopulationAvgFr_Rat.Pre_vHP_PYR{2}=[];
+PopulationAvgFr_Rat.Pre_vHP_PYR{3}=[];
+PopulationAvgFr_Rat.Pre_vHP_PYR{4}=[];
+PopulationAvgFr_Rat.Pre_vHP_PYR{5}=[];
+PopulationAvgFr_Rat.Pre_vHP_PYR{6}=[];
+PopulationAvgFr_Rat.Main_vHP_PYR{1}=[];
+PopulationAvgFr_Rat.Main_vHP_PYR{2}=[];
+PopulationAvgFr_Rat.Main_vHP_PYR{3}=[];
+PopulationAvgFr_Rat.Main_vHP_PYR{4}=[];
+PopulationAvgFr_Rat.Main_vHP_PYR{5}=[];
+PopulationAvgFr_Rat.Main_vHP_PYR{6}=[];
+
+for cl=1:length(Celltype_iHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_iHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && vHP(cl) == 1
+        switch Rat
+            case 448
+                PopulationAvgFr_Rat.Pre_vHP_PYR{1}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_vHP_PYR{1}(end+1)=AvgFr_iHP(cl,2); 
+            case 459
+                PopulationAvgFr_Rat.Pre_vHP_PYR{2}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_vHP_PYR{2}(end+1)=AvgFr_iHP(cl,2); 
+            case 463
+                PopulationAvgFr_Rat.Pre_vHP_PYR{3}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_vHP_PYR{3}(end+1)=AvgFr_iHP(cl,2); 
+            case 473
+                PopulationAvgFr_Rat.Pre_vHP_PYR{4}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_vHP_PYR{4}(end+1)=AvgFr_iHP(cl,2); 
+            case 488
+                PopulationAvgFr_Rat.Pre_vHP_PYR{5}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_vHP_PYR{5}(end+1)=AvgFr_iHP(cl,2); 
+            case 509
+                PopulationAvgFr_Rat.Pre_vHP_PYR{6}(end+1)=PreSleepRate_iHP(cl);   
+                PopulationAvgFr_Rat.Main_vHP_PYR{6}(end+1)=AvgFr_iHP(cl,2); 
+        end
+    end
+end
+
+
+% % ****** Plotting the mean +/- s.t.d grpah****** % %
+fig=figure; hold on; 
+fig.Position=[0 0 1000 500];
+Color.color=2; Color.alpha=1;
+Jin_MeanSTE_Line(1,PopulationAvgFr.Pre_dHP_PYR,Color);
+for i=1:6
+    plot(1, mean(PopulationAvgFr_Rat.Pre_dHP_PYR{i}),'r.')
+end
+Color.color=1;
+Jin_MeanSTE_Line(1,PopulationAvgFr.Pre_iHP_PYR,Color)
+for i=1:6
+    plot(1, mean(PopulationAvgFr_Rat.Pre_iHP_PYR{i}),'b.')
+end
+Color.color=3;
+Jin_MeanSTE_Line(1,PopulationAvgFr.Pre_vHP_PYR,Color)
+for i=1:6
+    plot(1, mean(PopulationAvgFr_Rat.Pre_vHP_PYR{i}),'g.')
+end
+Color.color=2; Color.alpha=1;
+Jin_MeanSTE_Line(2,PopulationAvgFr.Main_dHP_PYR,Color)
+for i=1:6
+    plot(2, mean(PopulationAvgFr_Rat.Main_dHP_PYR{i}),'r.')
+end
+Color.color=1;
+Jin_MeanSTE_Line(2,PopulationAvgFr.Main_iHP_PYR,Color)
+for i=1:6
+    plot(2, mean(PopulationAvgFr_Rat.Main_iHP_PYR{i}),'b.')
+end
+Color.color=3;
+Jin_MeanSTE_Line(2,PopulationAvgFr.Main_vHP_PYR,Color)
+for i=1:6
+    plot(2, mean(PopulationAvgFr_Rat.Main_vHP_PYR{i}),'g.')
+end
+g=gca; g.YLim=[0.4 2]; g.YTick=0:0.4:2;
+
+% % Statistical testing
+% % Two way mixed ANOVA
+dHP_Pre=[PopulationAvgFr.Pre_dHP_PYR]';
+dHP_Main=[PopulationAvgFr.Main_dHP_PYR]';
+iHP_Pre=[PopulationAvgFr.Pre_iHP_PYR]';
+iHP_Main=[PopulationAvgFr.Main_iHP_PYR]';
+vHP_Pre=[PopulationAvgFr.Pre_vHP_PYR]';
+vHP_Main=[PopulationAvgFr.Main_vHP_PYR]';
+
+Y = [dHP_Pre; dHP_Main; iHP_Pre; iHP_Main; vHP_Pre; vHP_Main];
+BS = [GetGroupingVar(dHP_Pre,1); GetGroupingVar(dHP_Main,1); GetGroupingVar(iHP_Pre,2); GetGroupingVar(iHP_Main,2); GetGroupingVar(vHP_Pre,3); GetGroupingVar(vHP_Main,3)];
+WS = [GetGroupingVar(dHP_Pre,1); GetGroupingVar(dHP_Main,2); GetGroupingVar(iHP_Pre,1); GetGroupingVar(iHP_Main,2); GetGroupingVar(vHP_Pre,1); GetGroupingVar(vHP_Main,2)];
+S = [GetGroupingVar(dHP_Pre); GetGroupingVar(dHP_Main); GetGroupingVar(iHP_Pre)+length(dHP_Pre); GetGroupingVar(iHP_Main)+length(dHP_Pre); GetGroupingVar(vHP_Pre)+length(dHP_Pre)+length(iHP_Pre); GetGroupingVar(vHP_Main)+length(dHP_Pre)+length(iHP_Pre)];
+X = [Y BS WS S];    
+[SSQs, DFs, MSQs, Fs, Ps] = Stat_ANOVA2_Mixed(X);
+
+
+%% Figure 1F, Theta-modulation index
+clear all
+load('Analyzable Unit Information.mat');
+main_dHP_exp = strcmp(SessionType_dHP,'SS') | strcmp(SessionType_dHP,'SSCH1') | strcmp(SessionType_dHP,'SSCH2') | strcmp(SessionType_dHP,'FRCH1') |...
+    strcmp(SessionType_dHP,'FRCH2') | strcmp(SessionType_dHP,'SSFR1') | strcmp(SessionType_dHP,'SSFR2') | strcmp(SessionType_dHP,'T-SSCH1') |...
+    strcmp(SessionType_dHP,'T-SSCH2') | strcmp(SessionType_dHP,'T-Quantity1') | strcmp(SessionType_dHP,'T-Quantity2');
+main_iHP_exp = strcmp(SessionType_iHP,'SS') | strcmp(SessionType_iHP,'SSCH1') | strcmp(SessionType_iHP,'SSCH2') | strcmp(SessionType_iHP,'FRCH1') |...
+    strcmp(SessionType_iHP,'FRCH2') | strcmp(SessionType_iHP,'SSFR1') | strcmp(SessionType_iHP,'SSFR2') | strcmp(SessionType_iHP,'T-SSCH1') |...
+    strcmp(SessionType_iHP,'T-SSCH2') | strcmp(SessionType_iHP,'T-Quantity1') | strcmp(SessionType_iHP,'T-Quantity2');
+iHP = DepthFromCortex_iHP < 5.5;
+vHP = DepthFromCortex_iHP >= 5.5;
+
+mask_dHP_LowIsolationQuality=(Assessment_dHP < 2);
+mask_dHP_HighIsolationQuality = ~mask_dHP_LowIsolationQuality;
+mask_dHP_LowStability=(NumberOfSpike_dHP(:,1)==0 | NumberOfSpike_dHP(:,4)==0) & mask_dHP_HighIsolationQuality;
+mask_dHP_HighStability = ~mask_dHP_LowStability;
+mask_dHP_GoodCluster=mask_dHP_HighStability & mask_dHP_HighIsolationQuality;
+
+%
+mask_iHP_LowIsolationQuality=(Assessment_iHP < 2);
+mask_iHP_HighIsolationQuality = ~mask_iHP_LowIsolationQuality;
+mask_iHP_LowStability=(NumberOfSpike_iHP(:,1)==0 | NumberOfSpike_iHP(:,4)==0) & mask_iHP_HighIsolationQuality;
+mask_iHP_HighStability = ~mask_iHP_LowStability;
+mask_iHP_GoodCluster=mask_iHP_HighStability & mask_iHP_HighIsolationQuality;
+
+a=1; b=1;
+for cl=1:length(Celltype_dHP)
+    if sum(Populationcorrelogram.dHP(cl,:)) > 100 && main_dHP_exp(cl)==1
+        if isequal(Celltype_dHP{cl},'Pyramidal')     
+            PopulationCorrelogram.dHP_PYR(a,:)=PopulationCorrelogram.dHP(cl,:)./max(PopulationCorrelogram.dHP(cl,62:65));        
+            PopulationTMI.dHP_PYR(a)=PopulationTMI.dHP(cl);        
+            a=a+1;
+        elseif isequal(Celltype_dHP{cl},'Interneruon')    
+            PopulationCorrelogram.dHP_INT(b,:)=PopulationCorrelogram.dHP(cl,:)./max(PopulationCorrelogram.dHP(cl,62:65));        
+            PopulationTMI.dHP_INT(b)=PopulationTMI.dHP(cl);        
+            b=b+1;
+        end
+    end
+end
+   
+a=1; b=1;
+for cl=1:length(Celltype_iHP)
+    if sum(Populationcorrelogram.iHP(cl,:)) > 100 && DepthFromCortex_iHP(cl) < 5.5 && main_iHP_exp(cl)==1
+        if isequal(Celltype_iHP{cl},'Pyramidal')        
+            PopulationCorrelogram.iHP_PYR(a,:)=PopulationCorrelogram.iHP(cl,:)./max(PopulationCorrelogram.iHP(cl,62:65));        
+            PopulationTMI.iHP_PYR(a)=PopulationTMI.iHP(cl);        
+            PopulationDepthIndex.iHP_PYR(a)=PopulationDepthIndex.iHP(cl);        
+            a=a+1;
+        elseif isequal(Celltype_iHP{cl},'Interneruon')    
+            PopulationCorrelogram.iHP_INT(b,:)=PopulationCorrelogram.iHP(cl,:)./max(PopulationCorrelogram.iHP(cl,62:65));          
+            PopulationTMI.iHP_INT(b)=PopulationTMI.iHP(cl);        
+            PopulationDepthIndex.iHP_INT(b)=PopulationDepthIndex.iHP(cl);        
+            b=b+1;
+        end
+    end
+end
+
+a=1; b=1;
+for cl=1:length(Celltype_iHP)
+    if sum(Populationcorrelogram.iHP(cl,:)) > 100 && DepthFromCortex_iHP(cl) >= 5.5 && main_iHP_exp(cl)==1
+        if isequal(Celltype_iHP{cl},'Pyramidal')        
+            PopulationCorrelogram.vHP_PYR(a,:)=PopulationCorrelogram.iHP(cl,:)./max(PopulationCorrelogram.iHP(cl,62:65));        
+            PopulationTMI.vHP_PYR(a)=PopulationTMI.iHP(cl);        
+            PopulationDepthIndex.vHP_PYR(a)=PopulationDepthIndex.iHP(cl);        
+            a=a+1;
+        elseif isequal(Celltype_iHP{cl},'Interneruon')    
+            PopulationCorrelogram.vHP_INT(b,:)=PopulationCorrelogram.iHP(cl,:)./max(PopulationCorrelogram.iHP(cl,62:65));          
+            PopulationTMI.vHP_INT(b)=PopulationTMI.iHP(cl);        
+            PopulationDepthIndex.vHP_INT(b)=PopulationDepthIndex.iHP(cl);        
+            b=b+1;
+        end
+    end
+end
+PopulationBasicFr_Rat.TMI_dHP_PYR{1}=[];
+PopulationBasicFr_Rat.TMI_dHP_PYR{2}=[];
+PopulationBasicFr_Rat.TMI_dHP_PYR{3}=[];
+PopulationBasicFr_Rat.TMI_dHP_PYR{4}=[];
+PopulationBasicFr_Rat.TMI_dHP_PYR{5}=[];
+PopulationBasicFr_Rat.TMI_dHP_PYR{6}=[];
+for cl=1:length(Celltype_dHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_dHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_dHP{cl},'Pyramidal') && mask_dHP_GoodCluster(cl)==1 && main_dHP_exp(cl)==1 && sum(Populationcorrelogram.dHP(cl,:)) > 100 
+        switch Rat
+            case 448
+                PopulationBasicFr_Rat.TMI_dHP_PYR{1}(end+1)=PopulationTMI.dHP(cl);  
+            case 459
+                PopulationBasicFr_Rat.TMI_dHP_PYR{2}(end+1)=PopulationTMI.dHP(cl);  
+            case 463
+                PopulationBasicFr_Rat.TMI_dHP_PYR{3}(end+1)=PopulationTMI.dHP(cl);  
+            case 473
+                PopulationBasicFr_Rat.TMI_dHP_PYR{4}(end+1)=PopulationTMI.dHP(cl);  
+            case 488
+%                 PopulationBasicFr_Rat.TMI_dHP_PYR{5}(end+1)=TMI_dHP(cl);  
+            case 509
+                PopulationBasicFr_Rat.TMI_dHP_PYR{6}(end+1)=PopulationTMI.dHP(cl);  
+        end
+    end
+end
+
+PopulationBasicFr_Rat.TMI_iHP_PYR{1}=[];
+PopulationBasicFr_Rat.TMI_iHP_PYR{2}=[];
+PopulationBasicFr_Rat.TMI_iHP_PYR{3}=[];
+PopulationBasicFr_Rat.TMI_iHP_PYR{4}=[];
+PopulationBasicFr_Rat.TMI_iHP_PYR{5}=[];
+PopulationBasicFr_Rat.TMI_iHP_PYR{6}=[];
+for cl=1:length(Celltype_iHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_iHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && sum(Populationcorrelogram.iHP(cl,:)) > 100 && iHP(cl) == 1
+        switch Rat
+            case 448
+                PopulationBasicFr_Rat.TMI_iHP_PYR{1}(end+1)=PopulationTMI.iHP(cl);  
+            case 459
+                PopulationBasicFr_Rat.TMI_iHP_PYR{2}(end+1)=PopulationTMI.iHP(cl);  
+            case 463
+                PopulationBasicFr_Rat.TMI_iHP_PYR{3}(end+1)=PopulationTMI.iHP(cl);  
+            case 473
+                PopulationBasicFr_Rat.TMI_iHP_PYR{4}(end+1)=PopulationTMI.iHP(cl);  
+            case 488
+%                 PopulationBasicFr_Rat.TMI_iHP_PYR{5}(end+1)=PopulationTMI.iHP(cl);  
+            case 509
+                PopulationBasicFr_Rat.TMI_iHP_PYR{6}(end+1)=PopulationTMI.iHP(cl);  
+        end
+    end
+end
+
+PopulationBasicFr_Rat.TMI_vHP_PYR{1}=[];
+PopulationBasicFr_Rat.TMI_vHP_PYR{2}=[];
+PopulationBasicFr_Rat.TMI_vHP_PYR{3}=[];
+PopulationBasicFr_Rat.TMI_vHP_PYR{4}=[];
+PopulationBasicFr_Rat.TMI_vHP_PYR{5}=[];
+PopulationBasicFr_Rat.TMI_vHP_PYR{6}=[];
+
+
+for cl=1:length(Celltype_iHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_iHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && sum(Populationcorrelogram.iHP(cl,:)) > 100 && vHP(cl) == 1
+        switch Rat
+            case 448
+                PopulationBasicFr_Rat.TMI_vHP_PYR{1}(end+1)=PopulationTMI.iHP(cl);  
+            case 459
+                PopulationBasicFr_Rat.TMI_vHP_PYR{2}(end+1)=PopulationTMI.iHP(cl);  
+            case 463
+                PopulationBasicFr_Rat.TMI_vHP_PYR{3}(end+1)=PopulationTMI.iHP(cl);  
+            case 473
+                PopulationBasicFr_Rat.TMI_vHP_PYR{4}(end+1)=PopulationTMI.iHP(cl);  
+            case 488
+                PopulationBasicFr_Rat.TMI_vHP_PYR{5}(end+1)=PopulationTMI.iHP(cl);  
+            case 509
+                PopulationBasicFr_Rat.TMI_vHP_PYR{6}(end+1)=PopulationTMI.iHP(cl);  
+        end
+    end
+end
+
+% % Plotting
+fig=figure; hold on; 
+fig.Position=[0 0 1000 500];
+Color.color=2; Color.alpha=1;
+Jin_MeanSTE_Line(1,PopulationTMI.dHP_PYR,Color)
+for i=1:6
+    plot(1, mean(PopulationBasicFr_Rat.TMI_dHP_PYR{i}),'r.')
+end
+Color.color=1;
+Jin_MeanSTE_Line(2,PopulationTMI.iHP_PYR,Color)
+for i=1:6
+    plot(2, mean(PopulationBasicFr_Rat.TMI_iHP_PYR{i}),'b.')
+end
+Color.color=3;
+Jin_MeanSTE_Line(3,PopulationTMI.vHP_PYR,Color)
+for i=1:6
+    plot(3, mean(PopulationBasicFr_Rat.TMI_vHP_PYR{i}),'g.')
+end
+
+% % Statistical testing
+dHP_PYR=[PopulationTMI.dHP_PYR]';
+iHP_PYR=[PopulationTMI.iHP_PYR]';
+vHP_PYR=[PopulationTMI.vHP_PYR]';
+% %
+Y = [dHP_PYR; iHP_PYR; vHP_PYR];
+GROUP = [GetGroupingVar(dHP_PYR,1); GetGroupingVar(iHP_PYR,12); GetGroupingVar(vHP_PYR,3)];
+[Pvalue, result, gnames] = Stat_ANOVA1(Y,GROUP);
+
+%% Figure 1G, Bursting index
+clear all
+load('Analyzable Unit Information.mat');
+main_dHP_exp = strcmp(SessionType_dHP,'SS') | strcmp(SessionType_dHP,'SSCH1') | strcmp(SessionType_dHP,'SSCH2') | strcmp(SessionType_dHP,'FRCH1') |...
+    strcmp(SessionType_dHP,'FRCH2') | strcmp(SessionType_dHP,'SSFR1') | strcmp(SessionType_dHP,'SSFR2') | strcmp(SessionType_dHP,'T-SSCH1') |...
+    strcmp(SessionType_dHP,'T-SSCH2') | strcmp(SessionType_dHP,'T-Quantity1') | strcmp(SessionType_dHP,'T-Quantity2');
+main_iHP_exp = strcmp(SessionType_iHP,'SS') | strcmp(SessionType_iHP,'SSCH1') | strcmp(SessionType_iHP,'SSCH2') | strcmp(SessionType_iHP,'FRCH1') |...
+    strcmp(SessionType_iHP,'FRCH2') | strcmp(SessionType_iHP,'SSFR1') | strcmp(SessionType_iHP,'SSFR2') | strcmp(SessionType_iHP,'T-SSCH1') |...
+    strcmp(SessionType_iHP,'T-SSCH2') | strcmp(SessionType_iHP,'T-Quantity1') | strcmp(SessionType_iHP,'T-Quantity2');
+iHP = DepthFromCortex_iHP < 5.5;
+vHP = DepthFromCortex_iHP >= 5.5;
+
+mask_dHP_LowIsolationQuality=(Assessment_dHP < 2);
+mask_dHP_HighIsolationQuality = ~mask_dHP_LowIsolationQuality;
+mask_dHP_LowStability=(NumberOfSpike_dHP(:,1)==0 | NumberOfSpike_dHP(:,4)==0) & mask_dHP_HighIsolationQuality;
+mask_dHP_HighStability = ~mask_dHP_LowStability;
+mask_dHP_GoodCluster=mask_dHP_HighStability & mask_dHP_HighIsolationQuality;
+
+%
+mask_iHP_LowIsolationQuality=(Assessment_iHP < 2);
+mask_iHP_HighIsolationQuality = ~mask_iHP_LowIsolationQuality;
+mask_iHP_LowStability=(NumberOfSpike_iHP(:,1)==0 | NumberOfSpike_iHP(:,4)==0) & mask_iHP_HighIsolationQuality;
+mask_iHP_HighStability = ~mask_iHP_LowStability;
+mask_iHP_GoodCluster=mask_iHP_HighStability & mask_iHP_HighIsolationQuality;
+
+
+a=1; b=1;
+for cl=1:length(Celltype_dHP)
+    if sum(Populationcorrelogram.dHP(cl,:)) > 100 
+        if isequal(Celltype_dHP{cl},'Pyramidal') && mask_dHP_GoodCluster(cl)==1 && main_dHP_exp(cl)==1
+            PopulationBasicFr.BurstingIndex_dHP_PYR(a)=BurstingIndex_dHP(cl,2);        
+            PopulationBasicFr.SpikeWidth_dHP_PYR(a)=SpikeWidth_dHP(cl); a=a+1;
+
+        elseif isequal(Celltype_dHP{cl},'Interneruon') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1
+            PopulationBasicFr.BurstingIndex_dHP_INT(b)=BurstingIndex_dHP(cl,2);
+            PopulationBasicFr.SpikeWidth_dHP_INT(b)=SpikeWidth_dHP(cl); b=b+1;
+
+        end
+    end
+end
+   
+a=1; b=1;
+for cl=1:length(Celltype_iHP)
+    if sum(Populationcorrelogram.iHP(cl,:)) > 100 
+        if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && iHP(cl) == 1
+            PopulationBasicFr.BurstingIndex_iHP_PYR(a)=BurstingIndex_iHP(cl,2);
+            PopulationBasicFr.SpikeWidth_iHP_PYR(a)=SpikeWidth_iHP(cl);
+            PopulationDepth.iHP_PYR(a)=DepthFromCortex_iHP(cl); a=a+1;
+        elseif isequal(Celltype_iHP{cl},'Interneruon') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && iHP(cl) == 1    
+            PopulationBasicFr.BurstingIndex_iHP_INT(b)=BurstingIndex_iHP(cl,2);
+            PopulationBasicFr.SpikeWidth_iHP_INT(b)=SpikeWidth_iHP(cl);
+            PopulationDepth.iHP_INT(b)=DepthFromCortex_iHP(cl); b=b+1;
+        end
+    end
+end
+       
+a=1; b=1;
+for cl=1:length(Celltype_iHP)
+    if sum(Populationcorrelogram.iHP(cl,:)) > 100 
+        if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && vHP(cl) == 1        
+            PopulationBasicFr.BurstingIndex_vHP_PYR(a)=BurstingIndex_iHP(cl,2);
+            PopulationBasicFr.SpikeWidth_vHP_PYR(a)=SpikeWidth_iHP(cl);
+            PopulationDepth.vHP_PYR(a)=DepthFromCortex_iHP(cl); a=a+1;
+        elseif isequal(Celltype_iHP{cl},'Interneruon') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && vHP(cl) == 1    
+            PopulationBasicFr.BurstingIndex_vHP_INT(b)=BurstingIndex_iHP(cl,2);
+            PopulationBasicFr.SpikeWidth_vHP_INT(b)=SpikeWidth_iHP(cl);
+            PopulationDepth.vHP_INT(b)=DepthFromCortex_iHP(cl); b=b+1;
+        end
+    end
+end
+
+PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{1}=[];
+PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{2}=[];
+PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{3}=[];
+PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{4}=[];
+PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{5}=[];
+PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{6}=[];
+for cl=1:length(Celltype_dHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_dHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_dHP{cl},'Pyramidal') && mask_dHP_GoodCluster(cl)==1 && main_dHP_exp(cl)==1 && sum(Populationcorrelogram.dHP(cl,:)) > 100 
+        switch Rat
+            case 448
+                PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{1}(end+1)=BurstingIndex_dHP(cl,2);  
+            case 459
+                PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{2}(end+1)=BurstingIndex_dHP(cl,2);  
+            case 463
+                PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{3}(end+1)=BurstingIndex_dHP(cl,2);  
+            case 473
+                PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{4}(end+1)=BurstingIndex_dHP(cl,2);  
+            case 488
+%                 PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{5}(end+1)=BurstingIndex_dHP(cl,2);  
+            case 509
+                PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{6}(end+1)=BurstingIndex_dHP(cl,2);  
+        end
+    end
+end
+
+PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{1}=[];
+PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{2}=[];
+PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{3}=[];
+PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{4}=[];
+PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{5}=[];
+PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{6}=[];
+for cl=1:length(Celltype_iHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_iHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && sum(Populationcorrelogram.iHP(cl,:)) > 100 && iHP(cl) == 1
+        switch Rat
+            case 448
+                PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{1}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 459
+                PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{2}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 463
+                PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{3}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 473
+                PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{4}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 488
+%                 PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{5}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 509
+                PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{6}(end+1)=BurstingIndex_iHP(cl,2);  
+        end
+    end
+end
+
+PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{1}=[];
+PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{2}=[];
+PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{3}=[];
+PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{4}=[];
+PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{5}=[];
+PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{6}=[];
+
+
+for cl=1:length(Celltype_iHP)
+    [Rat, Type, Day, TetrodeNumber, ClusterNumber, Session, Sessiontype, Index1] = GetSessionInfo(Clstname_iHP{cl});
+    Rat=str2num(Rat);
+    if isequal(Celltype_iHP{cl},'Pyramidal') && mask_iHP_GoodCluster(cl)==1 && main_iHP_exp(cl)==1 && sum(Populationcorrelogram.iHP(cl,:)) > 100 && vHP(cl) == 1
+        switch Rat
+            case 448
+                PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{1}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 459
+                PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{2}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 463
+                PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{3}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 473
+                PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{4}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 488
+                PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{5}(end+1)=BurstingIndex_iHP(cl,2);  
+            case 509
+                PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{6}(end+1)=BurstingIndex_iHP(cl,2);  
+        end
+    end
+end
+
+
+fig=figure; hold on; 
+fig.Position=[0 0 1000 500];
+Color.color=2; Color.alpha=1;
+Jin_MeanSTE_Line(1,PopulationBasicFr.BurstingIndex_dHP_PYR,Color)
+for i=1:6
+    plot(1, mean(PopulationBasicFr_Rat.BurstingIndex_dHP_PYR{i}),'r.')
