clear all
close all
clc
global spettro_spe
load Spettri_dati
load uscite_4ROI
load eeg_4ROI
% Definition of Variables
window = 50;
zeropadding = 1000;
width = 2;
font = 16;
Npop = 2; % Number of populations
% time definition
dt=0.0001;
f_eulero = 1/dt;
tend = 1 + 4*14;
t=(0:dt:tend);
N=length(t);
ROI = 1; % which ROI to simulate
% Noise
rng(13) % seed for noise generation
sigma_p = sqrt(9/dt); % Standard deviation of the input noise to excitatory neurons
sigma_f = sqrt(9/dt);% Standard deviation of the input noise to inhibitory neurons
np = randn(2,N)*sigma_p; % Generation of the input noise to excitatory neurons
nf = randn(2,N)*sigma_f; % Generation of the input noise to inhibitory neurons
%% Parameter Values
% base condition;
C(:,1) = 40.*ones(1,2); %Cep
C(:,2) = 40.*ones(1,2); %Cpe
C(:,3) = 40.*ones(1,2); %Csp
C(:,4) = 50.*ones(1,2); %Cps
C(:,5) = 20.*ones(1,2); %Cfs
C(:,6) = 40.*ones(1,2); %Cfp
C(:,7) = 60*ones(1,2); %Cpf
C(:,8) = 20.*ones(1,2); %Cff
Wp(1,2) = 0;
Wp(2,1) = 0;
%% simulation
e0 = 2.5; % Saturation value of the sigmoid
r = 0.56; % Slope of the sigmoid(1/mV)
% Delay between regions (16.6 ms)
D=[0.0166; 0.0166; 0.0166; 0.0166; 0.0166; 0.0166];
% Synaptic Poles (rad/s) (\omega)
a=[75 30 300 ]; %ae = 75;
%as = 30;
%af = 300;
% Synaptic gains (mV)
G=[5.17 4.45 57.1]; %Ge = 5.17;
%Gs = 4.45;
%Gf = 57.1;
load prova12_5giugno2020
v_m_prova1(1,:) = W13*zp_prova1(1,:) + W14*zp_prova1(2,:) +W15*zp_prova1(3,:) + W16*zp_prova1(4,:); %l'ingresso al primo neurone nella prova1
v_m_prova1(2,:) = W23*zp_prova1(1,:) + W24*zp_prova1(2,:) +W25*zp_prova1(3,:) + W26*zp_prova1(4,:); %l'ingresso al secondp neurone nella prova1
v_m_prova2(1,:) = W13*zp_prova2(1,:) + W14*zp_prova2(2,:) +W15*zp_prova2(3,:) + W16*zp_prova2(4,:); %l'ingresso al primo neurone nella prova1
v_m_prova2(2,:) = W23*zp_prova2(1,:) + W24*zp_prova2(2,:) +W25*zp_prova2(3,:) + W26*zp_prova2(4,:); %l'ingresso al secondp neurone nella prova1
v_m_prova3(1,:) = W13*zp_prova3(1,:) + W14*zp_prova3(2,:) +W15*zp_prova3(3,:) + W16*zp_prova3(4,:); %l'ingresso al primo neurone nella prova1
v_m_prova3(2,:) = W23*zp_prova3(1,:) + W24*zp_prova3(2,:) +W25*zp_prova3(3,:) + W26*zp_prova3(4,:); %l'ingresso al secondp neurone nella prova1
% v_m_prova1(1,:) = ones(1,570001)*v_m(1,1);
% v_m_prova1(2,:) = ones(1,570001)*v_m(2,1);
% v_m_prova2(1,:) = ones(1,570001)*v_m(1,2);
% v_m_prova2(2,:) = ones(1,570001)*v_m(2,2);
% v_m_prova3(1,:) = ones(1,570001)*v_m(1,3);
% v_m_prova3(2,:) = ones(1,570001)*v_m(2,3);
for prova = 1: 3
yp=zeros(Npop,N);
xp=zeros(Npop,N);
vp=zeros(Npop,1);
zp=zeros(Npop,N);
ye=zeros(Npop,N);
xe=zeros(Npop,N);
ve=zeros(Npop,1);
ze=zeros(Npop,N);
ys=zeros(Npop,N);
xs=zeros(Npop,N);
vs=zeros(Npop,1);
zs=zeros(Npop,N);
yf=zeros(Npop,N);
xf=zeros(Npop,N);
zf=zeros(Npop,N);
vf=zeros(Npop,1);
xl=zeros(Npop,N);
yl=zeros(Npop,N);
riduzione_passo = 100; % step reduction from 10000 to 100 Hz
fs = f_eulero/riduzione_passo;
eeg=zeros(Npop,(N-1-10000)/riduzione_passo); % exclusion of the first second due to a possible transitory
Coeher = cell(Npop,Npop);
for j1 = 1:Npop
for j2 = 1: Npop
Coher{j1,j2} = zeros(501,1);
end
end
kmax=round(max(D)/dt);
switch prova
case 1
m = v_m_prova1;
case 2
m = v_m_prova2;
case 3
m = v_m_prova3; % 2XN;
end
for k= kmax +1:N-1
up=np(:,k);
uf=nf(:,k);
if(k>kmax)
for i=1:Npop
up(i)=up(i)+ Wp(i,:)*zp(:,round(k-D(i)/dt)) + m(i,round(k-D(i)/dt));
uf(i)=uf(i)+Wf(i,:)*zp(:,round(k-D(i)/dt));
end
end
vp(:)=C(:,2).*ye(:,k)-C(:,4).*ys(:,k)-C(:,7).*yf(:,k);
ve(:)=C(:,1).*yp(:,k);
vs(:)=C(:,3).*yp(:,k);
