NCSI: Developing Dynamic Functional Connectivity Analysis Tools for Functional MRI Data

Status	Completed
Mentor Name	Unal Zak Sakoglu
Mentor's XSEDE Affiliation	Research Allocation
Mentor Has Been in XSEDE Community	1-2 years
Project Title	Developing Dynamic Functional Connectivity Analysis Tools for Functional MRI Data
Summary	Dynamic Functional Connectivity of Functional Magnetic Resonance Imaging (fMRI) data has been developed in the last decade, with the seminal methods paper by Sakoglu et al. which was applied to schizophrenia fMRI data [1-4]. A MATLAB-based software toolbox named DynaConn was developed by the PI and his former research assistant student [5]. The DynaConn has been made freely available by the PI for the neuromainging community for research [6]; however; due to lack of funding and other resources, further software development and maintainence has not been possible and the toolbox's use by the has been limited. Specifically, the toolbox was developed for dynamic time-series analysis of independent component analysis (ICA) results of fMRI data; the toolbox needs to be developed for region/atlas-based analysis, which will be nicely complementary to ICA-based analysis. The neuroimaging community will greatly benefit from such toolbox which will be offered freely by the PI. Its further development will also facilitate region-based dynamic functional connectivity analyses of some existing fMRI data by the PI and the student assisting the PI in this project. Reference: [1] Sakoglu U, Calhoun VD, "Temporal Dynamics of Functional Network Connectivity at Rest: A Comparison of Schizophrenia Patients and Healthy Controls," Proc. 15th Annual Meeting of the Organization for Human Brain Mapping, Vol. 47, Suppl. 1, pp. S169, June 2009, San Francisco, CA. [2] Sakoglu U, Michael AM, Calhoun VD, "Classification of schizophrenia patients vs healthy controls with dynamic functional network connectivity," Proc. 15th Annual Meeting of the Organization for Human Brain Mapping, Vol. 47, Suppl. 1, pp. S57, June 2009, San Francisco, CA. [3] Sakoglu U, Calhoun VD, "Dynamic windowing reveals task-modulation of functional connectivity in schizophrenia patients vs healthy controls," Proc. 17th Annual Meeting of the International Society for Magnetic Resonance in Medicine, #3676, April 2009, Honolulu, HI. [4] Sakoglu U, Pearlson GD, Kiehl KA, Wang YM, Michael AM, Calhoun VD, "A Method for Evaluating Dynamic Functional Network Connectivity and Task-Modulation: Application to Schizophrenia," Magnetic Resonance Materials in Physics, Biology and Medicine (MAGMA), Special Issue on MR Imaging of Brain Networks, Vol. 23, pp. 351-366 (2010). [5] Esquivel J, Mete M, Sakoglu U, "DynaConn: A Software for Analyzing Brain's Dynamic Functional Connectivity from fMRI Data," Midsouth Computational Biology and Bioinformatics Society Conference (MCBIOS), March 2014, Stillwater, OK. [6] http://www.drsakoglu.com/p/dynaconndfctoolbox.html
Job Description	The student will work 10 hours/week during the course of the project and -read the necessary literature provided by the PI, -meet with the PI regularly, i.e. at least weekly, -download and understand the existing MATLAB-based DynaConn functions, -modify MATLAB functions to fix region-mode of DynaConn functions and any other functions if necessary, -analyse a sample fMRI dataset using DynaConn in region-mode, -write monthly progress reports, -help PI publish any results (this may go beyond the dates of the project) in conference or journals, -any other duties which may be assigned by the PI, for the project.
Computational Resources	XSEDE supercomputing resources will be utilized to upload and run the updated the DynaConn functions which will be implemented in MATLAB. The PI has already access to TACC via EXSEDE until 02/2021, therefore existing access will be utilized; however, if necessary, new EXSEDE resources may be requested.
Contribution to Community
Position Type	Apprentice
Training Plan	The PI is currently training a volunteer undergraduate student at UHCL on magnetic resonance imaging data (MRI and fMRI) and basic MATLAB programming. The student is willing to continue to work with the PI to work on DynaConn in Fall 2020 and to do fMRI . Upon successful approval of the proposed project by XSEDE EMPOWER, the student will take any required available XSEDE trainings, including XSEDE HPC workshop (UHCL has also been a location of this training). The PI will continue to train the student on MRI data analysis using intermediate/advanced MATLAB programming, and will train the student on basics of dynamic functional connectivity and time-series analysis of fMRI data. The student is also expected to take XSEDE Big Data Analysis workshop, or a related workshop or course in lieu, if available. Intermediate skills of MATLAB programming, as well as working fundamental knowledge of linear algebra, statistics, and signals and systems is expected.
Student Prerequisites/Conditions/Qualifications	Intermediate MATLAB programming skills. Positive attitude, proactivity, willingness to learn, good math and analytical thinking skills, great communication skills.
Duration	Semester
Start Date	09/14/2020
End Date	12/04/2020