EXPLORING THE SENSORIMOTOR NETWORK USING FUNCTIONAL CONNECTIVITY AND GRAPH THEORY by Ronald Bishop Submitted in partial fulfillment of the requirements for the degree of Master of Science at Dalhousie University Halifax, Nova Scotia August 2014 © Copyright by Ronald Bishop, 2014 TABLE OF CONTENTS LIST OF TABLES ......................................................................................................................................... v LIST OF FIGURES ...................................................................................................................................... vi ABSTRACT ................................................................................................................................................. vii LIST OF ABBREVIATIONS USED ......................................................................................................... viii ACKNOWLEDGEMENTS ......................................................................................................................... xi CHAPTER 1: INTRODUCTION ................................................................................................................. 1 CHAPTER 2: LITERATURE REVIEW ..................................................................................................... 4 2.1 AN OVERVIEW OF NEURONAL COMMUNICATION ..................................................................................... 4 2.2 SYNCHRONOUS NEURAL FIRING ............................................................................................................... 5 2.2.1 The Beta Rhythm is Related to Movement – Motor Unit Synchrony ............................................. 8 2.2.2 Central – Peripheral Neural Synchrony ......................................................................................... 9 2.2.3 Cortico – Cortical Synchrony ....................................................................................................... 10 2.2.4 Determining Cortico – Cortical Synchrony with Neuroimaging ................................................. 11 2.3 WHAT IS A NEURAL NETWORK? ............................................................................................................ 13 2.4 THE BRAIN IS A NETWORK ..................................................................................................................... 14 2.5 WHAT IS STRUCTURAL CONNECTIVITY .................................................................................................. 15 2.6 WHAT IS FUNCTIONAL CONNECTIVITY .................................................................................................. 16 2.6.1 Functional Connectivity using PET .............................................................................................. 16 2.6.2 Functional Connectivity using fMRI ............................................................................................. 18 2.6.3 Examining Functional Connectivity at Rest: the Default Mode Network ..................................... 19 2.6.4 State-Related Functional Connectivity ......................................................................................... 20 2.7 FUNCTIONAL CONNECTIVITY WITH MEG ................................................................................................ 21 2.7.1 Neural Basis of MEG .................................................................................................................... 21 2.7.2 MEG Technology .......................................................................................................................... 22 2.7.3 Comparing MEG to other Modalities ........................................................................................... 24 2.8 WHAT IS GRAPH THEORY? ..................................................................................................................... 25 2.8.1 Complex Networks are Small World Networks ............................................................................. 26 2.8.2 What are Specific Network Measures? ......................................................................................... 27 2.8.3 Converting Neuroimaging Data into a Graph .............................................................................. 29 2.8.4 Applying Graph Theory to Neuroimaging Data ........................................................................... 29 2.8.5 Graph Theory Applied to Human FC Data .................................................................................. 30 2.8.6 Graph Theory and Clinical Populations ....................................................................................... 30 2.9 IMAGING THE MOTOR NETWORK – EARLY RESEARCH INTO FUNCTIONAL LOCALIZATION ..................... 32 ii 2.9.1 Imaging the Motor Network – The Importance of the SMA .......................................................... 33 2.9.2 Imaging the Motor Network – The Importance of Laterality ....................................................... 34 2.9.3 Imaging the Motor Network – Difference Between Unilateral and Bilateral Movements ........... 35 2.9.3 Imaging the Motor Network – Neural Changes Based on Varying Grip Tasks ........................... 37 2.10 CURRENT PROJECT ............................................................................................................................... 40 CHAPTER 3: METHODS .......................................................................................................................... 44 3.1 PARTICIPANTS ....................................................................................................................................... 44 3.2 TASK CHOICE ......................................................................................................................................... 44 3.2.1 Task Overview ............................................................................................................................... 45 3.2.2 Task Details .................................................................................................................................. 47 3.3 CHOICE OF RESPONSE DEVICE ................................................................................................................ 49 3.4 MRI ACQUISITION .................................................................................................................................. 50 3.5 MEG ACQUISITION ................................................................................................................................. 51 3.5.1 Participant Preparation ................................................................................................................ 51 3.5.2 Head Position Estimation ............................................................................................................. 52 3.5.3 MEG Data Acquisition .................................................................................................................. 53 3.6 DATA ANALYSIS - SINGLE SUBJECT ANALYSIS ....................................................................................... 54 3.6.1 Behavioral Data ............................................................................................................................ 54 3.6.2 MEG Pre-Processing .................................................................................................................... 54 3.6.3 MRI Pre-Processing ...................................................................................................................... 55 3.6.4 MEG – MRI Co-Registration ....................................................................................................... 56 3.6.5 Calculating CCC .......................................................................................................................... 56 3.7 GROUP LEVEL ANALYSIS ...................................................................................................................... 58 3.7.1 Partial Least Squares Analysis .................................................................................................... 58 3.7.2 Constructing a Task-Positive BSR Matrix ................................................................................... 59 3.7.3 Graph Theory Measures .............................................................................................................. 59 3.8 DIRECT LINKS FROM PARADIGM TO HYPOTHESES ................................................................................. 60 CHAPTER 4: RESULTS ............................................................................................................................ 62 4.1 BEHAVIOURAL RESULTS ....................................................................................................................... 62 4.1.1 Accuracy and Error ..................................................................................................................... 63 4.2 MEG RESULTS ....................................................................................................................................... 64 4.2.1 Task-Positive BSR Matrix ............................................................................................................ 66 4.3 GRAPH THEORY MEASURES ................................................................................................................... 69 4.3.1 Node Degree ...............................................................................................................................