vf(:)=C(:,6).*yp(:,k)-C(:,5).*ys(:,k)-C(:,8).*yf(:,k)+yl(:,k); %
zp(:,k)=2*e0./(1+exp(-r*(vp(:))))-e0;
ze(:,k)=2*e0./(1+exp(-r*(ve(:))))-e0;
zs(:,k)=2*e0./(1+exp(-r*(vs(:))))-e0;
zf(:,k)=2*e0./(1+exp(-r*(vf(:))))-e0;
xp(:,k+1)=xp(:,k)+(G(1)*a(1)*zp(:,k)-2*a(1)*xp(:,k)-a(1)*a(1)*yp(:,k))*dt; %eulero
yp(:,k+1)=yp(:,k)+xp(:,k)*dt; %eulero
xe(:,k+1)=xe(:,k)+(G(1)*a(1)*(ze(:,k)+up(:)./C(:,2))-2*a(1)*xe(:,k)-a(1)*a(1)*ye(:,k))*dt;
ye(:,k+1)=ye(:,k)+xe(:,k)*dt;
xs(:,k+1)=xs(:,k)+(G(2)*a(2)*zs(:,k)-2*a(2)*xs(:,k)-a(2)*a(2)*ys(:,k))*dt;
ys(:,k+1)=ys(:,k)+xs(:,k)*dt;
xl(:,k+1)=xl(:,k)+(G(1)*a(1)*uf(:)-2*a(1)*xl(:,k)-a(1)*a(1)*yl(:,k))*dt;
yl(:,k+1)=yl(:,k)+xl(:,k)*dt;
xf(:,k+1)=xf(:,k)+(G(3)*a(3)*zf(:,k)-2*a(3)*xf(:,k)-a(3)*a(3)*yf(:,k))*dt;
yf(:,k+1)=yf(:,k)+xf(:,k)*dt;
end
inizio = 10000; % exclusion of the first second due to a possible transitory
eeg=diag(C(:,2))*ye(:,inizio:riduzione_passo:end)-diag(C(:,4))*ys(:,inizio:riduzione_passo:end)-diag(C(:,7))*yf(:,inizio:riduzione_passo:end);
switch prova
case 1
colore=[0 1 0];
Pspe = P_baseline_media;
Max_spe = max(Pspe(80:end,:));
zp1_prova1 = zp;
eeg1_prova1 = eeg;
style = '-';
case 2
colore = [1 0 0];
Pspe = P_affected_media;
zp1_prova2 = zp;
eeg1_prova2 = eeg;
style = '-';
case 3
colore = [0 0 1];
Pspe = P_unaffected_media;
zp1_prova3 = zp;
eeg1_prova3 = eeg;
style = '-';
end
figure(1)
[Peeg,f] = pwelch(eeg(1,:),window,[],zeropadding,fs);
if prova == 1
Max_mod1 = max(Peeg(80:end));
end
subplot(121)
plot(f(80:end),Peeg(80:end)/Max_mod1,'color',colore,'linewidth',width,'linestyle',style)
if prova == 3
xlabel('Frequency (Hz)','fontsize',14)
ylabel('normalized PSD','fontsize',14)
legend1 = legend('basal','affected', 'unaffected');
set(legend1,'fontsize',10)
set(legend1,'location','northeast','box','off')
title('Model','fontsize',14)
set(gca,'fontsize',14)
elseif prova == 1
axis([0 50 0 1.1])
end
hold on
subplot(122)
plot(f(80:end),Pspe(80:end,ROI)/Max_spe(ROI),'color',colore,'linewidth', width,'linestyle',style)
if prova == 3
xlabel('Frequency (Hz)','fontsize',14)
ylabel('Normalized PSD','fontsize',14)
legend1 = legend('basal','affected', 'unaffected');
set(legend1,'fontsize',10)
set(legend1,'location','southwest','box','off')
title('Experimental','fontsize',14)
set(gca,'fontsize',14)
assi = axes;
t1 = title('\fontsize{18} M1h L');
assi.Visible = 'off';
t1.Visible = 'on';
elseif prova == 1
axis([0 50 0 1.1])
end
hold on
figure(3)
subplot(2,3,1+1*(prova-1))
plot(f(80:end),Peeg(80:end)/max(Peeg(80:end)),'color',colore,'linewidth',width)
hold on
plot(f(80:end),Pspe(80:end,ROI)/(max(Pspe(80:end,ROI))),'--','color',0.5*colore+0.3,'linewidth',width)
switch prova
case 1
ylabel('PSD PMCah (normalized)','fontsize',font)
title('basal','fontsize',font)
case 2
title('affected','fontsize',font)
case 3
title('unaffected','fontsize',font)
end
legend1 = legend('model','experimental');
set(legend1,'fontsize',12)
set(legend1,'location','northeast')
set(gca,'fontsize',font)
figure(2)
[Peeg,f] = pwelch(eeg(2,:),window,[],zeropadding,fs);
if prova == 1
Max_mod2 = max(Peeg(80:end));
end
subplot(121)
plot(f(80:end),Peeg(80:end)/Max_mod2,'color',colore,'linewidth',width,'linestyle',style)
if prova == 3
xlabel('Frequency (Hz)','fontsize',14)
ylabel('normalized PSD','fontsize',14)
legend1 = legend('basal','affected', 'unaffected');
set(legend1,'fontsize',10)
set(legend1,'location','northeast','box','off')
title('Model','fontsize',14)
set(gca,'fontsize',14)
elseif prova == 1
axis([0 50 0 1.1])
end
hold on
subplot(122)
