BOOK
Functional Connectivity, An Issue of Neuroimaging Clinics of North America, E-Book
(2017)
Additional Information
Book Details
Abstract
This issue of Neuroimaging Clinics of North America focuses on Functional Connectivity, and is edited by Dr. Jay Pillai. Articles will include: Applications of rs-fMRI to presurgical mapping: sensorimotor mapping; Dynamic functional connectivity methods; Machine learning applications to rs-fMRI analysis; Frequency domain analysis of rs-fMRI; Applications of rs-fMRI to epilepsy; Data-driven analysis methods for rs-fMRI; Applications of rs-fMRI to presurgical mapping: language mapping; Limitations of rs-fMRI in the setting of focal brain lesions; Applications of rs-fMRI to neuropsychiatric disease; Applications of rs-fMRI to Traumatic Brain Injury; Applications of rs-fMRI to neurodegenerative disease; Graph theoretic analysis of rs-fMRI; and more!
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Front Cover | Cover | ||
| Functional Connectivity\r | i | ||
| Copyright\r | ii | ||
| CME Accreditation Page | iii | ||
| PROGRAM OBJECTIVE | iii | ||
| TARGET AUDIENCE | iii | ||
| LEARNING OBJECTIVES | iii | ||
| ACCREDITATION | iii | ||
| DISCLOSURE OF CONFLICTS OF INTEREST | iii | ||
| UNAPPROVED/OFF-LABEL USE DISCLOSURE | iii | ||
| TO ENROLL | iv | ||
| METHOD OF PARTICIPATION | iv | ||
| CME INQUIRIES/SPECIAL NEEDS | iv | ||
| NEUROIMAGING CLINICS OF NORTH AMERICA\r | v | ||
| FORTHCOMING ISSUES | v | ||
| February 2018 | v | ||
| May 2018 | v | ||
| August 2018 | v | ||
| RECENT ISSUES | v | ||
| August 2017 | v | ||
| May 2017 | v | ||
| February 2017 | v | ||
| Contributors | vii | ||
| CONSULTING EDITOR | vii | ||
| EDITOR | vii | ||
| AUTHORS | vii | ||
| Contents | xi | ||
| Foreword: Functional Connectivity | xi | ||
| Preface: Functional Connectivity | xi | ||
| 1: Methods of Resting State Functional Connectivity (fMRI) Analysis | xi | ||
| Methods and Considerations for Dynamic Analysis of Functional MR Imaging Data547 | xi | ||
| Ten Key Observations on the Analysis of Resting-state Functional MR Imaging Data Using Independent Component Analysis561 | xi | ||
| A Review of Resting-State Analysis Methods581 | xi | ||
| Graph Theoretic Analysis of Resting State Functional MR Imaging593 | xi | ||
| Machine Learning Applications to Resting-State Functional MR Imaging Analysis609 | xii | ||
| 2: Clinical Applications of Resting State Functional Connectivity | xii | ||
| Resting-state Functional Magnetic Resonance Imaging in Presurgical Functional Mapping: Sensorimotor Localization621 | xii | ||
| Application of Resting State Functional MR Imaging to Presurgical Mapping: Language Mapping635 | xii | ||
| Limitations of Resting-State Functional MR Imaging in the Setting of Focal Brain Lesions645 | xiii | ||
| Applications of Resting-State Functional Connectivity to Neurodegenerative Disease663 | xiii | ||