+end
+Color.color=1;
+Jin_MeanSTE_Line(2,PopulationBasicFr.BurstingIndex_iHP_PYR,Color)
+for i=1:6
+%     mean(PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{i})
+    plot(2, mean(PopulationBasicFr_Rat.BurstingIndex_iHP_PYR{i}),'b.')
+end
+Color.color=3;
+Jin_MeanSTE_Line(3,PopulationBasicFr.BurstingIndex_vHP_PYR,Color)
+for i=1:6
+%     mean(PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{i})
+    plot(3, mean(PopulationBasicFr_Rat.BurstingIndex_vHP_PYR{i}),'g.')
+end
+
+% % Statistical testing
+dHP_PYR=[PopulationBasicFr.BurstingIndex_dHP_PYR]';
+iHP_PYR=[PopulationBasicFr.BurstingIndex_iHP_PYR]';
+vHP_PYR=[PopulationBasicFr.BurstingIndex_vHP_PYR]';
+
+Y = [dHP_PYR; iHP_PYR; vHP_PYR];
+GROUP = [GetGroupingVar(dHP_PYR,1); GetGroupingVar(iHP_PYR,12); GetGroupingVar(vHP_PYR,3)];
+[Pvalue, result, ~] = Stat_ANOVA1(Y,GROUP);
+
+%% Figure 1H, Spatial information
+clear all
+FR_Thre=0.25; 
+pvalue=0.01;
+Color=mapcolor(100,0);
+REGION='Total';
+SI_dHP_Thre=0.25;
+SI_iHP_Thre=0.25;
+load(['E:\Ongoing Project\Project - Value-based RW Navigation (dHP-vHP)\Analysis Data\OpenField_JPEG_SpatialAnalysis\FR_Thre_' num2str(FR_Thre) '_Pvalue_' num2str(pvalue) '\ClusterInfo_Openfield_' REGION '.mat'])
+
+Active_dHP=ClusterInfo.Total_dHP_AvgFiringRate >= FR_Thre;
+Active_iHP=ClusterInfo.Total_iHP_AvgFiringRate >= FR_Thre;
+Information_dHP = ClusterInfo.Total_dHP_SpatialInfo >= SI_dHP_Thre;
+Information_iHP = ClusterInfo.Total_iHP_SpatialInfo >= SI_iHP_Thre;
+SpatiallyModulated_dHP = ClusterInfo.Total_dHP_SpatialInfo_pvalue < pvalue;
+SpatiallyModulated_iHP = ClusterInfo.Total_iHP_SpatialInfo_pvalue < pvalue;
+PlaceCell_dHP=Active_dHP&Information_dHP&SpatiallyModulated_dHP;
+PlaceCell_iHP=Active_iHP&Information_iHP&SpatiallyModulated_iHP;
+iHP = (ClusterInfo.Total_iHP_DistFromCortex < 5.5);
+vHP = (ClusterInfo.Total_iHP_DistFromCortex >= 5.5);
+
+% Flag, Rat
+r448_dHP = logical(zeros(1,length(ClusterInfo.Total_dHP_Name)));
+r448_iHP = logical(zeros(1,length(ClusterInfo.Total_iHP_Name)));
+r459_dHP = logical(zeros(1,length(ClusterInfo.Total_dHP_Name)));
+r459_iHP = logical(zeros(1,length(ClusterInfo.Total_iHP_Name)));
+r463_dHP = logical(zeros(1,length(ClusterInfo.Total_dHP_Name)));
+r463_iHP = logical(zeros(1,length(ClusterInfo.Total_iHP_Name)));
+r473_dHP = logical(zeros(1,length(ClusterInfo.Total_dHP_Name)));
+r473_iHP = logical(zeros(1,length(ClusterInfo.Total_iHP_Name)));
+r488_dHP = logical(zeros(1,length(ClusterInfo.Total_dHP_Name)));
+r488_iHP = logical(zeros(1,length(ClusterInfo.Total_iHP_Name)));
+r509_dHP = logical(zeros(1,length(ClusterInfo.Total_dHP_Name)));
+r509_iHP = logical(zeros(1,length(ClusterInfo.Total_iHP_Name)));
+
+for i=1:1
+    for j=1:length(ClusterInfo.Total_iHP_Name)
+        name = ClusterInfo.Total_iHP_Name{1,j};
+        if ~isempty(name)
+            if isequal(name(13:15),'448')
+                r448_iHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'459')
+                r459_iHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'463')
+                r463_iHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'473')
+                r473_iHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'488')
+                r488_iHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'509')
+                r509_iHP(i,j) = logical(1);
+            end
+        end
+    end
+end
+for i=1:1
+    for j=1:length(ClusterInfo.Total_dHP_Name)
+        name = ClusterInfo.Total_dHP_Name{1,j};
+        if ~isempty(name)
+            if isequal(name(13:15),'448')
+                r448_dHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'459')
+                r459_dHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'463')
+                r463_dHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'473')
+                r473_dHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'488')
+                r488_dHP(i,j) = logical(1);
+            end
+            if isequal(name(13:15),'509')
+                r509_dHP(i,j) = logical(1);
+            end
+        end
+    end
+end
+
+SpatialInfo.dHP=ClusterInfo.Total_dHP_SpatialInfo(Active_dHP);
+SpatialInfo.dHP_Rat{1}=ClusterInfo.Total_dHP_SpatialInfo(Active_dHP & r448_dHP);
+SpatialInfo.dHP_Rat{2}=ClusterInfo.Total_dHP_SpatialInfo(Active_dHP & r459_dHP);
+SpatialInfo.dHP_Rat{3}=ClusterInfo.Total_dHP_SpatialInfo(Active_dHP & r463_dHP);
+SpatialInfo.dHP_Rat{4}=ClusterInfo.Total_dHP_SpatialInfo(Active_dHP & r473_dHP);
+SpatialInfo.dHP_Rat{5}=ClusterInfo.Total_dHP_SpatialInfo(Active_dHP & r488_dHP);
+SpatialInfo.dHP_Rat{6}=ClusterInfo.Total_dHP_SpatialInfo(Active_dHP & r509_dHP);
+
+SpatialInfo.iHP=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & iHP);
+SpatialInfo.iHP_Rat{1}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r448_iHP & iHP);
+SpatialInfo.iHP_Rat{2}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r459_iHP & iHP);
+SpatialInfo.iHP_Rat{3}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r463_iHP & iHP);
+SpatialInfo.iHP_Rat{4}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r473_iHP & iHP);
+SpatialInfo.iHP_Rat{5}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r488_iHP & iHP);
+SpatialInfo.iHP_Rat{6}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r509_iHP & iHP);
+
+SpatialInfo.vHP=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & vHP);
+SpatialInfo.vHP_Rat{1}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r448_iHP & vHP);
+SpatialInfo.vHP_Rat{2}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r459_iHP & vHP);
+SpatialInfo.vHP_Rat{3}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r463_iHP & vHP);
+SpatialInfo.vHP_Rat{4}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r473_iHP & vHP);
+SpatialInfo.vHP_Rat{5}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r488_iHP & vHP);
+SpatialInfo.vHP_Rat{6}=ClusterInfo.Total_iHP_SpatialInfo(Active_iHP & r509_iHP & vHP);
+
+
+fig=figure; hold on; 
+fig.Position=[0 0 1000 500];
+clear Color;
+Color.color=2; Color.alpha=1;
+Jin_MeanSTE_Line(1,SpatialInfo.dHP,Color);
+for i=1:6
+    mean(SpatialInfo.dHP_Rat{i})
+%     plot(1, mean(SpatialInfo.dHP_Rat{i}),'r.')
+end
+Color.color=1;
+Jin_MeanSTE_Line(2,SpatialInfo.iHP,Color)
+for i=1:6
+%     plot(2, mean(SpatialInfo.iHP_Rat{i}),'b.')
+end
+Color.color=3;
+Jin_MeanSTE_Line(3,SpatialInfo.vHP,Color)
+for i=1:6
+%     plot(3, mean(SpatialInfo.vHP_Rat{i}),'g.')
+end
+
+% Statistical testing
+y.data0 = SpatialInfo.dHP;
+y.data1 = SpatialInfo.iHP;
+y.data2 = SpatialInfo.vHP;
+Y = [y.data0'; y.data1'; y.data2'];
+GROUP = [GetGroupingVar(y.data0,'dHP'); GetGroupingVar(y.data1,'iHP'); GetGroupingVar(y.data2,'vHP')];
+[Pvalue, result, ~] = Stat_ANOVA1(Y,GROUP);
+% % Multiple comparision between groups
+[~,p]=ttest2(y.data0, y.data1);
+[~,p]=ttest2(y.data0, y.data2);
+[~,p]=ttest2(y.data2, y.data1);
+
+%% Figure 1I, Place cell ratio
+Numb.PlaceCell_dHP=length(find(Active_dHP & SpatiallyModulated_dHP & (Information_dHP)));
+Numb.Total_dHP=length((Active_dHP));
+PlaceCellRatio.dHP= Numb.PlaceCell_dHP / Numb.Total_dHP;
+Numb.PlaceCell_dHP_448=length(find(Active_dHP & SpatiallyModulated_dHP & Information_dHP & r448_dHP));
+Numb.Total_dHP_448=length(find(r448_dHP));
+PlaceCellRatio.dHP_448= Numb.PlaceCell_dHP_448 / Numb.Total_dHP_448;
+Numb.PlaceCell_dHP_459=length(find(Active_dHP & SpatiallyModulated_dHP & Information_dHP & r459_dHP));
+Numb.Total_dHP_459=length(find(r459_dHP));
+PlaceCellRatio.dHP_459= Numb.PlaceCell_dHP_459 / Numb.Total_dHP_459;
+Numb.PlaceCell_dHP_463=length(find(Active_dHP & SpatiallyModulated_dHP & Information_dHP & r463_dHP));
+Numb.Total_dHP_463=length(find(r463_dHP));
+PlaceCellRatio.dHP_463= Numb.PlaceCell_dHP_463 / Numb.Total_dHP_463;
+Numb.PlaceCell_dHP_473=length(find(Active_dHP & SpatiallyModulated_dHP & Information_dHP & r473_dHP));
+Numb.Total_dHP_473=length(find(r473_dHP));
+PlaceCellRatio.dHP_473= Numb.PlaceCell_dHP_473 / Numb.Total_dHP_473;
+Numb.PlaceCell_dHP_488=length(find(Active_dHP & SpatiallyModulated_dHP & Information_dHP & r488_dHP));
+Numb.Total_dHP_488=length(find(r488_dHP));
+PlaceCellRatio.dHP_488= Numb.PlaceCell_dHP_488 / Numb.Total_dHP_488;
+Numb.PlaceCell_dHP_509=length(find(Active_dHP & SpatiallyModulated_dHP & Information_dHP & r509_dHP));
+Numb.Total_dHP_509=length(find(r509_dHP));
+PlaceCellRatio.dHP_509= Numb.PlaceCell_dHP_509 / Numb.Total_dHP_509;
+
+Numb.PlaceCell_iHP=length(find(Active_iHP & SpatiallyModulated_iHP & iHP & (Information_iHP)));
+Numb.Total_iHP=length(find(iHP));
+PlaceCellRatio.iHP= Numb.PlaceCell_iHP / Numb.Total_iHP;
+Numb.PlaceCell_iHP_448=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & iHP & r448_iHP));
+Numb.Total_iHP_448=length(find(r448_iHP& iHP));
+PlaceCellRatio.iHP_448= Numb.PlaceCell_iHP_448 / Numb.Total_iHP_448;
+Numb.PlaceCell_iHP_459=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & iHP & r459_iHP));
+Numb.Total_iHP_459=length(find(r459_iHP& iHP));
+PlaceCellRatio.iHP_459= Numb.PlaceCell_iHP_459 / Numb.Total_iHP_459;
+Numb.PlaceCell_iHP_463=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & iHP & r463_iHP));
+Numb.Total_iHP_463=length(find(r463_iHP& iHP));
+PlaceCellRatio.iHP_463= Numb.PlaceCell_iHP_463 / Numb.Total_iHP_463;
+Numb.PlaceCell_iHP_473=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & iHP & r473_iHP));
+Numb.Total_iHP_473=length(find(r473_iHP& iHP));
+PlaceCellRatio.iHP_473= Numb.PlaceCell_iHP_473 / Numb.Total_iHP_473;
+Numb.PlaceCell_iHP_488=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & iHP & r488_iHP));
+Numb.Total_iHP_488=length(find(r488_iHP& iHP));
+PlaceCellRatio.iHP_488= Numb.PlaceCell_iHP_488 / Numb.Total_iHP_488;
+Numb.PlaceCell_iHP_509=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & iHP & r509_iHP));
+Numb.Total_iHP_509=length(find(r509_iHP& iHP));
+PlaceCellRatio.iHP_509= Numb.PlaceCell_iHP_509 / Numb.Total_iHP_509;
+
+Numb.PlaceCell_vHP=length(find(Active_iHP & SpatiallyModulated_iHP & vHP & (Information_iHP)));
+Numb.Total_vHP=length(find(vHP));
+PlaceCellRatio.vHP= Numb.PlaceCell_vHP / Numb.Total_vHP;
+Numb.PlaceCell_vHP_448=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & vHP & r448_iHP));
+Numb.Total_vHP_448=length(find(r448_iHP& vHP));
+PlaceCellRatio.vHP_448= Numb.PlaceCell_vHP_448 / Numb.Total_vHP_448;
+Numb.PlaceCell_vHP_459=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & vHP & r459_iHP));
+Numb.Total_vHP_459=length(find(r459_iHP& vHP));
+PlaceCellRatio.vHP_459= Numb.PlaceCell_vHP_459 / Numb.Total_vHP_459;
+Numb.PlaceCell_vHP_463=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & vHP & r463_iHP));
+Numb.Total_vHP_463=length(find(r463_iHP& vHP));
+PlaceCellRatio.vHP_463= Numb.PlaceCell_vHP_463 / Numb.Total_vHP_463;
+Numb.PlaceCell_vHP_473=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & vHP & r473_iHP));
+Numb.Total_vHP_473=length(find(r473_iHP& vHP));
+PlaceCellRatio.vHP_473= Numb.PlaceCell_vHP_473 / Numb.Total_vHP_473;
+Numb.PlaceCell_vHP_488=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & vHP & r488_iHP));
+Numb.Total_vHP_488=length(find(r488_iHP& vHP));
+PlaceCellRatio.vHP_488= Numb.PlaceCell_vHP_488 / Numb.Total_vHP_488;
+Numb.PlaceCell_vHP_509=length(find(Active_iHP & SpatiallyModulated_iHP & Information_iHP & vHP & r509_iHP));
+Numb.Total_vHP_509=length(find(r509_iHP& vHP));
+PlaceCellRatio.vHP_509= Numb.PlaceCell_vHP_509 / Numb.Total_vHP_509;
+
+fig=figure;
+hold on;
+plot(1,PlaceCellRatio.dHP,'r.');
+plot(1,PlaceCellRatio.dHP_448,'ro');
+plot(1,PlaceCellRatio.dHP_459,'ro');
+plot(1,PlaceCellRatio.dHP_463,'ro');
+plot(1,PlaceCellRatio.dHP_473,'ro');
+plot(1,PlaceCellRatio.dHP_509,'ro');
+
+plot(2,PlaceCellRatio.iHP,'b.');
+plot(2,PlaceCellRatio.iHP_448,'bo');
+plot(2,PlaceCellRatio.iHP_459,'bo');
+plot(2,PlaceCellRatio.iHP_463,'bo');
+plot(2,PlaceCellRatio.iHP_473,'bo');
+plot(2,PlaceCellRatio.iHP_509,'bo');
+
+plot(3,PlaceCellRatio.vHP,'g.');
+plot(3,PlaceCellRatio.vHP_448,'go');
+plot(3,PlaceCellRatio.vHP_459,'go');
+plot(3,PlaceCellRatio.vHP_463,'go');
+plot(3,PlaceCellRatio.vHP_488,'go');
+plot(3,PlaceCellRatio.vHP_509,'go');
+xlim([0.5 3.5])
+
+% % Statistical testing
+[~,p,stat]=chi2cont([Numb.PlaceCell_dHP  Numb.Total_dHP; Numb.PlaceCell_iHP Numb.Total_iHP; Numb.PlaceCell_vHP Numb.Total_vHP]);

Figure_2.m

@@ -0,0 +1,182 @@
+%% Figure 2B
+% % Reward preference data of rat [448, 459, 463, 473, 488, 509]
+SSCH = [80 85 90 90 95 80];
+FRCH = [75 85 85 85 90 90];
+SSFR = [35 35 50 50 55 65];
+
+%
+fig=figure; hold on;
+fig.Position=[0 0 400 500];
+% Width=0.3;
+c.color=53; c.alpha=0.4;
+Jin_MeanSTE_Line(1,SSCH)
+for i=1:length(SSCH)
+    plot(1,SSCH(i),'k.');
+end
+Jin_MeanSTE_Line(2,FRCH)
+for i=1:length(FRCH)
+    plot(2,FRCH(i),'k.');
+end
+Jin_MeanSTE_Line(3,SSFR)
+for i=1:length(SSFR)
+    plot(3,SSFR(i),'k.');
+end
+ylim([0 100])
+g=gca;
+g.YTick=0:20:100;
+
+% % statistical testing
+x1=1*ones(1,6);
+x2=2*ones(1,6);
+x3=3*ones(1,6);
+y1=SSCH;
+y2=FRCH;
+y3=SSFR;
+[p,anovatab,stats] = kruskalwallis([y1 y2 y3],[x1 x2 x3],'off');
+multcompare(stats);
+
+%% Figure 2C
+clear all; close all;
+load('TimeInformation.mat');
+
+% % session number
+SS=[1 8 15 22 29 36]; 
+SSCH=[2 3 9 10 16 17 23 24 30 31 37 38];
+FRCH=[4 5 11 12 18 19 25 26 32 33 39 40];
+SSFR=[6 7 13 14 20 21 27 28 34 35 41 42];
+
+BehaviorParam.SS.Time_B1_Approach=BehaviorParam.Time_B1_Approach(SS,:,:);
+BehaviorParam.SS.Time_B2_Approach=BehaviorParam.Time_B2_Approach(SS,:,:);
+BehaviorParam.SS.Time_B3_Approach=BehaviorParam.Time_B3_Approach(SS,:,:);
+BehaviorParam.SS.Time_B4_Approach=BehaviorParam.Time_B4_Approach(SS,:,:);
+BehaviorParam.SSCH.Time_B1_Approach=BehaviorParam.Time_B1_Approach(SSCH,:,:);
+BehaviorParam.SSCH.Time_B2_Approach=BehaviorParam.Time_B2_Approach(SSCH,:,:);
+BehaviorParam.FRCH.Time_B1_Approach=BehaviorParam.Time_B1_Approach(FRCH,:,:);
+BehaviorParam.FRCH.Time_B2_Approach=BehaviorParam.Time_B2_Approach(FRCH,:,:);
+BehaviorParam.SSFR.Time_B1_Approach=BehaviorParam.Time_B1_Approach(SSFR,:,:);
+BehaviorParam.SSFR.Time_B2_Approach=BehaviorParam.Time_B2_Approach(SSFR,:,:);
+BehaviorParam.SSCH.Time_B3_Approach=BehaviorParam.Time_B3_Approach(SSCH,:,:);
+BehaviorParam.SSCH.Time_B4_Approach=BehaviorParam.Time_B4_Approach(SSCH,:,:);
+BehaviorParam.FRCH.Time_B3_Approach=BehaviorParam.Time_B3_Approach(FRCH,:,:);
+BehaviorParam.FRCH.Time_B4_Approach=BehaviorParam.Time_B4_Approach(FRCH,:,:);
+BehaviorParam.SSFR.Time_B3_Approach=BehaviorParam.Time_B3_Approach(SSFR,:,:);
+BehaviorParam.SSFR.Time_B4_Approach=BehaviorParam.Time_B4_Approach(SSFR,:,:);
+
+BehaviorParam.SSCH.Time_B1_LeaveRewardZone=BehaviorParam.Time_B1_LeaveRewardZone(SSCH,:);
+BehaviorParam.SSCH.Time_B2_LeaveRewardZone=BehaviorParam.Time_B2_LeaveRewardZone(SSCH,:);
+BehaviorParam.FRCH.Time_B1_LeaveRewardZone=BehaviorParam.Time_B1_LeaveRewardZone(FRCH,:);
+BehaviorParam.FRCH.Time_B2_LeaveRewardZone=BehaviorParam.Time_B2_LeaveRewardZone(FRCH,:);
+BehaviorParam.SSFR.Time_B1_LeaveRewardZone=BehaviorParam.Time_B1_LeaveRewardZone(SSFR,:);
+BehaviorParam.SSFR.Time_B2_LeaveRewardZone=BehaviorParam.Time_B2_LeaveRewardZone(SSFR,:);
+BehaviorParam.SSCH.Time_B3_LeaveRewardZone=BehaviorParam.Time_B3_LeaveRewardZone(SSCH,:);
+BehaviorParam.SSCH.Time_B4_LeaveRewardZone=BehaviorParam.Time_B4_LeaveRewardZone(SSCH,:);
+BehaviorParam.FRCH.Time_B3_LeaveRewardZone=BehaviorParam.Time_B3_LeaveRewardZone(FRCH,:);
+BehaviorParam.FRCH.Time_B4_LeaveRewardZone=BehaviorParam.Time_B4_LeaveRewardZone(FRCH,:);
+BehaviorParam.SSFR.Time_B3_LeaveRewardZone=BehaviorParam.Time_B3_LeaveRewardZone(SSFR,:);
+BehaviorParam.SSFR.Time_B4_LeaveRewardZone=BehaviorParam.Time_B4_LeaveRewardZone(SSFR,:);
+track=21;
+
+for Trial=1:2:30
+    for i=1:size(BehaviorParam.SSCH.Time_B1_Approach,1)
+        for j=1:size(BehaviorParam.SSCH.Time_B1_Approach,3)
+            temp=(find(~isnan(BehaviorParam.SSCH.Time_B1_Approach(i,:,j))));
