diff --git a/Figures/Figure1C_phasic_tonic_epoch.m b/Figures/Figure1C_phasic_tonic_epoch.m index eab8c175e17f4a4cc1dbeadbf7ec8c627c74bcf2..a00150877668e13d82f376d5145e1398cdb69ac1 100644 --- a/Figures/Figure1C_phasic_tonic_epoch.m +++ b/Figures/Figure1C_phasic_tonic_epoch.m @@ -1,21 +1,14 @@ clear all; close all; -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eBOSC')); % eBOSC toolbox, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eBOSC')); % eBOSC toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\ISI_echt_psd_allsub_14-Mar-2023.mat') +Folderpath = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\'; +sub_Folderpath = dir([Folderpath,'Figure1C_RSN_001*']); -% Folderpath = 'S:\datasets\RSN\data\hdEEG\'; -% sub_Folderpath = dir([Folderpath,'RSN*']); -% -% waves_folder = 'S:\datasets\RSN\data\analysis\oscillation_detection'; - -Folderpath = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\'; -sub_Folderpath = dir([Folderpath,'RSN*']); - -Savefolder = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\'; %% Average across on and off blocks and calculate change lower_freq_alpha = 7.5; @@ -39,9 +32,6 @@ load([Folderpath,sub_Folderpath(s).name,filesep,goodREM_file(1).name]); nm_good_file = dir([Folderpath,sub_Folderpath(s).name,filesep,'*_nm_good.mat']); load([Folderpath,sub_Folderpath(s).name,filesep,nm_good_file(1).name]); -% waves_file = dir([waves_folder,sub_Folderpath(s).name,'*_eBOSC_waves.mat']); -% load([waves_folder,waves_file(1).name]) - waves_file = dir([Folderpath,sub_Folderpath(s).name,filesep,'*_eBOSC_waves.mat']); load([Folderpath,sub_Folderpath(s).name,filesep,waves_file(1).name]) @@ -684,7 +674,7 @@ load([Folderpath,sub_Folderpath(s).name,filesep,waves_file(1).name]) tileplot.TileSpacing = 'compact'; tileplot.Padding = 'compact'; - saveas(fig,[Savefolder,'Figure1C_phasic_tonic_epoch.svg']); +% saveas(fig,[Savefolder,'Figure1C_phasic_tonic_epoch.svg']); %%%%%%%%%%%%%%%%%%%%% With axis %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% @@ -1315,5 +1305,5 @@ load([Folderpath,sub_Folderpath(s).name,filesep,waves_file(1).name]) tileplot.Padding = 'compact'; - saveas(fig,[Savefolder,'Figure1C_phasic_tonic_epoch_axes.svg']); +% saveas(fig,[Savefolder,'Figure1C_phasic_tonic_epoch_axes.svg']); diff --git a/Figures/Figure1D_Suppl_Figure1_ntrials_across_night_erps.m b/Figures/Figure1D_Suppl_Figure1_ntrials_across_night_erps.m index d64ff6fa7b3f6e0c2e8788566654e9667c94421d..11148c8f08185bf033836672ca642c8bbe48121e 100644 --- a/Figures/Figure1D_Suppl_Figure1_ntrials_across_night_erps.m +++ b/Figures/Figure1D_Suppl_Figure1_ntrials_across_night_erps.m @@ -1,17 +1,17 @@ clear all; close all; -addpath(genpath('/users/nemo/software/Henry/useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -addpath(genpath('/users/nemo/software/DataViz')); % Dataviz toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\DataViz')); % Dataviz toolbox, see README on where to find this -load('/parallel_scratch/nemo/RSN/analysis/analysis/ntrials_vol/ERP_ntrials_allsub_13-Jun-2024.mat') -load('/parallel_scratch/nemo/RSN/analysis/analysis/ntrials_vol/nm_ntrials_allsub_12-Jun-2024.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures/Figure1D_ERP_ntrials_allsub_13-Jun-2024.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures/Figure1D_nm_ntrials_allsub_12-Jun-2024.mat') incl_sub = setdiff(1:19,12); bins = {'All' '1st third' '2nd third' '3rd third'}; -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% diff --git a/Figures/Figure2_Suppl_Figure2_phasic_tonic_psd_AEPs.m b/Figures/Figure2_Suppl_Figure2_phasic_tonic_psd_AEPs.m index 71859112efa4b3422f3c45a455cf646c31219cc3..52235340653ef270c823e4b411debd3cc1cc479d 100644 --- a/Figures/Figure2_Suppl_Figure2_phasic_tonic_psd_AEPs.m +++ b/Figures/Figure2_Suppl_Figure2_phasic_tonic_psd_AEPs.m @@ -1,20 +1,20 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('/users/nemo/software/Henry/useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -addpath(genpath('/users/nemo/software/colorGradient')); % colorGradient function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\colorGradient')); % colorGradient function, see README on where to find this -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/psd_allsub_mICA_avref_12-Mar-2023.mat'); -load('/parallel_scratch/nemo/RSN/analysis/analysis/power_allsub/power_allsub_mICA_avref_09-Mar-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_Figure3A_Figure4A_psd_allsub_mICA_avref_12-Mar-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_power_allsub_mICA_avref_09-Mar-2023.mat'); -load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_allsub_REM_mICA_avref04-Jun-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_ERP_allsub_REM_mICA_avref04-Jun-2023.mat'); ERP_REM = ERP_all; clear ERP_all -load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_allsub_wake_mICA_avref02-Jun-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_ERP_allsub_wake_mICA_avref02-Jun-2023.mat'); ERP_wake = ERP_all; clear ERP_all @@ -269,7 +269,7 @@ sig_bins_wake = find(p_psd_wake_state <= 0.05); plot(f(sig_bins_wake),ones(length(sig_bins_wake),1)*-0.2,'*','Color','k'); -saveas(fig,[Savefolder,'Figure2A_psd_EO_EC_',num2str(ch),'.svg']); +% saveas(fig,[Savefolder,'Figure2A_psd_EO_EC_',num2str(ch),'.svg']); %% PSD phasic, tonic off @@ -302,7 +302,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') sig_bins_REM = find(p_psd_rem_state <= 0.05); plot(f(sig_bins_REM),ones(length(sig_bins_REM),1)*-0.2,'*','Color','k'); -saveas(fig,[Savefolder,'Figure2B_psd_phasic_tonic_',num2str(ch),'.svg']); +% saveas(fig,[Savefolder,'Figure2B_psd_phasic_tonic_',num2str(ch),'.svg']); %% Compare EO vs EC @@ -382,7 +382,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') sig_bins_ttest = find(p_ERP_wake_state <= 0.05); plot(t(sig_bins_ttest),ones(length(sig_bins_ttest),1)*-2.5,'*','Color','k'); -saveas(fig,[Savefolder,'Figure2C_ERP_EOEC_notmatched.svg']); +% saveas(fig,[Savefolder,'Figure2C_ERP_EOEC_notmatched.svg']); %% Compare phasic vs tonic (not matched) @@ -454,7 +454,7 @@ plot(t(sig_bins_ttest),ones(length(sig_bins_ttest),1)*-2.5,'*','Color','k'); sig_times = t(sig_bins_ttest) -saveas(fig,[Savefolder,'Figure2D_ERP_phasictonic_notmatched.svg']); +% saveas(fig,[Savefolder,'Figure2D_ERP_phasictonic_notmatched.svg']); %% Compare phasic vs tonic (matched) @@ -534,7 +534,7 @@ end_diff(d) = t(sig_bins_ttest(diff_ndx(d))); end -saveas(fig,[Savefolder,'Suppl_Figure2A_ERP_phasictonic_matched.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure2A_ERP_phasictonic_matched.svg']); %% Compare eve vs mor @@ -615,7 +615,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual'); sig_bins_ttest = find(p_ERP_wake_evemor <= 0.05); plot(t(sig_bins_ttest),ones(length(sig_bins_ttest),1)*-2.5,'*','Color','k'); -saveas(fig,[Savefolder,'Suppl_Figure2B_ERP_evemor_notmatched.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure2B_ERP_evemor_notmatched.svg']); %% Compare tonic volumes using a lme (not matched) @@ -677,7 +677,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual'); sig_bins_lme = find(p_vol_tonic <= 0.05); plot(t(sig_bins_lme),ones(length(sig_bins_lme),1)*-3.75,'*','Color','k'); -saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_tonic_vol.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_tonic_vol.svg']); %% Compare phasic volumes using a lme (not matched) @@ -739,7 +739,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual'); sig_bins_lme = find(p_vol_phasic <= 0.05); plot(t(sig_bins_lme),ones(length(sig_bins_lme),1)*-3.75,'*','Color','k'); -saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_phasic_vol.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_phasic_vol.svg']); @@ -800,7 +800,7 @@ xtickangle(0) sig_bins_lme = find(p_vol_wake_e_EC <= 0.05); plot(t(sig_bins_lme),ones(length(sig_bins_lme),1)*-3.75,'*','Color','k'); -saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_wake_e_EC_vol.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_wake_e_EC_vol.svg']); %% Compare wake eve EO volumes using a lme (not matched) @@ -858,7 +858,7 @@ xtickangle(0) sig_bins_lme = find(p_vol_wake_e_EO <= 0.05); plot(t(sig_bins_lme),ones(length(sig_bins_lme),1)*-3.75,'*','Color','k'); -saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_wake_e_EO_vol.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_wake_e_EO_vol.svg']); %% Compare wake mor EC volumes using a lme (not matched) @@ -917,7 +917,7 @@ xtickangle(0) sig_bins_lme = find(p_vol_wake_m_EC <= 0.05); plot(t(sig_bins_lme),ones(length(sig_bins_lme),1)*-3.75,'*','Color','k'); -saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_wake_m_EC_vol.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_wake_m_EC_vol.svg']); %% Compare wake mor EO volumes using a lme (not matched) @@ -975,7 +975,7 @@ xtickangle(0) sig_bins_lme = find(p_vol_wake_m_EO <= 0.05); plot(t(sig_bins_lme),ones(length(sig_bins_lme),1)*-3.75,'*','Color','k'); -saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_wake_m_EO_vol.