| Applications of Resting State Functional MR Imaging to Traumatic Brain Injury685 | xiii | ||
| Applications of Resting-State Functional MR Imaging to Epilepsy697 | xiii | ||
| Applications of Resting State Functional MR Imaging to Neuropsychiatric Diseases709 | xiv | ||
| Foreword\r | xv | ||
| Functional Connectivity | xv | ||
| Preface\r | xvii | ||
| Functional Connectivity | xvii | ||
| Methods and Considerations for Dynamic Analysis of Functional MR Imaging Data | 547 | ||
| Key points | 547 | ||
| INTRODUCTION | 547 | ||
| METHODS FOR DYNAMIC FUNCTIONAL CONNECTIVITY ANALYSIS | 548 | ||
| Sliding Window Analysis (Temporal Resolution of Seconds to Minutes) | 548 | ||
| Time-Frequency Analysis (Multiscale Temporal Resolution) | 549 | ||
| Point Process Analysis (Toward the Resolution of a Single fMR Imaging Timeframe) | 550 | ||
| Temporal Graph Analysis | 550 | ||
| SUMMARIZING BRAIN DYNAMICS | 551 | ||
| Temporal Clustering | 551 | ||
| The Independence Assumption | 551 | ||
| Detecting Functional Connectivity Change Points | 552 | ||
| Incorporating Temporal Sequence Information | 552 | ||
| STATISTICAL TESTING | 553 | ||
| CONSIDERATIONS | 553 | ||
| Determination of Sources Contributing to Dynamic Functional Connectivity | 553 | ||
| Vigilance levels | 553 | ||
| Changes in signal amplitude, autocorrelation, and noise characteristics | 554 | ||
| Physiologic processes | 554 | ||
| Hemodynamic Confounds | 555 | ||
| Issues with Short Acquisitions | 555 | ||
| SUMMARY | 555 | ||
| ACKNOWLEDGMENTS | 555 | ||
| REFERENCES | 556 | ||
| Ten Key Observations on the Analysis of Resting-state Functional MR Imaging Data Using Independent Component Analysis | 561 | ||
| Key points | 561 | ||
| INTRODUCTION | 561 | ||
| THE BASICS OF INDEPENDENT COMPONENT ANALYSIS APPLIED TO FUNCTIONAL MAGNETIC RESONANCE IMAGING DATA | 562 | ||
| NUMBER 1: INDEPENDENT COMPONENT ANALYSIS APPROACHES ARE ROBUST TO ARTIFACTS | 564 | ||
| NUMBER 2: INDEPENDENT COMPONENT ANALYSIS IS AGNOSTIC TO THE TEMPORAL EVOLUTION OF BRAIN ACTIVITY SIGNALS | 564 | ||
| NUMBER 3: INDEPENDENT COMPONENT ANALYSIS COMPONENTS CAN BE COUPLED TO ONE ANOTHER SPATIALLY AND TEMPORALLY | 564 | ||
| NUMBER 4: INDEPENDENT COMPONENT ANALYSIS MAY BE DATA DRIVEN BUT IT IS ALSO USEFUL FOR HYPOTHESIS-BASED STUDIES | 566 | ||
| Assumptions of Independent Component Analysis | 567 | ||
| NUMBER 5: THERE IS NO PERFECT NUMBER OF COMPONENTS | 568 | ||
| NUMBER 6: INDEPENDENT COMPONENT ANALYSIS RESULTS ARE ROBUST TO FALSE-POSITIVES AND SPATIAL AUTOCORRELATION ASSUMPTIONS COMP ... | 568 | ||
| NUMBER 7: THE MANTRA OF “GARBAGE IN GARBAGE OUT” RINGS TRUE, BUT WITH INDEPENDENT COMPONENT ANALYSIS ONE PERSON’S GARBAGE M ... | 569 | ||
| NUMBER 8: LABELING THE INDEPENDENT COMPONENT ANALYSIS COMPONENTS IS STILL LARGELY MANUAL, BUT AUTOMATION APPROACHES CONTINU ... | 570 | ||
| NUMBER 9: INDEPENDENT COMPONENT ANALYSIS CAN BE LEVERAGED TO CAPTURE DYNAMIC (TIME-VARYING) FUNCTIONAL CONNECTIVITY | 572 | ||