+            Index_end=temp(end);
+            Pre_latency_SSCH_B1(i,j,Trial)=(BehaviorParam.SSCH.Time_B1_Approach(i,Index_end-Trial,j));
+            Post_latency_SSCH_B2(i,j,Trial)=(BehaviorParam.SSCH.Time_B2_Approach(i,Index_end+Trial,j));
+        end
+    end
+end
+for Trial=2:2:30
+    for i=1:size(BehaviorParam.SSCH.Time_B1_Approach,1)
+        for j=1:size(BehaviorParam.SSCH.Time_B1_Approach,3)
+            temp=(find(~isnan(BehaviorParam.SSCH.Time_B1_Approach(i,:,j))));
+            Index_end=temp(end);
+            Pre_latency_SSCH_B1(i,j,Trial)=(BehaviorParam.SSCH.Time_B1_Approach(i,Index_end-Trial+2,j));
+            Post_latency_SSCH_B2(i,j,Trial)=(BehaviorParam.SSCH.Time_B2_Approach(i,Index_end+Trial,j));
+        end
+    end
+end
+latency_SSCH_B12(:,track,5) = Pre_latency_SSCH_B1(:,track,1);
+latency_SSCH_B12(:,track,4) = Pre_latency_SSCH_B1(:,track,2);
+latency_SSCH_B12(:,track,3) = Pre_latency_SSCH_B1(:,track,3);
+latency_SSCH_B12(:,track,2) = Pre_latency_SSCH_B1(:,track,4);
+latency_SSCH_B12(:,track,1) = Pre_latency_SSCH_B1(:,track,5);
+for i=1:30
+    latency_SSCH_B12(:,track,i+5) = Post_latency_SSCH_B2(:,track,i);
+end
+
+for Trial=1:2:30
+    for i=1:size(BehaviorParam.FRCH.Time_B1_Approach,1)
+        for j=1:size(BehaviorParam.FRCH.Time_B1_Approach,3)
+            temp=(find(~isnan(BehaviorParam.FRCH.Time_B1_Approach(i,:,j))));
+            Index_end=temp(end);
+            Pre_latency_FRCH_B1(i,j,Trial)=(BehaviorParam.FRCH.Time_B1_Approach(i,Index_end-Trial,j));
+            Post_latency_FRCH_B2(i,j,Trial)=(BehaviorParam.FRCH.Time_B2_Approach(i,Index_end+Trial,j));
+        end
+    end
+end
+for Trial=2:2:30
+    for i=1:size(BehaviorParam.FRCH.Time_B1_Approach,1)
+        for j=1:size(BehaviorParam.FRCH.Time_B1_Approach,3)
+            temp=(find(~isnan(BehaviorParam.FRCH.Time_B1_Approach(i,:,j))));
+            Index_end=temp(end);
+            Pre_latency_FRCH_B1(i,j,Trial)=(BehaviorParam.FRCH.Time_B1_Approach(i,Index_end-Trial+2,j));
+            Post_latency_FRCH_B2(i,j,Trial)=(BehaviorParam.FRCH.Time_B2_Approach(i,Index_end+Trial,j));
+        end
+    end
+end
+
+latency_FRCH_B12(:,track,5) = Pre_latency_FRCH_B1(:,track,1);
+latency_FRCH_B12(:,track,4) = Pre_latency_FRCH_B1(:,track,2);
+latency_FRCH_B12(:,track,3) = Pre_latency_FRCH_B1(:,track,3);
+latency_FRCH_B12(:,track,2) = Pre_latency_FRCH_B1(:,track,4);
+latency_FRCH_B12(:,track,1) = Pre_latency_FRCH_B1(:,track,5);
+for i=1:30
+    latency_FRCH_B12(:,track,i+5) = Post_latency_FRCH_B2(:,track,i);
+end
+
+for Trial=1:2:30
+    for i=1:size(BehaviorParam.SSFR.Time_B1_Approach,1)
+        for j=1:size(BehaviorParam.SSFR.Time_B1_Approach,3)
+            temp=(find(~isnan(BehaviorParam.SSFR.Time_B1_Approach(i,:,j))));
+            Index_end=temp(end);
+            Pre_latency_SSFR_B1(i,j,Trial)=(BehaviorParam.SSFR.Time_B1_Approach(i,Index_end-Trial,j));
+            Post_latency_SSFR_B2(i,j,Trial)=(BehaviorParam.SSFR.Time_B2_Approach(i,Index_end+Trial,j));
+        end
+    end
+end
+for Trial=2:2:30
+    for i=1:size(BehaviorParam.SSFR.Time_B1_Approach,1)
+        for j=1:size(BehaviorParam.SSFR.Time_B1_Approach,3)
+            temp=(find(~isnan(BehaviorParam.SSFR.Time_B1_Approach(i,:,j))));
+            Index_end=temp(end);
+            Pre_latency_SSFR_B1(i,j,Trial)=(BehaviorParam.SSFR.Time_B1_Approach(i,Index_end-Trial+2,j));
+            Post_latency_SSFR_B2(i,j,Trial)=(BehaviorParam.SSFR.Time_B2_Approach(i,Index_end+Trial,j));
+        end
+    end
+end
+
+latency_SSFR_B12(:,track,5) = Pre_latency_SSFR_B1(:,track,1);
+latency_SSFR_B12(:,track,4) = Pre_latency_SSFR_B1(:,track,2);
+latency_SSFR_B12(:,track,3) = Pre_latency_SSFR_B1(:,track,3);
+latency_SSFR_B12(:,track,2) = Pre_latency_SSFR_B1(:,track,4);
+latency_SSFR_B12(:,track,1) = Pre_latency_SSFR_B1(:,track,5);
+for i=1:30
+    latency_SSFR_B12(:,track,i+5) = Post_latency_SSFR_B2(:,track,i);
+end
+
+
+% % Plotting
+figure; hold on;
+Jin_Errorbar(1,Latency.SSvsCR_pre)
+Jin_Errorbar(2,Latency.SSvsCR_post)
+Jin_Errorbar(3,Latency.FLvsCR_pre)
+Jin_Errorbar(4,Latency.FLvsCR_post)
+Jin_Errorbar(5,Latency.SSvsFL_pre)
+Jin_Errorbar(6,Latency.SSvsFL_post)
+g=gca; yaxis=g.YLim(2);
+
+% % Statistical testing
+[p_ssch, H, stats]=signrank(Latency.SSvsCR_pre,Latency.SSvsCR_post);
+[p_frch, H, stat]=signrank(Latency.FLvsCR_pre,Latency.FLvsCR_post);
+[p_ssfr, h, stat]=signrank(Latency.SSvsFL_pre,Latency.SSvsFL_post);

Figure_3.m

@@ -0,0 +1,528 @@
+load('Figure3.mat');
+%% Figure 3A
+thre=min(SpatialCorrelation.SS.dHP_B12_Odd_Maintain(find(SpatialCorrelation.SS.dHP_B12_Odd_Maintain)));
+% B12
+stable.dHP_SS=length(find(SpatialCorrelation.SS.dHP_B12_Odd_Maintain > thre));
+stable.dHP_SSCR=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain > thre));
+stable.dHP_FLCR=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain > thre));
+stable.dHP_SSFL=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain > thre));
+
+stable_RM.dHP_SS=length(find(SpatialCorrelation.SS.dHP_B12_Odd_Maintain > thre & InFieldRMI.SS.dHP_B12_Odd_Maintain > 0.25));
+stable_RM.dHP_SSCR=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain > thre & InFieldRMI.SSCR.dHP_B12_Odd_Maintain > 0.25));
+stable_RM.dHP_SSCR_Day1=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain_Day1 > thre & InFieldRMI.SSCR.dHP_B12_Odd_Maintain_Day1 > 0.25));
+stable_RM.dHP_SSCR_Day2=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain_Day2 > thre & InFieldRMI.SSCR.dHP_B12_Odd_Maintain_Day2 > 0.25));
+stable_RM.dHP_FLCR=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain > thre & InFieldRMI.FLCR.dHP_B12_Odd_Maintain > 0.25));
+stable_RM.dHP_FLCR_Day1=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain_Day1 > thre & InFieldRMI.FLCR.dHP_B12_Odd_Maintain_Day1 > 0.25));
+stable_RM.dHP_FLCR_Day2=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain_Day2 > thre & InFieldRMI.FLCR.dHP_B12_Odd_Maintain_Day2 > 0.25));
+stable_RM.dHP_SSFL=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain > thre & InFieldRMI.SSFL.dHP_B12_Odd_Maintain > 0.25));
+stable_RM.dHP_SSFL_Day1=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain_Day1 > thre & InFieldRMI.SSFL.dHP_B12_Odd_Maintain_Day1 > 0.25));
+stable_RM.dHP_SSFL_Day2=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain_Day2 > thre & InFieldRMI.SSFL.dHP_B12_Odd_Maintain_Day2 > 0.25));
+stable_nRM.dHP_SS=length(find(SpatialCorrelation.SS.dHP_B12_Odd_Maintain > thre & InFieldRMI.SS.dHP_B12_Odd_Maintain <= 0.25));
+stable_nRM.dHP_SSCR=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain > thre & InFieldRMI.SSCR.dHP_B12_Odd_Maintain <= 0.25));
+stable_nRM.dHP_SSCR_Day1=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain_Day1 > thre & InFieldRMI.SSCR.dHP_B12_Odd_Maintain_Day1 <= 0.25));
+stable_nRM.dHP_SSCR_Day2=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain_Day2 > thre & InFieldRMI.SSCR.dHP_B12_Odd_Maintain_Day2 <= 0.25));
+stable_nRM.dHP_FLCR=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain > thre & InFieldRMI.FLCR.dHP_B12_Odd_Maintain <= 0.25));
+stable_nRM.dHP_FLCR_Day1=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain_Day1 > thre & InFieldRMI.FLCR.dHP_B12_Odd_Maintain_Day1 <= 0.25));
+stable_nRM.dHP_FLCR_Day2=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain_Day2 > thre & InFieldRMI.FLCR.dHP_B12_Odd_Maintain_Day2 <= 0.25));
+stable_nRM.dHP_SSFL=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain > thre & InFieldRMI.SSFL.dHP_B12_Odd_Maintain <= 0.25));
+stable_nRM.dHP_SSFL_Day1=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain_Day1 > thre & InFieldRMI.SSFL.dHP_B12_Odd_Maintain_Day1 <= 0.25));
+stable_nRM.dHP_SSFL_Day2=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain_Day2 > thre & InFieldRMI.SSFL.dHP_B12_Odd_Maintain_Day2 <= 0.25));
+
+shift.dHP_SS=length(find(SpatialCorrelation.SS.dHP_B12_Odd_Maintain < thre));
+shift.dHP_SSCR=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain < thre));
+shift.dHP_SSCR_Day1=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain_Day1 < thre));
+shift.dHP_SSCR_Day2=length(find(SpatialCorrelation.SSCR.dHP_B12_Odd_Maintain_Day2 < thre));
+shift.dHP_FLCR=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain < thre));
+shift.dHP_FLCR_Day1=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain_Day1 < thre));
+shift.dHP_FLCR_Day2=length(find(SpatialCorrelation.FLCR.dHP_B12_Odd_Maintain_Day2 < thre));
+shift.dHP_SSFL=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain < thre));
+shift.dHP_SSFL_Day1=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain_Day1 < thre));
+shift.dHP_SSFL_Day2=length(find(SpatialCorrelation.SSFL.dHP_B12_Odd_Maintain_Day2 < thre));
+
+on.dHP_SS=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & SS_dHP));
+on.dHP_SSCR=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & SSCR_dHP));
+on.dHP_SSCR_Day1=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & SSCR1_dHP));
+on.dHP_SSCR_Day2=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & SSCR2_dHP));
+on.dHP_FLCR=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & FLCR_dHP));
+on.dHP_FLCR_Day1=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & FLCR1_dHP));
+on.dHP_FLCR_Day2=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & FLCR2_dHP));
+on.dHP_SSFL=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & SSFL_dHP));
+on.dHP_SSFL_Day1=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & SSFL1_dHP));
+on.dHP_SSFL_Day2=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Appear & SSFL2_dHP));
+
+off.dHP_SS=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & SS_dHP));
+off.dHP_SSCR=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & SSCR_dHP));
+off.dHP_SSCR_Day1=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & SSCR1_dHP));
+off.dHP_SSCR_Day2=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & SSCR2_dHP));
+off.dHP_FLCR=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & FLCR_dHP));
+off.dHP_FLCR_Day1=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & FLCR1_dHP));
+off.dHP_FLCR_Day2=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & FLCR2_dHP));
+off.dHP_SSFL=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & SSFL_dHP));
+off.dHP_SSFL_Day1=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & SSFL1_dHP));
+off.dHP_SSFL_Day2=length(ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP_Disappear & SSFL2_dHP));
+
+% % 
+stable.iHP_SS=length(find(SpatialCorrelation.SS.iHP_B12_Odd_Maintain > thre));
+stable.iHP_SSCR=length(find(SpatialCorrelation.SSCR.iHP_B12_Odd_Maintain > thre));
+stable.iHP_FLCR=length(find(SpatialCorrelation.FLCR.iHP_B12_Odd_Maintain > thre));
+stable.iHP_SSFL=length(find(SpatialCorrelation.SSFL.iHP_B12_Odd_Maintain > thre));
+
+stable_RM.iHP_SS=length(find(SpatialCorrelation.SS.iHP_B12_Odd_Maintain > thre & InFieldRMI.SS.iHP_B12_Odd_Maintain > 0.25));
+stable_RM.iHP_SSCR=length(find(SpatialCorrelation.SSCR.iHP_B12_Odd_Maintain > thre & InFieldRMI.SSCR.iHP_B12_Odd_Maintain > 0.25));
+stable_RM.iHP_FLCR=length(find(SpatialCorrelation.FLCR.iHP_B12_Odd_Maintain > thre & InFieldRMI.FLCR.iHP_B12_Odd_Maintain > 0.25));
+stable_RM.iHP_SSFL=length(find(SpatialCorrelation.SSFL.iHP_B12_Odd_Maintain > thre & InFieldRMI.SSFL.iHP_B12_Odd_Maintain > 0.25));
+stable_nRM.iHP_SS=length(find(SpatialCorrelation.SS.iHP_B12_Odd_Maintain > thre & InFieldRMI.SS.iHP_B12_Odd_Maintain <= 0.25));
+stable_nRM.iHP_SSCR=length(find(SpatialCorrelation.SSCR.iHP_B12_Odd_Maintain > thre & InFieldRMI.SSCR.iHP_B12_Odd_Maintain <= 0.25));
+stable_nRM.iHP_FLCR=length(find(SpatialCorrelation.FLCR.iHP_B12_Odd_Maintain > thre & InFieldRMI.FLCR.iHP_B12_Odd_Maintain <= 0.25));
+stable_nRM.iHP_SSFL=length(find(SpatialCorrelation.SSFL.iHP_B12_Odd_Maintain > thre & InFieldRMI.SSFL.iHP_B12_Odd_Maintain <= 0.25));
+
+shift.iHP_SS=length(find(SpatialCorrelation.SS.iHP_B12_Odd_Maintain < thre));
+shift.iHP_SSCR=length(find(SpatialCorrelation.SSCR.iHP_B12_Odd_Maintain < thre));
+shift.iHP_SSCR_Day1=length(find(SpatialCorrelation.SSCR.iHP_B12_Odd_Maintain_Day1 < thre));
+shift.iHP_SSCR_Day2=length(find(SpatialCorrelation.SSCR.iHP_B12_Odd_Maintain_Day2 < thre));
+shift.iHP_FLCR=length(find(SpatialCorrelation.FLCR.iHP_B12_Odd_Maintain < thre));
+shift.iHP_SSFL=length(find(SpatialCorrelation.SSFL.iHP_B12_Odd_Maintain < thre));
+
+on.iHP_SS=length(ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP_Appear & SS_ivHP));
+on.iHP_SSCR=length(ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP_Appear & SSCR_ivHP));
+on.iHP_FLCR=length(ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP_Appear & FLCR_ivHP));
+on.iHP_SSFL=length(ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP_Appear & SSFL_ivHP));
+
+off.iHP_SS=length(ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP_Disappear & SS_ivHP));
+off.iHP_SSCR=length(ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP_Disappear & SSCR_ivHP));
+off.iHP_FLCR=length(ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP_Disappear & FLCR_ivHP));
+off.iHP_SSFL=length(ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP_Disappear & SSFL_ivHP));
+
+[stable_nRM.dHP_SS stable_RM.dHP_SS shift.dHP_SS+on.dHP_SS+off.dHP_SS];
+[stable_nRM.dHP_SSFL stable_RM.dHP_SSFL shift.dHP_SSFL+on.dHP_SSFL+off.dHP_SSFL];
+[stable_nRM.dHP_SSCR+stable_nRM.dHP_FLCR stable_RM.dHP_SSCR+stable_RM.dHP_FLCR shift.dHP_SSCR+on.dHP_SSCR+off.dHP_SSCR+shift.dHP_FLCR+on.dHP_FLCR+off.dHP_FLCR];
+
+[stable_nRM.iHP_SS stable_RM.iHP_SS shift.iHP_SS+on.iHP_SS+off.iHP_SS];
+[stable_nRM.iHP_SSFL stable_RM.iHP_SSFL shift.iHP_SSFL+on.iHP_SSFL+off.iHP_SSFL];
+[stable_nRM.iHP_SSCR+stable_nRM.iHP_FLCR stable_RM.iHP_SSCR+stable_RM.iHP_FLCR shift.iHP_SSCR+on.iHP_SSCR+off.iHP_SSCR+shift.iHP_FLCR+on.iHP_FLCR+off.iHP_FLCR];
+
+figure
+pie([stable_nRM.dHP_SS stable_RM.dHP_SS shift.dHP_SS+on.dHP_SS+off.dHP_SS])
+figure
+pie([stable_nRM.dHP_SSFL stable_RM.dHP_SSFL shift.dHP_SSFL+on.dHP_SSFL+off.dHP_SSFL])
+figure
+pie([stable_nRM.dHP_SSCR+stable_nRM.dHP_FLCR stable_RM.dHP_SSCR+stable_RM.dHP_FLCR shift.dHP_SSCR+on.dHP_SSCR+off.dHP_SSCR+shift.dHP_FLCR+on.dHP_FLCR+off.dHP_FLCR])
+
+% % Statistical testing
+[h,p,STAT]=chi2cont([stable_nRM.iHP_SS stable_RM.iHP_SS shift.iHP_SS+on.iHP_SS+off.iHP_SS...
+    ; stable_nRM.iHP_SSFL stable_RM.iHP_SSFL shift.iHP_SSFL+on.iHP_SSFL+off.iHP_SSFL...
+    ; stable_nRM.iHP_SSCR+stable_nRM.iHP_FLCR stable_RM.iHP_SSCR+stable_RM.iHP_FLCR shift.iHP_SSCR+on.iHP_SSCR+off.iHP_SSCR+shift.iHP_FLCR+on.iHP_FLCR+off.iHP_FLCR]); %
+[h,p,STAT]=chi2cont([stable_nRM.iHP_SS stable_RM.iHP_SS shift.iHP_SS+on.iHP_SS+off.iHP_SS...
+    ; stable_nRM.iHP_SSFL stable_RM.iHP_SSFL shift.iHP_SSFL+on.iHP_SSFL+off.iHP_SSFL]); %
+[h,p,STAT]=chi2cont([stable_nRM.iHP_SS stable_RM.iHP_SS shift.iHP_SS+on.iHP_SS+off.iHP_SS...
+    ; stable_nRM.iHP_SSCR+stable_nRM.iHP_FLCR stable_RM.iHP_SSCR+stable_RM.iHP_FLCR shift.iHP_SSCR+on.iHP_SSCR+off.iHP_SSCR+shift.iHP_FLCR+on.iHP_FLCR+off.iHP_FLCR]); %
+[h,p,STAT]=chi2cont([stable_nRM.iHP_SSFL stable_RM.iHP_SSFL shift.iHP_SSFL+on.iHP_SSFL+off.iHP_SSFL...
+    ; stable_nRM.iHP_SSCR+stable_nRM.iHP_FLCR stable_RM.iHP_SSCR+stable_RM.iHP_FLCR shift.iHP_SSCR+on.iHP_SSCR+off.iHP_SSCR+shift.iHP_FLCR+on.iHP_FLCR+off.iHP_FLCR]); %
+
+[h,p,STAT]=chi2cont([stable_nRM.dHP_SS stable_RM.dHP_SS shift.dHP_SS+on.dHP_SS+off.dHP_SS...
+    ; stable_nRM.dHP_SSFL stable_RM.dHP_SSFL shift.dHP_SSFL+on.dHP_SSFL+off.dHP_SSFL...
+    ; stable_nRM.dHP_SSCR+stable_nRM.dHP_FLCR stable_RM.dHP_SSCR+stable_RM.dHP_FLCR shift.dHP_SSCR+on.dHP_SSCR+off.dHP_SSCR+shift.dHP_FLCR+on.dHP_FLCR+off.dHP_FLCR]); %
+[h,p,STAT]=chi2cont([stable_nRM.dHP_SS stable_RM.dHP_SS shift.dHP_SS+on.dHP_SS+off.dHP_SS...
+    ; stable_nRM.dHP_SSFL stable_RM.dHP_SSFL shift.dHP_SSFL+on.dHP_SSFL+off.dHP_SSFL]); %
+[h,p,STAT]=chi2cont([stable_nRM.dHP_SS stable_RM.dHP_SS shift.dHP_SS+on.dHP_SS+off.dHP_SS...