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure2C_ERP_wake_m_EO_vol.svg']); diff --git a/Figures/Figure3A_3F_ind_psd.m b/Figures/Figure3A_3F_ind_psd.m index cbcb0554766e0d8ca7c9f05caace58840fb49aca..6042516155fcd456d3fa9bde24f8e93c064b4f63 100644 --- a/Figures/Figure3A_3F_ind_psd.m +++ b/Figures/Figure3A_3F_ind_psd.m @@ -1,13 +1,13 @@ clear all; close all; -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Scripts\RSN')); % contains distinguishable colors function, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Scripts\RSN')); % contains distinguishable colors function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -Savefolder = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\'; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\psd_allsub_mICA_avref_12-Mar-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_Figure3A_Figure4A_psd_allsub_mICA_avref_12-Mar-2023.mat'); incl_sub = setdiff(1:19,12); @@ -173,7 +173,7 @@ colors = distinguishable_colors(18); xline(7.5,'LineWidth',1,'LineStyle','--') xline(12.5,'LineWidth',1,'LineStyle','--') -saveas(fig,[Savefolder,'Figure3A_Ind_spectrum_alpha.svg']); +% saveas(fig,[Savefolder,'Figure3A_Ind_spectrum_alpha.svg']); %% hdEEG - Theta @@ -310,5 +310,5 @@ colors = distinguishable_colors(18); xline(7.5,'LineWidth',1,'LineStyle','--') % xline(12.5,'LineWidth',1,'LineStyle','--') - saveas(fig,[Savefolder,'Figure3B_Ind_spectrum_theta.svg']); +% saveas(fig,[Savefolder,'Figure3B_Ind_spectrum_theta.svg']); \ No newline at end of file diff --git a/Figures/Figure3B_3G_eBOSC_frequency_histogram.m b/Figures/Figure3B_3G_eBOSC_frequency_histogram.m index 46b69491e17db9e9d8b624d6f453c55f0e6fe209..d7f6f72a0aa1a320b209ff2ba75294c122738b2b 100644 --- a/Figures/Figure3B_3G_eBOSC_frequency_histogram.m +++ b/Figures/Figure3B_3G_eBOSC_frequency_histogram.m @@ -1,20 +1,20 @@ clear all; close all; -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eBOSC')); % eBOSC toolbox, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eBOSC')); % eBOSC toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this % Folderpath = '/vol/research/nemo/datasets/RSN/data/hdEEG/'; % sub_Folderpath = dir([Folderpath,'RSN*']); % % waves_folder = '/vol/research/nemo/datasets/RSN/data/analysis/oscillation_detection/'; -Folderpath = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\RSN_002\'; +Folderpath = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure3B_RSN_002\'; -Savefolder = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\'; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\ISI_echt_psd_allsub_14-Mar-2023.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure3B_ISI_echt_psd_allsub_14-Mar-2023.mat') %% Average across on and off blocks and calculate change @@ -25,7 +25,7 @@ higher_freq_theta = 7.5; %% -% s = 2; %1:length(sub_Folderpath) +s = 2; %1:length(sub_Folderpath) % goodREM_file = dir([Folderpath,sub_Folderpath(s).name,filesep,'*_sleep*_fil_czref_goodREM.mat']); % load([Folderpath,sub_Folderpath(s).name,filesep,goodREM_file(1).name]); @@ -241,8 +241,7 @@ xticks(0:2:14); xlabel('Frequency (Hz)'); ylabel('Number') -% saveas(fig,[Savefolder,'Figure3B_',sub_Folderpath(s).name,'_alphastim_freq_findpeaks.svg']); -saveas(fig,[Savefolder,'Figure3B_example_alphastim_freq_findpeaks.svg']); +% saveas(fig,[Savefolder,'Figure3B_example_alphastim_freq_findpeaks.svg']); %% Theta stim frequency histogram - findpeaks @@ -336,7 +335,6 @@ xticks(0:2:14); xlabel('Frequency (Hz)'); ylabel('Number') -% saveas(fig,[Savefolder,'Figure3_',sub_Folderpath(s).name,'_thetastim_freq_findpeaks.svg']); -saveas(fig,[Savefolder,'Figure3G_example_thetastim_freq_findpeaks.svg']); +% saveas(fig,[Savefolder,'Figure3G_example_thetastim_freq_findpeaks.svg']); diff --git a/Figures/Figure3C_3H_eBOSC_frequency_corr_nwaves.m b/Figures/Figure3C_3H_eBOSC_frequency_corr_nwaves.m index c57d457d8c1eb43f78382296e2d1201553afad5a..5e07c18d398a056c238fb622e9aa360d004fdf25 100644 --- a/Figures/Figure3C_3H_eBOSC_frequency_corr_nwaves.m +++ b/Figures/Figure3C_3H_eBOSC_frequency_corr_nwaves.m @@ -3,10 +3,10 @@ close all; %% -load('/parallel_scratch/nemo/RSN/analysis/analysis/oscillation_detection/Oscillation_Freq_ISI_allsub_d03_08-Feb-2024.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure3C_Oscillation_Freq_ISI_allsub_d03_08-Feb-2024.mat'); close -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\'; %% incl_sub = setdiff(1:19,[12]); @@ -118,7 +118,7 @@ slope_SE_theta = mdl_theta.Coefficients(2,2) legend off - saveas(fig,[Savefolder,'Figure3H_corr_REM_theta_oscillations_ISI_Theta_',num2str(lower_freq_theta),'_',num2str(higher_freq_theta),'.svg']); +% saveas(fig,[Savefolder,'Figure3H_corr_REM_theta_oscillations_ISI_Theta_',num2str(lower_freq_theta),'_',num2str(higher_freq_theta),'.svg']); %% number of waves diff --git a/Figures/Figure3D_3I_Suppl_Figure4_polarhistogram.m b/Figures/Figure3D_3I_Suppl_Figure4_polarhistogram.m index 1d2188278163566b2b8649f20f4311cc3dbd82c9..a00985286522d6deea07b3ce0aed758a7b11036a 100644 --- a/Figures/Figure3D_3I_Suppl_Figure4_polarhistogram.m +++ b/Figures/Figure3D_3I_Suppl_Figure4_polarhistogram.m @@ -1,14 +1,14 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('/users/nemo/software/Henry/useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% Load file -load('/parallel_scratch/nemo/RSN/analysis/analysis/phase_allsub/phase_allsub_mICA_avref_alphathetafilt_notecht_19-Jun-2024.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure3D_3E_phase_allsub_mICA_avref_alphathetafilt03-Aug-2023.mat'); incl_sub = setdiff(1:19,12); @@ -33,13 +33,13 @@ for con = 1:4 end polarplot([0 circ_mean(m_alphafilt(incl_sub,ch,con))],[0 nanmean(r_alphafilt(incl_sub,ch,con))],'Color',colors(con,:),'LineWidth',5) - rlim([0 0.5]) + rlim([0 0.9]) end set(gca,'Fontsize',35,'TickDir','out','LineWidth',3); -saveas(gcf,[Savefolder,'Figure3D_polarplot_alpha_allsub_notecht.svg']); +% saveas(gcf,[Savefolder,'Figure3D_polarplot_alpha_allsub_notecht.svg']); %% Theta stim - alphafilt @@ -57,14 +57,14 @@ for con = 5:8 end polarplot([0 circ_mean(m_alphafilt(incl_sub,ch,con))],[0 nanmean(r_alphafilt(incl_sub,ch,con))],'Color',colors(con-4,:),'LineWidth',5) - rlim([0 0.5]) + rlim([0 0.9]) end set(gca,'Fontsize',35,'TickDir','out','LineWidth',3); -saveas(gcf,[Savefolder,'Suppl_Figure4C_polarplot_thetastim_alphafilt_allsub_notecht.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure4C_polarplot_thetastim_alphafilt_allsub_notecht.svg']); %% Theta stim - thetafilt @@ -86,14 +86,14 @@ for con = 5:8 end polarplot([0 circ_mean(m_thetafilt(incl_sub,ch,con))],[0 nanmean(r_thetafilt(incl_sub,ch,con))],'Color',colors(con-4,:),'LineWidth',5) - rlim([0 0.5]) + rlim([0 0.9]) end set(gca,'Fontsize',35,'TickDir','out','LineWidth',3); -saveas(gcf,[Savefolder,'Figure3I_polarplot_theta_allsub_notecht.svg']); +% saveas(gcf,[Savefolder,'Figure3I_polarplot_theta_allsub_notecht.svg']); %% Alpha stim - thetafilt @@ -110,12 +110,12 @@ for con = 1:4 end polarplot([0 circ_mean(m_thetafilt(incl_sub,ch,con))],[0 nanmean(r_thetafilt(incl_sub,ch,con))],'Color',colors(con,:),'LineWidth',5) - rlim([0 0.5]) + rlim([0 0.9]) end set(gca,'Fontsize',35,'TickDir','out','LineWidth',3); -saveas(gcf,[Savefolder,'Suppl_Figure4A_polarplot_alphastim_thetafilt_allsub_notecht.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure4A_polarplot_alphastim_thetafilt_allsub_notecht.svg']); %% diff --git a/Figures/Figure3E_3J_resultant_topo.m b/Figures/Figure3E_3J_resultant_topo.m index 4d7d2bcbb3a1fe2cc1c0eea7d671be5fe1cf6bd1..7c4374af18776ae5ae215668e468377adcabe748 100644 --- a/Figures/Figure3E_3J_resultant_topo.m +++ b/Figures/Figure3E_3J_resultant_topo.m @@ -1,19 +1,19 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('/users/nemo/software/Henry/useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -addpath(genpath('/users/nemo/software/ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% Load file -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\phase_allsub_mICA_avref_alphathetafilt03-Aug-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure3D_3E_phase_allsub_mICA_avref_alphathetafilt03-Aug-2023.mat'); % load('/parallel_scratch/nemo/RSN/analysis/analysis/phase_allsub/phase_allsub_mICA_avref_alphathetafilt_notecht_19-Jun-2024.mat'); -load('/users/nemo/projects/RSN/git/RSN/preprocessing/sleep/chans.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\chans.mat'); condition = {'Alpha Phase 0' 'Alpha Phase 90' 'Alpha Phase 180' 'Alpha Phase 270' ... 