| NUMBER 10: INDEPENDENT COMPONENT ANALYSIS ALGORITHM DEVELOPMENT IS ONGOING | 574 | ||
| SUMMARY | 575 | ||
| ACKNOWLEDGMENTS | 575 | ||
| REFERENCES | 575 | ||
| A Review of Resting-State Analysis Methods | 581 | ||
| Key points | 581 | ||
| INTRODUCTION | 581 | ||
| METHODS | 582 | ||
| Temporal Domain Methods | 583 | ||
| Seed-based correlation | 583 | ||
| Regional homogeneity | 583 | ||
| Four-dimensional consistency of local neural activities | 583 | ||
| Principle component analysis | 583 | ||
| Independent components analysis | 584 | ||
| Frequency Domain Methods | 584 | ||
| Coherence analysis | 584 | ||
| Amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation | 584 | ||
| Time-Frequency Domain Methods | 585 | ||
| Short-time Fourier transform | 585 | ||
| Wavelet transform coherence | 585 | ||
| Single-Subject Analysis | 585 | ||
| GROUP-LEVEL ANALYSIS | 585 | ||
| Regression Analysis | 585 | ||
| Dual Regression | 586 | ||
| Graph Theory | 586 | ||
| RESULTS | 586 | ||
| Healthy Subjects | 586 | ||
| Diseased Populations | 587 | ||
| Alzheimer Disease | 587 | ||
| Schizophrenia | 588 | ||
| DISCUSSION | 589 | ||
| REFERENCES | 591 | ||
| Graph Theoretic Analysis of Resting State Functional MR Imaging | 593 | ||
| Key points | 593 | ||
| INTRODUCTION | 593 | ||
| DATA COLLECTION AND PREPROCESSING | 594 | ||
| GRAPH THEORETIC ANALYSIS OF RESTING STATE FUNCTIONAL MR IMAGING DATA | 594 | ||
| GRAPHS IN RESTING STATE FUNCTIONAL MR IMAGING ANALYSIS | 594 | ||
| MICROSCALE, MESOSCALE, AND MACROSCALE NETWORK ANALYSIS | 595 | ||
| Microscale | 595 | ||
| Mesoscale | 597 | ||
| Macroscale | 597 | ||
| MAJOR FINDINGS IN RESTING STATE FUNCTIONAL MR IMAGING GRAPH THEORETIC ANALYSIS | 599 | ||
| Not All Resting State Functional MR Imaging Is Equal | 599 | ||
| Human Brain Organization Maintains a Complex Balance Among Randomness, Small Worldness, and Modularity | 600 | ||
| Resting State Networks form a Stable Organization Supporting Cognitive Function Within and Between Individuals | 600 | ||
| Resting State Network Graph Characteristics Are Altered in Numerous Clinical Populations | 601 | ||
| OPEN FRONTIERS IN RESTING STATE FUNCTIONAL MR IMAGING ANALYSIS | 602 | ||
| WHAT DOES RESTING STATE FUNCTIONAL MR IMAGING GRAPH ORGANIZATION REPRESENT? | 602 | ||
| OPTIMISM FOR CLINICAL IDENTIFICATION, PREDICTION, AND TRANSLATION | 602 | ||
| SUMMARY | 604 | ||
| REFERENCES | 604 | ||
| Machine Learning Applications to Resting-State Functional MR Imaging Analysis | 609 | ||
| Key points | 609 | ||
| INTRODUCTION | 609 | ||
| MACHINE LEARNING OVERVIEW | 610 | ||
| Support Vector Machines | 610 | ||
| Random Forests | 611 | ||
| Artificial Neural Networks | 611 | ||
| CLINICAL APPLICATIONS USING MACHINE LEARNING AND RESTING STATE FUNCTIONAL MR IMAGING | 611 | ||
| Mild Cognitive Impairment and Alzheimer's Dementia | 611 | ||
