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plot_fig2B_Amplitude_D1_vs_Trained.m
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plot_fig2B_Amplitude_D1_vs_Trained.m
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Script that plots the results presented in figure 2.B.
%
% Written by Pierre Le Merre
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Load Matrices
if exist('PathDatabase','var')==0 && exist('LFP_Data','var')==0 && exist('LFP_Data_description','var')==0
[PathDatabase,LFP_Data,LFP_Data_description]=Load_LFP_Multisite_database;
end
%learned days
load([PathDatabase filesep 'Learning_Days_Mtrx.mat']);
%% Parameters
Mouse_list=unique(LFP_Data.Mouse_Name(strcmp(LFP_Data.Session_Type,'DT')==1));
sr=str2double(LFP_Data_description.Trial_LFP_wS1.SamplingFrequencyHz);
t=linspace(0,5,sr*5);
Stimtime=3; %in sec
Baseline_duration=100; %in samples
% time windows in samples to look for peak amplitude for every channel
% (before first lick time)
Peak_window_in.wS1=12+6000;
Peak_window_in.wS2=12+6000;
Peak_window_in.wM1=20+6000;
Peak_window_in.PtA=20+6000;
Peak_window_in.dCA1=40+6000;
Peak_window_in.mPFC=60+6000;
Peak_window_out.wS1=80+6000;
Peak_window_out.wS2=100+6000;
Peak_window_out.wM1=100+6000;
Peak_window_out.PtA=120+6000;
Peak_window_out.dCA1=200+6000;
Peak_window_out.mPFC=200+6000;
%% Compute SEPs
Fields={'wS1','wS2','wM1','PtA','dCA1','mPFC'};
data_mouse_D1=[];
data_mouse_Learned=[];
for j=1:6
Field=char(Fields(j));
for i=1:size(Mouse_list,1)
Mouse=char(Mouse_list(i));
eval(['data_mouse_D1.' Field '(i,:)=nanmean(LFP_Data.Trial_LFP_' Field '(strcmp(LFP_Data.Mouse_Name,Mouse)==1 & LFP_Data.Session_Counter==1 & [LFP_Data.Trial_ID==1 | LFP_Data.Trial_ID==0],:));'])
eval(['data_mouse_Learned.' Field '(i,:)=nanmean(LFP_Data.Trial_LFP_' Field '(strcmp(LFP_Data.Mouse_Name,Mouse)==1 & [LFP_Data.Session_Counter==LDM(i,1) | LFP_Data.Session_Counter==LDM(i,2) | LFP_Data.Session_Counter==LDM(i,3)] & [LFP_Data.Trial_ID==1 | LFP_Data.Trial_ID==0],:));'])
eval(['data_mouse_D1.' Field '(i,:)=data_mouse_D1.' Field '(i,:)-nanmean(data_mouse_D1.' Field '(i,Stimtime*sr-Baseline_duration:Stimtime*sr),2);'])
eval(['data_mouse_Learned.' Field '(i,:)=data_mouse_Learned.' Field '(i,:)-nanmean(data_mouse_Learned.' Field '(i,Stimtime*sr-Baseline_duration:Stimtime*sr),2);'])
end
end
%% Mesure Peak
Ref_Peak_Learned=[];
Peak_loc=[];
Peaks_D1=[];
Peaks_Learned=[];
for j=1:6
Field=char(Fields(j));
for i=1:size(Mouse_list,1)
if strcmp(Field,'mPFC')==1
eval(['Ref_Peak_Learned.' Field '(i)=max(data_mouse_Learned.' Field '(i,Peak_window_in.' Field ':Peak_window_out.' Field '),[],2);'])
eval(['P=Ref_Peak_Learned.' Field '(i);'])
if isnan(P)==0
eval(['idx=find(data_mouse_Learned.' Field '(i,Peak_window_in.' Field ':Peak_window_out.' Field ')==(Ref_Peak_Learned.' Field '(i)));'])
else
idx=nan;
end
if isnan(idx)==0
eval(['Peak_loc.' Field '(i)=idx+Peak_window_in.' Field ';'])
eval(['Peaks_D1.' Field '(i)=mean(data_mouse_D1.' Field '(i,Peak_loc.' Field '(i)-5:Peak_loc.' Field '(i)+5),2);'])
eval(['Peaks_Learned.' Field '(i)=mean(data_mouse_Learned.' Field '(i,Peak_loc.' Field '(i)-5:Peak_loc.' Field '(i)+5),2);'])
else
