Changes in default mode network connectivity in the months following a motor vehicle collision The University of Toledo The University of Toledo Digital Repository Theses and Dissertations 2013 Change[.]
The University of Toledo The University of Toledo Digital Repository Theses and Dissertations 2013 Changes in default mode network connectivity in the months following a motor vehicle collision Andrew S Cotton The University of Toledo Follow this and additional works at: http://utdr.utoledo.edu/theses-dissertations Recommended Citation Cotton, Andrew S., "Changes in default mode network connectivity in the months following a motor vehicle collision" (2013) Theses and Dissertations Paper 50 This Thesis is brought to you for free and open access by The University of Toledo Digital Repository It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of The University of Toledo Digital Repository For more information, please see the repository's About page A Thesis entitled Changes in Default Mode Network Connectivity in the Months Following a Motor Vehicle Collision by Andrew S Cotton Submitted to the Graduate Faculty as Partial fulfillment of the requirements for Masters of Science in Biomedical Sciences in Medical Physics Dr Michael Dennis, Committee Chair Dr John Wall, Committee Member Dr Xin Wang, Committee Member Dr Patricia Komuniecki, Dean College of Graduate Studies The University of Toledo August 2013 Copyright 2013, Andrew Cotton This document is copyrighted material Under copyright law, no parts of this document may be reproduced without the expressed permission of the author An Abstract of Changes in Default Mode Network Connectivity in the Months Following a Motor Vehicle Collision by Andrew S Cotton Submitted to the Graduate Faculty as Partial fulfillment of the requirements for Master of Science in Biomedical Science in Medical Physics The University of Toledo August 2013 This study investigates stress-related changes in the connectivity to the posterior cingulate cortex, the central node in the default mode network, in the survivors of Motor Vehicle Collisions (MVCs) Thirty-two subjects underwent Functional Magnetic Resonance Imaging (fMRI) resting-state scans two weeks following their MVCs A subset of seventeen subjects completed an additional resting-state scan three months later Stress symptoms were assessed with the Posttraumatic Stress Disorder Checklist (PCL) stressor version at each time point Group difference analyses and correlation analyses between functional connectivity maps and PCL scores using SPM 5, fMRI analysis software, yielded significant results in the inferior parietal cortex/visual cortex, the hippocampi, the lateral temporal cortices, the anterior cingulate cortex, the amygdalae, and the dorsolateral prefrontal cortex The results suggest that there was increased functional connectivity to limbic structures during the acute stress period when stress symptoms were high This may reflect increased priming of those brain regions in response to acute stress The connectivity decreased for subjects whose stress symptoms decreased three months later Furthermore, correlations in the left inferior parietal iii cortex/visual cortex and left hippocampus indicate that there was a change in the way information was processed in the brain, consistent with a change from outwardly focused attention to inwardly focused attention as stress symptoms subsided iv Acknowledgements I would like to thank Dr Xin Wang, Dr Michael Dennis, and Dr John Wall for their patience and aid on this research project In addition, I would like to thank the MRI technologists, Cindy Grey, Michelle Hanus, and Sue Yeager, for assisting in the MRI scanning that allowed us to acquire data Furthermore, I would like to thank the team members of the University of Michigan fMRI research group who provided the initial technical support for this project I would, in particular, like to thank Dr Rebecca Sripada from Michigan, who taught me how to use the functional connectivity processing scripts v Table of Contents Acknowledgements v Table of Contents vi List of Tables xi List of Figures xii Introduction 1.1 Aim of Study 