Magnetic Resonance Imaging Of Healthy And Diseased Brain Networks PDF Download
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| Author | : Yong He |
| Publisher | : Frontiers Media SA |
| Total Pages | : 366 |
| Release | : 2015-03-05 |
| Genre | : Brain |
| ISBN | : 2889194353 |
Download Magnetic Resonance Imaging of Healthy and Diseased Brain Networks Book in PDF, ePub and Kindle
An important aspect of neuroscience is to characterize the underlying connectivity patterns of the human brain (i.e., human connectomics). Over the past few years, researchers have demonstrated that by combining a variety of different neuroimaging technologies (e.g., structural MRI, diffusion MRI and functional MRI) with sophisticated analytic strategies such as graph theory, it is possible to noninvasively map the patterns of structural and functional connectivity of human whole-brain networks. With these novel approaches, many studies have shown that human brain networks have nonrandom properties such as modularity, small-worldness and highly connected hubs. Importantly, these quantifiable network properties change with age, learning and disease. Moreover, there is growing evidence for behavioral and genetic correlates. Network analysis of neuroimaging data is opening up a new avenue of research into the understanding of the organizational principles of the brain that will be of interest for all basic scientists and clinical researchers. Such approaches are powerful but there are a number of challenging issues when extracting reliable brain networks from various imaging modalities and analyzing the topological properties, e.g., definitions of network nodes and edges and reproducibility of network analysis. We assembled contributions related to the state-of-the-art methodologies of brain connectivity and the applications involving development, aging and neuropsychiatric disorders such as Alzheimer’s disease, schizophrenia, attention deficit hyperactivity disorder and mood and anxiety disorders. It is anticipated that the articles in this Research Topic will provide a greater range and depth of provision for the field of imaging connectomics.
| Author | : Yan Tong |
| Publisher | : Frontiers Media SA |
| Total Pages | : 153 |
| Release | : 2023-03-09 |
| Genre | : Science |
| ISBN | : 2832516041 |
Download Multimodal magnetic resonance imaging methods to explore the visual pathway and brain network changes in blindness disease Book in PDF, ePub and Kindle
| Author | : Alex Fornito |
| Publisher | : Frontiers E-books |
| Total Pages | : 132 |
| Release | : |
| Genre | : |
| ISBN | : 288919051X |
Download Magnetic resonance imaging of disturbed brain connectivity in psychiatric illness Book in PDF, ePub and Kindle
The widespread application of brain imaging to the study of psychiatric disorders has led to a revolution in our understanding of the neural basis of psychiatric illness. In particular, the advent of magnetic resonance imaging (MRI) has provided an unprecedented capacity for quantifying diverse aspects of brain structure and function in vivo, and has been used to identify brain changes associated with the full spectrum of psychopathology. With respect to major psychiatric disorders, it is now abundantly clear from this literature that focal brain dysfunction is rare. Rather, most disorders are associated with abnormalities in large-scale networks of spatially distributed and interconnected brain regions; i.e., they are disorders of brain connectivity. Such considerations highlight the need to understand brain dysfunction in psychiatric illness from a network-based perspective. This goal is starting to be realized through recent advances in the use of MRI to map the brain’s complex connectivity architecture. In this special edition, we invite contributions that address brain network dysfunction in psychiatric illnesses. Specifically, the work must be concerned with understanding interactions between brain regions, and how their alterations are affected by psychiatric disease. These interactions can be studied at the level of anatomy using diffusion-MRI or function using functional MRI (fMRI), with the full range of methods available (e.g., tractography, seed-based correlations, independent component analysis, graph analysis, dynamic causal modeling, etc.). Contributions can be either reviews of recent, relevant literature addressing brain network dysfunction in psychiatric disease, or experimental papers describing novel insights into brain network disturbances in such illnesses. Contributions will be invited covering a broad spectrum of psychiatric disease, including mood and anxiety disorders, schizophrenia, autism, attention-deficit hyperactivity disorder and neurodegenerative conditions. It is intended that this volume will provide important insights into how brain networks are perturbed by psychiatric disease, and allow identification of commonalities and differences across diagnostic categories.
