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Neural Correlates of Convergence Eye Movements in Convergence Insufficiency Patients vs. Normal Binocular Vision Controls: An fMRI Study A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Biomedical Engineering by Chirag B. Limbachia B.S.B.M.E., Wright State University, 2014 2015 Wright State University Wright State University GRADUATE SCHOOL January 18, 2016 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPER- VISION BY Chirag B. Limbachia ENTITLED Neural Correlates of Convergence Eye Movements in Convergence Insufficiency Patients vs. Normal Binocular Vision Controls: An fMRI Study BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIRE- MENTS FOR THE DEGREE OF Master of Science in Biomedical Engineering. Nasser H. Kashou Thesis Director Jaime E. Ramirez-Vick, Ph.D., Chair, Department of Biomedical, Industrial, and Human Factors Engineering Committee on Final Examination Nasser H. Kashou, Ph.D. Marjean T. Kulp, O.D., M.S., F.A.A.O. Subhashini Ganapathy, Ph.D. Robert E.W. Fyffe, Ph.D. Vice President for Research and Dean of the Graduate School ABSTRACT Limbachia, Chirag. M.S.B.M.E., Department of Biomedical, Industrial, and Human Factor En- gineering, Wright State University, 2015. Neural Correlates of Convergence Eye Movements in Convergence Insufficiency Patients vs. Normal Binocular Vision Controls: An fMRI Study. Convergence Insufficiency is a binocular vision disorder, characterized by reduced abil- ity of performing convergence eye movements. Absence of convergence causes, eye strain, blurred vision, doubled vision, headaches, and difficulty reading due frequent loss of place. These symptoms commonly occur during near work. The purpose of this study was to quantify neural correlates associated with convergence eye movements in convergence in- sufficient (CI) patients vs. normal binocular vision (NBV) controls, and to examine statisti- cal differences between them. Functional magnetic resonance imaging (fMRI) scans were collected using a 3T Siemens scanner. A disparity-driven convergence task was designed using a standard block design approach, and was presented to all the subjects as a visual stimulus. Subjects performed tasks of two difficulty levels; an easy and a hard convergence task. FMRI data was analyzed using fMRI Expert Analysis Tool (FEAT) in FSL software package, and statistical data obtained from the FEAT was further analyzed in JMP to as- sess significant factors and interactions. Results showed significantly higher activation in the regions of interest (ROI), both in spatial extent and amplitude, of the patients compared to the controls (z-score > 2.3, p< 0.05). JMP analysis showed, hard task elicited higher activation than the easy task, in both controls and patients. iii Contents 1 Introduction1 1.1 Purpose....................................1 1.2 What is Convergence Insufficiency (CI)?...................1 1.3 Prevalence of CI................................2 1.4 Symptoms...................................2 1.5 Diagnosis of CI................................3 1.5.1 Near Point of Convergence (NPC)..................3 1.5.2 Positive Fusional Vergence......................4 1.5.3 Exophoria at Near..........................5 1.5.4 CISS.................................6 1.6 Causes and Treatments............................7 1.6.1 Causes................................7 1.6.2 Treatments..............................7 1.7 Clinical Significance of CI..........................9 1.7.1 What is Binocular Vision?......................9 1.8 Motivation for Study............................. 10 1.8.1 Previous Findings........................... 10 1.8.2 Hypothesis.............................. 11 2 Background 12 2.1 What is Magnetic Resonance Imaging (MRI)?................ 13 2.1.1 MRI Physics............................. 14 2.1.2 Image Acquisition.......................... 22 2.1.3 Image Quality............................. 23 2.2 What is fMRI?................................ 23 2.2.1 Blood Oxygen Level Dependent (BOLD) Effect........... 26 2.3 fMRI Paradigms................................ 31 2.3.1 Block Design............................. 31 2.3.2 Event Related Design......................... 32 2.3.3 Mixed Design............................. 33 2.4 Analysis of fMRI Data............................ 33 2.4.1 Pre-processing............................ 33 iv 2.4.2 Statistics............................... 34 3 Methods 38 3.1 Subject Recruitment.............................. 38 3.1.1 Eligibility Criteria.......................... 38 3.1.2 Recruitment and Eligibility Testing................. 42 3.1.3 fMRI Scanner and Site Location................... 42 3.1.4 fMRI Setup.............................. 42 3.1.5 fMRI Data Acquisition........................ 43 3.1.6 fMRI Visual Stimuli......................... 