1.1.1 Purpose 1.1.2 Introduction to the Default Mode Network 1.1.3 Hypotheses 1.1.4 Overview of MRI Physics, Stress, and the Default Mode Network Literature 1.2 Physics 1.2.1 General MRI Physics 1.2.2 Echo Planar Imaging 12 1.2.3 Blood Oxygen Level Dependent Imaging 13 1.3 The Stress Response and Trauma Related Stress Disorders 14 1.3.1 Stress Response 14 1.3.2 Acute Stress Disorder 16 1.3.3 Posttraumatic Stress Disorder 17 vi 1.4 Review of the Anatomy and Functional Characteristics of Regions of Importance in the Default Mode Network and Stress 19 1.4.1 Prefrontal Cortex 19 1.4.2 Anterior Cingulate Cortex 21 1.4.3 Posterior Cingulate Cortex 22 1.4.4 Inferior Parietal Cortices/Visual Cortices 23 1.4.5 Lateral Temporal Cortices 24 1.4.6 Hippocampi 24 1.4.7 Amygdalae 26 1.5 History of the Default Mode Network 27 Materials 33 2.1 Equipment 33 2.1.1 Scanner 33 2.1.2 Paradigm Computer 34 2.1.3 Goggle System 34 2.2 Software 35 2.2.1 SPM 35 2.2.2 SPM Add-Ons: xjView, Marsbar2.0, and VBM 35 2.2.3 SPSS 36 Methods 37 3.1 Recruitment 37 3.2 Timeline of Subject Activities 37 3.3 Positioning Subjects in Scanner 38 vii 3.4 Stress Related Surveys 38 3.4.1 Posttraumatic Stress Disorder Checklist 38 3.4.2 Clinician Administered Posttraumatic Stress Disorder Scale 39 3.5 MRI Scans 39 3.5.1 Localizer 39 3.5.2 Resting-State fMRI 40 3.5.3 Spoiled Gradient Echo 40 3.5.4 Overlay 40 3.6 System Check 40 3.7 Rebinning Data 41 3.8 Image Processing 41 3.8.1 Introduction to Processing 41 3.8.2 Physiological Correction 42 3.8.3 Preprocessing 42 3.8.4 Region of Interest Building 43 3.8.5 Segmentation 43 3.8.6 Nuisance Filtering 43 3.9 First Level Analysis 44 3.10 Second Level Analysis 44 3.10.1 Single Sample T-Tests 45 3.10.2 Difference Maps 45 3.10.3 Single Sample T-test of Difference Maps 45 Results 47 viii 4.1 Sample Statistics and Survey Results 47 4.2 Single Sample T-Tests of Functional Connectivity Maps 49 4.2.1 Single Sample T-Test for the Three-Week Posterior Cingulate Cortex Connectivity Map for 32 Subjects, Correcting for Age and Gender 49 4.2.2 Single Sample T-Test for the Three-Month Posterior Cingulate Connectivity Map for 17 Subjects, Correcting for Age and Gender 51 4.2.3 Single T-Test for the Posterior Cingulate Cortex Connectivity Difference Map for 17 Subjects, Correcting for Age and Gender 52 4.3 Results for the Whole Brain Correlation Analyses 53 4.3.1 The Whole Brain Correlation between the Two-Week Posterior Cingulate Cortex Connectivity and the Initial Posttraumatic Stress Disorder Checklist Scores for 32 Subjects, Correcting for Age and Gender 54 4.3.2 The Whole Brain Correlation Between the Three-Month Posterior Cingulate Cortex Connectivity and the Final Posttraumatic Stress Disorder Checklist Scores for 17 Subjects, Correcting for Age and Gender 54 4.3.3 The Whole Brain Correlation between the Change in Posterior Cingulate Cortex Connectivity and the Change in Posttraumatic Stress Disorder Checklist Scores for 17 Subjects, Correcting for Age and Gender 56 Discussion 59 5.1 Hippocampi 59 5.2 Anterior Cingulate Cortex 61 5.3 Inferior Parietal Cortex/Visual Cortex 62 5.4 Prefrontal Cortex 63 ix processes It is possible that such processes inhibit connectivity to the left IPC when an individual is in a non-stressed state It has been noted, for example, that verbal working memory tasks significantly hinder visual attention to detail in the right visual field more than in the left (Hellige and Cox 1976) In contrast, when an individual is in a stressed state, processes that support the monitoring of the environment predominate, leading to increased connectivity to the left IPC Attention to threat cues following a dangerous situation would have provided an evolutionary advantage This may also reflect the brain's healthy response to threats Individuals who have dissociative symptoms, such as decreased awareness of surroundings, immediately after a trauma are more likely to develop severe PTSD symptoms (Marshall and Schell 2002) Ultimately, as stress subsided, monitoring the external environment became less of a priority This led to the symptom correlated decrease in PCC connectivity to the IPC/visual cortex 5.4 