'Theta Phase 0' 'Theta Phase 90' 'Theta Phase 180' 'Theta Phase 270'}; @@ -103,7 +103,7 @@ incl_sub = setdiff(1:19,[12]); figure('Renderer','painters','units','normalized','outerposition',[0 0 0.8 0.8]) ft_plot_topo(layout2.pos(:,1),layout2.pos(:,2),nanmean(nanmean(r_alphafilt(incl_sub,:,1:4),1),3),'mask',layout2.mask,'outline',layout2.outline, ... - 'interplim','mask','clim',[0 0.37],'gridscale',300); + 'interplim','mask','clim',[0 0.8],'gridscale',300); hold on for con = 1:4 @@ -138,7 +138,7 @@ scatter(layout2.pos(2,1),layout2.pos(2,2),200,[0.6350 0.0780 0.1840],'x','LineWi hold on scatter(layout2.pos(sig_ch,1),layout2.pos(sig_ch,2),50,[0.9098 0.4588 0.4275],'o','filled','LineWidth',2); -saveas(gcf,[Savefolder,'Figure3E_alphastim_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Figure3E_alphastim_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); % saveas(gcf,[Savefolder,'Figure3E_alphastim_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar_notecht.svg']); clear sig_ch @@ -158,7 +158,7 @@ incl_sub = setdiff(1:19,[12]); figure('Renderer','painters','units','normalized','outerposition',[0 0 0.8 0.8]) ft_plot_topo(layout2.pos(:,1),layout2.pos(:,2),nanmean(nanmean(r_alphafilt(incl_sub,:,5:8),1),3),'mask',layout2.mask,'outline',layout2.outline, ... - 'interplim','mask','clim',[0 0.4],'gridscale',300); + 'interplim','mask','clim',[0 0.8],'gridscale',300); hold on for con = 5:8 @@ -195,7 +195,7 @@ axis off axis square -saveas(gcf,[Savefolder,'Suppl_Figure4D_thetastim_alphafilt_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure4D_thetastim_alphafilt_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); % saveas(gcf,[Savefolder,'Suppl_Figure4D_thetastim_alphafilt_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar_notecht.svg']); @@ -207,7 +207,7 @@ incl_sub = setdiff(1:19,[12]); figure('Renderer','painters','units','normalized','outerposition',[0 0 0.8 0.8]) ft_plot_topo(layout2.pos(:,1),layout2.pos(:,2),nanmean(nanmean(r_thetafilt(incl_sub,:,5:8),1),3),'mask',layout2.mask,'outline',layout2.outline, ... - 'interplim','mask','clim',[0 0.4],'gridscale',300); + 'interplim','mask','clim',[0 0.8],'gridscale',300); hold on clear pval vval @@ -253,7 +253,7 @@ std_dev_target_theta = rad2deg(circ_mean(std_dev_target(5:8,ch))) p_val_theta = pval(5:8,ch) v_val_theta = vval(5:8,ch) -saveas(gcf,[Savefolder,'Figure3J_thetastim_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Figure3J_thetastim_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); % saveas(gcf,[Savefolder,'Figure3J_thetastim_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar_notecht.svg']); %% Alpha stim thetafilt @@ -261,7 +261,7 @@ saveas(gcf,[Savefolder,'Figure3J_thetastim_topo_phase_accuracy_',num2str(length( figure('Renderer','painters','units','normalized','outerposition',[0 0 0.8 0.8]) ft_plot_topo(layout2.pos(:,1),layout2.pos(:,2),nanmean(nanmean(r_thetafilt(incl_sub,:,1:4),1),3),'mask',layout2.mask,'outline',layout2.outline, ... - 'interplim','mask','clim',[0 0.37],'gridscale',300); + 'interplim','mask','clim',[0 0.8],'gridscale',300); hold on clear pval vval @@ -296,6 +296,6 @@ scatter(layout2.pos(sig_ch,1),layout2.pos(sig_ch,2),50,[0.9098 0.4588 0.4275],'o axis off axis square -saveas(gcf,[Savefolder,'Suppl_Figure4B_alphastim_thetafilt_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure4B_alphastim_thetafilt_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); % saveas(gcf,[Savefolder,'Suppl_Figure4B_alphastim_thetafilt_topo_phase_accuracy_',num2str(length(incl_sub)),'_lapaz_colorbar_notecht.svg']); diff --git a/Figures/Figure4A_4G_Suppl_Figure5-9and13-18_Power_ON_OFF_allsub_topo_boxplots.m b/Figures/Figure4A_4G_Suppl_Figure5-9and13-18_Power_ON_OFF_allsub_topo_boxplots.m index d82fd9a37aade69a9a96dc58bd16c4e4edccb3f4..e658ffd232afee3df12b342e30414f1615c27eb7 100644 --- a/Figures/Figure4A_4G_Suppl_Figure5-9and13-18_Power_ON_OFF_allsub_topo_boxplots.m +++ b/Figures/Figure4A_4G_Suppl_Figure5-9and13-18_Power_ON_OFF_allsub_topo_boxplots.m @@ -1,20 +1,21 @@ clear all; close all; -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this -addpath(genpath('S:\projects\RSN\matlab\matlab\DataViz')); % Dataviz toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this + +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\DataViz')); % Dataviz toolbox, see README on where to find this % Folderpath = '/vol/research/nemo/datasets/RSN/data/hdEEG/'; % sub_Folderpath = dir([Folderpath,'RSN*']); -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\psd_allsub_mICA_avref_12-Mar-2023.mat'); -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\chans.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_Figure3A_Figure4A_psd_allsub_mICA_avref_12-Mar-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\chans.mat'); -statsresult_path = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\psd_allsub\statsresult\'; +statsresult_path = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\'; -Savefolder = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% Average across on and off blocks and calculate change @@ -181,7 +182,7 @@ title([band_name{band}]) end -saveas(gcf,[Savefolder,'Suppl_Figure5_alphastim_topo_lme_condition_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure5_alphastim_topo_lme_condition_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); @@ -242,7 +243,7 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Figure4A_alphastim_topo_lme_condition_',num2str(band_freq(band,1)),'_',num2str(band_freq(band,2)),'Hz_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Figure4A_alphastim_topo_lme_condition_',num2str(band_freq(band,1)),'_',num2str(band_freq(band,2)),'Hz_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); % end @@ -312,7 +313,7 @@ title([band_name{band}]) end -saveas(gcf,[Savefolder,'Suppl_Figure6_alphastim_topo_lme_substage_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure6_alphastim_topo_lme_substage_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% power change clusters @@ -393,7 +394,7 @@ xtickangle(45); box off axis square -saveas(gcf,[Savefolder,'Suppl_Figure8_alphastim_lme_substage_cluster_2_3Hz_3_4Hz','.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure8_alphastim_lme_substage_cluster_2_3Hz_3_4Hz','.svg']); %% Alpha stim - topo lme condition*substage @@ -456,7 +457,7 @@ title([band_name{band}]) end -saveas(gcf,[Savefolder,'Suppl_Figure7_alphastim_topo_lme_substagecondition_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure7_alphastim_topo_lme_substagecondition_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% Theta stim - Topo lme condition - all bins @@ -523,7 +524,7 @@ title([band_name{band}]) end -saveas(gcf,[Savefolder,'Suppl_Figure12_thetastim_topo_lme_condition_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure12_thetastim_topo_lme_condition_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% Theta stim - Topo lme condition - significant bins @@ -585,7 +586,7 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Figure4G_thetastim_topo_lme_condition_',num2str(band_freq(band,1)),'_',num2str(band_freq(band,2)),'Hz_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Figure4G_thetastim_topo_lme_condition_',num2str(band_freq(band,1)),'_',num2str(band_freq(band,2)),'Hz_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); % end @@ -653,7 +654,7 @@ title([band_name{band}]) end -saveas(gcf,[Savefolder,'Suppl_Figure13_thetastim_topo_lme_substage_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure13_thetastim_topo_lme_substage_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% power change clusters @@ -844,7 +845,7 @@ xtickangle(45); box off axis square -saveas(gcf,[Savefolder,'Suppl_Figure15_thetastim_lme_substage_cluster_2_3_4_5_6_12_Hz','.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure15_thetastim_lme_substage_cluster_2_3_4_5_6_12_Hz','.svg']); %% Theta stim - Topo lme condition*substage @@ -908,7 +909,7 @@ title([band_name{band}]) end -saveas(gcf,[Savefolder,'Suppl_Figure14_thetastim_topo_lme_substagecondition_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure14_thetastim_topo_lme_substagecondition_1Hzbands_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% power change clusters @@ -970,7 +971,7 @@ box off axis square -saveas(gcf,[Savefolder,'Suppl_Figure16_thetastim_lme_substagecondition_cluster_phasic_',band_name{band},'.