+    ; stable_nRM.dHP_SSCR+stable_nRM.dHP_FLCR stable_RM.dHP_SSCR+stable_RM.dHP_FLCR shift.dHP_SSCR+on.dHP_SSCR+off.dHP_SSCR+shift.dHP_FLCR+on.dHP_FLCR+off.dHP_FLCR]); %
+[h,p,STAT]=chi2cont([stable_nRM.dHP_SSFL stable_RM.dHP_SSFL shift.dHP_SSFL+on.dHP_SSFL+off.dHP_SSFL...
+    ; stable_nRM.dHP_SSCR+stable_nRM.dHP_FLCR stable_RM.dHP_SSCR+stable_RM.dHP_FLCR shift.dHP_SSCR+on.dHP_SSCR+off.dHP_SSCR+shift.dHP_FLCR+on.dHP_FLCR+off.dHP_FLCR]); %
+
+%% Figure 3B
+SpatialCorrelation.SS.dHP_B12_Odd=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & SS_dHP);
+SpatialCorrelation.SSCR.dHP_B12_Odd=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & SSCR_dHP);
+SpatialCorrelation.SSCR.dHP_B12_Odd_Day1=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & SSCR1_dHP);
+SpatialCorrelation.SSCR.dHP_B12_Odd_Day2=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & SSCR2_dHP);
+SpatialCorrelation.FLCR.dHP_B12_Odd=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & FLCR_dHP);
+SpatialCorrelation.FLCR.dHP_B12_Odd_Day1=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & FLCR1_dHP);
+SpatialCorrelation.FLCR.dHP_B12_Odd_Day2=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & FLCR2_dHP);
+SpatialCorrelation.SSFL.dHP_B12_Odd=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & SSFL_dHP);
+SpatialCorrelation.SSFL.dHP_B12_Odd_Day1=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & SSFL1_dHP);
+SpatialCorrelation.SSFL.dHP_B12_Odd_Day2=ClusterInfo.dHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_dHP & SSFL2_dHP);
+SpatialCorrelation.SS.iHP_B12_Odd=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & SS_ivHP);
+SpatialCorrelation.SSCR.iHP_B12_Odd=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & SSCR_ivHP);
+SpatialCorrelation.SSCR.iHP_B12_Odd_Day1=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & SSCR1_ivHP);
+SpatialCorrelation.SSCR.iHP_B12_Odd_Day2=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & SSCR2_ivHP);
+SpatialCorrelation.FLCR.iHP_B12_Odd=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & FLCR_ivHP);
+SpatialCorrelation.FLCR.iHP_B12_Odd_Day1=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & FLCR1_ivHP);
+SpatialCorrelation.FLCR.iHP_B12_Odd_Day2=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & FLCR2_ivHP);
+SpatialCorrelation.SSFL.iHP_B12_Odd=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & SSFL_ivHP);
+SpatialCorrelation.SSFL.iHP_B12_Odd_Day1=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & SSFL1_ivHP);
+SpatialCorrelation.SSFL.iHP_B12_Odd_Day2=ClusterInfo.ivHP_SpatialCorrelation_Odd_B12(LeftToRight_PlaceField_B12_iHP & SSFL2_ivHP);
+
+% % dHP, Mixed, SSvsCR + FLvsCR
+fig=figure; hold on;
+fig.Position=[0 0 800 800];
+g=gca; 
+cdfplot(SpatialCorrelation.SS.dHP_B12_Odd)
+cdfplot([SpatialCorrelation.SSCR.dHP_B12_Odd; SpatialCorrelation.FLCR.dHP_B12_Odd])
+cdfplot(SpatialCorrelation.SSFL.dHP_B12_Odd)
+
+% % Statistical testing
+data1=SpatialCorrelation.SS.dHP_B12_Odd;
+data2=[SpatialCorrelation.SSCR.dHP_B12_Odd; SpatialCorrelation.FLCR.dHP_B12_Odd];
+data3=SpatialCorrelation.SSFL.dHP_B12_Odd;
+Y = [data1; data2; data3];
+Session = [GetGroupingVar(data1,1); GetGroupingVar(data2,2); GetGroupingVar(data3,3)];
+[Pvalue.dHP_kruskal_main_Odd, result, stats] = kruskalwallis(Y,Session,'off');
+Pvalue.dHP_kruaskal_multcompare_Odd=multcompare(stats,'display','off');
+
+% % dHP, Separately, SSvsCR, FLvsCR
+fig=figure; hold on;
+fig.Position=[0 0 800 800];
+g=gca; 
+cdfplot(SpatialCorrelation.SS.dHP_B12_Odd)
+cdfplot(SpatialCorrelation.SSCR.dHP_B12_Odd)
+cdfplot(SpatialCorrelation.FLCR.dHP_B12_Odd)
+cdfplot(SpatialCorrelation.SSFL.dHP_B12_Odd)
+
+% % Statistical testing
+data1=SpatialCorrelation.SS.dHP_B12_Odd;
+data2=SpatialCorrelation.SSCR.dHP_B12_Odd; 
+data3=SpatialCorrelation.FLCR.dHP_B12_Odd;
+data4=SpatialCorrelation.SSFL.dHP_B12_Odd;
+Y = [data1; data2; data3; data4];
+Session = [GetGroupingVar(data1,1); GetGroupingVar(data2,2); GetGroupingVar(data3,3); GetGroupingVar(data4,4)];
+[Pvalue.dHP_kruskal_main_Odd, result, stats] = kruskalwallis(Y,Session,'off');
+Pvalue.dHP_kruaskal_multcompare_Odd=multcompare(stats,'display','off');
+
+% % iHP, Mixed, SSvsCR + FLvsCR
+fig=figure; hold on;
+fig.Position=[0 0 800 800];
+g=gca; 
+cdfplot(SpatialCorrelation.SS.iHP_B12_Odd)
+cdfplot([SpatialCorrelation.SSCR.iHP_B12_Odd; SpatialCorrelation.FLCR.iHP_B12_Odd])
+cdfplot(SpatialCorrelation.SSFL.iHP_B12_Odd)
+
+% % Statistical testing
+data1=SpatialCorrelation.SS.iHP_B12_Odd;
+data2=[SpatialCorrelation.SSCR.iHP_B12_Odd; SpatialCorrelation.FLCR.iHP_B12_Odd];
+data3=SpatialCorrelation.SSFL.iHP_B12_Odd;
+Y = [data1; data2; data3];
+Session = [GetGroupingVar(data1,1); GetGroupingVar(data2,2); GetGroupingVar(data3,3)];
+[Pvalue.iHP_kruskal_main_Odd, result, stats] = kruskalwallis(Y,Session,'off');
+Pvalue.iHP_kruaskal_multcompare_Odd=multcompare(stats,'display','off');
+
+% % iHP, Separately, SSvsCR, FLvsCR
+fig=figure; hold on;
+fig.Position=[0 0 800 800];
+g=gca; 
+cdfplot(SpatialCorrelation.SS.iHP_B12_Odd)
+cdfplot(SpatialCorrelation.SSCR.iHP_B12_Odd)
+cdfplot(SpatialCorrelation.FLCR.iHP_B12_Odd)
+cdfplot(SpatialCorrelation.SSFL.iHP_B12_Odd)
+
+% % Statistical testing
+data1=SpatialCorrelation.SS.iHP_B12_Odd;
+data2=SpatialCorrelation.SSCR.iHP_B12_Odd; 
+data3=SpatialCorrelation.FLCR.iHP_B12_Odd;
+data4=SpatialCorrelation.SSFL.iHP_B12_Odd;
+Y = [data1; data2; data3; data4];
+Session = [GetGroupingVar(data1,1); GetGroupingVar(data2,2); GetGroupingVar(data3,3); GetGroupingVar(data4,4)];
+[Pvalue.iHP_kruskal_main_Odd, result, stats] = kruskalwallis(Y,Session,'off');
+Pvalue.iHP_kruaskal_multcompare_Odd=multcompare(stats,'display','off');
+
+%% Figure 3D-3E
+% % Examples of population matrix (dHP, SS-SS)
+fig=figure;
+fig.Position=[0 0 1000 500];
+subplot(1,3,1)
+data1=[PopMatrix_SS.dHP_LeftToRight_B1_Maintain_Norm_sorted(:,1:end)];
+imagesc(data1)
+colormap('jet')
+g=gca; g.CLim=[0 1];g.YDir='normal';
+subplot(1,3,2)
+data2=[PopMatrix_SS.dHP_LeftToRight_B2_Maintain_Norm_sorted(:,1:end)];
+imagesc(data2)
+colormap('jet')
+g=gca; g.CLim=[0 1];g.YDir='normal';
+subplot(1,3,3)
+data3=[PopMatrix_SS.dHP_LeftToRight_B3_Maintain_Norm_sorted(:,1:end)];
+imagesc(data3)
+colormap('jet')
+g=gca; g.CLim=[0 1];g.YDir='normal';
+
+% % Correlation between population matrix
+data1=PopMatrix_SS.dHP_LeftToRight_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SS.dHP_LeftToRight_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SS_B12_dHP_LeftToRight = correl(1,2);
+data1=PopMatrix_SSCR.dHP_LeftToRight_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SSCR.dHP_LeftToRight_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SSCR_B12_dHP_LeftToRight = correl(1,2);
+data1=PopMatrix_FLCR.dHP_LeftToRight_B1_Maintain_Norm_sorted;
+data2=PopMatrix_FLCR.dHP_LeftToRight_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.FLCR_B12_dHP_LeftToRight = correl(1,2);
+data1=PopMatrix_SSFL.dHP_LeftToRight_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SSFL.dHP_LeftToRight_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SSFL_B12_dHP_LeftToRight = correl(1,2);
+data1=PopMatrix_SS.iHP_LeftToRight_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SS.iHP_LeftToRight_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SS_B12_iHP_LeftToRight = correl(1,2);
+data1=PopMatrix_SSCR.iHP_LeftToRight_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SSCR.iHP_LeftToRight_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SSCR_B12_iHP_LeftToRight = correl(1,2);
+data1=PopMatrix_FLCR.iHP_LeftToRight_B1_Maintain_Norm_sorted;
+data2=PopMatrix_FLCR.iHP_LeftToRight_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.FLCR_B12_iHP_LeftToRight = correl(1,2);
+data1=PopMatrix_SSFL.iHP_LeftToRight_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SSFL.iHP_LeftToRight_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SSFL_B12_iHP_LeftToRight = correl(1,2);
+
+data1=PopMatrix_SS.dHP_RightToLeft_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SS.dHP_RightToLeft_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SS_B12_dHP_RightToLeft = correl(1,2);
+data1=PopMatrix_SSCR.dHP_RightToLeft_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SSCR.dHP_RightToLeft_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SSCR_B12_dHP_RightToLeft = correl(1,2);
+data1=PopMatrix_FLCR.dHP_RightToLeft_B1_Maintain_Norm_sorted;
+data2=PopMatrix_FLCR.dHP_RightToLeft_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.FLCR_B12_dHP_RightToLeft = correl(1,2);
+data1=PopMatrix_SSFL.dHP_RightToLeft_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SSFL.dHP_RightToLeft_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SSFL_B12_dHP_RightToLeft = correl(1,2);
+data1=PopMatrix_SS.iHP_RightToLeft_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SS.iHP_RightToLeft_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SS_B12_iHP_RightToLeft = correl(1,2);
+data1=PopMatrix_SSCR.iHP_RightToLeft_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SSCR.iHP_RightToLeft_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SSCR_B12_iHP_RightToLeft = correl(1,2);
+data1=PopMatrix_FLCR.iHP_RightToLeft_B1_Maintain_Norm_sorted;
+data2=PopMatrix_FLCR.iHP_RightToLeft_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.FLCR_B12_iHP_RightToLeft = correl(1,2);
+data1=PopMatrix_SSFL.iHP_RightToLeft_B1_Maintain_Norm_sorted;
+data2=PopMatrix_SSFL.iHP_RightToLeft_B2_Maintain_Norm_sorted;
+[Data1, Data2] = GetPopulationCorrelation(data1, data2);
+correl=corrcoef(Data1,Data2);
+PopCorr.SSFL_B12_iHP_RightToLeft = correl(1,2);
+
+dHP_B12_LeftToRight=[PopCorr.SS_B12_dHP_LeftToRight-PopCorr.SS_B12_dHP_LeftToRight PopCorr.SSCR_B12_dHP_LeftToRight-PopCorr.SS_B12_dHP_LeftToRight ...
+    PopCorr.FLCR_B12_dHP_LeftToRight-PopCorr.SS_B12_dHP_LeftToRight PopCorr.SSFL_B12_dHP_LeftToRight-PopCorr.SS_B12_dHP_LeftToRight];
+
+iHP_B12_LeftToRight=[PopCorr.SS_B12_iHP_LeftToRight-PopCorr.SS_B12_iHP_LeftToRight PopCorr.SSCR_B12_iHP_LeftToRight-PopCorr.SS_B12_iHP_LeftToRight ...
+    PopCorr.FLCR_B12_iHP_LeftToRight-PopCorr.SS_B12_iHP_LeftToRight PopCorr.SSFL_B12_iHP_LeftToRight-PopCorr.SS_B12_iHP_LeftToRight];
+
+dHP_B12_RightToLeft=[PopCorr.SS_B12_dHP_RightToLeft-PopCorr.SS_B12_dHP_RightToLeft PopCorr.SSCR_B12_dHP_RightToLeft-PopCorr.SS_B12_dHP_RightToLeft ...
+    PopCorr.FLCR_B12_dHP_RightToLeft-PopCorr.SS_B12_dHP_RightToLeft PopCorr.SSFL_B12_dHP_RightToLeft-PopCorr.SS_B12_dHP_RightToLeft];
+
+iHP_B12_RightToLeft=[PopCorr.SS_B12_iHP_RightToLeft-PopCorr.SS_B12_iHP_RightToLeft PopCorr.SSCR_B12_iHP_RightToLeft-PopCorr.SS_B12_iHP_RightToLeft ...
+    PopCorr.FLCR_B12_iHP_RightToLeft-PopCorr.SS_B12_iHP_RightToLeft PopCorr.SSFL_B12_iHP_RightToLeft-PopCorr.SS_B12_iHP_RightToLeft];
+
+% % Figure 3E
+figure; hold on;
+plot(dHP_B12_LeftToRight,'r.-');
+plot(iHP_B12_LeftToRight,'b.-');
+plot(dHP_B12_RightToLeft,'r.:');
+plot(iHP_B12_RightToLeft,'b.:');
+ylim([-0.12 0]);
+
+%% Figure 3E, Mean correlation of each session vs. Velocity
+VelocityDiff_448_day2_SSCH=VelocityRatio.SSCH_B12(21,1);
+VelocityDiff_448_day3_SSCH=VelocityRatio.SSCH_B12(21,2);
+VelocityDiff_459_day2_SSCH=VelocityRatio.SSCH_B12(21,3);
+VelocityDiff_459_day3_SSCH=VelocityRatio.SSCH_B12(21,4);
+VelocityDiff_463_day2_SSCH=VelocityRatio.SSCH_B12(21,5);
+VelocityDiff_463_day3_SSCH=VelocityRatio.SSCH_B12(21,6);
+VelocityDiff_473_day2_SSCH=VelocityRatio.SSCH_B12(21,7);
+VelocityDiff_473_day3_SSCH=VelocityRatio.SSCH_B12(21,8);
+VelocityDiff_488_day2_SSCH=VelocityRatio.SSCH_B12(21,9);
+VelocityDiff_488_day3_SSCH=VelocityRatio.SSCH_B12(21,10);
+VelocityDiff_509_day2_SSCH=VelocityRatio.SSCH_B12(21,11);
+VelocityDiff_509_day3_SSCH=VelocityRatio.SSCH_B12(21,12);
+VelocityDiff_448_day2_FRCH=VelocityRatio.FRCH_B12(21,1);
+VelocityDiff_448_day3_FRCH=VelocityRatio.FRCH_B12(21,2);
+VelocityDiff_459_day2_FRCH=VelocityRatio.FRCH_B12(21,3);
+VelocityDiff_459_day3_FRCH=VelocityRatio.FRCH_B12(21,4);
+VelocityDiff_463_day2_FRCH=VelocityRatio.FRCH_B12(21,5);
+VelocityDiff_463_day3_FRCH=VelocityRatio.FRCH_B12(21,6);
+VelocityDiff_473_day2_FRCH=VelocityRatio.FRCH_B12(21,7);
+VelocityDiff_473_day3_FRCH=VelocityRatio.FRCH_B12(21,8);
+VelocityDiff_488_day2_FRCH=VelocityRatio.FRCH_B12(21,9);
+VelocityDiff_488_day3_FRCH=VelocityRatio.FRCH_B12(21,10);
+VelocityDiff_509_day2_FRCH=VelocityRatio.FRCH_B12(21,11);
+VelocityDiff_509_day3_FRCH=VelocityRatio.FRCH_B12(21,12);
+VelocityDiff_448_day2_SSFR=VelocityRatio.SSFR_B12(21,1);
+VelocityDiff_448_day3_SSFR=VelocityRatio.SSFR_B12(21,2);
+VelocityDiff_459_day2_SSFR=VelocityRatio.SSFR_B12(21,3);
+VelocityDiff_459_day3_SSFR=VelocityRatio.SSFR_B12(21,4);
+VelocityDiff_463_day2_SSFR=VelocityRatio.SSFR_B12(21,5);
+VelocityDiff_463_day3_SSFR=VelocityRatio.SSFR_B12(21,6);
+VelocityDiff_473_day2_SSFR=VelocityRatio.SSFR_B12(21,7);
+VelocityDiff_473_day3_SSFR=VelocityRatio.SSFR_B12(21,8);
+VelocityDiff_488_day2_SSFR=VelocityRatio.SSFR_B12(21,9);
+VelocityDiff_488_day3_SSFR=VelocityRatio.SSFR_B12(21,10);
+VelocityDiff_509_day2_SSFR=VelocityRatio.SSFR_B12(21,11);
+VelocityDiff_509_day3_SSFR=VelocityRatio.SSFR_B12(21,12);
+
+MeanCorr_iHP_448_day2_SSCH=Correlation.SSCH_iHP_B12_Maintain(1,1);
+MeanCorr_iHP_448_day3_SSCH=Correlation.SSCH_iHP_B12_Maintain(2,1);
+MeanCorr_iHP_459_day2_SSCH=Correlation.SSCH_iHP_B12_Maintain(3,1);
+MeanCorr_iHP_459_day3_SSCH=Correlation.SSCH_iHP_B12_Maintain(4,1);
+MeanCorr_iHP_463_day2_SSCH=Correlation.SSCH_iHP_B12_Maintain(5,1);
+MeanCorr_iHP_463_day3_SSCH=Correlation.SSCH_iHP_B12_Maintain(6,1);
+MeanCorr_iHP_473_day2_SSCH=Correlation.SSCH_iHP_B12_Maintain(7,1);
+MeanCorr_iHP_473_day3_SSCH=Correlation.SSCH_iHP_B12_Maintain(8,1);
+MeanCorr_iHP_488_day2_SSCH=Correlation.SSCH_iHP_B12_Maintain(9,1);
+MeanCorr_iHP_488_day3_SSCH=Correlation.SSCH_iHP_B12_Maintain(10,1);
+MeanCorr_iHP_509_day2_SSCH=Correlation.SSCH_iHP_B12_Maintain(11,1);
+MeanCorr_iHP_509_day3_SSCH=Correlation.SSCH_iHP_B12_Maintain(12,1);
+MeanCorr_iHP_448_day2_FRCH=Correlation.FRCH_iHP_B12_Maintain(1,1);
+MeanCorr_iHP_448_day3_FRCH=Correlation.FRCH_iHP_B12_Maintain(2,1);
+MeanCorr_iHP_459_day2_FRCH=Correlation.FRCH_iHP_B12_Maintain(3,1);
+MeanCorr_iHP_459_day3_FRCH=Correlation.FRCH_iHP_B12_Maintain(4,1);
+MeanCorr_iHP_463_day2_FRCH=Correlation.FRCH_iHP_B12_Maintain(5,1);
+MeanCorr_iHP_463_day3_FRCH=Correlation.FRCH_iHP_B12_Maintain(6,1);
+MeanCorr_iHP_473_day2_FRCH=Correlation.FRCH_iHP_B12_Maintain(7,1);
+MeanCorr_iHP_473_day3_FRCH=Correlation.FRCH_iHP_B12_Maintain(8,1);
+MeanCorr_iHP_488_day2_FRCH=Correlation.FRCH_iHP_B12_Maintain(9,1);
+MeanCorr_iHP_488_day3_FRCH=Correlation.FRCH_iHP_B12_Maintain(10,1);
+MeanCorr_iHP_509_day2_FRCH=Correlation.FRCH_iHP_B12_Maintain(11,1);
+MeanCorr_iHP_509_day3_FRCH=Correlation.FRCH_iHP_B12_Maintain(12,1);
+MeanCorr_iHP_448_day2_SSFR=Correlation.SSFR_iHP_B12_Maintain(1,1);
+MeanCorr_iHP_448_day3_SSFR=Correlation.SSFR_iHP_B12_Maintain(2,1);
+MeanCorr_iHP_459_day2_SSFR=Correlation.SSFR_iHP_B12_Maintain(3,1);
+MeanCorr_iHP_459_day3_SSFR=Correlation.SSFR_iHP_B12_Maintain(4,1);
+MeanCorr_iHP_463_day2_SSFR=Correlation.SSFR_iHP_B12_Maintain(5,1);
+MeanCorr_iHP_463_day3_SSFR=Correlation.SSFR_iHP_B12_Maintain(6,1);
+MeanCorr_iHP_473_day2_SSFR=Correlation.SSFR_iHP_B12_Maintain(7,1);
+MeanCorr_iHP_473_day3_SSFR=Correlation.SSFR_iHP_B12_Maintain(8,1);
+MeanCorr_iHP_488_day2_SSFR=Correlation.SSFR_iHP_B12_Maintain(9,1);
+MeanCorr_iHP_488_day3_SSFR=Correlation.SSFR_iHP_B12_Maintain(10,1);
+MeanCorr_iHP_509_day2_SSFR=Correlation.SSFR_iHP_B12_Maintain(11,1);
+MeanCorr_iHP_509_day3_SSFR=Correlation.SSFR_iHP_B12_Maintain(12,1);
+
+MeanCorr_dHP_448_day2_SSCH=Correlation.SSCH_dHP_B12_Maintain(1,1);
+MeanCorr_dHP_448_day3_SSCH=Correlation.SSCH_dHP_B12_Maintain(2,1);
+MeanCorr_dHP_459_day2_SSCH=Correlation.SSCH_dHP_B12_Maintain(3,1);
+MeanCorr_dHP_459_day3_SSCH=Correlation.SSCH_dHP_B12_Maintain(4,1);
+MeanCorr_dHP_463_day2_SSCH=Correlation.SSCH_dHP_B12_Maintain(5,1);
+MeanCorr_dHP_463_day3_SSCH=Correlation.SSCH_dHP_B12_Maintain(6,1);
+MeanCorr_dHP_473_day2_SSCH=Correlation.SSCH_dHP_B12_Maintain(7,1);
+MeanCorr_dHP_473_day3_SSCH=Correlation.SSCH_dHP_B12_Maintain(8,1);
+MeanCorr_dHP_488_day2_SSCH=Correlation.SSCH_dHP_B12_Maintain(9,1);
+MeanCorr_dHP_488_day3_SSCH=Correlation.SSCH_dHP_B12_Maintain(10,1);
+MeanCorr_dHP_509_day2_SSCH=Correlation.SSCH_dHP_B12_Maintain(11,1);
+MeanCorr_dHP_509_day3_SSCH=Correlation.SSCH_dHP_B12_Maintain(12,1);
+MeanCorr_dHP_448_day2_FRCH=Correlation.FRCH_dHP_B12_Maintain(1,1);
+MeanCorr_dHP_448_day3_FRCH=Correlation.FRCH_dHP_B12_Maintain(2,1);
+MeanCorr_dHP_459_day2_FRCH=Correlation.FRCH_dHP_B12_Maintain(3,1);
+MeanCorr_dHP_459_day3_FRCH=Correlation.FRCH_dHP_B12_Maintain(4,1);
+MeanCorr_dHP_463_day2_FRCH=Correlation.FRCH_dHP_B12_Maintain(5,1);
+MeanCorr_dHP_463_day3_FRCH=Correlation.FRCH_dHP_B12_Maintain(6,1);
+MeanCorr_dHP_473_day2_FRCH=Correlation.FRCH_dHP_B12_Maintain(7,1);
+MeanCorr_dHP_473_day3_FRCH=Correlation.FRCH_dHP_B12_Maintain(8,1);
+MeanCorr_dHP_488_day2_FRCH=Correlation.FRCH_dHP_B12_Maintain(9,1);
+MeanCorr_dHP_488_day3_FRCH=Correlation.FRCH_dHP_B12_Maintain(10,1);
+MeanCorr_dHP_509_day2_FRCH=Correlation.FRCH_dHP_B12_Maintain(11,1);
+MeanCorr_dHP_509_day3_FRCH=Correlation.FRCH_dHP_B12_Maintain(12,1);
+MeanCorr_dHP_448_day2_SSFR=Correlation.SSFR_dHP_B12_Maintain(1,1);
+MeanCorr_dHP_448_day3_SSFR=Correlation.SSFR_dHP_B12_Maintain(2,1);
+MeanCorr_dHP_459_day2_SSFR=Correlation.SSFR_dHP_B12_Maintain(3,1);
+MeanCorr_dHP_459_day3_SSFR=Correlation.SSFR_dHP_B12_Maintain(4,1);
+MeanCorr_dHP_463_day2_SSFR=Correlation.SSFR_dHP_B12_Maintain(5,1);
+MeanCorr_dHP_463_day3_SSFR=Correlation.SSFR_dHP_B12_Maintain(6,1);
+MeanCorr_dHP_473_day2_SSFR=Correlation.SSFR_dHP_B12_Maintain(7,1);
+MeanCorr_dHP_473_day3_SSFR=Correlation.SSFR_dHP_B12_Maintain(8,1);
+MeanCorr_dHP_488_day2_SSFR=Correlation.SSFR_dHP_B12_Maintain(9,1);
+MeanCorr_dHP_488_day3_SSFR=Correlation.SSFR_dHP_B12_Maintain(10,1);
+MeanCorr_dHP_509_day2_SSFR=Correlation.SSFR_dHP_B12_Maintain(11,1);
+MeanCorr_dHP_509_day3_SSFR=Correlation.SSFR_dHP_B12_Maintain(12,1);
+
+% iHP
+dataX = [VelocityDiff_448_day2_SSCH VelocityDiff_448_day3_SSCH VelocityDiff_459_day2_SSCH VelocityDiff_459_day3_SSCH VelocityDiff_463_day2_SSCH VelocityDiff_463_day3_SSCH VelocityDiff_473_day2_SSCH VelocityDiff_473_day3_SSCH VelocityDiff_488_day2_SSCH VelocityDiff_488_day3_SSCH VelocityDiff_509_day2_SSCH VelocityDiff_509_day3_SSCH...