Prefrontal Cortex The primary result for the PFC related to the change in connectivity between the two-week and three-month scans In the initial scan, there were more regions of significant connectivity in the mPFC and the dlPFC The former region has been identified as being involved in a number of higher order cognitive processes including self-referential thought and the top-down regulation of emotions (Gusnard, Akbudak et al 2001) It is possible that the mPFC was primed during the acute stress period in order to down-regulate negative emotions following the MVC This would have facilitated the ability to cope with stress and respond to additional threats after the trauma In addition, the dlPFCs are frequently associated with working memory tasks (Greicius, Krasnow et al 2003) and serve as a means for exchanging information with the attention networks It is possible that the dlPFCs were primed after the MVC to facilitate communication 63 between the DMN and the attention networks This would have allowed individuals to change attention strategies based on the internal mentation When subjects returned three months later for their second resting-state scan, the PCC connectivity to the mPFC and dlPFCs significantly decreased We believe the connectivity changes reflected decreased priming of those regions The mPFC was no longer primed to down-regulate emotions, and the dlPFCs were no longer primed to facilitate information exchange However, one must also consider the possibility that scanning familiarity promoted the changes The connectivity to the mPFC could have decreased due to decreased subject self-consciousness during the second scan In other words, because the subjects were familiar with the procedure, they were less likely to use self-monitoring and emotion regulation in order to relax in the scanner Because the dlPFCs demonstrate the greatest connectivity variation of all the DMN brain regions (Shehzad, Kelly et al 2009), the changes in those regions may have been due to chance Furthermore, the working memory regions in the dlPFCs may not have been primed during the second scan due to the fact that the scanning procedure had been committed to intermediate memory 5.5 Amygdala A significant negative correlation was present for the right amygdala for the whole brain analysis between the change in PCC connectivity and the change in PCL scores This indicated that connectivity to the right amygdala increased for the average subject whose stress scores decreased over time This may be related to the downregulation of the right amygdala by the ACC during the acute stress period Lanius noted that individuals with dissociative symptoms have greater activation of the ACC and decreased activation of the amygdalae (Lanius, Vermetten et al 2010) In addition, the 64 fact that our PCC connectivity to the right amygdala was correlated with the change in symptoms is arguably consistent with Lanius's research in which PCC connectivity to the right amygdala predicted CAPS scores 12 weeks following a MVC (Lanius, Bluhm et al 2010) In other words, those subjects who were better able to down-regulate activation of the right amygdala in the acute stress period were better able to cope with symptoms in the long-term As stress symptoms subsided and connectivity to the emotion regulation centers of the brain decreased at three months, the connectivity to the right amygdala increased While both amygdalae play important roles in processing emotion, researchers have observed greater excitability in the right amygdala in PTSD patients (Hamann 2001) Furthermore, because the spontaneous fluctuations in the DMN have been linked to the recall of episodic memories (Mason, Norton et al 2007), connectivity to the amygdala may reflect a tendency to experience emotion in response to internal mentation The connectivity correlations may reflect the actual emotional content of the thoughts or intrinsic patterns of information processing in the brain It is conceivable that experiencing the emotion could lead to symptoms of hyper-arousal It is therefore advantageous for an individual to be able to down-regulate activity in the amygdala