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A Probe Into the Dorsolateral Prefrontal Cortex in Alzheimer’S Disease

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A Probe Into the Dorsolateral Prefrontal Cortex in Alzheimer’S Disease Antisaccades: A Probe Into The Dorsolateral Prefrontal Cortex in Alzheimer’s Disease by Liam Kaufman Simpkins A thesis submitted in conformity with the requirements for the degree of Masters of Science Institute of Medical Science University of Toronto © Copyright by Liam Kaufman Simpkins 2008 Antisaccades: A Probe Into The Dorsolateral Prefrontal Cortex in Alzheimer’s Disease Liam Kaufman Simpkins Masters of Science Institute of Medical Science University of Toronto 2008 Abstract The number of people living with Alzheimer’s Disease (AD) is projected to increase dramatically over the next few decades, making the search for treatments and tools to measure the progression of AD increasingly urgent. The antisaccade task, a hands- and language-free metric, may provide a functional index of the Dorsolateral Prefrontal Cortex (DLPFC), which is damaged in the later stages of AD. Patients with AD make significantly more antisaccade errors than controls, however, performance in mild AD has remained unexplored. We hypothesized that mild patients will make more errors than controls. Thirty AD patients and 31 age-match controls completed both laptop-based and clinical versions of the antisaccade task. Two thirds of patients with AD made significantly more errors and corrected less of their errors than age-matched controls. Our findings indicate that antisaccade impairments exist in mild AD, suggesting DLPFC pathology may be present earlier than suggested by previous studies. ii Acknowledgments The completion of my M.Sc. thesis would not have been possible without the generous help of others. I would like to thank my supervisor, Sandra Black, for her tireless help and constant feedback. Sandy has demanded the most out of me, which has helped to improve both my ability to write and give presentations, skills that will be transferrable to where ever I end up. Second I would like to thank both Jay Pratt and Brian Levine for providing helpful feedback that strengthened my thesis and ultimately my understanding of the subject matter. I would like to acknowledge the efforts of Jen Brae who helped to recruit many of the participants who were included in this study. The LC Campbell Cognitive Neurology Unit has been integral in many aspects of my thesis and its members have provided me with helpful feedback! Julian Kirk-Elleker, thank-you for your wonderful illustration of the laptop-based antisaccade task. Mark Chiew, thank-you for developing an easy to use antisaccade application for the laptop. Cori Atlin helped with video coding and with coding criteria. The LC Cognitive Neurology Unit, Ontario Graduate Scholarship and the Scace Graduate Fellowship (OSOTF) provided the funding for my graduate work, thank you! Participants were part of CIHR funded project MT13129 held by Dr. Black. Lastly, I would like to thank my family for their support of my work, my decisions and my enthusiasm for different types of science. To my parents, Michael and Maureen, your scholarship has helped to guide my decisions, thank you. Lisa, my wife and best-friend, thank you for your never-ending support, feedback and your ability to keep me going! Liam iii Table of Contents List of Tables .................................................................................................vi List of Figures................................................................................................vii List of Abbreviations.....................................................................................viii Chapter 1: Rational and Objectives ............................................................1 1.1 Rationale 1.2 Objectives 1.2.1 Determine if mild AD patients make more antisaccade errors than age-matched controls 1.2.2 Determine if more errors are made on trials preceded by a trial of a different direction relative to trials preceded by a trial of the same direction Figure 1 – Same vs. Different Trials Chapter 2: Literature Review ......................................................................6 2.1 Alzheimer’s Disease Table 1 - Studies investigating antisaccade performance in Alzheimer’s Disease 2.2 The Antisaccade Task Figure 2 – Prosaccade And Antisaccade Tasks 2.3 Developmental Changes 2.4 Functional Imaging Studies 2.5 Focal Lesion Studies 2.6 Differentiating Alzheimer’s Disease From Healthy Aging Table 2 - Power Analysis and Differentiation Capabilities of the Antisaccade task in Alzheimer’s Disease 2.7 Antisaccade Errors and Dorsolateral Prefrontal Pathology in AD 2.8 Barriers in Adopting the Antisaccade Task as a Probe of DLPFC Function 2.9 The Antisaccade Task as an Index of Severity 2.10 Neuroimaging & Dementia 2.11 Fractionation of