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diff --git a/LogisticRegressionFramework/RSCHMM_PickAlpha.m b/LogisticRegressionFramework/PostProcessing/RSCHMM_PickAlpha.m
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diff --git a/LogisticRegressionFramework/RSCHMM_Generate_Coefficients.m b/LogisticRegressionFramework/Simulations/Miscellaneous/RSCHMM_Generate_Coefficients.m
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diff --git a/OtherApproaches/RSCHMM_SolveCS.m b/OtherApproaches/CSD_EC/RSCHMM_SolveCS.m
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diff --git a/OtherApproaches/SparseECfinder/ReadMe.txt b/OtherApproaches/CSD_EC/ReadMe.txt
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diff --git a/OtherApproaches/SparseECfinder/con_finder.m b/OtherApproaches/CSD_EC/con_finder.m
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diff --git a/OtherApproaches/PPA.m b/OtherApproaches/PPA_FC/PPA.m
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diff --git a/Script_Figure1.m b/Script_Figure1.m
deleted file mode 100644
index 0941a8f..0000000
--- a/Script_Figure1.m
+++ /dev/null
@@ -1,54 +0,0 @@
-%% Plots for Figure 2
-close all
-
-% The time courses
-figure;
-set(gcf,'color','w');
-imagesc(TC{1}(:,1:200));
-
-CM = cbrewer('div','RdBu',1001);
-%CM(501,:) = [1,1,1];
-colormap(flipud(CM));
-caxis([-6 6]);
-
-set(gca,'Box','off');
-
-% The ground truth matrices
-figure;
-set(gcf,'color','w');
-imagesc(Gamma_GT);
-axis off
-axis square
-colormap(flipud(CM));
-caxis([-1,1]);
-
-figure;
-set(gcf,'color','w');
-imagesc(Beta_GT_regions);
-axis off
-axis square
-colormap(flipud(CM));
-caxis([-1,1]);
-
-% The bar plots for density
-figure;
-set(gcf,'color','w');
-bar(1:R,Density_coact);
-xlim([0,R+1]);
-set(gca,'Box','off');
-
-figure;
-set(gcf,'color','w');
-bar(1:R,Density_causal);
-xlim([0,R+1]);
-set(gca,'Box','off');
-
-
-% The network-level graph
-[Graph] = RSCHMM_ConstructPopulationGraph(Beta_GT_regions,Figure3_GT,N);
-
-
-
-
-
-
diff --git a/readme.rtf b/readme.rtf
new file mode 100644
index 0000000..6213e3b
--- /dev/null
+++ b/readme.rtf
@@ -0,0 +1,22 @@
+{\rtf1\ansi\ansicpg1252\cocoartf1504\cocoasubrtf830
+{\fonttbl\f0\fswiss\fcharset0 Helvetica;}
+{\colortbl;\red255\green255\blue255;\red25\green25\blue25;}
+{\*\expandedcolortbl;;\cssrgb\c12941\c12941\c12941;}
+\paperw11900\paperh16840\margl1440\margr1440\vieww10800\viewh8400\viewkind0
+\pard\tx566\tx1133\tx1700\tx2267\tx2834\tx3401\tx3968\tx4535\tx5102\tx5669\tx6236\tx6803\pardirnatural\partightenfactor0
+
+\f0\fs24 \cf0 The present folder contains all the required MATLAB scripts and functions to run the sparse logistic regression (SLR) framework introduced in Bolton et al.\'92s \'93\cf2 \expnd0\expndtw0\kerning0
+Sparse coupled logistic regression to estimate co-activation and modulatory influences of brain regions\'94 (presently submitted to Journal of Neuroengineering).\
+\
+The \'93*_Figurei.m\'94 scripts contain the codes to reproduce Figures 2 to 5 from the paper.\
+\
+The \'93_Simulations_Figurei.m\'94 scripts contain the codes to run the simulations presented in Figures 2 to 4 from the paper.\
+\
+The \'93_Computations_Figurei.m\'94 scripts contain the codes to perform the computations on the generated simulations for Figures 2 to 4 of the paper.\
+\
+The \'93LogisticRegressionFramework\'94 folder contains all the MATLAB functions required to summon the SLR framework and associated utilities. Within this folder, the \'93Framework\'94 sub-folder contains the SLR routines themselves. The \'93Miscellaneous\'94 and \'93OlderImplementations\'94 folders are not required to run the latest version of the pipeline.\
+The \'93Plotting\'94 sub-folder contains utilities to graphically investigate some of the model\'92s outputs.\
+The \'93PostProcessing\'94 sub-folder contains the codes that perform further computations from the coefficients themselves (e.g., converting them into probabilistic couplings between pairs of regions).\
+The \'93Simulations\'94 sub-folder contains the codes needed to run the simulations presented in the article. The \'93Miscellaneous\'94 folder can be discarded, as it contains unused alternative attempts at simulating.\
+\
+The \'93OtherApproaches\'94 folder contains the MATLAB functions used to perform computations with other approaches, compared to the SLR framework in the paper\'92s Figure 4.}
\ No newline at end of file