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The Behavioral and Neurophysiological Effects of Music Training on Cognitive and Motor

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The Behavioral and Neurophysiological Effects of Music Training on Cognitive and Motor The behavioral and neurophysiological effects of music training on cognitive and motor inhibition in aging adults by Patricia Izbicki A dissertation proposal submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Neuroscience Program of Study Committee: Elizabeth Stegemöller, Major Professor Mack Shelley Ann Smiley Christina Svec Auriel Willette The student author, whose presentation of the scholarship herein was approved by the program of study committee, is solely responsible for the content of this dissertation. The Graduate College will ensure this dissertation is globally accessible and will not permit alterations after a degree is conferred. Iowa State University Ames, Iowa 2020 Copyright © Patricia Izbicki, 2020. All rights reserved. ii TABLE OF CONTENTS Page LIST OF FIGURES iv LIST OF TABLES vi ACKNOWLEDGEMENTS viii ABSTRACT x CHAPTER 1: BACKGROUND 1 1.1 General Introduction 1 1.2 Inhibitory Control – A Brief History 3 1.3 Cognitive Inhibition 5 1.3.1 Behavior and Brain 6 1.4 Motor Inhibition 11 1.4.1 Behavior and Brain 11 1.5 Relevance of Studying Cognitive and Motor Inhibition 18 1.6 Aging 19 1.6.1 Aging and Cognition 20 1.6.2 Aging and Motor Control 21 1.6.3 Aging and Neurophysiology 22 1.6.4 Aging and Cognitive Inhibition 25 1.6.5 Aging and Motor Inhibition 28 1.7 Musicians vs. Non-Musicians Throughout the Lifespan 31 1.7.1 Behavioral & Neurophysiological in Young Adult Musicians 31 1.7.2 Behavioral & Neurophysiological Differences in Cognitive Inhibition in Young Adult Musicians 34 1.7.3 Behavioral & Neurophysiological Differences in Motor Inhibition in Young Adult Musicians 35 1.7.4 Behavior & Neurophysiology in Older Adult Musicians 36 1.7.5 Behavioral & Neurophysiological Differences in Cognitive Inhibition in Older Adult Musicians 39 1.7.6 Behavioral & Neurophysiological Differences in Motor Inhibition in Older Adult Musicians 40 1.8 Why Music Training as an Alternative Strategy to Combat Aging 41 1.9 Why Does Music Training Work? Potential Mechanisms of Music Training 42 iii CHAPTER 2: EXPERIMENT 1 45 2.1 Background 45 2.2 Methods 48 2.2.1 Participants 48 2.2.2 Stimuli 50 2.2.3 Procedure 50 2.3 Results 52 2.4 Discussion 69 CHAPTER 3: EXPERIMENT 2 76 3.1 Background 76 3.2 Methods 78 3.2.1 Participants 78 3.2.2 Procedure 80 3.3 Results 83 3.4 Discussion 88 CHAPTER 4: EXPERIMENT 3 93 4.1 Background 93 4.2 Methods 96 4.2.1 Participants 96 4.2.2 Stimuli 98 4.2.3 Procedure 98 4.3 Results 102 4.4 Discussion 114 CHAPTER 5: EXPERIMENT 4 122 5.1 Background 122 5.2 Methods 125 5.2.1 Participants 125 5.2.2 Stimuli 127 5.2.3 Procedure 127 5.3 Results 128 5.4 Discussion 134 CHAPTER 6: GENERAL DISUCSSION 138 6.1 Summary 138 6.2 Aim 1 139 6.3 Aim 2 139 6.4 Implications for Music Training in Healthy Aging 140 6.5 Conclusions 141 REFERENCES 143 APPENDIX: INFORMED CONSENT/IRB APPROVAL 174 iv LIST OF FIGURES Figure 1: Inhibition in Aging Behavior and Brain 1 Figure 2: Separation of Inhibition into Cognitive and Behavioral Inhibition 5 Figure 3: Example of Incongruent Stimuli in the Stroop Task 7 Figure 4: Meta-Analysis Results for Cognitive Inhibition 8 Figure 5: Example of P300 Waveform 10 Figure 6: Meta-Analysis Results for Motor Inhibition 13 Figure 7: Functional Connectivity During Motor Inhibition 14 Figure 8: Motor Inhibition Schema Involving Fronto-Striatal Connections 15 Figure 9: Transcranial Magnetic Stimulation 17 Figure 10: Stroop Results for Accuracy 54 Figure 11: Stroop Results for Response Time 55 Figure 12: Stroop Interference Results for Response Time 56 Figure 13: Stroop Interference Results for Response Time 57 Figure 14: P300 Latency Results for Fz 58 Figure 15: P300 Latency Results for Cz 59 Figure 16: P300 Latency Results for Pz 60 Figure 17: P300 Latency Results for F3 61 Figure 18: P300 Latency Results for F4 62 Figure 19: P300 Amplitude Results for Fz 63 Figure 20: P300 Amplitude Results for Cz 64 Figure 21: P300 Amplitude Results for Pz 65 Figure 22: P300 Amplitude Results for F3 66 v Figure 23: P300 Amplitude Results for F4 67 Figure 24: P300 Latency and Amplitude Result Summary 67 Figure 25: Pre-Background Electromyography Activity Results 85 Figure 26: Post-Background Electromyography Activity Results 85 Figure 27: Motor Evoked Potential Peak-to-Peak Electromyography Results 86 Figure 28: Inhibition Percent Results 87 Figure 29: Finger Tapping Accuracy Results 104 Figure 30: Finger Tapping Accuracy Difference Results 104 Figure 31: Spread of Finger Tapping Accuracy Difference Results 105 Figure 32: Pre-Background Electromyography Single-Pulse Activity Results 106 Figure 33: Pre-Background Electromyography Inhibition Activity Results 107 Figure 34: Post-Background Electromyography Single-Pulse Activity Results 108 Figure 35: Post-Background Electromyography Inhibition Activity Results 109 