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure16_thetastim_lme_substagecondition_cluster_phasic_',band_name{band},'.svg']); %% Alpha stimulation - t-test ON vs OFF @@ -1063,7 +1064,7 @@ clear V end - saveas(gcf,[Savefolder,'Suppl_Figure9_alphastim_on_vs_off_topo.svg']) +% saveas(gcf,[Savefolder,'Suppl_Figure9_alphastim_on_vs_off_topo.svg']) % end @@ -1154,7 +1155,7 @@ clear V end - saveas(gcf,[Savefolder,'Suppl_Figure17_thetastim_on_vs_off_topo.svg']) +% saveas(gcf,[Savefolder,'Suppl_Figure17_thetastim_on_vs_off_topo.svg']) % end diff --git a/Figures/Figure4B_4C_Power_ON_OFF_change_psd_phasictonic_alpha.m b/Figures/Figure4B_4C_Power_ON_OFF_change_psd_phasictonic_alpha.m index 4af1537c666c70988f52e7f71833cb68b68f8d71..45d267ce4c5a57ee58da494f2ac2ff8a9ea46b2b 100644 --- a/Figures/Figure4B_4C_Power_ON_OFF_change_psd_phasictonic_alpha.m +++ b/Figures/Figure4B_4C_Power_ON_OFF_change_psd_phasictonic_alpha.m @@ -1,27 +1,27 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('/users/nemo/software/Henry/useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/psd_allsub_mICA_avref_12-Mar-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_Figure3A_Figure4A_psd_allsub_mICA_avref_12-Mar-2023.mat'); -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_alpha_7-8 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_alpha_7-8 Hz.mat'); alpha_cluster_el1 = statsresult.WhichCh_1_max_condition; clear statsresult -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_alpha_10-11 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_alpha_10-11 Hz.mat'); alpha_cluster_el2 = statsresult.WhichCh_1_max_condition; clear statsresult alpha_cluster_combined = unique([alpha_cluster_el1,alpha_cluster_el2]); -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_theta_7-8 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_theta_7-8 Hz.mat'); theta_cluster_el = statsresult.WhichCh_1_max_condition; clear statsresult @@ -249,7 +249,7 @@ yline(-26,'LineWidth',2); box off axis square -saveas(fig,[Savefolder,'Figure4B_psd_change_alpha_ttest_statsresult_cluster.svg']); +% saveas(fig,[Savefolder,'Figure4B_psd_change_alpha_ttest_statsresult_cluster.svg']); %% Plot normalized power spectrum ON-OFF change for Alpha stimulation @@ -309,5 +309,5 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') box off axis square -saveas(fig,[Savefolder,'Figure4C_npsd_change_alpha_ttest_statsresult_cluster.svg']); +% saveas(fig,[Savefolder,'Figure4C_npsd_change_alpha_ttest_statsresult_cluster.svg']); diff --git a/Figures/Figure4D_4J_Suppl_Figure11and19_Frequency_ON_OFF_allsub_topo.m b/Figures/Figure4D_4J_Suppl_Figure11and19_Frequency_ON_OFF_allsub_topo.m index 7a28f67aaf93ecd5434e23e1b9684361b22ff885..820a7c374369626c828027ec1489f7640765e107 100644 --- a/Figures/Figure4D_4J_Suppl_Figure11and19_Frequency_ON_OFF_allsub_topo.m +++ b/Figures/Figure4D_4J_Suppl_Figure11and19_Frequency_ON_OFF_allsub_topo.m @@ -1,15 +1,15 @@ clear all; close all; -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this -addpath(genpath('S:\projects\RSN\matlab\matlab\DataViz')); % Dataviz toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\DataViz')); % Dataviz toolbox, see README on where to find this % load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\freqalphatheta_allsub_23-Jan-2024'); -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\chans.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\chans.mat'); -Savefolder = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% Average across on and off blocks and calculate change @@ -104,7 +104,7 @@ close all band = 1; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_alphastim_alphafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_alphastim_alphafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -147,13 +147,13 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Figure4D_alphastim_topo_lme_condition_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Figure4D_alphastim_topo_lme_condition_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% band = 2; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_alphastim_thetafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_alphastim_thetafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -195,13 +195,13 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Figure4D_alphastim_topo_lme_condition_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Figure4D_alphastim_topo_lme_condition_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% Alpha stim - Topo lme substage band = 1;%:15 -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_alphastim_alphafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_alphastim_alphafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -244,13 +244,13 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Suppl_Figure10_alphastim_topo_lme_substage_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure10_alphastim_topo_lme_substage_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% band = 2;%:15 -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_alphastim_thetafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_alphastim_thetafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -294,13 +294,13 @@ axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Suppl_Figure10_alphastim_topo_lme_substage_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure10_alphastim_topo_lme_substage_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% Alpha stim - Topo lme condition*substage band = 1; %:15 -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_alphastim_alphafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_alphastim_alphafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -343,13 +343,13 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Suppl_Figure10_alphastim_topo_lme_substagecondition_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure10_alphastim_topo_lme_substagecondition_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% band = 2; %:15 -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_alphastim_thetafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_alphastim_thetafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -392,14 +392,14 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Suppl_Figure10_alphastim_topo_lme_substagecondition_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure10_alphastim_topo_lme_substagecondition_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% Theta stim - Topo lme condition band = 1; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_thetastim_alphafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_thetastim_alphafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -442,13 +442,13 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Figure4J_thetastim_topo_lme_condition_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Figure4J_thetastim_topo_lme_condition_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% band = 2; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_thetastim_thetafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_thetastim_thetafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -491,13 +491,13 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Figure4J_thetastim_topo_lme_condition_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Figure4J_thetastim_topo_lme_condition_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% Theta stim - Topo lme substage band = 1; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_thetastim_alphafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_thetastim_alphafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -540,13 +540,13 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Suppl_Figure18_thetastim_topo_lme_substage_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure18_thetastim_topo_lme_substage_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% band = 2; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_thetastim_thetafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_thetastim_thetafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -589,14 +589,14 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Suppl_Figure18_thetastim_topo_lme_substage_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure18_thetastim_topo_lme_substage_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% Theta stim - Topo lme substage *condition band = 1; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_thetastim_alphafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_thetastim_alphafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -639,13 +639,13 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Suppl_Figure18_thetastim_topo_lme_substage_condition_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure18_thetastim_topo_lme_substage_condition_alphaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); %% band = 2; -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_thetastim_thetafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_thetastim_thetafreq.mat') figure('Renderer','painters','units','normalized','outerposition',[0 0 0.5 0.5]) @@ -688,5 +688,5 @@ axis off axis square title([band_name{band}]) -saveas(gcf,[Savefolder,'Suppl_Figure18_thetastim_topo_lme_substage_condition_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure18_thetastim_topo_lme_substage_condition_thetaband_N',num2str(length(incl_sub)),'_lapaz_colorbar.svg']); diff --git a/Figures/Figure4E-F_4K-L_Frequency_ON_OFF_change_boxplots_time.m b/Figures/Figure4E-F_4K-L_Frequency_ON_OFF_change_boxplots_time.m index 2e9cb2416523034c6abbe03af6d12c664554c78f..ff3e5392d35e9c9403c8b7252c1db3c0470db08d 100644 --- a/Figures/Figure4E-F_4K-L_Frequency_ON_OFF_change_boxplots_time.m +++ b/Figures/Figure4E-F_4K-L_Frequency_ON_OFF_change_boxplots_time.m @@ -1,26 +1,21 @@ clear all; close all; -% addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eeglab')); % eeglab toolbox, see README on where to find this -% addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -% addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this -% addpath(genpath('S:\projects\RSN\matlab\matlab\DataViz')); % Dataviz toolbox, see README on where to find this -% +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\DataViz')); % Dataviz toolbox, see README on where to find this -addpath(genpath('/users/nemo/software/eeglab')); -addpath /users/nemo/software/Henry/useful_functions -addpath(genpath('/users/nemo/software/ScientificColourMaps7')); -addpath(genpath('/users/nemo/software/DataViz')); % load('/parallel_scratch/nemo/RSN/analysis/analysis/frequency_allsub/freqalphatheta_allsub_23-Jan-2024'); % ifq_old = ifq; % clear ifq -load('/parallel_scratch/nemo/RSN/analysis/analysis/frequency_allsub/freqalphatheta_allsub_27-May-2024.