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glass_brain_connectivity_2.m
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glass_brain_connectivity_2.m
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%% STEP 7: CREATING FIGURES
load('D:\Abhinav_Sharma\RS_peri_MEGLFP\brainstorm_db\MEG_LFP_peri\anat\@default_subject\tess_cortex_pial_low')
atlas_name = 'Mindboggle';
atlas_number = 6;
if ~strcmpi(atlas_name,Atlas(atlas_number).Name)
error('Check for valid atlas number')
end
ROIs = [3,4,5,6,11,12,15,16,19,20,21,22,23,24,25,26,27,28,29,30,...
33,34,35,36,37,38,41,42,45,46,47,48,51,52,53,54,55,56,57,58,59,60];
myLabel = cell(length(ROIs));
for i =1:1:length(ROIs)
myLabel{i} = Atlas(atlas_number).Scouts(ROIs(i)).Label;
end
total_parcellations = 12;
% Original ROI indices
contacts = [1,2,3,4,5,6];
contacts_right = [1,2,3];
contacts_left = flip([4,5,6]);
frontal = [7,8,11,12,21,22,23,24,25,26,33,34,35,36];
frontal_right = [8,12,22,24,26,34,36];
frontal_left = flip([7,11,21,23,25,33,35]);
medial_PFC = [1,2,15,16];
medial_PFC_right = [2,16];
medial_PFC_left = flip([1,15]);
temporal = [17,18,39,40];
temporal_right = [18,40];
temporal_left = flip([17,39]);
sensory_motor = [27,28,29,30];
sensory_motor_right = [28,30];
sensory_motor_left = flip([27,29]);
parietal = [5,6,19,20,31,32,37,38,41,42];
parietal_right = [6,20,32,38,42];
parietal_left = flip([5,19,31,37,41]);
visual = [3,4,9,10,13,14];
visual_right = [4,10,14];
visual_left = flip([3,9,13]);
re_ROIs = [visual_right,parietal_right,sensory_motor_right,temporal_right,medial_PFC_right,frontal_right,frontal_left,medial_PFC_left,temporal_left,sensory_motor_left,parietal_left,visual_left];
parc_lengths = [length(contacts_right),length(visual_right),length(parietal_right),length(sensory_motor_right),...
length(temporal_right),...
length(medial_PFC_right),length(frontal_right),length(frontal_left),length(medial_PFC_left),...
length(temporal_left),length(sensory_motor_left),length(parietal_left),length(visual_left),...
length(contacts_left)];
parc_color_nums = [1,7,6,5,4,3,2,2,3,4,5,6,7,1];
% Original indices of the Atlas Scouts
re_ROIs_2 = ROIs(re_ROIs);
% Create custom node labels
myLabel_2 = cell(length(re_ROIs) + 6);
for i = 1:3
myLabel_2{i} = ['contact_right' num2str(i)];
end
for i = 46:48
myLabel_2{i} = ['contact_left' num2str(i)];
end
for i =4:1:45
myLabel_2{i} = Atlas(atlas_number).Scouts(re_ROIs_2(i-3)).Label;
end
% Indices in the 48x48 matrix
re_ROIs_48_index = re_ROIs + 6;
re_ROIs_48_index_complete = [1:3,re_ROIs_48_index,4:6];
%% Node colors for schemaball
% 48 X 3
colors = lines(7);
colr_mat_2 = zeros(48,3);
begin_index = 1;
for tp = 1:(total_parcellations + 2)
colr_mat_2(begin_index:begin_index+parc_lengths(tp)-1,:) = repmat(colors(parc_color_nums(tp),:),[length(begin_index:begin_index+parc_lengths(tp)-1),1]);
begin_index = begin_index + parc_lengths(tp);
end
colr_mat_2_orig = colr_mat_2;
%% RING PLOTS
% Selecting significant connections
P_VALUE = input('enter your desired p-value for testing');
open view_surface_matrix
waitfor(msgbox('In the view_surface_matrix function manually set SurfAlpha to 0.7 and save'));
K = 6;
ndim = 48;
total_band_num = 3;
cortex = [7;48];
lfp_pos = [1;6];
mask_connections = 0;
within_state = 0;
threshold = 1;
fitmt_group_fact = fitmt_group_fact_4b;
% Mean activation/coherence across all states
if total_band_num == 1
Band_tag = 'Wideband';
M = zeros(ndim);
M_psd = zeros(ndim);
for k = 1:K
M = M + squeeze(abs(fitmt_group_fact_4b.state(k).coh(1,:,:))) / K;
M_psd = M_psd + squeeze(abs(fitmt_group_fact.state(k).psd(1,:,:))) / K;
end
end
for k = 1:1:K
for band = 1:1:total_band_num
% WITHIN A BAND BUT FOR ALL STATES FOR THIS BAND
if total_band_num > 1
Band_tag = 'Fourband';
M = zeros(ndim);
M_psd = zeros(ndim);
% Mean activation/coherence across all states
if ~within_state
for k1 = 1:K
M = M + squeeze(abs(fitmt_group_fact.state(k1).coh(band,:,:))) / K;
M_psd = M_psd + squeeze(abs(fitmt_group_fact.state(k1).psd(band,:,:))) / K;
end
end
if within_state
M = zeros(ndim);
M_psd = zeros(ndim);
% Within this state(k) taking mean across all the bands.