plot(f(80:end),Pspe(80:end,ROI+1)/Max_spe(ROI+1),'color',colore,'linewidth', width,'linestyle',style)
if prova == 3
xlabel('Frequency (Hz)','fontsize',14)
ylabel('Normalized PSD','fontsize',14)
legend1 = legend('basal','affected', 'unaffected');
set(legend1,'fontsize',10)
set(legend1,'location','southwest','box','off')
title('Experimental','fontsize',14)
set(gca,'fontsize',14)
assi = axes;
t1 = title('\fontsize{18} M1h R');
assi.Visible = 'off';
t1.Visible = 'on';
elseif prova == 1
axis([0 50 0 1.1])
end
hold on
figure(3)
subplot(2,3,4+1*(prova-1))
plot(f(80:end),Peeg(80:end)/max(Peeg(80:end)),'color',colore,'linewidth',width)
hold on
plot(f(80:end),Pspe(80:end,ROI+1)/(max(Pspe(80:end,ROI+1))),'--','color',0.5*colore+0.5,'linewidth',width)
switch prova
case 1
ylabel('PSD PMCuh (normalized)','fontsize',font)
case 2
xlabel('frequency (Hz)','fontsize',font)
end
legend1 = legend('model','experimental');
set(legend1,'fontsize',12)
set(legend1,'location','northeast')
set(gca,'fontsize',font)
figure(4)
subplot(2,3,1+1*(prova-1))
[Cxy f] = mscohere(eeg(1,:),eeg(2,:),50,[],zeropadding,fs);
switch prova
case 1
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{1,2}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{l} M1_{r}','fontsize',font)
title('basal','fontsize',font)
case 2
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{1,2}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{1,2}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
figure(5)
subplot(2,3,1+1*(prova-1))
switch prova
case 1
[Cxy f] = mscohere(eeg(1,:),eeg_prova1(1,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{1,3}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{l} SMA_{l}','fontsize',font)
title('basal','fontsize',font)
case 2
[Cxy f] = mscohere(eeg(1,:),eeg_prova2(1,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{1,3}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
[Cxy f] = mscohere(eeg(1,:),eeg_prova3(1,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{1,3}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
figure(6)
subplot(2,3,1+1*(prova-1))
switch prova
case 1
[Cxy f] = mscohere(eeg(1,:),eeg_prova1(2,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{1,4}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{l} SMA_{r}','fontsize',font)
title('basal','fontsize',font)
case 2
[Cxy f] = mscohere(eeg(1,:),eeg_prova2(2,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{1,4}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
[Cxy f] = mscohere(eeg(1,:),eeg_prova3(2,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{1,4}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
figure(7)
subplot(2,3,1+1*(prova-1))
switch prova
case 1
[Cxy f] = mscohere(eeg(1,:),eeg_prova1(3,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{1,5}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{l} PMC_{l}','fontsize',font)
title('basal','fontsize',font)
case 2
[Cxy f] = mscohere(eeg(1,:),eeg_prova2(3,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{1,5}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
[Cxy f] = mscohere(eeg(1,:),eeg_prova3(3,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{1,5}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
figure(8)
subplot(2,3,1+1*(prova-1))
switch prova
case 1
[Cxy f] = mscohere(eeg(1,:),eeg_prova1(4,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{1,6}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{l} PMC_{r}','fontsize',font)
title('basal','fontsize',font)
case 2
[Cxy f] = mscohere(eeg(1,:),eeg_prova2(4,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{1,6}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