Figure 36: Motor Evoked Potential Peak-to-Peak Single-Pulse Activity Results 110 Figure 37: Motor Evoked Potential Peak-to-Peak Inhibition Activity Results 111 Figure 38: Inhibition Percent for Synchronization Results 112 Figure 39: Inhibition Percent for Syncopation Results 112 vi LIST OF TABLES Table 1: Healthy Young Adult Demographic Information (Experiment 1) 49 Table 2: Healthy Older Adult Demographic Information (Experiment 1) 49 Table 3: Stepwise Multiple Linear Regression for Incongruent Accuracy 68 Table 4: Stepwise Multiple Linear Regression for Incongruent Response Time 69 Table 5: Healthy Young Adult Demographic Information (Experiment 2) 80 Table 6: Healthy Older Adult Demographic Information (Experiment 2) 80 Table 7: Multiple Regression for Single-Pulse MEP 88 Table 8: Multiple Regression for SICI MEP 88 Table 9: Multiple Regression for Inhibition Percent 88 Table 10: Healthy Young Adult Demographic Information (Experiment 3) 97 Table 11: Healthy Older Adult Demographic Information (Experiment 3) 98 Table 12: Stepwise Multiple Linear Regression for Syncopated Accuracy 113 Table 13: Stepwise Multiple Linear Regression for Syncopated Accuracy Difference 114 Table 14: Healthy Young Adult Demographic Information (Experiment 4) 126 Table 15: Healthy Older Adult Demographic Information (Experiment 4) 126 Table 16: Stepwise Multiple Linear Regression for Behavioral Cognitive Inhibition 130 Table 17: Stepwise Multiple Linear Regression for Neural Cognitive Inhibition 131 Table 18: Stepwise Multiple Linear Regression for Neural Cognitive Inhibition 131 Table 19: Stepwise Multiple Linear Regression for Neural Cognitive Inhibition 132 Table 20: Stepwise Multiple Linear Regression for Neural Cognitive Inhibition 132 Table 21: Stepwise Multiple Linear Regression for Neural Cognitive Inhibition 132 Table 22: Stepwise Multiple Linear Regression for Behavioral Motor Inhibition 133 vii Table 23: Stepwise Multiple Linear Regression for Behavioral Cognitive Inhibition 133 Table 24: Predictors Associated with Behavioral Cognitive Inhibition 133 Table 25: Predictors Associated with Neural Cognitive Inhibition 134 Table 26: Predictors Associated with Neural Cognitive Inhibition 134 Table 27: Predictors Associated with Neural Cognitive Inhibition 134 viii ACKNOWLEDGEMENTS It truly takes a village to help a human achieve their dreams. This cannot be more evident for a dissertation. I’m the luckiest person in the world with the best village in the world. First, I would like to thank my major professor, Dr. Elizabeth Stegemöller, and my committee members, Dr. Mack Shelley, Dr. Ann Smiley, Dr. Christina Svec, Dr. Auriel Willette, for their time, efforts, and guidance through this journey. Thank you for allowing me the space and support to explore my interests and ideas in the arts and sciences. Dr. Stegemöller, I am especially grateful to you for your unlimited and exemplary kindness, patience, and generosity for the last five years. Second, I would like to thank my family. Monika and Krzysztof Izbicki, you instilled in me the work ethic, compassion, and humanity needed to thrive as a first generation Polish- American. Your sacrifices have allowed me to grow up in the land of opportunity and pursue my academic, musical, and athletic passions. Words cannot describe my eternal gratefulness. Dr. Hedi Salanki-Rubardt, I never would have considered completing a degree in Music Performance and a PhD in the field of neuroscience and music without your mentorship for the last 12 years. You will always be my role model as a scholar, harpsichordist, pianist, and, most importantly, an incredible human being. My First Baptist Church family, especially Mindy Radke Phomvisay, Julie Johnston, Susan Russell, and Dr. David Russell, thank you for loving me in my best and worst moments and letting me express and share my love for music. Third, I would like to thank all my supportive colleagues and friends who are like family to me. Dr. Sondra Ashmore, I never would have had the confidence and financial support to complete my PhD without your constant advocacy and mentorship on my behalf. Thank you for showing me the importance of being a great mentor and mentee. Dr. Matthew Jefferson, you ix were kind to me from the very first moment I arrived at Iowa State University. I am grateful our friendship has surpassed the test of time. Kasandra Diaz, your resilience in the face of adversity has inspired me to constantly strive to be better. Your advice and support as a lab mate and as a best friend have been incredible. Dr. Katheryn Friesen, after spending three weeks in Stockholm, Sweden teaching global leadership, I knew we were long lost sisters. I couldn’t have gotten through my last year of my PhD without you. Dr. Anthony Andenoro, thank you for instilling in me the importance of exceptional leadership and teaching, providing me with extraordinary leadership opportunities, and helping me take a step back to realize that life is a celebration and full of possibility every corner.
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