in the acute trauma period in order to plan for future threats 65 Conclusion Ultimately, the results may be summarized in terms of their relationship to monitoring the visual field, emotion regulation, and memory function Between two weeks and three months, there was a decrease in PCC connectivity to the left IPC/visual cortex This change was positively correlated with the decrease in stress symptoms Thus, the results were consistent with our first and second hypotheses During the acute stress period, we believe the left IPC was primed to monitor the visual field We believe that the decrease in connectivity over three months corresponded with a decrease in hypervigilance symptoms and outwardly directed attention Between two weeks and three months, furthermore, there were also decreases in connectivity to emotion regulation centers such as the ACC and mPFC This was consistent with our first hypothesis We believe the high connectivity to those regions in the acute stress period aided individuals with coping with negative emotions elicited by a trauma In addition, changes in memory function may have been associated with the correlations in the left hippocampus and the right hippocampus The PCC connectivity to the left hippocampus increased as stress symptoms decreased, perhaps reflecting an increase in autobiographical memory encoding and recall The negative correlation in the right hippocampus at three months following the MVC suggests that higher connectivity to the hippocampi, in general, is related to better stress coping 66 References Addis, D R., M Moscovitch, et al (2004) "Recollective qualities modulate hippocampal activation during autobiographical memory retrieval." Hippocampus 14(6): 752762 American Psychiatric Association and American Psychiatric Association Task Force on DSM-IV (2000) Diagnostic and statistical manual of mental disorders : DSMIV-TR Washington, DC, American Psychiatric Association Anand, A., Y Li, et al (2005) "Activity and connectivity of brain mood regulating circuit in depression: A functional magnetic resonance study." Biological psychiatry 57(10): 1079-1088 Andrews-Hanna, J R., A Z Snyder, et al (2007) "Disruption of large-scale brain systems in advanced aging." Neuron 56(5): 924-935 Ashburner, J and K J Friston (2000) "Voxel-based morphometry the methods." Neuroimage 11(6 Pt 1): 805-821 Baker, J F., S E Petersen, et al (1981) "Visual response properties of neurons in four extrastriate visual areas of the owl monkey (Aotus trivirgatus): a quantitative comparison of medial, dorsomedial, dorsolateral, and middle temporal areas." Journal of neurophysiology 45(3): 397-416 Biswal, B., F Z Yetkin, et al (1995) "Functional connectivity in the motor cortex of resting human brain using echo-planar MRI." Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine 34(4): 537-541 Bluhm, R L., P C Williamson, et al (2009) "Alterations in default network connectivity in posttraumatic stress disorder related to early-life trauma." Journal of psychiatry & neuroscience : JPN 34(3): 187-194 Boly, M., L Tshibanda, et al (2009) "Functional Connectivity in the Default Network During Resting State is Preserved in a Vegetative but Not in a Brain Dead Patient." Human Brain Mapping 30(8): 2393-2400 Bracha, H S (2004) "Freeze, flight, fight, fright, faint: adaptationist perspectives on the acute stress response spectrum." CNS spectrums 9(9): 679-685 67 Brodal, P (2004) The central nervous system : structure and function Oxford ; New York, Oxford University Press Broyd, S J., C Demanuele, et al (2009) "Default-mode brain dysfunction in mental disorders: A systematic review." Neuroscience and Biobehavioral Reviews 33(3): 279-296 Buckner, R L., J R Andrews-Hanna, et al (2008) "The brain's default network Anatomy, function, and relevance to disease." Year in Cognitive Neuroscience 2008 1124: 1-38 Burgess, N., E A Maguire, et al (2002) "The human hippocampus and spatial and episodic memory." Neuron 35(4): 625-641 Bushberg, J T (2012) The essential physics of medical imaging Philadelphia, Wolters Kluwer Health/Lippincott Williams & Wilkins Butler, A J and K H James (2010) "The neural correlates of attempting