Intersubj_pipeline/JOVE_Perform_Bootstrapping.m
1fe5fb1cead4master

JOVE_Perform_Bootstrapping.m
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			%% This function performs the ISFC bootstrapping scheme on a specific type
			% of session for a group of subjects
			%
			% Inputs:
			%
			% - TC contains the time courses of all sessions to jointly compute ISFC on
			% in a cell array format (each cell of size n_ROI x n_timepoints)
			% - Session_Label contains the index of the session of each recording; this
			% is used to include an equal number of samples from each session in the
			% reference group of the bootstrapping scheme
			% - W is the window length (in TR)
			% - S is the window step size (in TR)
			% - n_boot is the number of bootstrapping folds to perform
			% - n_refsubj is the number of subjects to use in the reference group at
			% each fold
			function [ISFC] = JOVE_Perform_Bootstrapping(TC,Session_Label,W,S,TR,n_boot,n_refsubj,hGroups,hISFC,hObject,handles)

			% Number of sliding window estimates that we will have according to W
			% (window length) and S (step size)
			n_swtp = floor((size(TC{1},2)-W)/S)+1;

			n_ROI = size(TC{1},1);
			n_conn = n_ROI*(n_ROI-1)/2;

			% Session indices present in this call
			sesvals = unique(Session_Label);

			% ISFC will contain the final ISFC estimates for all sessions
			% (one per cell)
			ISFC = cell(1,length(Session_Label));
			[ISFC{:}] = deal(zeros(n_conn,n_swtp));

			% Denom_factor will highlight, for each session, how many times ISFC
			% was computed on it (i.e., how many times it was not part of the
			% reference group out of the n_boot folds)
			Denom_factor = cell(1,length(Session_Label));
			[Denom_factor{:}] = deal(0);

			% tmp_denom will temporarily contain the information for a given fold,
			% with 1 highlighting sessions on which ISFC was computed
			tmp_denom = cell(1,length(Session_Label));
			[tmp_denom{:}] = deal(0);

			% idx_allsessions contains the indices of all included sessions, while
			% idx_sepsessions will contain all indices of session s in its cell s
			idx_allsessions = 1:length(Session_Label);
			idx_sepsessions = cell(1,length(sesvals));

			% n_recperses is the number of recordings that should be sampled, at
			% each fold, for each session index; it can be a non-integer value at
			% this point (e.g., 1.5 if we want to have 6 reference samples out of 4
			% different session subtypes)
			n_recperses = n_refsubj/length(sesvals);

			% We iterate over folds...
			for boot = 1:n_boot

			if boot == 1
			tic;
			end

			idx_inref = [];
			tmp_rand = 0;

			for s = 1:length(sesvals)

			% For each session subtype s, samples only the related indices
			% and permutes them into a random order
			idx_sepsessions{s} = idx_allsessions(Session_Label == sesvals(s));
			idx_sepsessions{s} = idx_sepsessions{s}(randperm(length(idx_sepsessions{s})));

			% For each session subtype s, picks how many samples should be
			% incorporated in the reference group
			if s == length(sesvals)
			tmp_rand(s) = n_refsubj-sum(tmp_rand);
			else
			tmp_rand(s) = randi([floor(n_recperses),ceil(n_recperses)]);
			end

			% Adds the sample indices from session subtype s to idx_inref
			idx_inref = [idx_inref,idx_sepsessions{s}(1:tmp_rand(s))];
			end

			clear tmp_rand

			% Sorts the selected indices in ascending order
			idx_inref = sort(idx_inref,'ascend');

			% idx_notinref contains all the indices of the sessions on which
			% ISFC will be computed at this fold (not in the reference)
			idx_notinref = 1:length(TC);
			idx_notinref(idx_inref) = [];

			% Selects the sessions in the reference group, and the ones not in
			% there
			tmp_ref = TC(idx_inref);
			tmp_notref = TC(idx_notinref);

			% Computes ISFC for tmp_notref, using tmp_ref as a reference
			% subgroup, for the current fold
			ISFC_onefold = ISFC_ToReferenceGroup(tmp_notref,tmp_ref,W,S);

			% We save the current fold output in tmp_cell, and sum it to the
			% ISFC variable (which keeps track of the sum of ISFC through all
			% folds)
			tmp_cell = cell(1,length(Session_Label));
			[tmp_cell{:}] = deal(zeros(n_conn,n_swtp));
			tmp_cell(idx_notinref) = ISFC_onefold;
			ISFC = cellfun(@(x,y) x+y,tmp_cell,ISFC,'UniformOutput',0);
			clear tmp_cell

			% At the same time, we also keep track of how many times each
			% subject belonged to the non-reference side in Denom_factor, which
			% is incremented as needed here
			tmp_denom(idx_notinref) = {1};
			Denom_factor = cellfun(@(x,y) x+y,tmp_denom,Denom_factor,'UniformOutput',0);
			[tmp_denom{:}] = deal(0);

			% Update the graphical layout
			hGroups = JOVE_PlotISFCGroups(hGroups,n_boot,cell2mat(Denom_factor));
			guidata(hObject,handles);

			pause(1);

			% Update the ISFC layout
			temporary_ISFC = cell(1,length(Session_Label));
			[temporary_ISFC{:}] = deal(zeros(n_conn,n_swtp));

			temporary_ISFC = cellfun(@(x,y) x/y,ISFC,Denom_factor,'UniformOutput',0);


			% Picks the largest variance time courses
			[tmp,IDX] = sort(sum(abs(temporary_ISFC{1}),2),'descend');


			IDX = IDX(~isnan(tmp));


			if Denom_factor{1} == 0
			else
			hISFC = JOVE_PlotAtlasTC(hISFC,temporary_ISFC{1},IDX(1:50),'ISFC',W,S,TR);
			end

			pause(1);

			if boot == 1
			time_onefold = toc;

			disp(['Estimated total run time: ',num2str((n_boot-1)*time_onefold),' seconds...']);
			end
			end

			% Averages the results; we divide by the number of times a given subject has
			% been included
			ISFC = cellfun(@(x,y) x/y,ISFC,Denom_factor,'UniformOutput',0);
			end

Intersubj_pipeline/JOVE_Perform_Bootstrapping.m1fe5fb1cead4master

JOVE_Perform_Bootstrapping.mView Options

Intersubj_pipeline/JOVE_Perform_Bootstrapping.m
1fe5fb1cead4master

JOVE_Perform_Bootstrapping.m
View Options