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4E_freqalphatheta_allsub_27-May-2024.mat'); % ifq_new = ifq; % clear ifq -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% Average across on and off blocks and calculate change @@ -41,22 +36,22 @@ colors = linspecer(4); %% % load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_alphastim_alphafreq.mat') -load('/parallel_scratch/nemo/RSN/analysis/analysis/frequency_allsub/statsresult/statsresult_alphastim_alphafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_alphastim_alphafreq.mat') alphastim_alpha_cluster_el = statsresult.WhichCh_1_max_condition; clear statsresult % load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_alphastim_thetafreq.mat') -load('/parallel_scratch/nemo/RSN/analysis/analysis/frequency_allsub/statsresult/statsresult_alphastim_thetafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_alphastim_thetafreq.mat') alphastim_theta_cluster_el = [statsresult.WhichCh_1_max_condition statsresult.WhichCh_3_max_condition]; clear statsresult % load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_thetastim_alphafreq.mat') -load('/parallel_scratch/nemo/RSN/analysis/analysis/frequency_allsub/statsresult/statsresult_thetastim_alphafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_thetastim_alphafreq.mat') thetastim_alpha_cluster_el = [statsresult.WhichCh_1_max_condition statsresult.WhichCh_2_max_condition]; clear statsresult % load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\frequency_allsub\statsresult\statsresult_thetastim_thetafreq.mat') -load('/parallel_scratch/nemo/RSN/analysis/analysis/frequency_allsub/statsresult/statsresult_thetastim_thetafreq.mat') +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4D_frequency_allsub\statsresult\statsresult_thetastim_thetafreq.mat') thetastim_theta_cluster_el = [statsresult.WhichCh_1_max_condition statsresult.WhichCh_2_max_condition]; clear statsresult @@ -284,7 +279,7 @@ box off axis square ylim([-3 4]); -saveas(gcf,[Savefolder,'Figure4E_InstFreq_boxplot_conditions_alphastim','.svg']); +% saveas(gcf,[Savefolder,'Figure4E_InstFreq_boxplot_conditions_alphastim','.svg']); %% thetastim - alpha band @@ -422,7 +417,7 @@ box off axis square ylim([-3 4]); -saveas(gcf,[Savefolder,'Figure4K_InstFreq_boxplot_conditions_thetastim','.svg']); +% saveas(gcf,[Savefolder,'Figure4K_InstFreq_boxplot_conditions_thetastim','.svg']); %% Time course - Alphastim - alpha freq - Compare conditions using a lme - OFF to ON @@ -554,7 +549,7 @@ axis square yline(-1.3,'LineWidth',2); title('7-12 Hz'); -saveas(fig,[Savefolder,'Figure4F_alphastim_alpha_frequency_change_time.png']); +% saveas(fig,[Savefolder,'Figure4F_alphastim_alpha_frequency_change_time.png']); %% Time course - Alphastim - theta freq - Compare conditions using a lme @@ -689,7 +684,7 @@ title('4-7 Hz'); % saveas(fig,[Savefolder,'Figure4F_alphastim_theta_frequency_change_time.svg']); -saveas(fig,[Savefolder,'Figure4F_alphastim_theta_frequency_change_time.png']); +% saveas(fig,[Savefolder,'Figure4F_alphastim_theta_frequency_change_time.png']); %% Time course - Thetastim - alpha freq - Compare conditions using a lme @@ -822,7 +817,7 @@ title('7-12 Hz'); % saveas(fig,[Savefolder,'Figure4L_thetastim_alpha_frequency_change_time.svg']); -saveas(fig,[Savefolder,'Figure4L_thetastim_alpha_frequency_change_time.png']); +% saveas(fig,[Savefolder,'Figure4L_thetastim_alpha_frequency_change_time.png']); %% Time course - Thetastim - theta freq - Compare conditions using a lme @@ -954,7 +949,7 @@ yline(-1.3,'LineWidth',2); title('4-7 Hz'); % saveas(fig,[Savefolder,'Figure4L_thetastim_theta_frequency_change_time.svg']); -saveas(fig,[Savefolder,'Figure4L_thetastim_theta_frequency_change_time.png']); +% saveas(fig,[Savefolder,'Figure4L_thetastim_theta_frequency_change_time.png']); diff --git a/Figures/Figure4H_4I_Power_ON_OFF_change_psd_phasictonic_theta.m b/Figures/Figure4H_4I_Power_ON_OFF_change_psd_phasictonic_theta.m index 7c01ec1bcc83efa5a26156c3217e2e923d1f5c2b..ab9d93c2cef4ef940fd89efd621715cd11755df0 100644 --- a/Figures/Figure4H_4I_Power_ON_OFF_change_psd_phasictonic_theta.m +++ b/Figures/Figure4H_4I_Power_ON_OFF_change_psd_phasictonic_theta.m @@ -1,27 +1,27 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('/users/nemo/software/Henry/useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/psd_allsub_mICA_avref_12-Mar-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_Figure3A_Figure4A_psd_allsub_mICA_avref_12-Mar-2023.mat'); -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_alpha_7-8 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_alpha_7-8 Hz.mat'); alpha_cluster_el1 = statsresult.WhichCh_1_max_condition; clear statsresult -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_alpha_10-11 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_alpha_10-11 Hz.mat'); alpha_cluster_el2 = statsresult.WhichCh_1_max_condition; clear statsresult alpha_cluster_combined = unique([alpha_cluster_el1,alpha_cluster_el2]); -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_theta_7-8 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_theta_7-8 Hz.mat'); theta_cluster_el = statsresult.WhichCh_1_max_condition; clear statsresult @@ -242,7 +242,7 @@ yline(-26,'LineWidth',2); box off axis square -saveas(fig,[Savefolder,'Figure4H_psd_change_theta_ttest_statsresult_cluster.svg']); +% saveas(fig,[Savefolder,'Figure4H_psd_change_theta_ttest_statsresult_cluster.svg']); %% Plot normalized power spectrum ON-OFF change for Theta stimulation @@ -296,4 +296,4 @@ yline(-14,'LineWidth',2); box off axis square -saveas(fig,[Savefolder,'Figure4I_npsd_change_theta_ttest_statsresult_cluster.svg']); +% saveas(fig,[Savefolder,'Figure4I_npsd_change_theta_ttest_statsresult_cluster.svg']); diff --git a/Figures/Rev_Suppl_Figure3_2_ERPs_phase_reset_nm_alpha.m b/Figures/Rev_Suppl_Figure3_2_ERPs_phase_reset_nm_alpha.m index 0da44eae6632bec367395a1d0744f473e66445bb..263717eb448786d115343d782e1d4607119cdaa2 100644 --- a/Figures/Rev_Suppl_Figure3_2_ERPs_phase_reset_nm_alpha.m +++ b/Figures/Rev_Suppl_Figure3_2_ERPs_phase_reset_nm_alpha.m @@ -1,12 +1,12 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); -addpath(genpath('/users/nemo/projects/RSN')); -addpath(genpath('/users/nemo/software/Henry/useful_functions')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +% addpath(genpath('/users/nemo/projects/RSN')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this % addpath(genpath('/user/HS301/m17462/matlab/colorGradient')); -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; % incl_sub = setdiff(1:19,[12]); % 14 excluded because no phasic trials, 9 because no wake eve trials incl_sub = setdiff(1:19,[12]); % 14 excluded because no phasic trials, 9 because no wake eve trials @@ -15,7 +15,7 @@ incl_sub = setdiff(1:19,[12]); % 14 excluded because no phasic trials, 9 because %% ERP phase bins - REM % load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_nm_allsub_REM_mICA_avref09-Feb-2024.mat'); -load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_nm_broadband_allsub_REM_mICA_avref07-Jun-2024.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Rev_Suppl_Figure3_2_ERP_nm_broadband_allsub_REM_mICA_avref07-Jun-2024.mat'); %% plot alpha ERP - averaged across triggers @@ -79,9 +79,9 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') % end -saveas(fig,[Savefolder,'Suppl_Figure4_ERP_nm.