% We will subtract this mean from the connections across all states
% and plot the connections
for band1 = 1:total_band_num
M = M + squeeze(abs(fitmt_group_fact.state(k).coh(band1,:,:))) / total_band_num;
M_psd = M_psd + squeeze(abs(fitmt_group_fact.state(k).psd(band1,:,:))) / total_band_num;
end
end
end
coherence_value = squeeze(abs(fitmt_group_fact.state(k).coh(band,:,:)));
% PSD controls the size of the schemaball nodes
% Subtracting the mean PSD calculated across states or within
% states for the psd values for the current state and the band
psd_amp_centered = diag(squeeze(fitmt_group_fact.state(k).psd(band,:,:))) - diag(M_psd);
schemaball_size = 20*ones(48,1);
[r_schm,c_schm] = find(schemaball_size <= 0);
colr_mat_2_schm = colr_mat_2_orig;
% Coherence values for connectivity plot
graph = coherence_value;
%Subtract the mean across states from the current state
%coherence matrix
graph = (graph - M);
if mask_connections
mask = NaN(ndim,ndim);
mask(lfp_pos(1):lfp_pos(2),cortex(1):cortex(2)) = ...
ones(length(lfp_pos(1):lfp_pos(2)),...
length(cortex(1):cortex(2)));
mask(cortex(1):cortex(2),lfp_pos(1):lfp_pos(2)) = ...
ones(length(cortex(1):cortex(2)),length(lfp_pos(1):lfp_pos(2))...
);
graph = graph.*mask;
end
tmp = squash(tril(graph));
inds2 = find(tmp>1e-10);
% inds2 = find(abs(tmp) >1e-10);
data = tmp(inds2);
if ~exist('mask','var')
mask = ones(ndim,ndim);
end
if (~isempty(data) && (length(find(mask == 1)) > 36 ) && threshold)
S2 = [];
S2.data = data;
S2.do_fischer_xform = false;
S2.do_plots = 0;
S2.pvalue_th = P_VALUE/length(S2.data); %(Division corrects for multiple corrections)
graph_ggm = teh_graph_gmm_fit(S2);
th = graph_ggm.normalised_th;
graph = graph_ggm.data';
graph(graph<th) = NaN;
graphmat = zeros(ndim, ndim);
graphmat(inds2) = graph;
graph = graphmat;
else
if threshold
graphmat = NaN(ndim, ndim);
graph(graph < 0 | graph == 0) = 0;
graph(21,22) = 0.05;
end
graph(graph < 0 | graph == 0) = 0;
end
graph(isnan(graph)) = 0;
graph_schemaball = graph;
graph_schemaball = normalize(graph_schemaball,1,'range',[0 1]);
graph = tril(graph);
if ndim == 48
graph2 = graph + graph';
graph2 = graph2(re_ROIs_48_index_complete,re_ROIs_48_index_complete);
graph2 = tril(graph2);
graph_schemaball = normalize(graph2,1,'range',[0 1]);
end
glass_brain_connectivity
end
end