+    VelocityDiff_448_day2_FRCH VelocityDiff_448_day3_FRCH VelocityDiff_459_day2_FRCH VelocityDiff_459_day3_FRCH VelocityDiff_463_day2_FRCH VelocityDiff_463_day3_FRCH VelocityDiff_473_day2_FRCH VelocityDiff_473_day3_FRCH VelocityDiff_488_day2_FRCH VelocityDiff_488_day3_FRCH VelocityDiff_509_day2_FRCH VelocityDiff_509_day3_FRCH...
+    VelocityDiff_448_day2_SSFR VelocityDiff_448_day3_SSFR VelocityDiff_459_day2_SSFR VelocityDiff_459_day3_SSFR VelocityDiff_463_day2_SSFR VelocityDiff_463_day3_SSFR VelocityDiff_473_day2_SSFR VelocityDiff_473_day3_SSFR VelocityDiff_488_day2_SSFR VelocityDiff_488_day3_SSFR VelocityDiff_509_day2_SSFR VelocityDiff_509_day3_SSFR];
+
+dataY = [MeanCorr_iHP_448_day2_SSCH MeanCorr_iHP_448_day3_SSCH MeanCorr_iHP_459_day2_SSCH MeanCorr_iHP_459_day3_SSCH MeanCorr_iHP_463_day2_SSCH MeanCorr_iHP_463_day3_SSCH MeanCorr_iHP_473_day2_SSCH MeanCorr_iHP_473_day3_SSCH MeanCorr_iHP_488_day2_SSCH MeanCorr_iHP_488_day3_SSCH MeanCorr_iHP_509_day2_SSCH MeanCorr_iHP_509_day3_SSCH...
+    MeanCorr_iHP_448_day2_FRCH MeanCorr_iHP_448_day3_FRCH MeanCorr_iHP_459_day2_FRCH MeanCorr_iHP_459_day3_FRCH MeanCorr_iHP_463_day2_FRCH MeanCorr_iHP_463_day3_FRCH MeanCorr_iHP_473_day2_FRCH MeanCorr_iHP_473_day3_FRCH MeanCorr_iHP_488_day2_FRCH MeanCorr_iHP_488_day3_FRCH MeanCorr_iHP_509_day2_FRCH MeanCorr_iHP_509_day3_FRCH...
+    MeanCorr_iHP_448_day2_SSFR MeanCorr_iHP_448_day3_SSFR MeanCorr_iHP_459_day2_SSFR MeanCorr_iHP_459_day3_SSFR MeanCorr_iHP_463_day2_SSFR MeanCorr_iHP_463_day3_SSFR MeanCorr_iHP_473_day2_SSFR MeanCorr_iHP_473_day3_SSFR MeanCorr_iHP_488_day2_SSFR MeanCorr_iHP_488_day3_SSFR MeanCorr_iHP_509_day2_SSFR MeanCorr_iHP_509_day3_SSFR];
+
+% Robust regression
+figure; g=gca; hold on;
+plot(dataX,dataY,'.')
+[Regression, f]=GetLinearRegression(dataX,dataY,g);
+x=-0.2:0.01:0.7;
+y=Regression.a1 * x + Regression.a0;
+
+y=dataY';
+x=dataX';
+x=x(~isnan(y));
+y=y(~isnan(y));
+[b_ls,~,~,~,stats_linreg] = regress(y,[ones(size(x)) x]);
+[b_rob, stats_rob] = robustfit(x,y);
+rquare_linreg = stats_linreg(1);
+clear corr
+rsquare_robustfit = corr(y,b_rob(1)+b_rob(2)*x)^2;
+sse = stats_rob.dfe * stats_rob.robust_s^2;
+phat = b_rob(1) + b_rob(2)*x;
+ssr = norm(phat-mean(phat))^2;
+possible_rsquare_robustfit = 1 - sse / (sse + ssr);
+x=-0.2:0.01:0.7;
+y=b_rob(2) * x + b_rob(1);
+stats_rob.p
+plot(x,y,'r');
+
+% 
+% dHP
+dataX = [VelocityDiff_448_day2_SSCH VelocityDiff_448_day3_SSCH VelocityDiff_459_day2_SSCH VelocityDiff_459_day3_SSCH VelocityDiff_463_day2_SSCH VelocityDiff_463_day3_SSCH VelocityDiff_473_day2_SSCH VelocityDiff_473_day3_SSCH VelocityDiff_488_day2_SSCH VelocityDiff_488_day3_SSCH VelocityDiff_509_day2_SSCH VelocityDiff_509_day3_SSCH...
+    VelocityDiff_448_day2_FRCH VelocityDiff_448_day3_FRCH VelocityDiff_459_day2_FRCH VelocityDiff_459_day3_FRCH VelocityDiff_463_day2_FRCH VelocityDiff_463_day3_FRCH VelocityDiff_473_day2_FRCH VelocityDiff_473_day3_FRCH VelocityDiff_488_day2_FRCH VelocityDiff_488_day3_FRCH VelocityDiff_509_day2_FRCH VelocityDiff_509_day3_FRCH...
+    VelocityDiff_448_day2_SSFR VelocityDiff_448_day3_SSFR VelocityDiff_459_day2_SSFR VelocityDiff_459_day3_SSFR VelocityDiff_463_day2_SSFR VelocityDiff_463_day3_SSFR VelocityDiff_473_day2_SSFR VelocityDiff_473_day3_SSFR VelocityDiff_488_day2_SSFR VelocityDiff_488_day3_SSFR VelocityDiff_509_day2_SSFR VelocityDiff_509_day3_SSFR];
+
+dataY = [MeanCorr_dHP_448_day2_SSCH MeanCorr_dHP_448_day3_SSCH MeanCorr_dHP_459_day2_SSCH MeanCorr_dHP_459_day3_SSCH MeanCorr_dHP_463_day2_SSCH MeanCorr_dHP_463_day3_SSCH MeanCorr_dHP_473_day2_SSCH MeanCorr_dHP_473_day3_SSCH MeanCorr_dHP_488_day2_SSCH MeanCorr_dHP_488_day3_SSCH MeanCorr_dHP_509_day2_SSCH MeanCorr_dHP_509_day3_SSCH...
+    MeanCorr_dHP_448_day2_FRCH MeanCorr_dHP_448_day3_FRCH MeanCorr_dHP_459_day2_FRCH MeanCorr_dHP_459_day3_FRCH MeanCorr_dHP_463_day2_FRCH MeanCorr_dHP_463_day3_FRCH MeanCorr_dHP_473_day2_FRCH MeanCorr_dHP_473_day3_FRCH MeanCorr_dHP_488_day2_FRCH MeanCorr_dHP_488_day3_FRCH MeanCorr_dHP_509_day2_FRCH MeanCorr_dHP_509_day3_FRCH...
+    MeanCorr_dHP_448_day2_SSFR MeanCorr_dHP_448_day3_SSFR MeanCorr_dHP_459_day2_SSFR MeanCorr_dHP_459_day3_SSFR MeanCorr_dHP_463_day2_SSFR MeanCorr_dHP_463_day3_SSFR MeanCorr_dHP_473_day2_SSFR MeanCorr_dHP_473_day3_SSFR MeanCorr_dHP_488_day2_SSFR MeanCorr_dHP_488_day3_SSFR MeanCorr_dHP_509_day2_SSFR MeanCorr_dHP_509_day3_SSFR];
+
+% Robust regression
+figure; g=gca; hold on;
+plot(dataX,dataY,'.')
+[Regression, f]=GetLinearRegression(dataX,dataY,g);
+x=-0.2:0.01:0.7;
+y=Regression.a1 * x + Regression.a0;
+
+y=dataY';
+x=dataX';
+x=x(~isnan(y));
+y=y(~isnan(y));
+[b_ls,~,~,~,stats_linreg] = regress(y,[ones(size(x)) x]);
+[b_rob, stats_rob] = robustfit(x,y);
+rquare_linreg = stats_linreg(1);
+clear corr
+rsquare_robustfit = corr(y,b_rob(1)+b_rob(2)*x)^2;
+sse = stats_rob.dfe * stats_rob.robust_s^2;
+phat = b_rob(1) + b_rob(2)*x;
+ssr = norm(phat-mean(phat))^2;
+possible_rsquare_robustfit = 1 - sse / (sse + ssr);
+x=-0.2:0.01:0.7;
+y=b_rob(2) * x + b_rob(1);
+plot(x,y,'r');
+% 

Figure_4.m

@@ -0,0 +1,161 @@
+load('Figure4.mat');
+%% Figure 4A-i
+load(['Rat448-Main2-PositionData.mat']);
+load(['Rat448-Main2-TT24-C1.mat']);
+RasterInfo.Left=2; RasterInfo.Right=1;
+thisCLST = GetSpikePosition(thisCLST,Pos);
+thisCLST = GetSpikeOutboundFlag(thisCLST, TrialNumber, Time);
+[PETHspike] = PeriEventTimeHistogram_Spike(TrialNumber, thisCLST, Time, RasterInfo);
+
+% 3D plotting
+FiringRate_3D=zeros(size(PETHspike.Choice,1),60);
+for i=1:size(PETHspike.Choice,1)
+    for j=1:size(PETHspike.Choice,2)
+        temp=PETHspike.Choice(i,j);
+        if ~isnan(temp)
+            temp=ceil((temp+4)*10);
+            FiringRate_3D(i,temp) = FiringRate_3D(i,temp) +1;
+        end
+    end
+end
+FiringRate_3D=FiringRate_3D*10;
+
+fig=figure; hold on;
+set(fig,'position', [0 0 600 600]);
+%
+for i=2:2:size(FiringRate_3D,1)
+    x = i/2 * ones(1,60);
+    temp1=GetGaussianSmoothing(FiringRate_3D(i,1:40),11);
+    temp2=GetGaussianSmoothing(FiringRate_3D(i,41:60),11);
+    temp=[temp1 temp2];
+    p=plot3(x(1:40),1:40,temp(1:40),'--'); p.LineWidth=0.5; p.Color = [0 0 0]/255; p.MarkerSize=12;
+    p=plot3(x(40:60),40:60,temp(40:60),'-'); p.LineWidth=0.5; p.Color = [0 0 0]/255; p.MarkerSize=12;
+end
+xlim([(TrialNumber.Block(2) - 7)/2 (TrialNumber.Block(2) + 9)/2]);
+g=gca; 
+g.ZAxis.TickValues=0:5:30;
+grid off
+g=gca;
+g.YDir='rev';
+grid on
+FontSize=8;
+set(gca,'FontSize',FontSize,'FontWeight','bold');
+
+%% Figure 4A-ii
+load('Rat448-Main4-TT24-C1_p2.mat')
+% B1
+temp1 = InFieldRate(MoreActiveField.Even).Even_B1_Individual; 
+% B2
+temp2 = InFieldRate(MoreActiveField.Even).Even_B2_Individual;
+% B3
+temp3 = InFieldRate(MoreActiveField.Even).Even_B3_Individual;
+% B4
+temp4 = InFieldRate(MoreActiveField.Even).Even_B4_Individual;    
+clear temp
+temp=[temp1 temp2 temp3 temp4];
+
+figure; hold on; 
+title('Rat448-Main4-TT24-C1_p2.mat')
+p1=plot(temp,'.k-'); p1.MarkerSize=10;
+g=gca;
+l1=line([length(temp1)+0.5 length(temp1)+0.5], g.YLim); l1.Color='r'; l1.LineStyle='--';
+l1=line([length(temp1)+length(temp2)+0.5 length(temp1)+length(temp2)+0.5], g.YLim); l1.Color='r'; l1.LineStyle='--';
+l1=line(g.XLim, [max(temp) max(temp)]); l1.Color='b'; l1.LineStyle='-';
+l1=line(g.XLim, [max(temp)*0.2 max(temp)*0.2]); l1.Color='b'; l1.LineStyle='--';    
+
+%% Figure 4D
+% Cumulative, "ON" cell
+Timing_SS_iHP_Odd=[];
+for i=1:length(Timing.SS.iHP_Odd)
+        Timing_SS_iHP_Odd(end+1)=Timing.SS.iHP_Odd(i);
+end
+Timing_SSCR_iHP_Odd=[];
+for i=1:length(Timing.SSCR.iHP_Odd)
+        Timing_SSCR_iHP_Odd(end+1)=Timing.SSCR.iHP_Odd(i);
+end
+Timing_FLCR_iHP_Odd=[];
+for i=1:length(Timing.FLCR.iHP_Odd)
+        Timing_FLCR_iHP_Odd(end+1)=Timing.FLCR.iHP_Odd(i);
+end
+Timing_SSFL_iHP_Odd=[];
+for i=1:length(Timing.SSFL.iHP_Odd)
+        Timing_SSFL_iHP_Odd(end+1)=Timing.SSFL.iHP_Odd(i);
+end
+
+
+Timing_SS_iHP_Even=[];
+for i=1:length(Timing.SS.iHP_Even)
+        Timing_SS_iHP_Even(end+1)=Timing.SS.iHP_Even(i);
+end
+Timing_SSCR_iHP_Even=[];
+for i=1:length(Timing.SSCR.iHP_Even)
+        Timing_SSCR_iHP_Even(end+1)=Timing.SSCR.iHP_Even(i);
+end
+Timing_FLCR_iHP_Even=[];
+for i=1:length(Timing.FLCR.iHP_Even)
+        Timing_FLCR_iHP_Even(end+1)=Timing.FLCR.iHP_Even(i);
+end
+Timing_SSFL_iHP_Even=[];
+for i=1:length(Timing.SSFL.iHP_Even)
+        Timing_SSFL_iHP_Even(end+1)=Timing.SSFL.iHP_Even(i);
+end
+
+Timing_SS_dHP_Odd=[];
+for i=1:length(Timing.SS.dHP_Odd)
+        Timing_SS_dHP_Odd(end+1)=Timing.SS.dHP_Odd(i);
+end
+Timing_SSCR_dHP_Odd=[];
+for i=1:length(Timing.SSCR.dHP_Odd)
+        Timing_SSCR_dHP_Odd(end+1)=Timing.SSCR.dHP_Odd(i);
+end
+Timing_FLCR_dHP_Odd=[];
+for i=1:length(Timing.FLCR.dHP_Odd)
+        Timing_FLCR_dHP_Odd(end+1)=Timing.FLCR.dHP_Odd(i);
+end
+Timing_SSFL_dHP_Odd=[];
+for i=1:length(Timing.SSFL.dHP_Odd)
+        Timing_SSFL_dHP_Odd(end+1)=Timing.SSFL.dHP_Odd(i);
+end
+
+
+Timing_SS_dHP_Even=[];
+for i=1:length(Timing.SS.dHP_Even)
+        Timing_SS_dHP_Even(end+1)=Timing.SS.dHP_Even(i);
+end
+Timing_SSCR_dHP_Even=[];
+for i=1:length(Timing.SSCR.dHP_Even)
+        Timing_SSCR_dHP_Even(end+1)=Timing.SSCR.dHP_Even(i);
+end
+Timing_FLCR_dHP_Even=[];
+for i=1:length(Timing.FLCR.dHP_Even)
+        Timing_FLCR_dHP_Even(end+1)=Timing.FLCR.dHP_Even(i);
+end
+Timing_SSFL_dHP_Even=[];
+for i=1:length(Timing.SSFL.dHP_Even)
+        Timing_SSFL_dHP_Even(end+1)=Timing.SSFL.dHP_Even(i);
+end
+
+temp=30;
+iHP_Value=[Timing_SSCR_iHP_Odd(Timing_SSCR_iHP_Odd<=temp) Timing_SSCR_iHP_Even(Timing_SSCR_iHP_Even<=temp)...
+    Timing_FLCR_iHP_Odd(Timing_FLCR_iHP_Odd<=temp) Timing_FLCR_iHP_Even(Timing_FLCR_iHP_Even<=temp)];
+iHP_Same=[Timing_SS_iHP_Odd(Timing_SS_iHP_Odd<=temp) Timing_SS_iHP_Even(Timing_SS_iHP_Even<=temp) ...
+    Timing_SSFL_iHP_Odd(Timing_SSFL_iHP_Odd<=temp) Timing_SSFL_iHP_Even(Timing_SSFL_iHP_Even<=temp)];
+iHP_Same1=[Timing_SSFL_iHP_Odd(Timing_SSFL_iHP_Odd<=temp) Timing_SSFL_iHP_Even(Timing_SSFL_iHP_Even<=temp)];
+iHP_Same2=[Timing_SS_iHP_Odd(Timing_SS_iHP_Odd<=temp) Timing_SS_iHP_Even(Timing_SS_iHP_Even<=temp)];
+dHP_Value=[Timing_SSCR_dHP_Odd(Timing_SSCR_dHP_Odd<=temp) Timing_SSCR_dHP_Even(Timing_SSCR_dHP_Even<=temp)...
+    Timing_FLCR_dHP_Odd(Timing_FLCR_dHP_Odd<=temp) Timing_FLCR_dHP_Even(Timing_FLCR_dHP_Even<=temp)];
+dHP_Same=[Timing_SS_dHP_Odd(Timing_SS_dHP_Odd<=temp) Timing_SS_dHP_Even(Timing_SS_dHP_Even<=temp)... 