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure4_ERP_nm.svg']); -%% plot alpha ERP - averaged across first 10 triggers - alphafilt +%% plot alpha ERP - averaged across triggers - alphafilt t = (-dt*fs:dt*fs-1)/fs*1000; % time in ms @@ -121,79 +121,6 @@ xtickangle(0) set(groot,'defaultAxesXTickLabelRotationMode','manual') % end -saveas(fig,[Savefolder,'Suppl_Figure4_ERP_nm_alphafilt.svg']); - - -%% check non-uniformity across circle - alphafilt - -fig = figure('Renderer','painters','units','normalized','outerposition',[0 0 1 1]) - -trig = 1; - -for samp = 1:size(ERP_nm_all.trial_data_alphafilt_phase,4) - - mean_phase_allcon_REM = reshape(ERP_nm_all.trial_data_alphafilt_phase(incl_sub,1:4,trig,samp),[length(incl_sub)*4 1]); - resultant_phase_allcon_REM = reshape(ERP_nm_all.trial_data_alphafilt_phase_r(incl_sub,1:4,trig,samp),[length(incl_sub)*4 1]); - - mean_phase_allcon_REM(isnan(mean_phase_allcon_REM))= []; - resultant_phase_allcon_REM(resultant_phase_allcon_REM == 0)= []; - - [p_val_REM(samp) z_val_REM(samp)] = circ_rtest(mean_phase_allcon_REM,resultant_phase_allcon_REM); - -end - - - -% plot alpha ERP phase - -t = (-dt*fs:dt*fs-1)/fs*1000; % time in ms - -colors = linspecer(4); - - -% tileplot = tiledlayout(1,4); -% -% nexttile(1) - -% subplot(2,5,trig) - -for con = 1:4 -% plot(t,squeeze(nanmean(ERP_nm_all.trial_data(:,con,trig,:),1)),'Color',colors(con,:)) -incl_sub2 = find(~isnan(squeeze(ERP_nm_all.trial_data_alphafilt_phase(:,con,trig,1))) == 1); -incl_sub3 = intersect(incl_sub,incl_sub2); -plot(t,squeeze(circ_mean(ERP_nm_all.trial_data_alphafilt_phase(incl_sub3,con,trig,:))),'Color',colors(con,:)) -hold on -% sig_samps = find(p_val_REM < 0.05); -% plot(t(sig_samps),ones(length(sig_samps),1)*3.5,'*','Color','k'); -% hold on -end - -hold on -% plot(t,squeeze(circ_mean(nanmean(ERP_nm_all.trial_data_alphafilt_phase(incl_sub,1:4,trig,:),2))),'Color','k','LineWidth',3) -xline(0,'LineStyle','--','LineWidth',2); - -xlim([-500 500]); -xlabel('Time (ms)') -ylabel('Phase (radians)') -set(gca,'Fontsize',15,'TickDir','out','LineWidth',2); -box off -axis square -% legend({'Peak' 'Falling' 'Trough' 'Rising'}); -legend off -ylim([-4 4]); -yticks([-pi:pi:pi]); -yticklabels({'-\pi' '0' '\pi'}) -xticks(-200:200:1000); -title(['Stimulus ',num2str(trig)]); - -clear p_val_REM z_val_REM -% end - -% saveas(fig,[Savefolder,'Figure6_ERP_alpha_nm_alphafilt_phase.svg']); - - - - - +% saveas(fig,[Savefolder,'Suppl_Figure4_ERP_nm_alphafilt.svg']); diff --git a/Figures/Rev_Suppl_Figure3_2_ERPs_phase_reset_nm_theta.m b/Figures/Rev_Suppl_Figure3_2_ERPs_phase_reset_nm_theta.m index 35cdec1a0760d51ed01a7d330e7af6576952985e..525da48bd311e06ba4f83ed8bac15ab46ca08de6 100644 --- a/Figures/Rev_Suppl_Figure3_2_ERPs_phase_reset_nm_theta.m +++ b/Figures/Rev_Suppl_Figure3_2_ERPs_phase_reset_nm_theta.m @@ -1,12 +1,12 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); -addpath(genpath('/users/nemo/projects/RSN')); -addpath(genpath('/users/nemo/software/Henry/useful_functions')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +% addpath(genpath('/users/nemo/projects/RSN')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this % addpath(genpath('/user/HS301/m17462/matlab/colorGradient')); -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; % incl_sub = setdiff(1:19,[12]); % 14 excluded because no phasic trials, 9 because no wake eve trials incl_sub = setdiff(1:19,[12]); % 14 excluded because no phasic trials, 9 because no wake eve trials @@ -15,7 +15,7 @@ incl_sub = setdiff(1:19,[12]); % 14 excluded because no phasic trials, 9 because %% ERP phase bins - REM % load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_nm_allsub_REM_mICA_avref09-Feb-2024.mat'); -load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_nm_broadband_allsub_REM_mICA_avref07-Jun-2024.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Rev_Suppl_Figure3_2_ERP_nm_broadband_allsub_REM_mICA_avref07-Jun-2024.mat'); %% plot alpha ERP - averaged across triggers @@ -79,7 +79,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') % end -saveas(fig,[Savefolder,'Suppl_Figure4_ERP_nm_thetastim.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure4_ERP_nm_thetastim.svg']); %% plot alpha ERP - averaged across first 10 triggers - alphafilt @@ -121,6 +121,6 @@ xtickangle(0) set(groot,'defaultAxesXTickLabelRotationMode','manual') % end -saveas(fig,[Savefolder,'Suppl_Figure4_ERP_nm_thetastim_thetafilt.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure4_ERP_nm_thetastim_thetafilt.svg']); diff --git a/Figures/Suppl_Figure10_TF_Power_ON_OFF_change_psd_phasictonic_alpha.m b/Figures/Suppl_Figure10_TF_Power_ON_OFF_change_psd_phasictonic_alpha.m index 4579e51b5872a127d20d65c387385215b6bde245..9378be65c13e37989fb052287f5da91815fd47bf 100755 --- a/Figures/Suppl_Figure10_TF_Power_ON_OFF_change_psd_phasictonic_alpha.m +++ b/Figures/Suppl_Figure10_TF_Power_ON_OFF_change_psd_phasictonic_alpha.m @@ -1,39 +1,28 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); -addpath(genpath('/users/nemo/projects/RSN')); -addpath(genpath('/users/nemo/software/Henry/useful_functions')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -Folderpath = '/parallel_scratch/nemo/RSN/hdEEG/'; -sub_Folderpath = dir([Folderpath,'RSN*']); +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/TF/'; - -% load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/psd_allsub_mICA_avref_12-Mar-2023.mat'); -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/psd_allsub_mICA_avref_OFFONOFF28-May-2024.mat'); - -% load('/user/HS301/m17462/matlab/Scripts/RSN/analyses/psd/topo/Cluster_el_9_10_Hz.mat'); - -% load('/user/HS301/m17462/matlab/Scripts/RSN/analyses/psd/topo/EEG_chanlocs.mat'); - -% load('/vol/research/nemo/datasets/RSN/data/analysis/topo_allsub/statsresult/statsresult_theta_3-4 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Suppl_Figure10_psd_allsub_mICA_avref_OFFONOFF28-May-2024'); conditions = {'Alpha Peak' 'Alpha Falling' 'Alpha Trough' 'Alpha Rising' 'Theta Peak' 'Theta Falling' 'Theta Trough' 'Theta Rising'}; -%% +%% -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_alpha_7-8 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_alpha_7-8 Hz.mat'); alpha_cluster_el1 = statsresult.WhichCh_1_max_condition; clear statsresult -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_alpha_10-11 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_alpha_10-11 Hz.mat'); alpha_cluster_el2 = statsresult.WhichCh_1_max_condition; clear statsresult alpha_cluster_combined = unique([alpha_cluster_el1,alpha_cluster_el2]); -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_theta_7-8 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_theta_7-8 Hz.mat'); theta_cluster_el = statsresult.WhichCh_1_max_condition; clear statsresult @@ -544,6 +533,6 @@ psd_tf_falling_minus_rising = psd_tf_falling-psd_tf_rising; title('Alpha Falling vs Alpha Rising'); - saveas(fig,[Savefolder,'TF_ttest_alpha_statsresult_cluster_falling_vs_rising.svg']); +% saveas(fig,[Savefolder,'TF_ttest_alpha_statsresult_cluster_falling_vs_rising.svg']); diff --git a/Figures/Suppl_Figure10_TF_Power_ON_OFF_change_psd_phasictonic_theta.m b/Figures/Suppl_Figure10_TF_Power_ON_OFF_change_psd_phasictonic_theta.m index 5db7d43a66e00539d3564d963b03ab0551c3d7b3..406a2abf9594ef85ecdb833b137e276e9a5ee8bf 100644 --- a/Figures/Suppl_Figure10_TF_Power_ON_OFF_change_psd_phasictonic_theta.m +++ b/Figures/Suppl_Figure10_TF_Power_ON_OFF_change_psd_phasictonic_theta.m @@ -1,39 +1,28 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); -addpath(genpath('/users/nemo/projects/RSN')); -addpath(genpath('/users/nemo/software/Henry/useful_functions')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -Folderpath = '/parallel_scratch/nemo/RSN/hdEEG/'; -sub_Folderpath = dir([Folderpath,'RSN*']); +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/TF/'; - -% load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/psd_allsub_mICA_avref_12-Mar-2023.mat'); -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/psd_allsub_mICA_avref_OFFONOFF28-May-2024.mat'); - -% load('/user/HS301/m17462/matlab/Scripts/RSN/analyses/psd/topo/Cluster_el_9_10_Hz.mat'); - -% load('/user/HS301/m17462/matlab/Scripts/RSN/analyses/psd/topo/EEG_chanlocs.mat'); - -% load('/vol/research/nemo/datasets/RSN/data/analysis/topo_allsub/statsresult/statsresult_theta_3-4 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Suppl_Figure10_psd_allsub_mICA_avref_OFFONOFF28-May-2024'); conditions = {'Alpha Peak' 'Alpha Falling' 'Alpha Trough' 'Alpha Rising' 'Theta Peak' 'Theta Falling' 'Theta Trough' 'Theta Rising'}; -%% +%% -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_alpha_7-8 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_alpha_7-8 Hz.mat'); alpha_cluster_el1 = statsresult.WhichCh_1_max_condition; clear statsresult -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_alpha_10-11 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_alpha_10-11 Hz.mat'); alpha_cluster_el2 = statsresult.WhichCh_1_max_condition; clear statsresult alpha_cluster_combined = unique([alpha_cluster_el1,alpha_cluster_el2]); -load('/parallel_scratch/nemo/RSN/analysis/analysis/psd_allsub/statsresult/statsresult_theta_7-8 Hz.