shuss006 / Dynamic_Connectivity_Analysis

This code utilizes inputs of fMRI data and ROI masks created in FSL in the form of nifti files to acquire the static and dynamic connectivity measurements between the ROIs in a network.

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Sana Hussain

Hello,

My name is Sana Hussain and I am a 3rd year PhD student at UC Riverside. I currently work under the advisement of Dr. Xiaoping Hu and Dr. Megan Peters. As part of my graduate studies I have written the above scripts in MATLAB which are briefly described below, and described in futher detail in the m files.

main_script.m calls extract_BOLD_signal.m to extract the BOLD signal from designated ROIs, while LC_analysis.m extracts the signal from an LC atlas used in our lab. It calls static_corrletion.m to perform a static correlation between the BOLD signal of ROIs, and calls dynamic_connectivity.m to analyze the dynamic functional connectivity using a sliding time window analysis. rest_filter.m is a bandpass filter. Included in the scrip is also code for a series of plots to visualize the results.

The second set of scripts (Bayesian_analysis.m and Bayesian_analysis_function.m) employ Bayes' rule to determine whether a subject squeezed a squeeze-ball given his/her network connectivity patterns.

Please feel free to contact me with any questions. Thank you!

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This code utilizes inputs of fMRI data and ROI masks created in FSL in the form of nifti files to acquire the static and dynamic connectivity measurements between the ROIs in a network.


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