| Traumatic Brain Injury | 614 | ||
| Epilepsy | 614 | ||
| Schizophrenia | 614 | ||
| Bipolar Disorder | 615 | ||
| Social Anxiety | 615 | ||
| Major Depressive Disorder | 616 | ||
| Attention Deficit Hyperactivity Disorder | 616 | ||
| Autism Spectrum Disorder | 617 | ||
| Addiction | 618 | ||
| Aging | 618 | ||
| ACKNOWLEDGMENTS | 618 | ||
| REFERENCES | 618 | ||
| Resting-state Functional Magnetic Resonance Imaging in Presurgical Functional Mapping | 621 | ||
| Key points | 621 | ||
| INTRODUCTION | 622 | ||
| METHODS | 622 | ||
| Patients | 622 | ||
| Acquisition | 622 | ||
| Preprocessing | 622 | ||
| Resting-state functional magnetic resonance imaging | 622 | ||
| Task functional magnetic resonance imaging processing | 624 | ||
| Anatomic Regions | 624 | ||
| Brodmann Primary Sensorimotor Region of Interest | 624 | ||
| FreeSurfer Primary Sensorimotor Region of Interest | 624 | ||
| Jaccard Index Overlap | 626 | ||
| Task Threshold | 626 | ||
| Multilayer Perceptron Threshold | 626 | ||
| Hemisphere Masks | 626 | ||
| RESULTS | 626 | ||
| Fixed Multilayer Perceptron Threshold | 626 | ||
| Maximum Jaccard Index Multilayer Perceptron Threshold | 626 | ||
| DISCUSSION | 627 | ||
| SUMMARY | 631 | ||
| REFERENCES | 631 | ||
| Application of Resting State Functional MR Imaging to Presurgical Mapping | 635 | ||
| Key points | 635 | ||
| BACKGROUND | 635 | ||
| CONSIDERATIONS DURING RESTING STATE FUNCTIONAL MR IMAGING ACQUISITION | 636 | ||
| IMAGE PROCESSING | 636 | ||
| CONNECTIVITY ANALYSIS | 636 | ||
| RELIABILITY OF RESTING STATE FUNCTIONAL MR IMAGING METRICS | 638 | ||
| RELIABILITY OF RESTING STATE FUNCTIONAL MR IMAGING LANGUAGE NETWORK IN HEALTHY SUBJECTS | 638 | ||
| RESTING STATE FUNCTIONAL MR IMAGING IN PREOPERATIVE PLANNING: LANGUAGE LOCALIZATION | 639 | ||
| RESTING STATE FUNCTIONAL MR IMAGING IN PREOPERATIVE PLANNING: LANGUAGE LATERALIZATION | 641 | ||
| NEUROVASCULAR UNCOUPLING | 641 | ||
| MULTILINGUAL SUBJECTS | 641 | ||
| LANGUAGE PREDICTION | 641 | ||
| CHILDREN | 642 | ||
| SUMMARY | 642 | ||
| REFERENCES | 642 | ||
| Limitations of Resting-State Functional MR Imaging in the Setting of Focal Brain Lesions | 645 | ||
| Key points | 645 | ||
| INTRODUCTION | 645 | ||
| SUSCEPTIBILITY EFFECTS | 646 | ||
| HEAD MOTION AND PHYSIOLOGIC NOISE | 646 | ||
| NEUROVASCULAR UNCOUPLING | 647 | ||
| EXAMPLES OF EACH OF THE PREVIOUSLY MENTIONED LIMITATIONS IN THE SETTING OF FOCAL BRAIN PATHOLOGY | 649 | ||
| NEUROVASCULAR UNCOUPLING EFFECTS ON RESTING-STATE FUNCTIONAL CONNECTIVITY (SEED CORRELATION ANALYSIS AND INDEPENDENT COMPON ... | 650 | ||
| NEUROVASCULAR UNCOUPLING EFFECTS ON REGIONAL HOMOGENEITY (KENDALL COEFFICIENT OF CONCORDANCE AND COHERENCE TO EVALUATE) | 654 | ||
| NEUROVASCULAR UNCOUPLING EFFECTS ON FREQUENCY-DOMAIN METRICS (AMPLITUDE OF LOW-FREQUENCY FLUCTUATIONS AND FRACTIONAL AMPLIT ... | 656 | ||
| NEUROVASCULAR UNCOUPLING EFFECTS ON MAPPING OF THE LANGUAGE NETWORK | 656 | ||