eval(['Peak_loc.' Field '(i)=NaN;'])
eval(['Peaks_D1.' Field '(i)=NaN;'])
eval(['Peaks_Learned.' Field '(i)=NaN;'])
end
else
eval(['Ref_Peak_Learned.' Field '(i)=min(data_mouse_Learned.' Field '(i,Peak_window_in.' Field ':Peak_window_out.' Field '),[],2);'])
eval(['P=Ref_Peak_Learned.' Field '(i);'])
if isnan(P)==0
eval(['idx=find(data_mouse_Learned.' Field '(i,Peak_window_in.' Field ':Peak_window_out.' Field ')==(Ref_Peak_Learned.' Field '(i)));'])
else
idx=nan;
end
if isnan(idx)==0
eval(['Peak_loc.' Field '(i)=idx+Peak_window_in.' Field ';'])
eval(['Peaks_D1.' Field '(i)=mean(data_mouse_D1.' Field '(i,Peak_loc.' Field '(i)-5:Peak_loc.' Field '(i)+5),2);'])
eval(['Peaks_Learned.' Field '(i)=mean(data_mouse_Learned.' Field '(i,Peak_loc.' Field '(i)-5:Peak_loc.' Field '(i)+5),2);'])
else
eval(['Peak_loc.' Field '(i)=NaN;'])
eval(['Peaks_D1.' Field '(i)=NaN;'])
eval(['Peaks_Learned.' Field '(i)=NaN;'])
end
end
end
end
%% Compute Amplitude p values
for j=1:6
Field=char(Fields(j));
if j~=6
eval(['p_value(j)=signrank(Peaks_D1.' Field '*-10^(6),Peaks_Learned.' Field '*-10^(6));'])
else
eval(['p_value(j)=signrank(Peaks_D1.' Field '*10^(6),Peaks_Learned.' Field '*10^(6));'])
end
end
%% Plot peak amplitude with SD
Peaks_D1.wS1=Peaks_D1.wS1';
Peaks_D1.wS2=Peaks_D1.wS2';
Peaks_D1.wM1=Peaks_D1.wM1';
Peaks_D1.PtA=Peaks_D1.PtA';
Peaks_D1.dCA1=Peaks_D1.dCA1';
Peaks_D1.mPFC=Peaks_D1.mPFC';
Peaks_Learned.wS1=Peaks_Learned.wS1';
Peaks_Learned.wS2=Peaks_Learned.wS2';
Peaks_Learned.wM1=Peaks_Learned.wM1';
Peaks_Learned.PtA=Peaks_Learned.PtA';
Peaks_Learned.dCA1=Peaks_Learned.dCA1';
Peaks_Learned.mPFC=Peaks_Learned.mPFC';
figure
for j=1:6
Field=char(Fields(j));
ax(1)=subplot(3,2,j);
if j~=6
eval(['temp=[Peaks_D1.' Field '*-10^(6) Peaks_Learned.' Field '*-10^(6)];'])
plot(temp','color',[0.5,0.5,0.5]);
hold on
eval(['temp1=[nanmean(Peaks_D1.' Field '*-10^(6),1) NaN];'])
eval(['temp2=[NaN nanmean(Peaks_Learned.' Field '*-10^(6),1)];'])
eval(['SemH=[nanstd((Peaks_D1.' Field '*-10^(6)),[],1); NaN];'])
eval(['SemM=[NaN; nanstd((Peaks_Learned.' Field '*-10^(6)),[],1)];'])
else
eval(['temp=[Peaks_D1.' Field '*10^(6) Peaks_Learned.' Field '*10^(6)];'])
plot(temp','color',[0.5,0.5,0.5]);
hold on
eval(['temp1=[nanmean(Peaks_D1.' Field '*10^(6),1) NaN];'])
eval(['temp2=[NaN nanmean(Peaks_Learned.' Field '*10^(6),1)];'])
eval(['SemH=[nanstd((Peaks_D1.' Field '*10^(6)),[],1); NaN];'])
eval(['SemM=[NaN; nanstd((Peaks_Learned.' Field '*10^(6)),[],1)];'])
end
errorbar(temp1,SemH,'bo');
errorbar(temp2,SemM,'ro');
title(Field ,'fontweight','bold','fontsize',12,'fontname','times new roman');
xlim([0.5 2.5]);
NumTicks = 4;
L1 = get(gca,'XLim');
set(gca,'XTick',linspace(L1(1),L1(2),NumTicks))
set(gca,'XTickLabel',{'','D1','Trained',''})
ylabel('Amp (\muV)')
if strcmp(Field,'wS1')==1
ylim([100 500]);
NumTicks = 5;
elseif strcmp(Field,'wS2')==1
ylim([0 300]);
elseif strcmp(Field,'wM1')==1
ylim([-100 200]);
elseif strcmp(Field,'PtA')==1
ylim([-50 150]);
elseif strcmp(Field,'dCA1')==1
ylim([0 200]);
elseif strcmp(Field,'mPFC')==1
ylim([-100 200]);
end
if p_value(j)<0.05
xlabel(['p=' num2str(p_value(j))],'color','r')
else
xlabel(['p=' num2str(p_value(j))])
end
end
%%
clear all