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Structural-Functional Brain Connectivity Underlying Integrative Sensorimotor Function After Stroke Benjamin Thomas Kalinosky Marquette University

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Structural-Functional Brain Connectivity Underlying Integrative Sensorimotor Function After Stroke Benjamin Thomas Kalinosky Marquette University Marquette University e-Publications@Marquette Dissertations (2009 -) Dissertations, Theses, and Professional Projects Structural-Functional Brain Connectivity Underlying Integrative Sensorimotor Function After Stroke Benjamin Thomas Kalinosky Marquette University Recommended Citation Kalinosky, Benjamin Thomas, "Structural-Functional Brain Connectivity Underlying Integrative Sensorimotor Function After Stroke" (2016). Dissertations (2009 -). Paper 616. http://epublications.marquette.edu/dissertations_mu/616 STRUCTURAL-FUNCTIONAL BRAIN CONNECTIVITY UNDERLYING INTEGRATIVE SENSORIMOTOR FUNCTION AFTER STROKE by Benjamin T. Kalinosky, B.S. A Dissertation submitted to the Faculty of the Graduate School, Marquette University, in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Milwaukee, Wisconsin May 2016 ABSTRACT STRUCTURAL-FUNCTIONAL BRAIN CONNECTIVITY UNDERLYING INTEGRATIVE SENSORIMOTOR FUNCTION AFTER STROKE Benjamin T. Kalinosky, B.S. Marquette University, 2016 In this dissertation research project, we demonstrated the relationship between the structural and functional connections across the brain in stroke survivors. We used this information to predict arm function in stroke survivors, suggesting that the tools developed through this research will be useful for prescribing individualized rehabilitation strategies in people after stroke. Current clinical methods for rehabilitating sensorimotor function after stroke are not based on the locus of injury in the brain. Instead, therapies are generalized, treating symptoms such as weakness and spasticity. This results in outcomes that are highly variable, with severity of impairment immediately following stroke as the best predictor of recovery. By using measures of brain structural and functional relations, we can better prognosticate and plan rehabilitation interventions. This research study utilized diffusion and functional magnetic resonance imaging (MRI) to quantify anatomical connectivity and functional networks of the brain after stroke. In the first aim, diffusion MRI was used to track the white matter pathways throughout the entire brain. A new imaging biomarker sensitive to stroke lesions was developed that quantifies the level of anatomical connections between every point in the brain. It was found that cortical areas most responsible for integration of sensorimotor and multisensory integration were the best predictors of motor impairments in chronic stroke subjects. Our second aim investigated the role of multisensory integration during sensorimotor control in healthy adults and stroke survivors. A novel functional MRI task paradigm involving wrist movement was developed to gain insight into the effects of multimodal sensory feedback on brain functional networks in stroke subjects. We found that the loss of functional interactions between the cerebellum and lesioned sensorimotor area were correlated with loss of movement function. Our final aim investigated the relationship between structural and functional connectivity after stroke. A model that marries diffusion MRI fiber tracking and resting-state functional MRI was designed to enhance indirect functional connections with structural information. The technique was capable of detecting changes in cortical networks that were not seen in functional or structural analysis alone. In conclusion, structure is essential to functional networks and ultimately, recovery of functional movements after stroke. i ACKNOWLEDGEMENTS Benjamin T. Kalinosky, B.S. Dr. Brian D. Schmit has been a great mentor. He is the embodiment of outstanding. I would like to thank Mary Wesley for being extremely helpful. My family has kept me alive. I thank God for them. I would also like to thank everyone in the Integrated Neural Engineering and Rehabilitation Laboratory (INERL) for their assistance in pilot experiments, feedback at lab meetings, and fellowship. Dr. Sheila Schindler-Ivens and Dr. Nutta-on Promjunyakul collected the data used in my first aim. Dr. Reivian Berrios completed the clinical assessments in my second two aims. I am honored to have had a PhD committee of rock stars, including Dr. Scott Beardsley, Dr. Peter LaViolette, Dr. Tugan Muftuler, Dr. Christopher Pawela, Dr. Sheila Schindler-Ivens, and Dr. Taly Gilat-Schmidt. They provided me with excellent feedback over the last few years. ii TABLE OF CONTENTS ABSTRACT ......................................................................................................................... i ACKNOWLEDGEMENTS ................................................................................................. i TABLE OF CONTENTS .................................................................................................... ii LIST OF FIGURES ......................................................................................................... viii LIST OF TABLES ............................................................................................................ vii CHAPTER 1 : INTRODUCTION & BACKGROUND ..................................................... 