+    Timing_SSFL_dHP_Odd(Timing_SSFL_dHP_Odd<=temp) Timing_SSFL_dHP_Even(Timing_SSFL_dHP_Even<=temp)];
+dHP_Value(6)=[]; % remove minus value;
+
+% % Statistical testing
+[h,p, STAT]=chi2cont([11 28; 2 20; 1 20]);
+[h,p, STAT]=chi2cont([11 28; 2 20]);
+[h,p, STAT]=chi2cont([11 28; 1 20;]);
+
+figure; hold on;
+cdfplot(iHP_Value);
+cdfplot(iHP_Same);
+cdfplot(dHP_Value);
+cdfplot(dHP_Same);
+

Figure_5.m

@@ -0,0 +1,88 @@
+load('Figure5.mat')
+%% Figure 5D
+LearningTrial.B1_SS = LearningTrial.B1(:,1:2);
+LearningTrial.B2_SS = LearningTrial.B2(:,1:2);
+LearningTrial.B3_SS = LearningTrial.B3(:,1:2);
+LearningTrial.B4_SS = LearningTrial.B4(:,1:2);
+LearningTrial.B1_QQ = LearningTrial.B1(:,3:4);
+LearningTrial.B2_QQ = LearningTrial.B2(:,3:4);
+LearningTrial.B3_QQ = LearningTrial.B3(:,3:4);
+LearningTrial.B4_QQ = LearningTrial.B4(:,3:4);
+
+% SS
+y1=reshape(LearningTrial.B1_SS,1,12);
+y2=reshape(LearningTrial.B2_SS,1,12);
+y3=reshape(LearningTrial.B3_SS,1,12);
+
+y1=GetZeroToNaN(y1);
+y2=GetZeroToNaN(y2);
+y3=GetZeroToNaN(y3);
+y1(3)=NaN;y2(3)=NaN;y3(3)=NaN;
+figure; hold on;
+clear Color
+Color.color=2; Color.alpha=1;
+Jin_MeanSTE_Line(1,y1,Color);
+Jin_MeanSTE_Line(3,y2,Color);
+Jin_MeanSTE_Line(5,y3,Color);
+
+% QQ
+y1=reshape(LearningTrial.B1_QQ,1,12);
+y2=reshape(LearningTrial.B2_QQ,1,12);
+y3=reshape(LearningTrial.B3_QQ,1,12);
+y1(1)=NaN;y2(1)=NaN;y3(1)=NaN;
+y1=GetZeroToNaN(y1);
+y2=GetZeroToNaN(y2);
+y3=GetZeroToNaN(y3);
+
+% figure; 
+hold on;
+Color.color=1; Color.alpha=1;
+Jin_MeanSTE_Line(1,y1,Color);
+Jin_MeanSTE_Line(3,y2,Color);
+Jin_MeanSTE_Line(5,y3,Color);
+
+% % Statistical testing
+[B1_QQ.data, B1_QQ.index]=GetNaNToNull(LearningTrial.B1_QQ(:));
+[B2_QQ.data, B2_QQ.index]=GetNaNToNull(LearningTrial.B2_QQ(:));
+[B3_QQ.data, B3_QQ.index]=GetNaNToNull(LearningTrial.B3_QQ(:));
+[B1_SS.data, B1_SS.index]=GetNaNToNull(LearningTrial.B1_SS(:));
+[B2_SS.data, B2_SS.index]=GetNaNToNull(LearningTrial.B2_SS(:));
+[B3_SS.data, B3_SS.index]=GetNaNToNull(LearningTrial.B3_SS(:));
+
+[h,p,~,stat]=ttest2(B1_QQ.data,B1_SS.data)
+[h,p,~,stat]=ttest2(B2_QQ.data,B2_SS.data)
+[h,p,~,stat]=ttest2(B3_QQ.data,B3_SS.data)
+
+%% Figure 5E
+SSCH=[1 2 4 5 8 9 14 17 18 21 22];
+Quantity=[3 6 7 10 11 12 13 15 16 19 20];
+
+Latency.B1_SSCH=Latency.B1(SSCH);
+Latency.B1_Quantity=Latency.B1(Quantity);
+Latency.B2_SSCH=Latency.B2(SSCH);
+Latency.B2_Quantity=Latency.B2(Quantity);
+Latency.B3_SSCH=Latency.B3(SSCH);
+Latency.B3_Quantity=Latency.B3(Quantity);
+Latency.B4_SSCH=Latency.B4(SSCH);
+Latency.B4_Quantity=Latency.B4(Quantity);
+
+figure; hold on;
+Color.color=2; Color.alpha=1;
+Jin_MeanSTE_Line(1,Latency.B1_SSCH,Color);
+Jin_MeanSTE_Line(3,Latency.B2_SSCH,Color);
+Jin_MeanSTE_Line(5,Latency.B3_SSCH,Color);
+
+% figure; hold on;
+Color.color=1; Color.alpha=1;
+Jin_MeanSTE_Line(1,Latency.B1_Quantity,Color);
+Jin_MeanSTE_Line(3,Latency.B2_Quantity,Color);
+Jin_MeanSTE_Line(5,Latency.B3_Quantity,Color);
+ylim([0 3]);
+
+[h,p,~,~]=ttest2(Latency.B1,Latency.B2)
+[h,p,~,~]=ttest2(Latency.B1,Latency.B3)
+[h,p,~,~]=ttest2(Latency.B1,Latency.B4)
+[h,p,~,~]=ttest2(Latency.B2,Latency.B3)
+[h,p,~,~]=ttest2(Latency.B2,Latency.B4)
+[h,p,~,~]=ttest2(Latency.B3,Latency.B4)
+

Figure_6.m

@@ -0,0 +1,402 @@
+clear all
+load('Figure6.mat');
+%% Figure 6C
+% Blocks 1 vs 2 
+% % SS vs CR
+Corr_dHP_B12=ClusterInfo.Outbound_dHP_SpaCorr_B12((PlaceField_dHP_B1 & PlaceField_dHP_B3 & ChoiceFieldRatio_dHP_B13) | (PlaceField_dHP_B2 & PlaceField_dHP_B4 & ChoiceFieldRatio_dHP_B24) & Sunflower_dHP);
+Corr_iHP_B12=ClusterInfo.Outbound_iHP_SpaCorr_B12((PlaceField_iHP_B1 & PlaceField_iHP_B3 & ChoiceFieldRatio_iHP_B13) | (PlaceField_iHP_B2 & PlaceField_iHP_B4 & ChoiceFieldRatio_iHP_B24) & Sunflower_iHP);
+fig=figure; hold on;
+fig.Position=[0 0 500 500];
+cdfplot(Corr_dHP_B12);
+cdfplot(Corr_iHP_B12);   
+xlim([-0.6 1]);
+[p,~,stat]=ranksum(Corr_dHP_B12, Corr_iHP_B12);
+
+% % 4/4 SS vs 1/4 SS
+Corr_dHP_B12_qauntity=ClusterInfo.Outbound_dHP_SpaCorr_B12((PlaceField_dHP_B1 & PlaceField_dHP_B3 & ChoiceFieldRatio_dHP_B13) | (PlaceField_dHP_B2 & PlaceField_dHP_B4 & ChoiceFieldRatio_dHP_B24) & Quantity_dHP);
+Corr_iHP_B12_qauntity=ClusterInfo.Outbound_iHP_SpaCorr_B12((PlaceField_iHP_B1 & PlaceField_iHP_B3 & ChoiceFieldRatio_iHP_B13) | (PlaceField_iHP_B2 & PlaceField_iHP_B4 & ChoiceFieldRatio_iHP_B24) & Quantity_iHP);
+fig=figure; hold on; 
+fig.Position=[0 0 500 500];
+cdfplot(Corr_dHP_B12_qauntity);
+cdfplot(Corr_iHP_B12_qauntity);   
+xlim([-0.6 1]);
+[p,~,stat]=ranksum(Corr_dHP_B12_qauntity, Corr_iHP_B12_qauntity);
+
+%% Figure 6D
+% Blocks 1 vs 3 
+% % SS vs CR
+Corr_dHP_B13=ClusterInfo.Outbound_dHP_SpaCorr_B13((PlaceField_dHP_B1 | PlaceField_dHP_B3) & Sunflower_dHP);
+Corr_iHP_B13=ClusterInfo.Outbound_iHP_SpaCorr_B13((PlaceField_iHP_B1 | PlaceField_iHP_B3) & Sunflower_iHP);
+fig=figure; hold on; 
+fig.Position=[0 0 500 500];
+cdfplot(Corr_dHP_B13);
+cdfplot(Corr_iHP_B13);
+xlim([-0.6 1])
+% line([0.69 0.69], [0 1])
+[p,~,stat]=ranksum(Corr_dHP_B13, Corr_iHP_B13);
+
+% % 4/4 SS vs 1/4 SS
+Corr_dHP_B13_qauntity=ClusterInfo.Outbound_dHP_SpaCorr_B13(PlaceField_dHP_B1 | PlaceField_dHP_B3 & Quantity_dHP);
+Corr_iHP_B13_qauntity=ClusterInfo.Outbound_iHP_SpaCorr_B13(PlaceField_iHP_B1 | PlaceField_iHP_B3 & Quantity_iHP);
+fig=figure; hold on; 
+fig.Position=[0 0 500 500];
+cdfplot(Corr_dHP_B13_qauntity);
+cdfplot(Corr_iHP_B13_qauntity);   
+% line([0.69 0.69], [0 1])
+[p,~,stat]=ranksum(Corr_dHP_B13_qauntity, Corr_iHP_B13_qauntity);
+
+%% Figure 6E and 6F
+PeakRate=1;
+% Dorsal, B1_Post
+j=1; k=1;
+for session=1:4
+    Session.dHP=find(Indexing.dHP(session,:));
+    for i=1:length(Session.dHP)
+        iHP_B3_distance_High = PopulationMaximumBin.dHP_B1_Post(session,Session.dHP(i));
+        ratio = FieldCoverageRatio.dHP(session,Session.dHP(i));
+        [value] = max([iHP_B3_distance_High]);
+        if value > PeakRate && ratio < 0.25
+                    PopMatrix.dHP_B1_Post(j,:)=transpose(squeeze(PopulationLinearizedFiringRate.dHP_B1_Post(session,Session.dHP(i),:))/PopulationMaximumBin.dHP_B1_Post(session,Session.dHP(i)));
+                    PopMatrix.MaximumBin_dHP_B1_Post(j,:)=MaximumBin.dHP_B1_Post(session,Session.dHP(i),:);
+                    PopMatrix.dHP_B1_PostName{j,1}=CLSTname.dHP{session,Session.dHP(i)}; j=j+1;
+        end    
+    end
+end
+
+Temp=0;
+for i=1:size(PopMatrix.dHP_B1_Post,1)
+    temp=find(PopMatrix.dHP_B1_Post(i,:)==1);
+    if ~isempty(temp)
+        Temp(i)=temp(1);
+    else
+        Temp(i)=0;
+    end
+end
+[Sorted.dHP_B1_Post,SortedIndexing.dHP_B1_Post]=sort(Temp);
+PopMatrix.Sorted_dHP_B1_Post=PopMatrix.dHP_B1_Post(SortedIndexing.dHP_B1_Post,:);
+PopMatrix.Sorted_dHP_B1_Post_Name=PopMatrix.dHP_B1_PostName(SortedIndexing.dHP_B1_Post,1);
+PopMatrix.Sorted_dHP_B1_Post=PopMatrix.Sorted_dHP_B1_Post(4:end,:);
+% figure, Dorsal
+figure;
+imagesc(PopMatrix.Sorted_dHP_B1_Post)
+colormap('jet')
+g=gca; g.CLim=[0 1];g.YDir='normal';
+
+% Intermediate, B1_Post
+j=1; k=1;
+% clear PopMatrix Session
+for session=1:4
+    Session.iHP=find(Indexing.iHP(session,:));
+    for i=1:length(Session.iHP)
+        iHP_B3_distance_High = PopulationMaximumBin.iHP_B1_Post(session,Session.iHP(i));
+        ratio = FieldCoverageRatio.iHP(session,Session.iHP(i));
+        [value] = max([iHP_B3_distance_High]);
+        if (Depth.iHP(session,Session.iHP(i)) >= 2 && Depth.iHP(session,Session.iHP(i)) < 8) && value > PeakRate && ratio < 0.25
+            PopMatrix.iHP_B1_Post(j,:)=transpose(squeeze(PopulationLinearizedFiringRate.iHP_B1_Post(session,Session.iHP(i),:))/PopulationMaximumBin.iHP_B1_Post(session,Session.iHP(i)));
+            PopMatrix.MaximumBin_iHP_B1_Post(j,:)=MaximumBin.iHP_B1_Post(session,Session.iHP(i),:);
+            PopMatrix.iHP_B1_PostName{j,1}=CLSTname.iHP{session,Session.iHP(i)}; j=j+1;
+        end
+        
+    end
+end
+Temp=0;
+for i=1:size(PopMatrix.iHP_B1_Post,1)
+    temp=find(PopMatrix.iHP_B1_Post(i,:)==1);
+    if ~isempty(temp)
+        Temp(i)=temp(1);
+    else
+        Temp(i)=0;
+    end
+end
+[Sorted.iHP_B1_Post,SortedIndexing.iHP_B1_Post]=sort(Temp);
+PopMatrix.Sorted_iHP_B1_Post=PopMatrix.iHP_B1_Post(SortedIndexing.iHP_B1_Post,:);
+PopMatrix.Sorted_iHP_B1_Post_Name=PopMatrix.iHP_B1_PostName(SortedIndexing.iHP_B1_Post,1);
+PopMatrix.Sorted_iHP_B1_Post=PopMatrix.Sorted_iHP_B1_Post(4:end,:);
+% figure, Dorsal
+figure;
+imagesc(PopMatrix.Sorted_iHP_B1_Post)
+colormap('jet')
+g=gca; g.CLim=[0 1];g.YDir='normal';
+
+% Dorsal, B3_Post
+j=1; k=1;
+for session=1:4
+    Session.dHP=find(Indexing.dHP(session,:));
+    for i=1:length(Session.dHP)
+        iHP_B3_distance_High = PopulationMaximumBin.dHP_B3_Post(session,Session.dHP(i));
+        ratio = FieldCoverageRatio.dHP(session,Session.dHP(i));
+        [value] = max([iHP_B3_distance_High]);
+        if value > PeakRate && ratio < 0.25         
+                    PopMatrix.dHP_B3_Post(j,:)=transpose(squeeze(PopulationLinearizedFiringRate.dHP_B3_Post(session,Session.dHP(i),:))/PopulationMaximumBin.dHP_B3_Post(session,Session.dHP(i)));
+                    PopMatrix.MaximumBin_dHP_B3_Post(j,:)=MaximumBin.dHP_B3_Post(session,Session.dHP(i),:);
+                    PopMatrix.dHP_B3_PostName{j,1}=CLSTname.dHP{session,Session.dHP(i)}; j=j+1;
+        end
+        
+    end
+end
+
+Temp=0;
+for i=1:size(PopMatrix.dHP_B3_Post,1)
+    temp=find(PopMatrix.dHP_B3_Post(i,:)==1);
+    if ~isempty(temp)
+        Temp(i)=temp(1);
+    else
+        Temp(i)=0;
+    end
+end
+[Sorted.dHP_B3_Post,SortedIndexing.dHP_B3_Post]=sort(Temp);
+PopMatrix.Sorted_dHP_B3_Post=PopMatrix.dHP_B3_Post(SortedIndexing.dHP_B3_Post,:);
+PopMatrix.Sorted_dHP_B3_Post_Name=PopMatrix.dHP_B3_PostName(SortedIndexing.dHP_B3_Post,1);
+PopMatrix.Sorted_dHP_B3_Post=PopMatrix.Sorted_dHP_B3_Post(5:end,:);
+% figure
+figure;
+imagesc(GetSwap(PopMatrix.Sorted_dHP_B3_Post))
+colormap('jet')
+g=gca; g.CLim=[0 1];
+
+% Intermediate, B3_Post
+j=1; k=1;
+% clear PopMatrix Session
+for session=1:4
+    Session.iHP=find(Indexing.iHP(session,:));
+    for i=1:length(Session.iHP)
+        iHP_B3_distance_High = PopulationMaximumBin.iHP_B3_Post(session,Session.iHP(i));
+        ratio = FieldCoverageRatio.iHP(session,Session.iHP(i));
+        [value] = max([iHP_B3_distance_High]);
+        if (Depth.iHP(session,Session.iHP(i)) >= 2 && Depth.iHP(session,Session.iHP(i)) < 8) && value > PeakRate && ratio < 0.25
+            PopMatrix.iHP_B3_Post(j,:)=transpose(squeeze(PopulationLinearizedFiringRate.iHP_B3_Post(session,Session.iHP(i),:))/PopulationMaximumBin.iHP_B3_Post(session,Session.iHP(i)));
+            PopMatrix.MaximumBin_iHP_B3_Post(j,:)=MaximumBin.iHP_B3_Post(session,Session.iHP(i),:);
+            PopMatrix.iHP_B3_PostName{j,1}=CLSTname.iHP{session,Session.iHP(i)}; j=j+1;
+        end
+        
+    end
+end
+Temp=0;
+for i=1:size(PopMatrix.iHP_B3_Post,1)
+    temp=find(PopMatrix.iHP_B3_Post(i,:)==1);
+    if ~isempty(temp)
+        Temp(i)=temp(1);
+    else
+        Temp(i)=0;
+    end
+end
+[Sorted.iHP_B3_Post,SortedIndexing.iHP_B3_Post]=sort(Temp);
+PopMatrix.Sorted_iHP_B3_Post=PopMatrix.iHP_B3_Post(SortedIndexing.iHP_B3_Post,:);
+PopMatrix.Sorted_iHP_B3_Post_Name=PopMatrix.iHP_B3_PostName(SortedIndexing.iHP_B3_Post,1);
+PopMatrix.Sorted_iHP_B3_Post=PopMatrix.Sorted_iHP_B3_Post(6:end,:);
+% figure, 
+figure;
+imagesc(GetSwap(PopMatrix.Sorted_iHP_B3_Post))
+colormap('jet')
+g=gca; g.CLim=[0 1];
+
+%% Figure 6G
+dHP_b1=[2 2 3 3 3 3 3 4 4 4 5 5 5 5 5 5 6 6 6 7 7 8 8 10 10 11 11 11 11 12 12 14 16 16 16 17 17 18 20 20 21 22 23 23 23 25 26 28 30 30 30 31 33 34 34 35 36 36 37 38 38 40 41 42 43 45 45 45 45 46 46 46 47 47 47 48 49 49 50 50 51 51 52 52 52 53 53 54 55 55 55 56 56 ]
+iHP_b1=[1 2 2 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 8 8 8 8 10 11 11 11 11 11 11 11 12 12 15 15 15 16 17 17 18 18 21 23 23 24 26 33 33 33 34 36 37 38 38 38 39 40 40 40 41 41 42 43 43 44 45 46 46 47 47 47 48 49 49 49 49 49 49 49 50 50 51 51 51 52 52 52 52 52 53 53 53 53 53 53 54 54 54 55 55 56 56 56];
+dHP_b3=[1 1 2 2 2 2 3 3 3 3 3 3 3 4 4 5 6 6 6 6 7 7 7 8 8 8 8 9 9 9 10 10 12 12 13 13 13 13 14 14 15 15 16 16 17 17 17 17  18 19 20 20 23 26 33 34 34 35 35 36 37 37 38 39 40 41 42 42 42 42 43 43 44 44 45 45 45 45 46 46 47 49 50 50 50 50 50 51 51 52 53 53 53 53 53 53 53 54 55 55 55 55 56 56];
+iHP_b3=[2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 6 6 6 7 7 7 7 7 8 8 9 10 10 11 11 11 11 11 12 12 12 12 13 13 13 13 13 14 14 15 15 16 22 22 27 30 31 31 32 32 33 35 35 35 36 36 36 37 38 38 39 39 40 41 41 41 42 42 43 44 44 44 44 44 45 46 46 47 47 47 47 47 47 47 47 47 50 50 50 50 51 51 51 52 52 52 52 52 52 53 53 53 53 53 55 55 55 55 56];
+dHP_b3_rev=flip(57-dHP_b3)
+iHP_b3_rev=flip(57-iHP_b3)
+
+% % Histogram
+dHP_B1=sum(PopMatrix.Sorted_dHP_B1_Post==1)/sum(sum(PopMatrix.Sorted_dHP_B1_Post==1))
+dHP_B3=flip(sum(PopMatrix.Sorted_dHP_B3_Post==1)/sum(sum(PopMatrix.Sorted_dHP_B3_Post==1)))
+iHP_B1=sum(PopMatrix.Sorted_iHP_B1_Post==1)/sum(sum(PopMatrix.Sorted_iHP_B1_Post==1))
+iHP_B3=flip(sum(PopMatrix.Sorted_iHP_B3_Post==1)/sum(sum(PopMatrix.Sorted_iHP_B3_Post==1)))
+
+% %
+PopMatrix.Sorted_dHP_B1_Post = [PopMatrix.Sorted_dHP_B1_Post(:,1:25) PopMatrix.Sorted_dHP_B1_Post(:,32:end)]; % 1:47 / 53:end
+PopMatrix.Sorted_iHP_B1_Post = [PopMatrix.Sorted_iHP_B1_Post(:,1:25) PopMatrix.Sorted_iHP_B1_Post(:,32:end)]; % 1:62
+dHP_B1_high = PopMatrix.Sorted_dHP_B1_Post(1:46,1:25)
+dHP_B1_low = PopMatrix.Sorted_dHP_B1_Post(53:end,26:50)
+iHP_B1_high = PopMatrix.Sorted_iHP_B1_Post(1:61,1:25)
+iHP_B1_low = PopMatrix.Sorted_iHP_B1_Post(63:end,26:50)
+
+PopMatrix.Sorted_dHP_B3_Post = [PopMatrix.Sorted_dHP_B3_Post(:,1:25) PopMatrix.Sorted_dHP_B3_Post(:,32:end)]; % 1:47 / 53:end
+PopMatrix.Sorted_iHP_B3_Post = [PopMatrix.Sorted_iHP_B3_Post(:,1:25) PopMatrix.Sorted_iHP_B3_Post(:,32:end)]; % 1:62
+dHP_B3_high = PopMatrix.Sorted_dHP_B3_Post(1:53,1:25)
+dHP_B3_low = PopMatrix.Sorted_dHP_B3_Post(55:end,26:50)
+iHP_B3_high = PopMatrix.Sorted_iHP_B3_Post(1:67,1:25)
+iHP_B3_low = PopMatrix.Sorted_iHP_B3_Post(69:end,26:50)
+
+
+
+j=1;
+for i=1:2:56
+    dHP_B1_2(j)=dHP_B1(i)+dHP_B1(i+1); j=j+1;
+end
+j=1;
+for i=1:2:56
+    dHP_B3_2(j)=dHP_B3(i)+dHP_B3(i+1); j=j+1;
+end
+j=1;
+for i=1:2:56
+    iHP_B1_2(j)=iHP_B1(i)+iHP_B1(i+1); j=j+1;
+end
+j=1;
+for i=1:2:56
+    iHP_B3_2(j)=iHP_B3(i)+iHP_B3(i+1); j=j+1;
+end
+% dHP figure;
+figure; hold on;
+b1=bar(dHP_B1); b1.FaceColor='r'; b1.FaceAlpha = 0.3; b1.EdgeColor=[1 1 1]; b1.EdgeAlpha=0;
+b2=bar(dHP_B3); b2.FaceColor='b'; b2.FaceAlpha = 0.3; b2.EdgeColor=[1 1 1]; b2.EdgeAlpha=0;
+ylim([0 0.12]); g=gca; g.YTick=0:0.04:0.12;
+
+% iHP figure;
+figure; hold on;
+b1=bar(iHP_B1); b1.FaceColor='r'; b1.FaceAlpha = 0.3; b1.EdgeColor=[1 1 1]; b1.EdgeAlpha=0;
+b2=bar(iHP_B3); b2.FaceColor='b'; b2.FaceAlpha = 0.3; b2.EdgeColor=[1 1 1]; b2.EdgeAlpha=0;
+ylim([0 0.12]); g=gca; g.YTick=0:0.04:0.12;
+
+% Statistical testing
+[h,p,stat]=kstest2(dHP_b3_rev, dHP_b1)
+[h,p,stat]=kstest2(iHP_b3_rev, iHP_b1)
+
+%% Figure 6H
+zone=4;
+for i=1:size(dHP_B1_high,1)
+    for j=1:1:size(dHP_B1_high,2)
+        if dHP_B1_high(i,j)==1
+            dHP_B1_high_index(i)=j;
+        end
+    end
+end
+for i=1:size(dHP_B1_low,1)
+    for j=1:1:size(dHP_B1_low,2)
+        if dHP_B1_low(i,j)==1
+            dHP_B1_low_index(i)=j;
+        end
+    end
+end
+prop.dHP_B1_high(zone)=length(find(dHP_B1_high_index<=zone))/length(dHP_B1_high_index);
+prop.dHP_B1_low(zone)=length(find(dHP_B1_low_index>25-zone))/length(dHP_B1_low_index);
+
+for i=1:size(dHP_B3_high,1)
+    for j=1:1:size(dHP_B3_high,2)
+        if dHP_B3_high(i,j)==1
+            dHP_B3_high_index(i)=j;
+        end
+    end
+end
+for i=1:size(dHP_B3_low,1)
+    for j=1:1:size(dHP_B3_low,2)
+        if dHP_B3_low(i,j)==1
+            dHP_B3_low_index(i)=j;
+        end
+    end
+end
+prop.dHP_B3_high(zone)=length(find(dHP_B3_high_index<=zone))/length(dHP_B3_high_index);