44 4 Analysis 48 4.1 fMRI Expert Analysis Tool (FEAT)..................... 48 4.2 First Level FEAT Analysis.......................... 49 4.2.1 Preprocessing............................. 49 4.2.2 Processing.............................. 51 4.2.3 Post Processing............................ 52 4.3 Group Level FEAT Analysis......................... 53 4.3.1 Analysis of Easy & Hard Convergence Task............. 53 4.4 Talairach Client................................ 56 4.5 SAS JMP 11.................................. 57 5 Results 60 5.1 FEAT Results................................. 60 5.1.1 Easy Convergence Task....................... 60 5.1.2 Hard Convergence Task....................... 64 5.2 JMP Results.................................. 67 5.2.1 Analysis of Variance (ANOVA) & Effect Test of the Model..... 67 5.2.2 Factors................................ 67 5.2.3 Interactions.............................. 70 6 Conclusion 73 7 Future Work 75 Bibliography 76 A Appendix A 91 B Another Example Appendix 100 v List of Figures 1.1 PFV testing..................................4 2.1 Super Conduction MRI Scanner....................... 13 2.2 Gradient Coils & RF Head Coil........................ 14 2.3 Influence of B0 on Hydrogen Protons.................... 15 2.4 T1 & T2 Relaxation Curves.......................... 17 2.5 Slice Select Gradient............................. 20 2.6 K-Space to Image Space........................... 23 2.7 Voxels..................................... 24 2.8 MRI Images vs. fMRI Images........................ 26 2.9 Neurovascular Coupling........................... 27 2.10 BOLD Signal Generation........................... 28 2.11 BOLD Response to an Impulse Stimulus................... 29 2.12 HRF for Impulse Stimulus.......................... 30 2.13 HRF Convolution............................... 32 2.14 Different fMRI Paradigms.......................... 34 2.15 fMRI Data Example.............................. 37 3.1 Red/Blue 3D Glasses............................. 43 3.2 Visual Stimuli................................. 45 3.3 Stimuli Pattern................................ 46 4.1 Pipeline of First Level Analysis........................ 49 4.2 Group Level Analysis............................. 55 4.3 JMP Table................................... 59 5.1 Easy Task: Mean activation maps for controls and patients, in MFG and SFG 61 5.2 Easy Task: Mean activation maps for controls and patients, in LG and cuneus 62 5.3 Easy Task: Mean activation maps for controls and patients, in cerebellum.. 62 5.4 Easy Task: Patients vs. Controls unpaired t-test activation image...... 63 5.5 Hard Task: Mean activation maps for controls and patients, in MFG, SFG, and LG.................................... 64 5.6 Hard Task: Mean activation maps for controls and patients, in cuneus and cerebellum................................... 65 vi 5.7 Hard Task: Patients vs. Controls unpaired t-test image............ 65 5.8 ANOVA of Model............................... 67 5.9 Effect Test of Model.............................. 67 5.10 Tasks..................................... 68 5.11 Subjects.................................... 68 5.12 Connecting letter report for Regions..................... 69 5.13 Tasks-Subject Interaction........................... 70 5.14 Subjects-Regions Interaction......................... 71 5.15 Tasks-Regions Interaction........................... 72 A.1 Easy Task: Mean activation maps for controls and patients, in FEF...... 92 A.2 Easy Task: Mean activation maps for controls and patients, in DLPFC.... 92 A.3 Easy Task: Mean activation maps for controls and patients, PEF....... 93 A.4 Easy Task: Mean activation maps for controls and patients, SEF, cerebel- lum and midbrain................................ 93 A.5 Easy Task: Patients vs. Controls unpaired t-test image, FEF......... 94 A.6 Easy Task: Patients vs. Controls unpaired t-test image, DLPFC....... 94 A.7 Easy Task: Patients vs. Controls unpaired t-test image, PEF......... 95 A.8 Easy Task: Patients vs. Controls unpaired t-test image, SEF, cerebellum, and midbrain.................................. 95 A.9 Hard Task: Mean activation maps for controls and patients, FEF....... 96 A.10 Hard Task: Mean activation maps for controls and patients, in DLPFC.... 96 A.11 Hard Task: Mean activation maps for controls and patients, in PEF..... 97 A.12 Hard Task: Mean activation maps for controls and patients, in SEF, cere- bellum, and midbrain.............................. 97 A.13 Hard Task: Patients vs. Controls unpaired t-test image, FEF......... 98 A.14 Hard Task: Patients vs. Controls unpaired t-test image, DLPFC....... 98 A.15 Hard Task: Patients vs. Controls unpaired t-test image, PEF......... 99 A.16 Hard Task: Patients vs. Controls
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