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure4A_psd_allsub\statsresult\statsresult_theta_7-8 Hz.mat'); theta_cluster_el = statsresult.WhichCh_1_max_condition; clear statsresult @@ -238,7 +227,7 @@ fig = figure('Renderer','painters','units','normalized','outerposition',[0 0 1 1 title(conditions{cond}); - saveas(fig,[Savefolder,'TF_ttest_theta_statsresult_cluster_con',conditions{cond},'_notnorm.svg']); +% saveas(fig,[Savefolder,'TF_ttest_theta_statsresult_cluster_con',conditions{cond},'_notnorm.svg']); % end @@ -389,7 +378,7 @@ psd_tf_peak_minus_trough = psd_tf_peak-psd_tf_trough; title('Theta Peak vs Theta Trough'); - saveas(fig,[Savefolder,'TF_ttest_theta_statsresult_cluster_peak_vs_trough.svg']); +% saveas(fig,[Savefolder,'TF_ttest_theta_statsresult_cluster_peak_vs_trough.svg']); %% Theta Falling vs Rising @@ -535,5 +524,5 @@ psd_tf_falling_minus_rising = psd_tf_falling-psd_tf_rising; title('Theta Falling vs Theta Rising'); - saveas(fig,[Savefolder,'TF_ttest_theta_statsresult_cluster_falling_vs_rising.svg']); +% saveas(fig,[Savefolder,'TF_ttest_theta_statsresult_cluster_falling_vs_rising.svg']); diff --git a/Figures/Suppl_Figure12_20_connectivity.m b/Figures/Suppl_Figure12_20_connectivity.m index 92b0025f935f085639be646636fae5b643c078ed..c004782037c4de5b5e07d9a5a6fdece2f7d4b452 100644 --- a/Figures/Suppl_Figure12_20_connectivity.m +++ b/Figures/Suppl_Figure12_20_connectivity.m @@ -1,23 +1,23 @@ clear all; close all; -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\eeglab')); % eeglab toolbox, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this -addpath(genpath('S:\projects\RSN\matlab\matlab\DataViz')); % Dataviz toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\ScientificColourMaps7')); % ScientificColourMaps toolbox, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\DataViz')); % Dataviz toolbox, see README on where to find this -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\connectivity_allsub_07-Dec-2023.mat'); -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\chans.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Suppl_Figure12_20_connectivity_allsub_07-Dec-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\chans.mat'); band_name = {'1-4 Hz' '4-7 Hz' '7-12 Hz' '13-30 Hz' '8-12 Hz'}; conditions = {'Peak'; 'Falling'; 'Trough'; 'Rising'; 'Peak'; 'Falling'; 'Trough'; 'Rising';} -statsresult_folder = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\connectivity_allsub\statsresult_sensor\'; +statsresult_folder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Suppl_Figure12_20_connectivity_allsub\statsresult_sensor\'; -Savefolder = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% topoplot layout @@ -152,7 +152,7 @@ axis off axis square title(['PLV']) -saveas(gcf,[Savefolder,'Suppl_Figure11_lme_alphastim_PLV_frontalseeds_',band_name{band1},'-',band_name{band2},'.svg']) +% saveas(gcf,[Savefolder,'Suppl_Figure11_lme_alphastim_PLV_frontalseeds_',band_name{band1},'-',band_name{band2},'.svg']) end @@ -277,7 +277,7 @@ end tileplot.TileSpacing = 'tight'; tileplot.Padding = 'compact'; -saveas(gcf,[Savefolder,'Suppl_Figure11_ttest_frontalseeds_',band_name{band1},'-',band_name{band2},'allch_alpha_dots_PLV.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure11_ttest_frontalseeds_',band_name{band1},'-',band_name{band2},'allch_alpha_dots_PLV.svg']); end @@ -342,7 +342,7 @@ axis off axis square title(['PLI']) -saveas(gcf,[Savefolder,'Suppl_Figure11_lme_alphastim_PLI_frontalseeds_',band_name{band1},'-',band_name{band2},'.svg']) +% saveas(gcf,[Savefolder,'Suppl_Figure11_lme_alphastim_PLI_frontalseeds_',band_name{band1},'-',band_name{band2},'.svg']) end @@ -406,7 +406,7 @@ axis off axis square title(['PLV']) -saveas(gcf,[Savefolder,'Suppl_Figure19_lme_thetastim_PLV_frontalseeds_',band_name{band1},'-',band_name{band2},'.svg']) +% saveas(gcf,[Savefolder,'Suppl_Figure19_lme_thetastim_PLV_frontalseeds_',band_name{band1},'-',band_name{band2},'.svg']) end @@ -470,7 +470,7 @@ axis off axis square title(['PLI']) -saveas(gcf,[Savefolder,'Suppl_Figure19_lme_thetastim_PLI_frontalseeds_',band_name{band1},'-',band_name{band2},'.svg']) +% saveas(gcf,[Savefolder,'Suppl_Figure19_lme_thetastim_PLI_frontalseeds_',band_name{band1},'-',band_name{band2},'.svg']) end @@ -564,7 +564,7 @@ box off axis square ylim([-10 10]); -saveas(gcf,[Savefolder,'Suppl_Figure11_Connectivity_boxplot_alphastim_',band_name{band1},'-',band_name{band2},'.svg']); +% saveas(gcf,[Savefolder,'Suppl_Figure11_Connectivity_boxplot_alphastim_',band_name{band1},'-',band_name{band2},'.svg']); for s = 1:19 diff --git a/Figures/Suppl_Figure21_ERPs_phase_reset_alpha.m b/Figures/Suppl_Figure21_ERPs_phase_reset_alpha.m index 18329b511c1770e87e25092bd9e8cdbd27a8505d..5c4700e78dc784e2ba5a9034ad1d88cf4e97ef05 100644 --- a/Figures/Suppl_Figure21_ERPs_phase_reset_alpha.m +++ b/Figures/Suppl_Figure21_ERPs_phase_reset_alpha.m @@ -1,19 +1,19 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); -addpath(genpath('/users/nemo/projects/RSN')); -addpath(genpath('/users/nemo/software/Henry/useful_functions')); -addpath(genpath('/users/nemo/software/colorGradient')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +% addpath(genpath('/users/nemo/projects/RSN')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\colorGradient')); -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; incl_sub = setdiff(1:19,[9 12 14]); % 14 excluded because no phasic trials, 9 because no wake eve trials %% ERP phase bins - REM -load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_allsub_REM_mICA_avref04-Jun-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_ERP_allsub_REM_mICA_avref04-Jun-2023.mat'); ERP = ERP_all; state = 1; % 1 = tonic, 2 = phasic @@ -66,7 +66,7 @@ clear ERP %% ERP phase bins - wake -load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_allsub_wake_mICA_avref02-Jun-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_ERP_allsub_wake_mICA_avref02-Jun-2023.mat'); ERP = ERP_all; state = 1; % 1 = eyes open, 2 = eyes closed @@ -282,7 +282,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') % tileplot.Padding = 'compact'; % Savefolder = '/vol/research/nemo/datasets/RSN/data/analysis/Figures/'; -saveas(fig,[Savefolder,'Suppl_Figure22_ERP_phase_reset_alpha.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure22_ERP_phase_reset_alpha.svg']); %% check non-uniformity across circle - REM @@ -472,7 +472,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') % Savefolder = '/vol/research/nemo/datasets/RSN/data/analysis/Figures/'; -saveas(fig,[Savefolder,'Suppl_Figure22_ERP_phase_reset_alpha_phase.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure22_ERP_phase_reset_alpha_phase.svg']); %% check amplitude of bins @@ -719,7 +719,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') % set(gca,'Fontsize',15,'TickDir','out','LineWidth',2); % title(''); -saveas(fig,[Savefolder,'Suppl_Figure22_ERP_phase_reset_alpha_regression.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure22_ERP_phase_reset_alpha_regression.svg']); diff --git a/Figures/Suppl_Figure22_ERPs_phase_reset_theta.m b/Figures/Suppl_Figure22_ERPs_phase_reset_theta.m index a7266da345274a5f2df2986be427e6f55fd22a97..b3ca0b6afcdeba2afa194722ed73861aea73f422 100644 --- a/Figures/Suppl_Figure22_ERPs_phase_reset_theta.m +++ b/Figures/Suppl_Figure22_ERPs_phase_reset_theta.m @@ -1,19 +1,19 @@ clear all; close all; -addpath(genpath('/users/nemo/software/eeglab')); -addpath(genpath('/users/nemo/projects/RSN')); -addpath(genpath('/users/nemo/software/Henry/useful_functions')); -addpath(genpath('/users/nemo/software/colorGradient')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\eeglab')); % eeglab toolbox, see README on where to find this +% addpath(genpath('/users/nemo/projects/RSN')); +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\colorGradient')); -Savefolder = '/parallel_scratch/nemo/RSN/analysis/analysis/Figures/'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; incl_sub = setdiff(1:19,[9 12 14]); % 14 excluded because no phasic trials, 9 because no wake eve trials %% ERP phase bins - REM -load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_allsub_REM_mICA_avref04-Jun-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_ERP_allsub_REM_mICA_avref04-Jun-2023.mat'); ERP = ERP_all; state = 1; % 1 = tonic, 2 = phasic @@ -62,7 +62,7 @@ clear ERP %% ERP phase bins - wake -load('/parallel_scratch/nemo/RSN/analysis/analysis/erp_allsub/ERP_allsub_wake_mICA_avref02-Jun-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure2_ERP_allsub_wake_mICA_avref02-Jun-2023.mat'); ERP = ERP_all; state = 1; % 1 = eyes open, 2 = eyes closed @@ -273,7 +273,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') % tileplot.Padding = 'compact'; % Savefolder = '/vol/research/nemo/datasets/RSN/data/analysis/Figures/'; -saveas(fig,[Savefolder,'Suppl_Figure23_ERP_phase_reset_theta.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure23_ERP_phase_reset_theta.svg']); %% check non-uniformity across circle - REM @@ -463,7 +463,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') % Savefolder = '/vol/research/nemo/datasets/RSN/data/analysis/Figures/'; -saveas(fig,[Savefolder,'Suppl_Figure23_ERP_phase_reset_theta_phase.