to suppress negative versus neutral memories." Cognitive, affective & behavioral neuroscience 10(2): 182-194 Buxton, R B (2002) Introduction to functional magnetic resonance imaging : principles and techniques Cambridge, UK ; New York, Cambridge University Press Buxton, R B., K Uludag, et al (2004) "Modeling the hemodynamic response to brain activation." Neuroimage 23 Suppl 1: S220-233 Cabeza, R and P St Jacques (2007) "Functional neuroimaging of autobiographical memory." Trends in Cognitive Sciences 11(5): 219-227 Chau, W and A R McIntosh (2005) "The Talairach coordinate of a point in the MNI space: how to interpret it." Neuroimage 25(2): 408-416 Choi, D W (1994) "Calcium and excitotoxic neuronal injury." Annals of the New York Academy of Sciences 747: 162-171 Daniels, J K., P Frewen, et al (2011) "Default mode alterations in posttraumatic stress disorder related to early-life trauma: a developmental perspective." Journal of psychiatry & neuroscience : JPN 36(1): 56-59 Dolcos, F., K S LaBar, et al (2005) "Remembering one year later: role of the amygdala and the medial temporal lobe memory system in retrieving emotional memories." Proceedings of the National Academy of Sciences of the United States of America 102(7): 2626-2631 Ehlers, A and R Steil (1995) "Maintenance of intrusive memories in posttraumatic stress disorder: a cognitive approach." Behavioural and cognitive psychotherapy 23(3): 217-249 68 Engel, A K., P Fries, et al (2001) "Dynamic predictions: oscillations and synchrony in top-down processing." Nature reviews Neuroscience 2(10): 704-716 Engel, A K., P Konig, et al (1992) "Temporal coding in the visual cortex: new vistas on integration in the nervous system." Trends in neurosciences 15(6): 218-226 Etkin, A., T Egner, et al (2006) "Resolving emotional conflict: a role for the rostral anterior cingulate cortex in modulating activity in the amygdala." Neuron 51(6): 871-882 Fair, D A., A L Cohen, et al (2008) "The maturing architecture of the brain's default network." Proceedings of the National Academy of Sciences of the United States of America 105(10): 4028-4032 Fox, M D and M E Raichle (2007) "Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging." Nature reviews Neuroscience 8(9): 700-711 Fransson, P and G Marrelec (2008) "The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis." Neuroimage 42(3): 1178-1184 Friston, K J., C D Frith, et al (1993) "Functional Connectivity - the PrincipalComponent Analysis of Large (Pet) Data Sets." Journal of Cerebral Blood Flow and Metabolism 13(1): 5-14 Gazzaniga, M S (2000) The new cognitive neurosciences Cambridge, Mass., MIT Press Gerdes, A B., M J Wieser, et al (2010) "Brain Activations to Emotional Pictures are Differentially Associated with Valence and Arousal Ratings." Frontiers in human neuroscience 4: 175 Greicius, M D., B Krasnow, et al (2003) "Functional connectivity in the resting brain: a network analysis of the default mode hypothesis." Proceedings of the National Academy of Sciences of the United States of America 100(1): 253-258 Gusnard, D., E Akbudak, et al (2001) "Role of medial prefrontal cortex in a default mode of brain function." Neuroimage 13(6): S414-S414 Hahn, B., T J Ross, et al (2007) "Cingulate activation increases dynamically with response speed under stimulus unpredictability." Cerebral cortex 17(7): 16641671 Hamann, S (2001) "Cognitive and neural mechanisms of emotional memory." Trends in Cognitive Sciences 5(9): 394-400 69 Hellige, J B and P J Cox (1976) "Effects of concurrent verbal memory on recognition of stimuli from the left and right visual fields." Journal of experimental psychology Human perception and performance 2(2): 210-221 Henke, K (2010) "A model for memory systems based on processing modes rather than consciousness." Nature reviews Neuroscience 11(7): 523-532 Horovitz, S G., A R Braun, et al (2009) "Decoupling of the brain's default mode network during deep sleep." Proceedings of the National Academy of Sciences of the United States of America 106(27): 11376-11381 Howseman, A M., S Grootoonk, et al (1999) "The effect of slice order and thickness on fMRI activation data using multislice echo-planar