NCSI: Application of Improved Dynamic Functional Connectivity Analysis Tool to Functional MRI Data

Status	Completed
Mentor Name	Unal Zak Sakoglu
Mentor's XSEDE Affiliation	Research Allocation; Current/Former EMPOWER PI
Mentor Has Been in XSEDE Community	1-2 years
Project Title	Application of Improved Dynamic Functional Connectivity Analysis Tool to 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; thus, 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. During a current XSEDE EMPOWER project in Fall 2020, the PI is supervising a senior undergraduate student to further improve the toolbox for region/atlas-based analysis, which will be nicely complementary to ICA-based analysis, and the neuroimaging community will greatly benefit from such an improved toolbox which will be offered freely by the PI. In this continuation of the project, the PI will supervise the student to apply and test extensively the improved toolbox to perform region-based dynamic functional connectivity analyses of an existing fMRI dataset that will be provided by the PI. 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, -modify and debug the legacy MATLAB-based DynaConn functions and the new ones that are being developed, -test and debug MATLAB functions to fix region-mode of DynaConn functions and any other functions when necessary, -test extensively the DynaConn in region-mode by applying it to a large fMRI dataset which will be provided by the PI, -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 may be utilized to upload, run, debg and test 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	The project will lead to i) a software product that can be more easily and freely used by the neuroimaging community; ii) potential findings from an fMRI dataset about how different conditions affect the functionaing of the human brain, iii) training of a student / future researcher in scientific programming and data analysis. Refinements (e.g. slides, exercises, code, and videos) from myself and suggestions made from the student will be added and shared with the greater community.
Position Type	Intern
Training Plan	The PI is currently supervising an XSEDE EMPOWER undergraduate student as an apprentice who is working on development and MATLAB implementation of the region-mode codes for the DynaConn tolbox during Fall 2020. Upon successful approval of the proposed continuation project by XSEDE EMPOWER, the student will take any further required trainings and will be briefed on the fMRI dataset to be used for testing and analysis and he will need to read some literature on the dataset and recent results. The PI has trained the student on MATLAB-based MRI/fMRI data analysis using intermediate/advanced MATLAB programming, and on the basics of dynamic functional connectivity and time-series analysis of fMRI data, and will continue to train the student throughout the project. The student may be required to continue to do training such as advanced level MATLAB online courses and XSEDE Big Data Analysis workshop or a related workshop or course in lieu, if available. Participation in this project and the related training will lead to development of advanced skills of MATLAB programming, as well as fundamental linear algebra, statistics, signal and image processing application skills to analyze and existing neuroimaging dataset.
Student Prerequisites/Conditions/Qualifications	Existing XSEDE EMPOWER student; with intermediate/advanced MATLAB programming skills.
Duration	Semester
Start Date	01/25/2021
End Date	05/21/2021