+prop.dHP_B3_low(zone)=length(find(dHP_B3_low_index>25-zone))/length(dHP_B3_low_index);
+
+for i=1:size(iHP_B1_high,1)
+    for j=1:1:size(iHP_B1_high,2)
+        if iHP_B1_high(i,j)==1
+            iHP_B1_high_index(i)=j;
+        end
+    end
+end
+for i=1:size(iHP_B1_low,1)
+    for j=1:1:size(iHP_B1_low,2)
+        if iHP_B1_low(i,j)==1
+            iHP_B1_low_index(i)=j;
+        end
+    end
+end
+prop.iHP_B1_high(zone)=length(find(iHP_B1_high_index<=zone))/length(iHP_B1_high_index);
+prop.iHP_B1_low(zone)=length(find(iHP_B1_low_index>25-zone))/length(iHP_B1_low_index);
+
+for i=1:size(iHP_B3_high,1)
+    for j=1:1:size(iHP_B3_high,2)
+        if iHP_B3_high(i,j)==1
+            iHP_B3_high_index(i)=j;
+        end
+    end
+end
+for i=1:size(iHP_B3_low,1)
+    for j=1:1:size(iHP_B3_low,2)
+        if iHP_B3_low(i,j)==1
+            iHP_B3_low_index(i)=j;
+        end
+    end
+end
+prop.iHP_B3_high(zone)=length(find(iHP_B3_high_index<=zone))/length(iHP_B3_high_index);
+prop.iHP_B3_low(zone)=length(find(iHP_B3_low_index>25-zone))/length(iHP_B3_low_index);
+
+% figure
+zone=4;
+figure; hold on;
+plot(1:2, [prop.dHP_B1_low(zone) prop.dHP_B1_high(zone)],'ro-');
+plot(1:2, [prop.iHP_B1_low(zone) prop.iHP_B1_high(zone)],'bo-');
+plot(3:4, [prop.dHP_B3_low(zone) prop.dHP_B3_high(zone)],'ro-');
+plot(3:4, [prop.iHP_B3_low(zone) prop.iHP_B3_high(zone)],'bo-');
+ylim([0 0.5])
+xlim([0.5 4.5])
+
+
+%% Figure 6I
+% % Field width
+THRE=0.5;
+dHP_B3_high_field=dHP_B3_high>THRE;
+m=0;
+for i=1:size(dHP_B3_high,1)
+    for j=size(dHP_B3_high,2):-1:1
+        if dHP_B3_high_field(i,j)==1
+            m=m+1;
+        end
+    end
+    dHP_B3_high_size(i)=m;
+    m=0;
+end
+mean(dHP_B3_high_size)
+
+dHP_B3_low_field=dHP_B3_low>THRE;
+m=0;
+for i=1:size(dHP_B3_low,1)
+    for j=size(dHP_B3_low,2):-1:1
+        if dHP_B3_low_field(i,j)==1
+            m=m+1;
+        end
+    end
+    dHP_B3_low_size(i)=m;
+    m=0;
+end
+mean(dHP_B3_low_size)
+
+iHP_B3_high_field=iHP_B3_high>THRE;
+m=0;
+for i=1:size(iHP_B3_high,1)
+    for j=size(iHP_B3_high,2):-1:1
+        if iHP_B3_high_field(i,j)==1
+            m=m+1;
+        end
+    end
+    iHP_B3_high_size(i)=m;
+    m=0;
+end
+mean(iHP_B3_high_size)
+[p1,p]=ranksum((iHP_B3_high_size), (dHP_B3_high_size))
+
+iHP_B3_low_field=iHP_B3_low>THRE;
+m=0;
+for i=1:size(iHP_B3_low,1)
+    for j=size(iHP_B3_low,2):-1:1
+        if iHP_B3_low_field(i,j)==1
+            m=m+1;
+        end
+    end
+    iHP_B3_low_size(i)=m;
+    m=0;
+end
+mean(iHP_B3_low_size)
+
+% figure
+figure; hold on;
+Jin_MeanSTE_Line(6,dHP_B3_high_size)
+Jin_MeanSTE_Line(7,dHP_B3_low_size)
+Jin_MeanSTE_Line(8,iHP_B3_high_size)
+Jin_MeanSTE_Line(9,iHP_B3_low_size)
+
+% statistical testing
+[h,p, ~, T]=ttest2(dHP_B3_high_size, dHP_B3_low_size)
+[h,p, ~, T]=ttest2(iHP_B3_high_size, iHP_B3_low_size)

Figure_7.m

@@ -0,0 +1,430 @@
+%% Figure 7B to 7G
+clear all
+load('Figure7.mat')
+%
+window=7;
+alpha=1.75;
+smooth=1;
+FR_Thre=0.1;
+variance=80;
+mode = 2;
+gaussFilt = gausswin(window,alpha);
+clear gaussFilter
+% gaussFilter = gaussFilter / sum(gaussFilter);
+for i=1:(window+1)/2
+    gaussFilter(:,i)= gaussFilt / sum(gaussFilt((window+1)/2+1-i:window));
+end
+colorMap = parula(256);
+
+% LearningTrial.r463_B3_Day1_SS
+B1=length(Prob_v2.B1_WinBugs);
+B2=length(Prob_v2.B2_WinBugs);
+B3=length(Prob_v2.B3_WinBugs);
+B4=length(Prob_v2.B4_WinBugs);
+
+for i=1:length(Prob_v2.B3_WinBugs)
+    LearningLearningCurve.r463_Day1(i+B1+B2)=Prob_v2.B3_WinBugs(i,3);
+end
+for i=1:length(Prob_v2.B4_WinBugs)
+    LearningLearningCurve.r463_Day1(i+B1+B2+B3)=Prob_v2.B4_WinBugs(i,3);
+end
+
+LearningTrial.r463_B1_Day1=TrialInformation_v2.LearningTrial_B1;
+LearningTrial.r463_B2_Day1=TrialInformation_v2.LearningTrial_B2;
+LearningTrial.r463_B3_Day1=TrialInformation_v2.LearningTrial_B3;
+LearningTrial.r463_B4_Day1=TrialInformation_v2.LearningTrial_B4;
+% LearningTrial.r463_B3_Day1=36;
+clear Index
+[~,Index.r463_Day1]=sort(TrialInformation_v2.B3_SSCH);
+j=1; k=1;
+for i=1:length(Index.r463_Day1)
+    if sum(TrialInformation_v2.B3_SSCH(i) == TrialInformation_v2.B3_SS)
+        LearningCurve.r463_B3_Day1_WinBugs_SS(j)=Prob_v2.B3_WinBugs(i,3);
+        Index.r463_Day1_SS(j)=i; j=j+1;
+    else
+        LearningCurve.r463_B3_Day1_WinBugs_CR(k)=Prob_v2.B3_WinBugs(i,3);
+        Index.r463_Day1_CR(k)=i; k=k+1;
+    end
+    if Index.r463_Day1(i) == LearningTrial.r463_B3_Day1
+        LearningTrial.r463_B3_Day1_SS = j-1;
+        LearningTrial.r463_B3_Day1_CR = k-1;
+    end
+end
+% %%%%%%%%%%%%%%%%%%% All trial
+[Tar.r463_Day1_dHP, Tar.r463_Day1_dHP_Name]=GetAvailablePCAUnit(PCA.r463_Day1_dHP_MeanFiringRate_B3(Index.r463_Day1,:),FR_Thre,PCA.r463_Day1_dHP_Name);
+[Tar.r463_Day1_iHP, Tar.r463_Day1_iHP_Name]=GetAvailablePCAUnit(PCA.r463_Day1_iHP_MeanFiringRate_B3(Index.r463_Day1,:),FR_Thre,PCA.r463_Day1_iHP_Name);
+
+j=1;
+for i=1:size(Tar.r463_Day1_dHP,2)
+    if ~sum(isnan(Tar.r463_Day1_dHP(:,i)))
+        Target.r463_Day1_dHP(:,j)=Tar.r463_Day1_dHP(:,i);
+        Target.r463_Day1_dHP_Name{j,1}=Tar.r463_Day1_dHP_Name{i}; j=j+1;
+    end
+end
+j=1;
+for i=1:size(Tar.r463_Day1_iHP,2)
+    if ~sum(isnan(Tar.r463_Day1_iHP(:,i)))
+        Target.r463_Day1_iHP(:,j)=Tar.r463_Day1_iHP(:,i);
+        Target.r463_Day1_iHP_Name{j,1}=Tar.r463_Day1_iHP_Name{i}; j=j+1;
+    end
+end
+
+Average.r463_Day1_dHP=mean(Tar.r463_Day1_dHP);
+Average.r463_Day1_iHP=mean(Tar.r463_Day1_iHP);
+Normalized.r463_Day1_dHP=zscore(Target.r463_Day1_dHP(:,:));
+Normalized.r463_Day1_iHP=zscore(Target.r463_Day1_iHP(:,:));
+
+% %%%%%%%%%%%%%%%%%%%%%% All trial
+[w.r463_Day1_dHP, PC.r463_Day1_dHP,~,~,Variance.r463_Day1_dHP] = pca(zscore(Target.r463_Day1_dHP(:,:)));
+[w.r463_Day1_iHP, PC.r463_Day1_iHP,~,~,Variance.r463_Day1_iHP] = pca(zscore(Target.r463_Day1_iHP(:,:)));
+
+PC.r463_Day1_dHP_SS = PC.r463_Day1_dHP(Index.r463_Day1_SS,:);
+PC.r463_Day1_dHP_CR = PC.r463_Day1_dHP(Index.r463_Day1_CR,:);
+PC.r463_Day1_iHP_SS = PC.r463_Day1_iHP(Index.r463_Day1_SS,:);
+PC.r463_Day1_iHP_CR = PC.r463_Day1_iHP(Index.r463_Day1_CR,:);
+
+for i=1:length(Variance.r463_Day1_dHP)
+    if sum(Variance.r463_Day1_dHP(1:i)) > variance
+        Dimension.r463_Day1_dHP=i;
+        break;
+    end
+end
+for i=1:length(Variance.r463_Day1_iHP)
+    if sum(Variance.r463_Day1_iHP(1:i)) > variance
+        Dimension.r463_Day1_iHP=i;
+        break;
+    end
+end
+
+% figure
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+PC.r463_Day1_dHP_GaussFiltered = GetPC_GaussianFiltering(PC.r463_Day1_dHP, window, gaussFilter);
+PC.r463_Day1_iHP_GaussFiltered = GetPC_GaussianFiltering(PC.r463_Day1_iHP, window, gaussFilter);
+PC.r463_Day1_dHP_SS_GaussFiltered = GetPC_GaussianFiltering(PC.r463_Day1_dHP(Index.r463_Day1_SS,:), window, gaussFilter);
+PC.r463_Day1_dHP_CR_GaussFiltered = GetPC_GaussianFiltering(PC.r463_Day1_dHP(Index.r463_Day1_CR,:), window, gaussFilter);
+PC.r463_Day1_iHP_SS_GaussFiltered = GetPC_GaussianFiltering(PC.r463_Day1_iHP(Index.r463_Day1_SS,:), window, gaussFilter);
+PC.r463_Day1_iHP_CR_GaussFiltered = GetPC_GaussianFiltering(PC.r463_Day1_iHP(Index.r463_Day1_CR,:), window, gaussFilter);
+
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+LearnedState.r463_Day1_dHP_SS_GaussFiltered=mean(PC.r463_Day1_dHP_SS_GaussFiltered(LearningTrial.r463_B3_Day1_SS:length(Index.r463_Day1_SS),1:Dimension.r463_Day1_dHP),1);
+LearnedState.r463_Day1_iHP_SS_GaussFiltered=mean(PC.r463_Day1_iHP_SS_GaussFiltered(LearningTrial.r463_B3_Day1_SS:length(Index.r463_Day1_SS),1:Dimension.r463_Day1_iHP),1);
+for i=1:size(PC.r463_Day1_dHP_SS_GaussFiltered,1)
+    x=PC.r463_Day1_dHP_SS_GaussFiltered(i,1:Dimension.r463_Day1_dHP);
+    y=LearnedState.r463_Day1_dHP_SS_GaussFiltered;
+    z=Variance.r463_Day1_dHP(1:Dimension.r463_Day1_dHP);
+    EUdist.r463_Day1_dHP_SS_Weighted_GaussFiltered(i,:)=GetWeightedEuclideanDistance(x,y,z);
+    EUdist.r463_Day1_dHP_SS_GaussFiltered(i,:)=pdist2(x,y);
+end
+
+for i=1:size(PC.r463_Day1_iHP_SS_GaussFiltered,1)
+    x=PC.r463_Day1_iHP_SS_GaussFiltered(i,1:Dimension.r463_Day1_iHP);
+    y=LearnedState.r463_Day1_iHP_SS_GaussFiltered;
+    z=Variance.r463_Day1_iHP(1:Dimension.r463_Day1_iHP);
+    EUdist.r463_Day1_iHP_SS_Weighted_GaussFiltered(i,:)=GetWeightedEuclideanDistance(x,y,z);
+    EUdist.r463_Day1_iHP_SS_GaussFiltered(i,:)=pdist2(x,y);
+end
+
+LearnedState.r463_Day1_dHP_CR_GaussFiltered=mean(PC.r463_Day1_dHP_CR_GaussFiltered(LearningTrial.r463_B3_Day1_CR:length(Index.r463_Day1_CR),1:Dimension.r463_Day1_dHP),1);
+LearnedState.r463_Day1_iHP_CR_GaussFiltered=mean(PC.r463_Day1_iHP_CR_GaussFiltered(LearningTrial.r463_B3_Day1_CR:length(Index.r463_Day1_CR),1:Dimension.r463_Day1_iHP),1);
+for i=1:size(PC.r463_Day1_dHP_CR_GaussFiltered,1)
+    x=PC.r463_Day1_dHP_CR_GaussFiltered(i,1:Dimension.r463_Day1_dHP);
+    y=LearnedState.r463_Day1_dHP_CR_GaussFiltered;
+    z=Variance.r463_Day1_dHP(1:Dimension.r463_Day1_dHP);
+    EUdist.r463_Day1_dHP_CR_Weighted_GaussFiltered(i,:)=GetWeightedEuclideanDistance(x,y,z);
+    EUdist.r463_Day1_dHP_CR_GaussFiltered(i,:)=pdist2(x,y);
+end
+
+for i=1:size(PC.r463_Day1_iHP_CR_GaussFiltered,1)
+    x=PC.r463_Day1_iHP_CR_GaussFiltered(i,1:Dimension.r463_Day1_iHP);
+    y=LearnedState.r463_Day1_iHP_CR_GaussFiltered;
+    z=Variance.r463_Day1_iHP(1:Dimension.r463_Day1_iHP);
+    EUdist.r463_Day1_iHP_CR_Weighted_GaussFiltered(i,:)=GetWeightedEuclideanDistance(x,y,z);
+    EUdist.r463_Day1_iHP_CR_GaussFiltered(i,:)=pdist2(x,y);
+end
+
+% %%%%%%%%%%%%%%%%%%%%%
+fig=figure; fig.Position=[0 0 2000 1000];
+if Dimension.r463_Day1_dHP > 2
+    sheetTitle = subplot('Position', [0.05 0.5 0.2 0.4]); hold on;
+    p0=plot3(PC.r463_Day1_dHP_SS_GaussFiltered(:,1),PC.r463_Day1_dHP_SS_GaussFiltered(:,2),PC.r463_Day1_dHP_SS_GaussFiltered(:,3),'k--'); p0.LineWidth=0.5; p0.MarkerSize=5;
+    scale=floor(256/size(PC.r463_Day1_dHP_SS_GaussFiltered,1));
+    for i=1:size(PC.r463_Day1_dHP_SS_GaussFiltered,1)
+        p3=plot3(PC.r463_Day1_dHP_SS_GaussFiltered(i,1),PC.r463_Day1_dHP_SS_GaussFiltered(i,2),PC.r463_Day1_dHP_SS_GaussFiltered(i,3),'.'); p3.MarkerSize=40;
+        p3.Color=colorMap(256-scale*(i-1),:);
+    end
+    p1=plot3(LearnedState.r463_Day1_dHP_SS_GaussFiltered(1),LearnedState.r463_Day1_dHP_SS_GaussFiltered(2),LearnedState.r463_Day1_dHP_SS_GaussFiltered(3),'.'); p1.Color=[0.5 0.5 0.5]; p1.MarkerSize=50;
+    grid on
+    g=gca; g.FontSize=12;
+    xlabel('PC1'); ylabel('PC2'); zlabel('PC3');
+    title('r463-Day1, B3, dHP, SS');
+    % CR
+    sheetTitle = subplot('Position', [0.3 0.5 0.2 0.4]); hold on;
+    p0=plot3(PC.r463_Day1_dHP_CR_GaussFiltered(:,1),PC.r463_Day1_dHP_CR_GaussFiltered(:,2),PC.r463_Day1_dHP_CR_GaussFiltered(:,3),'k--'); p0.LineWidth=0.5; p0.MarkerSize=5;
+    scale=floor(256/size(PC.r463_Day1_dHP_CR_GaussFiltered,1));
+    for i=1:size(PC.r463_Day1_dHP_CR_GaussFiltered,1)
+        p3=plot3(PC.r463_Day1_dHP_CR_GaussFiltered(i,1),PC.r463_Day1_dHP_CR_GaussFiltered(i,2),PC.r463_Day1_dHP_CR_GaussFiltered(i,3),'.'); p3.MarkerSize=40;
+        p3.Color=colorMap(256-scale*(i-1),:);
+    end
+    p1=plot3(LearnedState.r463_Day1_dHP_CR_GaussFiltered(1),LearnedState.r463_Day1_dHP_CR_GaussFiltered(2),LearnedState.r463_Day1_dHP_CR_GaussFiltered(3),'.'); p1.Color=[0.5 0.5 0.5]; p1.MarkerSize=50;
+    grid on
+    g=gca; g.FontSize=12;
+    xlabel('PC1'); ylabel('PC2'); zlabel('PC3');
+    title('r463-Day1, B3, dHP, CR');
+end
+% iHP, SS
+sheetTitle = subplot('Position', [0.55 0.5 0.2 0.4]); hold on;
+p0=plot3(PC.r463_Day1_iHP_SS_GaussFiltered(:,1),PC.r463_Day1_iHP_SS_GaussFiltered(:,2),PC.r463_Day1_iHP_SS_GaussFiltered(:,3),'k--'); p0.LineWidth=0.5; p0.MarkerSize=5;
+scale=floor(256/size(PC.r463_Day1_iHP_SS_GaussFiltered,1));
+for i=1:size(PC.r463_Day1_iHP_SS_GaussFiltered,1)
+    p3=plot3(PC.r463_Day1_iHP_SS_GaussFiltered(i,1),PC.r463_Day1_iHP_SS_GaussFiltered(i,2),PC.r463_Day1_iHP_SS_GaussFiltered(i,3),'.'); p3.MarkerSize=40;
+    p3.Color=colorMap(256-scale*(i-1),:);
+end
+p1=plot3(LearnedState.r463_Day1_iHP_SS_GaussFiltered(1),LearnedState.r463_Day1_iHP_SS_GaussFiltered(2),LearnedState.r463_Day1_iHP_SS_GaussFiltered(3),'.'); p1.Color=[0.5 0.5 0.5]; p1.MarkerSize=50;
+grid on
+g=gca; g.FontSize=12;
+xlabel('PC1'); ylabel('PC2'); zlabel('PC3');
+title('r463-Day1, B3, iHP, SS');
+% CR
+sheetTitle = subplot('Position', [0.8 0.5 0.2 0.4]); hold on;
+p0=plot3(PC.r463_Day1_iHP_CR_GaussFiltered(:,1),PC.r463_Day1_iHP_CR_GaussFiltered(:,2),PC.r463_Day1_iHP_CR_GaussFiltered(:,3),'k--'); p0.LineWidth=0.5; p0.MarkerSize=5;
+scale=floor(256/size(PC.r463_Day1_iHP_CR_GaussFiltered,1));
+for i=1:size(PC.r463_Day1_iHP_CR_GaussFiltered,1)
+    p3=plot3(PC.r463_Day1_iHP_CR_GaussFiltered(i,1),PC.r463_Day1_iHP_CR_GaussFiltered(i,2),PC.r463_Day1_iHP_CR_GaussFiltered(i,3),'.'); p3.MarkerSize=40;
+    p3.Color=colorMap(256-scale*(i-1),:);
+end
+p1=plot3(LearnedState.r463_Day1_iHP_CR_GaussFiltered(1),LearnedState.r463_Day1_iHP_CR_GaussFiltered(2),LearnedState.r463_Day1_iHP_CR_GaussFiltered(3),'.'); p1.Color=[0.5 0.5 0.5]; p1.MarkerSize=50;
+grid on
+g=gca; g.FontSize=12;
+xlabel('PC1'); ylabel('PC2'); zlabel('PC3');
+title('r463-Day1, B3, iHP, CR');
+
+% SS- distance
+sheetTitle = subplot('Position', [0.1 0.1 0.3 0.3]); hold on;
+if Dimension.r463_Day1_dHP > 2
+    DHP=EUdist.r463_Day1_dHP_SS_Weighted_GaussFiltered;
+    DHP=DHP/max(DHP);
+    p1=plot(1:length(DHP),DHP(1:end),'r.-'); p1(1,1).MarkerSize=20; p1(1,1).LineWidth=1.5;
+    xlim([1 length(DHP)]);
+end
+hold on;
+VHP=EUdist.r463_Day1_iHP_SS_Weighted_GaussFiltered;
+VHP=VHP/max(VHP);
+p2=plot(1:length(VHP),VHP(1:end),'b.-'); p2(1,1).MarkerSize=20; p2(1,1).LineWidth=1.5;
+ylabel('SS-chosen trial');
+legend([p1,p2],'dHP','ivHP')
+%
+yyaxis right
+p3=plot(LearningCurve.r463_B3_Day1_WinBugs_SS,'k-'); p3(1,1).MarkerSize=20; p3(1,1).LineWidth=1.5;
+g=gca; g.YDir='rev';
+g.FontSize=12;
+%         g.YLim=[0.39 1]
+l1=legend([p1 p2], 'Dorsal', 'Ventral'); l1.FontSize=10;
+l1=line([LearningTrial.r463_B3_Day1_SS LearningTrial.r463_B3_Day1_SS], [g.YLim]); l1.LineWidth=1; l1.Color='k';
+g.XLabel.String='Trial';
+t1=text(6,g.YLim(1)+(g.YLim(2)-g.YLim(1))*0.15, ['Dorsal n = ' num2str(size(PC.r463_Day1_dHP,2)) ', (' num2str(variance) '% Var = ' num2str(Dimension.r463_Day1_dHP) ')']); t1.FontSize=12;
+t1=text(6,g.YLim(1)+(g.YLim(2)-g.YLim(1))*0.05, ['Ventral n = ' num2str(size(PC.r463_Day1_iHP,2)) ', (' num2str(variance) '% Var = ' num2str(Dimension.r463_Day1_iHP) ')']); t1.FontSize=12;
+
+% CR- distance
+sheetTitle = subplot('Position', [0.55 0.1 0.3 0.3]); hold on;
+if Dimension.r463_Day1_dHP > 2
+    DHP=EUdist.r463_Day1_dHP_CR_Weighted_GaussFiltered;
+    DHP=DHP/max(DHP);
+    p1=plot(1:length(DHP),DHP(1:end),'r.-'); p1(1,1).MarkerSize=20; p1(1,1).LineWidth=1.5;
+    xlim([1 length(DHP)]);
+end
+hold on;
+VHP=EUdist.r463_Day1_iHP_CR_Weighted_GaussFiltered;
+VHP=VHP/max(VHP);
+p2=plot(1:length(VHP),VHP(1:end),'b.-'); p2(1,1).MarkerSize=20; p2(1,1).LineWidth=1.5;
+ylabel('CR-chosen trial');
+legend([p1,p2],'dHP','ivHP');
+%
+yyaxis right
+p3=plot(LearningCurve.r463_B3_Day1_WinBugs_CR,'k-'); p3(1,1).MarkerSize=20; p3(1,1).LineWidth=1.5;
+g=gca; g.YDir='rev';
+g.FontSize=12;
+%         g.YLim=[0.4 0.92]
+l1=legend([p1 p2], 'Dorsal', 'Ventral'); l1.FontSize=10;
+l1=line([LearningTrial.r463_B3_Day1_CR LearningTrial.r463_B3_Day1_CR], [g.YLim]); l1.LineWidth=1; l1.Color='k';
+g.XLabel.String='Trial';
+t1=text(6,g.YLim(1)+(g.YLim(2)-g.YLim(1))*0.15, ['Dorsal n = ' num2str(size(PC.r463_Day1_dHP,2)) ', (' num2str(variance) '% Var = ' num2str(Dimension.r463_Day1_dHP) ')']); t1.FontSize=12;
+t1=text(6,g.YLim(1)+(g.YLim(2)-g.YLim(1))*0.05, ['Ventral n = ' num2str(size(PC.r463_Day1_iHP,2)) ', (' num2str(variance) '% Var = ' num2str(Dimension.r463_Day1_iHP) ')']); t1.FontSize=12;
+
+%% Figure 7I
+Trials = [LearningTrial.r448_B3_Day1_SS-1 LearningTrial.r448_B3_Day2_SS-1 LearningTrial.r448_B3_Day3_SS-1 LearningTrial.r448_B3_Day3_SS-1 ...