imaging." Neuroimage 9(4): 363-376 Kim, J J and D M Diamond (2002) "The stressed hippocampus, synaptic plasticity and lost memories." Nature reviews Neuroscience 3(6): 453-462 Kim, M J., J Chey, et al (2008) "Diminished rostral anterior cingulate activity in response to threat-related events in posttraumatic stress disorder." Journal of psychiatric research 42(4): 268-277 Lanius, R A., R L Bluhm, et al (2010) "Default mode network connectivity as a predictor of post-traumatic stress disorder symptom severity in acutely traumatized subjects." Acta Psychiatrica Scandinavica 121(1): 33-40 Lanius, R A., E Vermetten, et al (2010) "Emotion modulation in PTSD: Clinical and neurobiological evidence for a dissociative subtype." The American journal of psychiatry 167(6): 640-647 Larson-Prior, L J., J M Zempel, et al (2009) "Cortical network functional connectivity in the descent to sleep." Proceedings of the National Academy of Sciences of the United States of America 106(11): 4489-4494 Lating, J (2012) A clinical guide to the treatment of the human stress response, third edition New York, Springer Layton, B and R Krikorian (2002) "Memory mechanisms in posttraumatic stress disorder." The Journal of neuropsychiatry and clinical neurosciences 14(3): 254261 Lemogne, C., H Mayberg, et al (2010) "Self-referential processing and the prefrontal cortex over the course of depression: a pilot study." Journal of affective disorders 124(1-2): 196-201 Liberzon, I and B Martis (2006) "Neuroimaging studies of emotional responses in PTSD." Psychobiology of Posttraumatic Stress Disorder: A Decade of Progress 1071: 87-109 70 Liberzon, I., S F Taylor, et al (1999) "Brain activation in PTSD in response to traumarelated stimuli." Biological psychiatry 45(7): 817-826 Lui, S., X Huang, et al (2009) "High-field MRI reveals an acute impact on brain function in survivors of the magnitude 8.0 earthquake in China." Proceedings of the National Academy of Sciences of the United States of America 106(36): 15412-15417 Marshall, G N and T L Schell (2002) "Reappraising the link between peritraumatic dissociation and PTSD symptom severity: Evidence from a longitudinal study of community violence survivors." Journal of Abnormal Psychology 111(4): 626636 Mason, M F., M I Norton, et al (2007) "Wandering minds: the default network and stimulus-independent thought." Science 315(5810): 393-395 McDonald, S D and P S Calhoun (2010) "The diagnostic accuracy of the PTSD Checklist: A critical review." Clinical Psychology Review 30(8): 976-987 McDonald, S D and P S Calhoun (2010) "The diagnostic accuracy of the PTSD checklist: a critical review." Clinical Psychology Review 30(8): 976-987 McNally, R J (1998) "Experimental approaches to cognitive abnormality in posttraumatic stress disorder." Clinical Psychology Review 18(8): 971-982 McRobbie, D W (2003) MRI from picture to proton Cambridge, UK ; New York, Cambridge University Press Ochsner, K N and J J Gross (2005) "The cognitive control of emotion." Trends in Cognitive Sciences 9(5): 242-249 Petersen, S E., H van Mier, et al (1998) "The effects of practice on the functional anatomy of task performance." Proceedings of the National Academy of Sciences of the United States of America 95(3): 853-860 Poustchi-Amin, M., S A Mirowitz, et al (2001) "Principles and applications of echoplanar imaging: a review for the general radiologist." Radiographics : a review publication of the Radiological Society of North America, Inc 21(3): 767-779 Raichle, M E., A M MacLeod, et al (2001) "A default mode of brain function." Proceedings of the National Academy of Sciences of the United States of America 98(2): 676-682 Rauch, S L., L M Shin, et al (2006) "Neurocircuitry models of posttraumatic stress disorder and extinction: Human neuroimaging research - Past, present, and future." Biological psychiatry 60(4): 376-382 71 Sapolsky, R M (2000) "Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders." Archives of General Psychiatry 57(10): 925-935 Shehzad, Z., A M Kelly, et al (2009) "The resting brain: unconstrained yet reliable." Cerebral cortex 19(10): 2209-2229 Shin, L M., P J Whalen, et al (2001) "An fMRI study of