This repository contains all the codes required to run our sparse coupled logistic regression framework.

Diffusion Sparse coupled logistic regression (master)

# Recent Commits

Recent Commits

Commit | Author | Details | Committed | ||||
---|---|---|---|---|---|---|---|

1f50b9a012ab | Thomas Bolton | Finished adjusting the guided script; the content should now be understandable… | Jun 11 | ||||

236f8ba97023 | Thomas Bolton | Simulation scripts are now well commented and properly architectured | Jun 11 | ||||

65052593ddc4 | Thomas Bolton | Clarifying the simulation scripts... | Jun 11 | ||||

6ab86d197383 | Thomas Bolton | Added some forgotten utilities | Jun 11 | ||||

ed5475e0691f | Thomas Bolton | Adding an example dataset (used in Figure 2) | Jun 11 | ||||

98f59babc8bc | Thomas Bolton | Improving the content to make it clearer to the new user... | Jun 11 | ||||

c5f5e4464253 | Thomas Bolton | Re-organised to clarify the content (ongoing) | Jun 11 | ||||

bb18ee5f9edd | Thomas Bolton | Added files for the framework | Jun 9 | ||||

68ccf309b343 | Thomas Bolton | Removed old file versions | Jun 9 | ||||

6839a4b65145 | Thomas Bolton | Latest | Oct 11 2018 | ||||

37cb3356dc70 | Thomas Bolton | no message | Sep 26 2018 | ||||

c4dd9e32c182 | Thomas Bolton | Preprocessing files for the HCP data... | Sep 26 2018 | ||||

a4b11526e2f7 | Thomas Bolton | aaa | Sep 26 2018 |

# readme.rtf

readme.rtf

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\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 \'93RSCHMM_Simulations_Figure*.m\'94 scripts contain the codes to generate the simulations presented in Figures 2 to 5 from the paper.\

\

The \'93RSCHMM_Computations*.m\'94 scripts shows all the codes to perform the computations of the SLR framework, step by step, and also displays some example plotting utilities. Looking at this script should be enough to get a good sense of all the steps of the SLR pipeline.\

\

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 in there 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 in there can be discarded, as it contains unused alternative attempts at simulating.\

\

The \'93Script_OtherApproaches.m\'94 script shows how to extract co-activation or causal coefficient matrices with the four approaches compared to our SLR framework: the graphical lasso, a point-process analysis, a multivariate autoregressive model, or a cross-spectral density-based approach.\

\

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.}

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\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 \'93RSCHMM_Simulations_Figure*.m\'94 scripts contain the codes to generate the simulations presented in Figures 2 to 5 from the paper.\

\

The \'93RSCHMM_Computations*.m\'94 scripts shows all the codes to perform the computations of the SLR framework, step by step, and also displays some example plotting utilities. Looking at this script should be enough to get a good sense of all the steps of the SLR pipeline.\

\

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 in there 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 in there can be discarded, as it contains unused alternative attempts at simulating.\

\

The \'93Script_OtherApproaches.m\'94 script shows how to extract co-activation or causal coefficient matrices with the four approaches compared to our SLR framework: the graphical lasso, a point-process analysis, a multivariate autoregressive model, or a cross-spectral density-based approach.\

\

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.}

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