+    LearningTrial.r459_B3_Day1_SS-1 LearningTrial.r459_B3_Day2_SS-1 LearningTrial.r459_B3_Day3_SS-1 LearningTrial.r459_B3_Day4_SS-1 ...
+    LearningTrial.r463_B3_Day1_SS-1 LearningTrial.r463_B3_Day3_SS-1 LearningTrial.r463_B3_Day4_SS-1 LearningTrial.r463_B3_Day4_SS-1 ...
+    LearningTrial.r473_B3_Day2_SS-1 LearningTrial.r473_B3_Day3_SS-1 LearningTrial.r473_B3_Day4_SS-1 ...
+    LearningTrial.r509_B3_Day1_SS-1 LearningTrial.r509_B3_Day2_SS-1 LearningTrial.r509_B3_Day3_SS-1 LearningTrial.r509_B3_Day4_SS-1];
+PreLearend_Scaling=1;    
+for i=1:length(Trials)
+    PreLearend_Scaling = lcm(PreLearend_Scaling, Trials(i));
+end
+PreLearned_DownScale=PreLearend_Scaling/14/23/2;
+PreLearned_X=1/PreLearned_DownScale:1/PreLearned_DownScale:1;
+
+Trials = [size(PC.r448_Day1_dHP_SS,1)-LearningTrial.r448_B3_Day1_SS size(PC.r448_Day2_dHP_SS,1)-LearningTrial.r448_B3_Day2_SS size(PC.r448_Day3_dHP_SS,1)-LearningTrial.r448_B3_Day3_SS ...
+    size(PC.r459_Day1_dHP_SS,1)-LearningTrial.r459_B3_Day1_SS, size(PC.r459_Day2_dHP_SS,1)-LearningTrial.r459_B3_Day2_SS, size(PC.r459_Day3_dHP_SS,1)-LearningTrial.r459_B3_Day3_SS, size(PC.r459_Day4_dHP_SS,1)-3-LearningTrial.r459_B3_Day4_SS ...
+    size(PC.r463_Day1_dHP_SS,1)-LearningTrial.r463_B3_Day1_SS, size(PC.r463_Day2_dHP_SS,1)-LearningTrial.r463_B3_Day2_SS, size(PC.r463_Day3_dHP_SS,1)-LearningTrial.r463_B3_Day3_SS, size(PC.r463_Day4_dHP_SS,1)-LearningTrial.r463_B3_Day4_SS ...
+    size(PC.r473_Day2_dHP_SS,1)-LearningTrial.r473_B3_Day2_SS, size(PC.r473_Day3_dHP_SS,1)-LearningTrial.r473_B3_Day3_SS, size(PC.r473_Day4_dHP_SS,1)-LearningTrial.r473_B3_Day4_SS, ...
+    size(PC.r509_Day1_dHP_SS,1)-LearningTrial.r509_B3_Day1_SS, size(PC.r509_Day2_dHP_SS,1)-LearningTrial.r509_B3_Day2_SS, size(PC.r509_Day3_dHP_SS,1)-LearningTrial.r509_B3_Day3_SS, size(PC.r509_Day4_dHP_SS,1)-LearningTrial.r509_B3_Day4_SS];
+PostLearend_Scaling=1;    
+for i=1:length(Trials)
+    PostLearend_Scaling = lcm(PostLearend_Scaling, Trials(i));
+end
+PostLearned_DownScale=PostLearend_Scaling/17/13/15/19/2;
+PostLearned_X=1:1/PostLearned_DownScale:2-1/PostLearned_DownScale;
+
+TotalTrials = [size(PC.r448_Day1_dHP_SS,1), size(PC.r448_Day2_dHP_SS,1), size(PC.r448_Day3_dHP_SS,1)...
+    size(PC.r459_Day1_dHP_SS,1), size(PC.r459_Day2_dHP_SS,1), size(PC.r459_Day3_dHP_SS,1), size(PC.r459_Day4_dHP_SS,1)-3 ...
+    size(PC.r463_Day1_dHP_SS,1), size(PC.r463_Day2_dHP_SS,1), size(PC.r463_Day3_dHP_SS,1), size(PC.r463_Day4_dHP_SS,1) ...
+    size(PC.r473_Day2_dHP_SS,1), size(PC.r473_Day3_dHP_SS,1), size(PC.r473_Day4_dHP_SS,1), ...
+    size(PC.r509_Day1_dHP_SS,1), size(PC.r509_Day2_dHP_SS,1), size(PC.r509_Day3_dHP_SS,1), size(PC.r509_Day4_dHP_SS,1)];
+TotalLearend_Scaling=1;    
+for i=1:length(TotalTrials)
+    TotalLearend_Scaling = lcm(TotalLearend_Scaling, TotalTrials(i));
+end
+TotalLearned_DownScale=TotalLearend_Scaling/28/29/26/5/9;
+TotalLearned_X=1/TotalLearned_DownScale:1/TotalLearned_DownScale:1;
+
+Normal_iHP = [1 2 3 5 6 8 11 12 13 14 15 16]; 
+SSCH_iHP=[2 5 8 12 15 16];
+Quantity_iHP=[3 6 11 13 14];
+FewUnits_iHP=[7 17 18];
+FailToLearn_iHP=[4 9 10];
+
+Normal_dHP = [5 6 7 8 11]; 
+SSCH_dHP=[5 8];
+Quantity_dHP=[6 7 11];
+FewUnits_dHP=[2 3 12 13 14 15 16 17 18];
+FailToLearn_dHP=[4 9 10];
+Performance = [2 3 5 6 7 8 11 12 13 14 15 16 17 18];
+
+% % Line graph plot
+fig=figure; hold on;
+fig.Position=[0 0 1000 1000];
+% iHP
+for i=1:9:90
+    Jin_MeanSTE_Line(PreLearned_X(i),PreleaernED.iHP(Normal_iHP,i));
+end
+plot(PreLearned_X,mean(PreleaernED.iHP(Normal_iHP,:)),'k');
+
+for i=1:15:length(PostLearned_X)
+    Jin_MeanSTE_Line(PostLearned_X(i),PostleaernED.iHP(Normal_iHP,i));
+end
+plot(PostLearned_X,mean(PostleaernED.iHP(Normal_iHP,:)),'k');
+
+% dHP
+Color.color=2; Color.alpha=0.4;
+for i=1:9:90
+    Jin_MeanSTE_Line(PreLearned_X(i),PreleaernED.dHP(Normal_dHP,i),Color);
+end
+plot(PreLearned_X,mean(PreleaernED.dHP(Normal_dHP,:)),'R');
+for i=1:15:length(PostLearned_X)
+    Jin_MeanSTE_Line(PostLearned_X(i),PostleaernED.dHP(Normal_dHP,i),Color);
+end
+plot(PostLearned_X,mean(PostleaernED.dHP(Normal_dHP,:)),'R');
+g=gca; g.FontSize=18;
+ylim([0.1 1]);   
+xlim([0 2]);
+g.YTick=g.YTick(1:end-1);
+g.XTick=[0.5 1.5];
+g.XTickLabel={'Pre-learn phase','Learned phase'};
+l1=line([1 1], [0 1.1]); l1.LineWidth=1.5; l1.Color='k';
+ylabel('Normalized Euclidean distance');
+
+% statistical testing
+m=1;
+for i=1:10:90
+    [~,p_ttest(m)]=ttest2(PreleaernED.iHP(Normal_iHP,i), PreleaernED.dHP(Normal_dHP,i));
+    m=m+1;
+end
+
+%% Figure 7J
+Trials_CR = [LearningTrial.r448_B3_Day1_CR-1 LearningTrial.r448_B3_Day2_CR-1 LearningTrial.r448_B3_Day3_CR-1 LearningTrial.r448_B3_Day3_CR-1 ...
+    LearningTrial.r459_B3_Day1_CR-1 LearningTrial.r459_B3_Day2_CR-1 LearningTrial.r459_B3_Day3_CR-1 LearningTrial.r459_B3_Day4_CR-1 ...
+    LearningTrial.r463_B3_Day1_CR-1 LearningTrial.r463_B3_Day3_CR-1 LearningTrial.r463_B3_Day4_CR-1 LearningTrial.r463_B3_Day4_CR-1 ...
+    LearningTrial.r473_B3_Day2_CR-1 LearningTrial.r473_B3_Day3_CR-1 LearningTrial.r473_B3_Day4_CR-1 ...
+    LearningTrial.r509_B3_Day1_CR-1 LearningTrial.r509_B3_Day2_CR-1 LearningTrial.r509_B3_Day3_CR-1 LearningTrial.r509_B3_Day4_CR-1];
+PreLearend_Scaling_CR=1;    
+for i=1:length(Trials_CR)
+    PreLearend_Scaling_CR = lcm(PreLearend_Scaling_CR, Trials_CR(i));
+end
+PreLearned_DownScale_CR=PreLearend_Scaling_CR/19/14/15/4;
+PreLearned_X_CR=1/PreLearned_DownScale_CR:1/PreLearned_DownScale_CR:1;
+
+Trials_CR = [size(PC.r448_Day1_dHP_CR,1)-LearningTrial.r448_B3_Day1_CR+1 size(PC.r448_Day2_dHP_CR,1)-LearningTrial.r448_B3_Day2_CR+1 size(PC.r448_Day3_dHP_CR,1)-LearningTrial.r448_B3_Day3_CR+1 ...
+    size(PC.r459_Day1_dHP_CR,1)-LearningTrial.r459_B3_Day1_CR+1, size(PC.r459_Day2_dHP_CR,1)-LearningTrial.r459_B3_Day2_CR+1, size(PC.r459_Day3_dHP_CR,1)-LearningTrial.r459_B3_Day3_CR+1, size(PC.r459_Day4_dHP_CR,1)-LearningTrial.r459_B3_Day4_CR+1 ...
+    size(PC.r463_Day1_dHP_CR,1)-LearningTrial.r463_B3_Day1_CR+1, size(PC.r463_Day2_dHP_CR,1)-LearningTrial.r463_B3_Day2_CR+1, size(PC.r463_Day3_dHP_CR,1)-LearningTrial.r463_B3_Day3_CR+1, size(PC.r463_Day4_dHP_CR,1)-LearningTrial.r463_B3_Day4_CR+1 ...
+    size(PC.r473_Day2_dHP_CR,1)-LearningTrial.r473_B3_Day2_CR+1, size(PC.r473_Day3_dHP_CR,1)-LearningTrial.r473_B3_Day3_CR+1, size(PC.r473_Day4_dHP_CR,1)-LearningTrial.r473_B3_Day4_CR+1, ...
+    size(PC.r509_Day1_dHP_CR,1)-LearningTrial.r509_B3_Day1_CR+1, size(PC.r509_Day2_dHP_CR,1)-LearningTrial.r509_B3_Day2_CR+1, size(PC.r509_Day3_dHP_CR,1)-LearningTrial.r509_B3_Day3_CR+1, size(PC.r509_Day4_dHP_CR,1)-LearningTrial.r509_B3_Day4_CR+1];
+PostLearend_Scaling_CR=1;    
+Trials_CR(Trials_CR==0)=[];
+for i=1:length(Trials_CR)
+    PostLearend_Scaling_CR = lcm(PostLearend_Scaling_CR, Trials_CR(i));
+end
+PostLearned_DownScale_CR=PostLearend_Scaling_CR;
+PostLearned_X_CR=1:1/PostLearned_DownScale_CR:2-1/PostLearned_DownScale_CR;
+
+TotalTrials_CR = [size(PC.r448_Day1_dHP_CR,1), size(PC.r448_Day2_dHP_CR,1), size(PC.r448_Day3_dHP_CR,1)...
+    size(PC.r459_Day1_dHP_CR,1), size(PC.r459_Day2_dHP_CR,1), size(PC.r459_Day3_dHP_CR,1), size(PC.r459_Day4_dHP_CR,1) ...
+    size(PC.r463_Day1_dHP_CR,1), size(PC.r463_Day2_dHP_CR,1), size(PC.r463_Day3_dHP_CR,1), size(PC.r463_Day4_dHP_CR,1) ...
+    size(PC.r473_Day2_dHP_CR,1), size(PC.r473_Day3_dHP_CR,1), size(PC.r473_Day4_dHP_CR,1), ...
+    size(PC.r509_Day1_dHP_CR,1), size(PC.r509_Day2_dHP_CR,1), size(PC.r509_Day3_dHP_CR,1), size(PC.r509_Day4_dHP_CR,1)];
+TotalLearend_Scaling_CR=1;    
+for i=1:length(TotalTrials_CR)
+    TotalLearend_Scaling_CR = lcm(TotalLearend_Scaling_CR, TotalTrials_CR(i));
+end
+TotalLearned_DownScale_CR=TotalLearend_Scaling_CR/24/19/17/31/6;
+TotalLearned_X_CR=1/TotalLearned_DownScale_CR:1/TotalLearned_DownScale_CR:1;
+
+
+Normal_iHP = [1 2 3 5 6 8 11 12 13 14 15 16]; 
+SSCH_iHP=[2 5 8 12 15 16];
+Quantity_iHP=[3 6 11 13 14];
+FewUnits_iHP=[7 17 18];
+FailToLearn_iHP=[4 9 10];
+
+Normal_dHP = [5 6 7 8 11]; 
+SSCH_dHP=[5 8];
+Quantity_dHP=[6 7 11];
+FewUnits_dHP=[2 3 12 13 14 15 16 17 18];
+FailToLearn_dHP=[4 9 10];
+Performance = [2 3 5 6 7 8 11 12 13 14 15 16 17 18];
+
+% % Line graph version
+% Normal session
+fig=figure; hold on;
+fig.Position=[0 0 1000 1000];
+% iHP
+for i=1:17:174
+    Jin_MeanSTE_Line(PreLearned_X_CR(i),PreleaernED_CR.iHP(Normal_iHP,i));
+end
+plot(PreLearned_X_CR,mean(PreleaernED_CR.iHP(Normal_iHP,:)),'k');
+
+for i=1:6:length(PostLearned_X_CR)
+    Jin_MeanSTE_Line(PostLearned_X_CR(i),PostleaernED_CR.iHP(Normal_iHP,i));
+end
+plot(PostLearned_X_CR,mean(PostleaernED_CR.iHP(Normal_iHP,:)),'k');
+
+% dHP
+Color.color=2; Color.alpha=0.4;
+for i=1:17:174
+    Jin_MeanSTE_Line(PreLearned_X_CR(i),PreleaernED_CR.dHP(Normal_dHP,i),Color);
+end
+plot(PreLearned_X_CR,mean(PreleaernED_CR.dHP(Normal_dHP,:)),'R');
+for i=1:6:length(PostLearned_X_CR)
+    Jin_MeanSTE_Line(PostLearned_X_CR(i),PostleaernED_CR.dHP(Normal_dHP,i),Color);
+end
+plot(PostLearned_X_CR,mean(PostleaernED_CR.dHP(Normal_dHP,:)),'R');
+
+[h,p]=ttest2(PreleaernED_CR.iHP(Normal_iHP,5), PreleaernED_CR.dHP(Normal_dHP,5))
+
+g=gca; g.FontSize=18;
+ylim([0 1]);   
+xlim([0 2]);
+g.YTick=g.YTick(1:end-1);
+g.XTick=[0.5 1.5];
+g.XTickLabel={'Pre-learn phase','Learned phase'};
+l1=line([1 1], [0 1.1]); l1.LineWidth=1.5; l1.Color='k';
+ylabel('Normalized Euclidean distance');

SpatialRateMap_Related.m

@@ -0,0 +1,79 @@
+%% Figure 2D-G
+% % Example of rate map making 
+clear all
+load('Rat448-Main1-TT8-C2.mat')
+load('Rat448-Main1-TT8-C2_p2.mat')
+load('Rat448-Main1-PositionData.mat')
+XsizeOfVideo = 720;
+YsizeOfVideo = 480;
+samplingRate = 30;
+scaleForRateMap = 10;
+binXForRateMap = XsizeOfVideo / scaleForRateMap;
+binYForRateMap = YsizeOfVideo / scaleForRateMap;
+Alt_Rate_Odd_X_Range=[12 45]; Alt_Rate_Odd_Y_Range=[21 48];
+Alt_Rate_Even_X_Range=[14 48]; Alt_Rate_Even_Y_Range=[21 48];
+Alt_Rate_X_Range=[12 48]; Alt_Rate_Y_Range=[21 48];
+
+% % Rate map construction
+% Total rate map
+[Ratemap.occMat_Odd_Total, Ratemap.spkMat_Odd_Total, Ratemap.rawMat_Odd_Total, Ratemap.skaggsrateMat_Odd_Total] = abmFiringRateMap( ...
+    [thisCLST.t(Spike.Odd_Total_Track), thisCLST.x(Spike.Odd_Total_Track), thisCLST.y(Spike.Odd_Total_Track)],...
+    [Pos.t(Position.Odd_Total_Track), Pos.x(Position.Odd_Total_Track), Pos.y(Position.Odd_Total_Track)],...
+    binYForRateMap, binXForRateMap, scaleForRateMap, samplingRate);
+
+% B1 rate map
+[Ratemap.occMat_Odd_B1, Ratemap.spkMat_Odd_B1, Ratemap.rawMat_Odd_B1, Ratemap.skaggsrateMat_Odd_B1] = abmFiringRateMap( ...
+    [thisCLST.t(Spike.Odd_B1_Track), thisCLST.x(Spike.Odd_B1_Track), thisCLST.y(Spike.Odd_B1_Track)],...
+    [Pos.t(Position.Odd_B1_Track), Pos.x(Position.Odd_B1_Track), Pos.y(Position.Odd_B1_Track)],...
+    binYForRateMap, binXForRateMap, scaleForRateMap, samplingRate);
+
+% B2 rate map
+[Ratemap.occMat_Odd_B2, Ratemap.spkMat_Odd_B2, Ratemap.rawMat_Odd_B2, Ratemap.skaggsrateMat_Odd_B2] = abmFiringRateMap( ...
+    [thisCLST.t(Spike.Odd_B2_Track), thisCLST.x(Spike.Odd_B2_Track), thisCLST.y(Spike.Odd_B2_Track)],...
+    [Pos.t(Position.Odd_B2_Track), Pos.x(Position.Odd_B2_Track), Pos.y(Position.Odd_B2_Track)],...
+    binYForRateMap, binXForRateMap, scaleForRateMap, samplingRate);
+
+% % Contour of occupancy map
+OVERALL=load('Rat448-Main1-TT8-C2_p2.mat', 'Ratemap');
+outer = OVERALL.Ratemap.skaggsrateMat_Odd_Total >= 0;
+Contour_Odd = bwconncomp(outer);
+Contour_Odd.Label = labelmatrix(Contour_Odd);
+FieldBoundary_Odd = (Contour_Odd.Label==1);
+
+% % Rate map plotting        
+figure; hold on;
+i1=imagesc((Ratemap.skaggsrateMat_Odd_B1));
+minmaxColor=get(gca,'CLim');
+if minmaxColor(1) == -1 && minmaxColor(2) == 1; minmaxColor(2)=0.1; end
+Cmax(1)=minmaxColor(2);
+set(gca,'fontsize',10,'fontweight','bold')
+set(gca, 'YDir', 'rev', 'XLim', Alt_Rate_Odd_X_Range, 'YLim', Alt_Rate_Odd_Y_Range, 'FontSize', 9);
+colormap(jet);
+thisAlphaZ_RF_1stHalf = Ratemap.skaggsrateMat_Odd_B1;
+thisAlphaZ_RF_1stHalf(isnan(Ratemap.skaggsrateMat_Odd_B1)) = 0;
+thisAlphaZ_RF_1stHalf(~isnan(Ratemap.skaggsrateMat_Odd_B1)) = 1;
+alpha(thisAlphaZ_RF_1stHalf);axis off;
+hold on;
+[C,h]=contour(FieldBoundary_Odd,1);
+h.LineColor='k'; h.LineWidth=0.1;
+
+% % Spatial correlation between Block 1 and 2
+SpaCorr.Odd_B12 = GetSpatialCorrelation(Ratemap.skaggsrateMat_Odd_B1, Ratemap.skaggsrateMat_Odd_B2);
+
+% % Mean firing rate of block 1
+FiringRate.Average_Odd_B1 = GetFiringRate(Ratemap.skaggsrateMat_Odd_B1);
+
+% % Spatial information score
+InformationScore.Odd=GetSpaInfo(Ratemap.occMat_Odd_Total, Ratemap.skaggsrateMat_Odd_Total);
+
+% % Spatial informatio score's p-value
+Pos.Flag_Position_pvalue = Position.Odd_Total;
+thisCLST.Flag_Position_pvalue = Spike.Odd_Total;
+SpaInfo = InformationScore.Odd;
+InformationScore.pvalue_Odd = GetSpatialInfo_pvalue_ALT(thisCLST, Pos, SpaInfo);
+
+% % Place field size
+FieldSize_Odd = GetPlaceFieldSize(Ratemap.skaggsrateMat_Odd_Total);
+FieldSize_PhysicalSize_Odd=sum(sum(~isnan(Ratemap.skaggsrateMat_Odd_Total)));
+FieldSize_RelativeFieldSize_Odd=round(FieldSize_Odd/FieldSize_PhysicalSize_Odd*100,2);
+