anterior cingulate function in posttraumatic stress disorder." Biological psychiatry 50(12): 932-942 Shulman, G L., J A Fiez, et al (1997) "Common blood flow changes across visual tasks Decreases in cerebral cortex." Journal of Cognitive Neuroscience 9(5): 648-663 Sonuga-Barke, E J S and F X Castellanos (2007) "Spontaneous attentional fluctuations in impaired states and pathological conditions: A neurobiological hypothesis." Neuroscience and Biobehavioral Reviews 31(7): 977-986 Spreng, R N and C L Grady (2010) "Patterns of brain activity supporting autobiographical memory, prospection, and theory of mind, and their relationship to the default mode network." Journal of Cognitive Neuroscience 22(6): 11121123 Spreng, R N and C L Grady (2010) "Patterns of Brain Activity Supporting Autobiographical Memory, Prospection, and Theory of Mind, and Their Relationship to the Default Mode Network." Journal of Cognitive Neuroscience 22(6): 1112-1123 Taylor, V A., V Daneault, et al (2013) "Impact of meditation training on the default mode network during a restful state." Social Cognitive and Affective Neuroscience 8(1): 4-14 Thomaes, K., E Dorrepaal, et al (2009) "Increased activation of the left hippocampus region in Complex PTSD during encoding and recognition of emotional words: A pilot study." Psychiatry Research-Neuroimaging 171(1): 44-53 Tzourio-Mazoyer, N., B Landeau, et al (2002) "Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain." Neuroimage 15(1): 273-289 Uddin, L Q., A M C Kelly, et al (2009) "Functional Connectivity of Default Mode Network Components: Correlation, Anticorrelation, and Causality." Human Brain Mapping 30(2): 625-637 van den Heuvel, M P and H E H Pol (2010) "Exploring the brain network: A review on resting-state fMRI functional connectivity." European Neuropsychopharmacology 20(8): 519-534 72 Van Dijk, K R A., T Hedden, et al (2010) "Intrinsic Functional Connectivity As a Tool For Human Connectomics: Theory, Properties, and Optimization." Journal of neurophysiology 103(1): 297-321 Vincent, J L., A Z Snyder, et al (2006) "Coherent spontaneous activity identifies a hippocampal-parietal memory network." Journal of neurophysiology 96(6): 35173531 Wagner, A D., B J Shannon, et al (2005) "Parietal lobe contributions to episodic memory retrieval." Trends in Cognitive Sciences 9(9): 445-453 Weathers, F W., A M Ruscio, et al (1999) "Psychometric properties of nine scoring rules for the clinician-administered posttraumatic stress disorder scale." Psychological Assessment 11(2): 124-133 Wermke, M., C Sorg, et al (2008) "A new integrative model of cerebral activation, deactivation and default mode function in Alzheimer's disease." European journal of nuclear medicine and molecular imaging 35 Suppl 1: S12-24 73 Appendix A: Result Tables Table A.1: This displays the statistics for the 32 subjects who completed the initial scan The columns, from left to right, identify the identification number, gender, initial PCL score, final PCL score, and change in PCL scores for each of the subjects Sample statistics for the 32 subjects who completed the initial MRI scan ID Number 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 Gender male female female male female male female male male male male female female male female female male female male female male female female male male female female female male female male female Age 24 29 31 26 43 24 24 51 46 29 42 40 29 49 36 42 20 22 36 24 51 54 58 26 29 27 23 27 60 30 30 34 Initial PCL 64 35 38 21 44 18 45 31 40 17 69 72 41 36 34 34 28 27 20 24 22 46 31 33 24 51 24 21 36 54 40 48 74 Final PCL 41 Change in PCL -23 50 17 12 -4 17 -23 58 17 25 38 18 22 25 24 17 35 27 32 24 20 21 17 26 44 40 48 17 -19 -9 -10 -5 -5 -11 -4 -1 -31 -3 -4 -10 -10 0 Table A.2: This displays the properties of the clusters for the single sample T-test on the PCC difference maps The columns, from right to left, identify the MNI coordinates of the peak voxel in a cluster, the total number of voxels in each cluster, the minimum or maximum value of the peak voxel, the aal regions in the cluster, and the number of voxels associated with each aal region Cluster properties for the single