1 1.1 THESIS STATEMENT ................................................................................... 1 1.2 IMPAIRMENT AND RECOVERY OF MOTOR FUNCTION AFTER STROKE .......................................................................................................... 1 1.2.1 Neurophysiology of an infarct .......................................................... 1 1.2.2 Neural basis of sensorimotor impairments after stroke .................... 2 1.2.3 Neural plasticity following stroke ..................................................... 3 1.3 NEURAL MECHANISMS IN SENSORY INTEGRATION AND MOVEMENT .................................................................................................. 4 1.3.1 Sensorimotor and multisensory integration ...................................... 4 1.4 MAGNETIC RESONANCE IMAGING ......................................................... 7 1.4.1 The MRI Signal................................................................................. 7 1.5 DIFFUSION MRI OF WHITE MATTER ....................................................... 8 1.5.1 Diffusion-weighted MRI ................................................................... 8 1.5.2 Diffusion anisotropy in white matter ................................................ 9 1.5.3 Models for fiber orientation ............................................................ 10 1.5.4 Tractography ................................................................................... 11 1.6 STRUCTURAL CONNECTIVITY............................................................... 13 1.7 FUNCTIONAL MRI OF GRAY MATTER ................................................. 13 1.7.1 Neuronal activity and the BOLD signal .......................................... 13 iii 1.7.2 Functional MRI acquisition ............................................................ 14 1.7.3 Slice-time correction, motion correction, detrending ..................... 14 1.8 FUNCTIONAL CONNECTIVITY .............................................................. 16 1.8.1 Correlation-based Functional Connectivity .................................... 16 1.8.2 Independent Component Analysis .................................................. 16 1.9 STRUCTURAL AND FUNCTIONAL BRAIN NETWORKS ................... 17 1.9.1 Human Connectome........................................................................ 17 1.9.2 Predicting function from structure .................................................. 18 1.9.3 Structure-function relationship in plasticity after stroke ................ 18 1.10 IMAGING BIOMARKERS IN STROKE ................................................... 19 1.10.1 Diffusion MRI ............................................................................... 19 1.10.2 Functional MRI ............................................................................. 19 1.10.3 Personalized rehabilitation based on network models .................. 20 1.11 SPECIFIC AIMS ......................................................................................... 20 1.11.1 AIM 1: Determine whether full brain white matter structural connectivity can predict motor impairment in chronic stroke. ..... 21 1.11.2 AIM 2: Show that functional connectivity underlying sensorimotor and multisensory integration is associated with motor function after stroke. ................................. 21 1.11.3 AIM 3: Demonstrate the relationship between resting-state cortical networks and their anatomical connections in chronic stroke survivors. ............................................................... 22 CHAPTER 2 : WHITE MATTER STRUCTURAL CONNECTIVITY IS ASSOCIATED WITH SENSORIMOTOR FUNCTION IN STROKE SURVIVORS .................................................................................................................... 23 2.1 INTRODUCTION .......................................................................................... 23 2.2 METHODS ..................................................................................................... 26 2.2.1 Data Collection ............................................................................... 26 iv 2.2.2 Subject-Specific Data Processing ................................................... 31 2.3 RESULTS ....................................................................................................... 44 2.3.1 Comparison of VISC, fiber count, and mean fiber length .............. 44 2.3.2 Weak correlations of FA
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