Processes in the Antisaccade Task 2.11.1 Fractioning the Antisaccade Task: Inhibition Control 2.11.2 Fractioning the Antisaccade Task: Fixation 2.11.3 Fractioning the Antisaccade Task: Vector Inversion 2.11.4 Fractioning the Antisaccade Task: Voluntary Saccades 2.12 Memory, Understanding & Attention 2.13 Task Sequence 2.14 Clinical Adaptation 2.15 Non-Alzheimer’s Dementia Table 3 - Studies investigating antisaccade performance in non-Alzheimer’s Dementia 2.16 Discussion 2.17 Conclusion Chapter 3......................................................................................................33 3.1 Background 3.2 Hypotheses 3.3 Methods 3.3.1 Study Participants 3.3.2 Saccade Tasks iv Figure 4 – Experimental Setup 3.3.3 Saccade Coding 3.3.4 Statistical Analysis 3.4 Results Table 4 - Demographics Table 5 – AD Neuropsychology Results Figure 5 – Antisaccade Errors and Uncorrected Errors Table 7 - Diagnostic Capacity of Antisaccade Metrics Figure 6 – Same Direction Errors Compared To Different Direction Errors 3.5 Discussion 3.6 Clinical Antisaccade Task 3.7 Antisaccade Errors Elevated in Mild AD 3.8 Dementia Severity and Antisaccade Error Rates 3.9 Antisaccade Errors On Same Relative To Different Direction Trials 3.10 Prosaccade Errors 3.11 Antisaccade Errors and Neuropsychology Chapter 4......................................................................................................57 4.1 Performance Monitoring and Task Setting Deficits 4.2 Clinical Relevance of The Antisaccade Task 4.3 Study Limitations 4.4 Future Directions 4.4.1 Fractionation: domain specific and domain general 4.4.2 Neural Correlates: Structural and Functional Imaging in Conjunction with Pathological Data 4.4.3 Large Scale Validation Of The Antisaccade Task In AD 4.4.4 Same Trials Versus Different Trials 4.5 Conclusions References ....................................................................................................66 v List of Tables 1. Studies investigating antisaccade performance in Alzheimer’s Disease – page 7 2. Power Analysis and Differentiation Capabilities of the Antisaccade task in Alzheimer’s Disease – page 16 3. Studies investigating antisaccade performance in non-Alzheimer’s Dementia – page 32 4. Demographics – page 44 5. AD Neuropsychology Results – page 44 6. Antisaccade Performance – page 46 7. Diagnostic Capacity of Antisaccade Metrics - page 47 vi List of Figures 1. Same vs. Different Trials - page 5 2. Prosaccade And Antisaccade Tasks – page 9 3. Laptop Prosaccade and Antisaccade Tasks - page 38 4. Experimental Setup - page 39 5. Antisaccade Errors and Uncorrected Errors - page 45 6. Same Direction Errors Compared To Different Direction Errors - page 48 vii List of Abbreviations AD – Alzheimer’s Disease AP - Amyloid Pathology BOLD - Blood Oxygen Level Dependent CBD - Corticobasal Syndrome DTI - Diffusion Tensor Imaging DLPFC – Dorsolateral Prefrontal Cortex EEG – Electroencephalogrophy FA - Fractional Anisotropy FEF – Frontal Eye Fields fMRI – Functional Magnetic Resonance Imaging FTD - Frontotemporal Degeneration MEG - Magnetoencephelography MMSE - Mini-mental Status Exam NFC - Neurofibrillary Changes PET – Positron Emission Tomography PSP - Progressive Supranuclear Palsy SEF – Supplementary Eye Fields WCST - Wisconsin Card Sorting Task viii 1 Chapter 1: Rational and Objectives 1.1 Rationale Alzheimer’s disease (AD) is the number one cause of dementia and its prevalence is projected to increase three and four fold in developed and developing countries respectively (Ferri et al., 2005). New treatments and the potential for disease prevention have increased the need for early AD detection. In addition to early diagnosis, monitoring the progression of AD will be crucial in determining the effectiveness of various treatments. Recent technological advances coupled with increased volumes of data have led to a revised set of criteria for the diagnosis of AD that has placed a greater emphasis on the role of neuroimaging techniques (Dubois et al., 2007). For instance, MRI measured volumetric loss of the hippocampus surrounding structures, provides a sensitivity and specificity greater than 85%. Likewise, in vivo PET imaging methods, such as PiB imaging (Pittsburg Compound B), also provide strong levels of sensitivity and specificity for the detection of AD pathology (Dubois et al., 2007). While imaging techniques can detect and monitor the progression of AD, low-tech tests have also shown to be diagnostically beneficial. For instance, results from the Clock-drawing paradigm, using revised scoring criteria, can differentiate between individuals with Mild Cognitive Impairment who progress to AD from those who do not (Babins et al., 2008). Others have shown that a utilizing a collection of neurospychological tests provides a strong metric for the progression of AD (Behl et al., 2005). However, there is no single test,
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