sample T-test on the PCC difference maps Coordinate Total Voxels Peak Intensity Regions Sub Voxels 46 -74 -20 4.2677 Fusiform_R Lingual_R -92 -16 157 6.8094 Lingual_R 74 Calcarine_L 33 Lingual_L 16 -44 26 -18 -3.9849 Frontal_Inf_Orb_L Temporal_Pole_Sup_L -20 -78 -12 31 4.256 Lingual_L 25 Fusiform_L -22 -66 -10 4.0025 Lingual_L -38 50 -8 -4.1259 Frontal_Mid_Orb_L 52 -72 -6 3.8984 Temporal_Inf_R -8 38 -6 11 -4.1476 Cingulum_Ant_L 10 Frontal_Med_Orb_L -18 -84 101 4.7562 Calcarine_L 58 Cuneus_L 17 Occipital_Sup_L Lingual_L 34 39 -4.3608 Cingulum_Ant_R 19 16 56 107 -4.6997 Frontal_Sup_Medial_R 85 Frontal_Sup_R 14 Frontal_Sup_Medial_L -50 -56 4.0224 Temporal_Mid_L -42 24 10 72 -5.9428 Frontal_Inf_Tri_L 72 56 18 25 -4.2609 Frontal_Sup_Medial_L 14 Frontal_Sup_Medial_R 10 22 28 32 61 -4.4041 Frontal_Sup_R 28 Frontal_Mid_R -48 22 26 23 -4.7049 Frontal_Inf_Tri_L 23 -36 -76 32 35 -4.4419 Occipital_Mid_L 35 -10 48 38 79 -4.3296 Frontal_Sup_L 46 Frontal_Sup_Medial_L 23 Frontal_Mid_L 10 54 38 39 -4.8229 Frontal_Sup_Medial_R 34 Frontal_Sup_Medial_L -34 18 38 47 -4.7266 Frontal_Mid_L 47 75 Table A.3: This displays the properties of the correlation clusters for the whole brain analysis between the two week PCC connectivity and the initial PCL scores The columns, from right to left, identify the MNI coordinates of the peak voxel in a cluster, the total number of voxels in each cluster, the minimum or maximum value of the peak voxel, the aal regions in the cluster, and the number of voxels associated with each aal region Cluster properties for the correlation between two-week connectivity maps and the initial PCL scores Coordinates Total Voxels Peak Intensity Regions Sub Voxels -40 -6 -34 -3.9317 Temporal_Inf_L 34 -10 -28 -3.9027 ParaHippocampal_R Fusiform_R 28 -10 -32 -4.1175 ParaHippocampal_R Fusiform_R 40 12 -26 11 -4.1869 Temporal_Pole_Sup_R 11 38 48 -20 11 4.2048 Frontal_Mid_Orb_R -40 16 -18 -3.5565 Temporal_Pole_Sup_L -34 -92 -16 3.9844 Lingual_L -58 -44 -16 -3.5431 Temporal_Inf_L 42 44 -14 18 3.7344 Frontal_Inf_Orb_R 14 Frontal_Mid_Orb_R -6 -88 -10 24 3.7627 Calcarine_L 15 Lingual_L 52 -20 32 27 -4.1557 Postcentral_R 25 SupraMarginal_R 76 Table A.4: This displays the properties of the correlation clusters for the whole brain analysis between the three-month PCC connectivity and the initial PCL scores The columns, from right to left, identify the MNI coordinates of the peak voxel in a cluster, the total number of voxels in each cluster, the minimum or maximum value of the peak voxel, the aal regions in the cluster, and the number of voxels associated with each aal region Cluster properties for the correlation between the three-month connectivity maps and the final PCL scores Coordinates Total Voxels Peak Intensity Regions Sub Voxels 28 -36 -18 91 -5.3296 Fusiform_R 49 Temporal_Mid_R 12 ParaHippocampal_R Temporal_Inf_R 44 -18 -18 -4.1884 Hippocampus_R Fusiform_R -26 -44 -16 36 -6.4304 Fusiform_L 35 20 -8 11 -7.7141 Pallidum_R Putamen_R 50 34 -4 4.2423 Frontal_Inf_Orb_R 20 -12 14 19 4.2397 Thalamus_R -40 -18 22 59 5.1146 Rolandic_Oper_L 30 Insula_L 24 44 -38 22 4.4438 SupraMarginal_R -2 -42 54 -4.1264 Cingulum_Mid_L -28 -66 58 4.1208 Parietal_Sup_L 28 60 4.0176 Frontal_Sup_Medial_R -60 62 4.8915 Precuneus_R Table A.5: This displays the properties of the correlation clusters for the whole brain analysis between change in PCC connectivity and the change in PCL scores The columns, from right to left, identify the MNI coordinates of the peak voxel in a cluster, the total number of voxels in each cluster, the minimum or maximum value of the peak voxel, the aal regions in the cluster, and the number of voxels associated with each aal region Cluster properties for the correlation between the connectivity difference maps and the change in PCL scores Coordinates Total Voxels Peak Intensity Regions Sub Voxels -36 -18 -28 12 -4.6258 Temporal_Inf_L Fusiform_L 34 -26 -4.661 Temporal_Pole_Sup_R Amygdala_R -38 -24 13 -4.9876 Temporal_Pole_Sup_L -20 -36 156 -6.758 Hippocampus_L 78 ParaHippocampal_L Thalamus_L Lingual_L -36 40 20 -4.4263 Frontal_Mid_L -30 -62 28 144 6.1038 Occipital_Mid_L 64 Precuneus_L Occipital_Sup_L Angular_L 77