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure23_ERP_phase_reset_theta_phase.svg']); %% check non-uniformity across circle for bins - REM @@ -698,7 +698,7 @@ set(groot,'defaultAxesXTickLabelRotationMode','manual') % set(gca,'Fontsize',15,'TickDir','out','LineWidth',2); % title(''); -saveas(fig,[Savefolder,'Suppl_Figure23_ERP_phase_reset_theta_regression.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure23_ERP_phase_reset_theta_regression.svg']); diff --git a/Figures/Suppl_Figure3_ISI_autocorr.m b/Figures/Suppl_Figure3_ISI_autocorr.m index 275a626e744708b1d03b4465b032b5076e56c238..a0806bb239ed09360b5eab74ba56ace3e603f2c7 100644 --- a/Figures/Suppl_Figure3_ISI_autocorr.m +++ b/Figures/Suppl_Figure3_ISI_autocorr.m @@ -1,15 +1,15 @@ clear all; close all; -addpath(genpath('\\surrey.ac.uk\personal\hs301\m17462\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this +addpath(genpath('F:\Valeria\m17462\bigdata\matlab\Henry\useful_functions')); % contains linspecer function, circular statistics toolbox functions, echt function, shadedErrorBar function, see README on where to find this -load('D:\Valeria\RSN\data\for_sharing\data_to_make_figures\ISI_echt_psd_allsub_14-Mar-2023.mat'); +load('F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figure3B_ISI_echt_psd_allsub_14-Mar-2023'); incl_sub = setdiff(1:19,12); colors = linspecer(4); -Savefolder = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; +Savefolder = 'F:\Valeria\RSN\data\for_sharing\data_to_make_figures\Figures\'; %% @@ -47,7 +47,7 @@ box off axis square xticks([0:5:20]); -saveas(fig,[Savefolder,'Suppl_Figure3_ISI_autocorr_alphastim.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure3_ISI_autocorr_alphastim.svg']); %% Theta @@ -68,6 +68,6 @@ box off axis square xticks([0:5:20]); -saveas(fig,[Savefolder,'Suppl_Figure3_ISI_autocorr_thetastim.svg']); +% saveas(fig,[Savefolder,'Suppl_Figure3_ISI_autocorr_thetastim.svg']); diff --git a/Figures/Suppl_Table1_questionnaires.R b/Figures/Suppl_Table1_questionnaires.R new file mode 100644 index 0000000000000000000000000000000000000000..661882404bc1b951cec56c48eb9a4fe7083cc689 --- /dev/null +++ b/Figures/Suppl_Table1_questionnaires.R @@ -0,0 +1,172 @@ +# Clear plots +if(!is.null(dev.list())) dev.off() +# Clear console +cat("\014") +# Clean workspace +rm(list=ls()) + +# install and load packages + +install.packages("readxl") +install.packages("foreign") +install.packages("nnet") +install.packages("car") + +library(readxl) +library(foreign) +library(nnet) +library(car) + + +setwd("F:/Valeria/RSN/data/for_sharing/data_to_make_figures") + +# load KSS data + +KSS_data <- read_excel("Suppl_Table1_KarolinskaSleepinessAnswers.xlsx") + +head(KSS_data) + +KSS_data$ID <- factor(KSS_data$ID) +KSS_data$daytime <- factor(KSS_data$daytime) + + +# mean and SD + +KSS_eve = KSS_data$KSS[which(KSS_data$daytime == 'eve')] +KSS_mor = KSS_data$KSS[which(KSS_data$daytime == 'mor')] + +mean(KSS_eve) +sd(KSS_eve) + +mean(KSS_mor) +sd(KSS_mor) + +KSS_data$KSS <- factor(KSS_data$KSS, order = TRUE) + +head(KSS_data) + + +# ---------- Multinomial logistic regression for KSS --------------------- +# Does the number of responses per response type vary for different stimulation conditions +KSS_data$daytime <- relevel(KSS_data$daytime, ref = "eve") +m_KSS <- multinom(KSS ~ daytime, data = KSS_data) +summary(m_KSS) +exp(coef(m_KSS)) + + +# Check the Z-score for the model (wald Z) +z <- summary(m_KSS)$coefficients/summary(m_KSS)$standard.errors +z +p <- (1 - pnorm(abs(z), 0, 1))*2 +p + +Anova(m_KSS) + + +# load VAMS data + +VAMS_data <- read_excel("Suppl_Table1_VisualAnalogueMoodAnswers.xlsx") + +head(VAMS_data) + +VAMS_data$ID <- factor(VAMS_data$ID) +VAMS_data$daytime <- factor(VAMS_data$daytime) + + +VAMS_data$happysad = VAMS_data$happy - VAMS_data$sad +VAMS_data$calmtense = VAMS_data$calm - VAMS_data$tense +VAMS_data$energeticsleepy = VAMS_data$energetic - VAMS_data$sleepy + + +# mean and SD + +VAMS_happysad_eve = VAMS_data$happysad[which(VAMS_data$daytime == 'eve')] +VAMS_happysad_mor = VAMS_data$happysad[which(VAMS_data$daytime == 'mor')] + +VAMS_calmtense_eve = VAMS_data$calmtense[which(VAMS_data$daytime == 'eve')] +VAMS_calmtense_mor = VAMS_data$calmtense[which(VAMS_data$daytime == 'mor')] + +VAMS_energeticsleepy_eve = VAMS_data$energeticsleepy[which(VAMS_data$daytime == 'eve')] +VAMS_energeticsleepy_mor = VAMS_data$energeticsleepy[which(VAMS_data$daytime == 'mor')] + +mean(VAMS_happysad_eve) +sd(VAMS_happysad_eve) + +mean(VAMS_happysad_mor) +sd(VAMS_happysad_mor) + +mean(VAMS_calmtense_eve) +sd(VAMS_calmtense_eve) + +mean(VAMS_calmtense_mor) +sd(VAMS_calmtense_mor) + +mean(VAMS_energeticsleepy_eve) +sd(VAMS_energeticsleepy_eve) + +mean(VAMS_energeticsleepy_mor) +sd(VAMS_energeticsleepy_mor) + + +VAMS_data$happysad <- factor(VAMS_data$happysad, order = TRUE) +VAMS_data$calmtense <- factor(VAMS_data$calmtense, order = TRUE) +VAMS_data$energeticsleepy <- factor(VAMS_data$energeticsleepy, order = TRUE) + +head(VAMS_data) + + +# ---------- Multinomial logistic regression for happysad --------------------- + + +VAMS_data$daytime <- relevel(VAMS_data$daytime, ref = "eve") +m_happysad <- multinom(happysad ~ daytime, data = VAMS_data) +summary(m_happysad) +exp(coef(m_happysad)) + + +# Check the Z-score for the model (wald Z) +z <- summary(m_happysad)$coefficients/summary(m_happysad)$standard.errors +z +p <- (1 - pnorm(abs(z), 0, 1))*2 +p + +Anova(m_happysad) + + +# ---------- Multinomial logistic regression for calmtense --------------------- + + +VAMS_data$daytime <- relevel(VAMS_data$daytime, ref = "eve") +m_calmtense <- multinom(calmtense ~ daytime, data = VAMS_data) +summary(m_calmtense) +exp(coef(m_calmtense)) + + +# Check the Z-score for the model (wald Z) +z <- summary(m_calmtense)$coefficients/summary(m_calmtense)$standard.errors +z +p <- (1 - pnorm(abs(z), 0, 1))*2 +p + +Anova(m_calmtense) + + + +# ---------- Multinomial logistic regression for energeticsleepy --------------------- + + +VAMS_data$daytime <- relevel(VAMS_data$daytime, ref = "eve") +m_energeticsleepy <- multinom(energeticsleepy ~ daytime, data = VAMS_data) +summary(m_energeticsleepy) +exp(coef(m_energeticsleepy)) + + +# Check the Z-score for the model (wald Z) +z <- summary(m_energeticsleepy)$coefficients/summary(m_energeticsleepy)$standard.errors +z +p <- (1 - pnorm(abs(z), 0, 1))*2 +p + +Anova(m_energeticsleepy) + + diff --git a/Figures/Suppl_Table1_questionnaires.m b/Figures/Suppl_Table1_questionnaires.m deleted file mode 100644 index 1c15f6dd48c80412d7b2d857d4e6e54e3cea14d2..0000000000000000000000000000000000000000 --- a/Figures/Suppl_Table1_questionnaires.m +++ /dev/null @@ -1,72 +0,0 @@ -clear all; -close all; - -excel = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\KarolinskaSleepinessAnswers.xlsx'; -sheet = 'Sheet1'; - -[sub_excel sub_excel] = xlsread(excel,sheet,'A2:A19'); -KSS_eve = xlsread(excel,sheet,'B2:B19'); -KSS_mor = xlsread(excel,sheet,'C2:C19'); - -[h p_KSS ci stats_KSS] = ttest(KSS_mor,KSS_eve) - -m_eve = nanmean(KSS_eve) -m_mor = nanmean(KSS_mor) - -sd_eve = nanstd(KSS_eve) -sd_mor = nanstd(KSS_mor) - -%% - -clear all; -close all; - -excel = 'D:\Valeria\RSN\data\for_sharing\data_to_make_figures\VisualAnalogueMoodAnswers.xlsx'; -sheet = 'Sheet1'; - -[sub_excel sub_excel] = xlsread(excel,sheet,'A3:A20'); -happy_eve = xlsread(excel,sheet,'B3:B20'); -sad_eve = xlsread(excel,sheet,'C3:C20'); -calm_eve = xlsread(excel,sheet,'D3:D20'); -tense_eve = xlsread(excel,sheet,'E3:E20'); -energetic_eve = xlsread(excel,sheet,'F3:F20'); -sleepy_eve = xlsread(excel,sheet,'G3:G20'); - -happy_mor = xlsread(excel,sheet,'H3:H20'); -sad_mor = xlsread(excel,sheet,'I3:I20'); -calm_mor = xlsread(excel,sheet,'J3:J20'); -tense_mor = xlsread(excel,sheet,'K3:K20'); -energetic_mor = xlsread(excel,sheet,'L3:L20'); -sleepy_mor = xlsread(excel,sheet,'M3:M20'); - -happy_sad_eve = happy_eve - sad_eve; -calm_tense_eve = calm_eve - tense_eve; -energetic_sleepy_eve = energetic_eve - sleepy_eve; - -happy_sad_mor = happy_mor - sad_mor; -calm_tense_mor = calm_mor - tense_mor; -energetic_sleepy_mor = energetic_mor - sleepy_mor; - -[h p_happy_sad ci stats_happy_sad] = ttest(happy_sad_eve,happy_sad_mor) -[h p_calm_tense ci stats_calm_tense] = ttest(calm_tense_eve,calm_tense_mor) -[h p_energetic_sleepy ci stats_energetic_sleepy] = ttest(energetic_sleepy_eve,energetic_sleepy_mor) - -m_happy_sad_eve = nanmean(happy_sad_eve) -m_happy_sad_mor = nanmean(happy_sad_mor) - -m_calm_tense_eve = nanmean(calm_tense_eve) -m_calm_tense_mor = nanmean(calm_tense_mor) - -m_energetic_sleepy_eve = nanmean(energetic_sleepy_eve) -m_energetic_sleepy_mor = nanmean(energetic_sleepy_mor) - - -sd_happy_sad_eve = nanstd(happy_sad_eve) -sd_happy_sad_mor = nanstd(happy_sad_mor) - -sd_calm_tense_eve = nanstd(calm_tense_eve) -sd_calm_tense_mor = nanstd(calm_tense_mor) - -sd_energetic_sleepy_eve = nanstd(energetic_sleepy_eve) -sd_energetic_sleepy_mor = nanstd(energetic_sleepy_mor) -