[Cxy f] = mscohere(eeg(1,:),eeg_prova3(4,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{1,6}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
figure(9)
subplot(2,3,1+1*(prova-1))
switch prova
case 1
[Cxy f] = mscohere(eeg(2,:),eeg_prova1(1,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{2,3}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{r} SMA_{l}','fontsize',font)
title('basal','fontsize',font)
case 2
[Cxy f] = mscohere(eeg(2,:),eeg_prova2(1,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{2,3}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
[Cxy f] = mscohere(eeg(2,:),eeg_prova3(1,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{2,3}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
figure(10)
subplot(2,3,1+1*(prova-1))
switch prova
case 1
[Cxy f] = mscohere(eeg(2,:),eeg_prova1(2,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{2,4}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{r} SMA_{r}','fontsize',font)
title('basal','fontsize',font)
case 2
[Cxy f] = mscohere(eeg(2,:),eeg_prova2(2,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{2,4}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
[Cxy f] = mscohere(eeg(2,:),eeg_prova3(2,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{2,4}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
figure(11)
subplot(2,3,1+1*(prova-1))
switch prova
case 1
[Cxy f] = mscohere(eeg(2,:),eeg_prova1(3,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{2,5}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{r} PMC_{l}','fontsize',font)
title('basal','fontsize',font)
case 2
[Cxy f] = mscohere(eeg(2,:),eeg_prova2(3,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{2,5}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
[Cxy f] = mscohere(eeg(2,:),eeg_prova3(3,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{2,5}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
figure(12)
subplot(2,3,1+1*(prova-1))
switch prova
case 1
[Cxy f] = mscohere(eeg(2,:),eeg_prova1(4,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_baseline_media{2,6}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
ylabel('Coeher. M1_{r} PMC_{r}','fontsize',font)
title('basal','fontsize',font)
case 2
[Cxy f] = mscohere(eeg(2,:),eeg_prova2(4,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_affected_media{2,6}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('affected','fontsize',font)
xlabel('Frequency (Hz)','fontsize',font)
case 3
[Cxy f] = mscohere(eeg(2,:),eeg_prova3(4,:),50,[],zeropadding,fs);
plot(f(100:end),Cxy(100:end),'color',0.5*colore+0.3,'linewidth',2)
hold on
plot(f(100:end),C_unaffected_media{2,6}(100:end),'--','color',0.5*colore+0.3,'linewidth',2)
title('unaffected','fontsize',font)
end
axis([0 50 0 1])
set(gca,'fontsize',font)
end
figure
subplot(321)
plot(t,zp1_prova1(1,:))
subplot(322)
plot(t,zp1_prova1(2,:))
subplot(323)
plot(t,zp1_prova2(1,:))
subplot(324)
plot(t,zp1_prova2(2,:))
subplot(325)
plot(t,zp1_prova3(1,:))
subplot(326)
plot(t,zp1_prova3(2,:))
figure
teeg = t(inizio:riduzione_passo:end);
subplot(321)
plot(teeg,eeg1_prova1(1,:))
subplot(322)
plot(teeg,eeg1_prova1(2,:))
subplot(323)
plot(teeg,eeg1_prova2(1,:))
subplot(324)
plot(teeg,eeg1_prova2(2,:))
subplot(325)
plot(teeg,eeg1_prova3(1,:))
subplot(326)
plot(teeg,eeg1_prova3(2,:))
mean(zp1_prova1,2)
mean(zp1_prova2,2)
mean(zp1_prova3,2)
% save uscite_12 zp1_prova1 zp1_prova2 zp1_prova3
% save eeg_12 eeg1_prova1 eeg1_prova2 eeg1_prova3