| NEUROVASCULAR UNCOUPLING IN THE CONTEXT OF NETWORK/GRAPH THEORETIC ANALYSIS | 656 | ||
| SUMMARY | 658 | ||
| REFERENCES | 658 | ||
| Applications of Resting-State Functional Connectivity to Neurodegenerative Disease | 663 | ||
| Key points | 663 | ||
| INTRODUCTION | 663 | ||
| MAPPING BRAIN CIRCUITS: RESTING-STATE FUNCTIONAL MAGNETIC RESONANCE IMAGING | 664 | ||
| CAN RESTING-STATE FUNCTIONAL MR IMAGING–BASED CONNECTIVITY ANALYSES REVEAL SYNDROME-SPECIFIC NETWORK CHANGES? | 666 | ||
| CAN RESTING-STATE FUNCTIONAL MR IMAGING–BASED CONNECTIVITY ANALYSES UNCOVER DISEASE MECHANISM AND THE UNDERLYING NEUROPATHO ... | 668 | ||
| CAN RESTING-STATE FUNCTIONAL MR IMAGING–BASED CONNECTIVITY ANALYSES DETECT EARLY CHANGES AND TRACK DISEASE SEVERITY? | 674 | ||
| SUMMARY AND FUTURE DIRECTIONS | 676 | ||
| REFERENCES | 677 | ||
| Applications of Resting State Functional MR Imaging to Traumatic Brain Injury | 685 | ||
| Key points | 685 | ||
| INTRODUCTION | 685 | ||
| NORMAL ANATOMY AND IMAGING TECHNIQUE | 686 | ||
| RESTING STATE FUNCTIONAL MR IMAGING PROTOCOLS | 687 | ||
| RESTING STATE FUNCTIONAL MR IMAGING FINDINGS | 688 | ||
| Graph Theoretic Measures | 689 | ||
| Mounting Evidence for Connectivity Changes in Traumatic Brain Injury | 689 | ||
| Evidence for Hypoconnectivity in Traumatic Brain Injury | 689 | ||
| Evidence for Hyperconnectivity in Traumatic Brain Injury | 690 | ||
| Automating Diagnosis with Machine Learning | 691 | ||
| Longitudinal Recovery Monitoring and Outcome Prediction | 691 | ||
| MAGNETOENCEPHALOGRAPHY PROTOCOLS | 692 | ||
| Acquisition | 692 | ||
| Reconstruction Techniques | 692 | ||
| MAGNETOENCEPHALOGRAPHY FINDINGS | 692 | ||
| Frequency Domain | 692 | ||
| Automating Diagnosis with Machine Learning | 693 | ||
| PEARLS, PITFALLS, VARIANTS | 693 | ||
| DISCUSSION | 694 | ||
| REFERENCES | 694 | ||
| Applications of Resting-State Functional MR Imaging to Epilepsy | 697 | ||
| Key points | 697 | ||
| WHAT CAN FUNCTIONAL MR IMAGING ADD TO EPILEPSY SURGICAL EVALUATIONS? | 697 | ||
| RESTING-STATE FUNCTIONAL MR IMAGING AND MEMORY IN MEDIAL TEMPORAL-LOBE EPILEPSY | 698 | ||
| RESTING-STATE FUNCTIONAL CONNECTIVITY AND LANGUAGE IN MEDIAL TEMPORAL-LOBE EPILEPSY | 701 | ||
| RESTING-STATE FUNCTIONAL MR IMAGING AND OTHER CLINICAL QUESTIONS IN EPILEPSY | 702 | ||
| POSSIBILITIES AND LIMITATIONS | 703 | ||
| SUMMARY | 704 | ||
| REFERENCES | 705 | ||
| Applications of Resting State Functional MR Imaging to Neuropsychiatric Diseases | 709 | ||
| Key points | 709 | ||
| INTRODUCTION | 709 | ||
| ALZHEIMER DISEASE AND ITS PRECURSOR, AMNESTIC MILD COGNITIVE IMPAIRMENT | 713 | ||
| PARKINSON DISEASE | 715 | ||
| COMA | 715 | ||
| PSYCHOTIC ILLNESSES INCLUDING PSYCHOTIC BIPOLAR DISORDER | 715 | ||
| Novel Analyses | 716 | ||
| ACUTE DRUG INTOXICATION | 718 | ||
| CHRONIC DRUG AND ALCOHOL ABUSE | 718 | ||
| REFERENCES | 718 |