| Author | : Philip Seeman |
| Publisher | : Elsevier |
| Total Pages | : 534 |
| Release | : 2013-11-15 |
| Genre | : Science |
| ISBN | : 012418684X |
Download Imaging of the Human Brain in Health and Disease Book in PDF, ePub and Kindle
Brain imaging technology remains at the forefront of advances in both our understanding of the brain and our ability to diagnose and treat brain disease and disorders. Imaging of the Human Brain in Health and Disease examines the localization of neurotransmitter receptors in the nervous system of normal, healthy humans and compares that with humans who are suffering from various neurologic diseases. Opening chapters introduce the basic science of imaging neurotransmitters, including sigma, acetylcholine, opioid, and dopamine receptors. Imaging the healthy and diseased brain includes brain imaging of anger, pain, autism, the release of dopamine, the impact of cannabinoids, and Alzheimer's disease. This book is a valuable companion to a wide range of scholars, students, and researchers in neuroscience, clinical neurology, and psychiatry, and provides a detailed introduction to the application of advanced imaging to the treatment of brain disorders and disease. A focused introduction to imaging healthy and diseased brains Focuses on the primary neurotransmitter release Includes sigma, acetylcholine, opioid, and dopamine receptors Presents the imaging of healthy and diseased brains via anger, pain, autism, and Alzheimer's disease
| Author | : Dorina Papageorgiou |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 682 |
| Release | : 2014-05-31 |
| Genre | : Science |
| ISBN | : 9535112031 |
Download Advanced Brain Neuroimaging Topics in Health and Disease Book in PDF, ePub and Kindle
The brain is the most complex computational device we know, consisting of highly interacting and redundant networks of areas, supporting specific brain functions. The rules by which these areas organize themselves to perform specific computations have only now started to be uncovered. Advances in non-invasive neuroimaging technologies have revolutionized our understanding of the functional anatomy of cortical circuits in health and disease states, which is the focus of this book. The first section of this book focuses on methodological issues, such as combining functional MRI technology with other brain imaging modalities. The second section examines the application of brain neuroimaging to understand cognitive, visual, auditory, motor and decision-making networks, as well as neurological diseases. The use of non-invasive neuroimaging technologies will continue to stimulate an exponential growth in understanding basic brain processes, largely as a result of sustained advances in neuroimaging methods and applications.
| Author | : Jay J. Pillai |
| Publisher | : Elsevier Health Sciences |
| Total Pages | : 209 |
| Release | : 2017-10-11 |
| Genre | : Medical |
| ISBN | : 032354892X |
Download Functional Connectivity, An Issue of Neuroimaging Clinics of North America Book in PDF, ePub and Kindle
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!
| Author | : Catherine Elizabeth Chang |
| Publisher | : Stanford University |
| Total Pages | : 237 |
| Release | : 2011 |
| Genre | : |
| ISBN | : |
Download Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging Book in PDF, ePub and Kindle
Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast is a powerful technique for non-invasive measurement of brain activity. Recent fMRI studies have revealed that the spontaneous BOLD fluctuations of the human brain organize into distributed, temporally-coherent networks ("resting-state networks"; RSNs). Examination of RSNs has yielded valuable insight into neural organization and development, and demonstrates potential as a biomarker for conditions such as Alzheimer's disease and depression. However, the accuracy by which the spatio-temporal properties of RSNs can be delineated using fMRI is compromised by the presence of physiological (cardiac and respiratory) noise and vascular hemodynamic variability. Further, our present understanding of how RSNs may interact and support cognitive function has been limited by the fact that the vast majority of studies to-date analyze RSNs in a manner that assumes temporal stationarity. Here, we describe efforts to correct for non-neural physiological influences on the BOLD signal, as well as investigations into the dynamic character of resting-state network connectivity. It is found that low-frequency variations in cardiac and respiratory processes account for significant noise across widespread gray matter regions, and that a constrained deconvolution approach may prove effective for modeling and reducing their effects. Application of the proposed noise-reduction procedure is observed to yield negative correlations between the spontaneous fluctuations of two major RSNs. The relationship between respiratory volume changes and the BOLD signal is further examined by simultaneously monitoring and comparing chest expansion data, end-tidal gas concentrations, and spontaneous BOLD fluctuations. The use of a breath-holding task is proposed for quantifying regional differences in BOLD signal timing that arise from local vasomotor response delays; such non-neural timing delays are found to impact inferences of resting-state connectivity and causality. Finally, a preliminary analysis of non-stationary connectivity between RSNs is performed using wavelet and sliding-window approaches, and it is observed that interactions between networks may reconfigure on time-scales of seconds to minutes.
| Author | : Federico Giove |
| Publisher | : Frontiers Media SA |
| Total Pages | : 150 |
| Release | : 2018-09-06 |
| Genre | : |
| ISBN | : 2889455548 |
Download Proceedings of the International School on Magnetic Resonance and Brain Function - XII Workshop Book in PDF, ePub and Kindle
In the last thirty years, Magnetic Resonance has generated a wide revolution in biomedical research and in medical imaging in general. More recently, the "in vivo" studies of the human brain were extended by new original ways to the dynamic study of function and metabolism of the human brain. The enormous interest in expanding the investigation of the brain is emphasizing the search for new NMR methods capable of extracting information of so-far obscure aspects of the brain function. In fact, many quantitative approaches have been proposed in order to complement the information obtained by functional MRI, and several multimodal and multiparametric approaches have been developed to exploit the information, either functional or structural, made available by the flexible contrast generation typical of MRI, and to combine it with complementary information. The XII workshop of the International School on Magnetic Resonanceand Brain Function, held in Erice between 17 April and 6 May, 2016, was specially devoted to novel approaches aimed at better structural characterization of brain diseases, and at investigating frontiers MRI approaches to better understand the brain function. The papers included in this eBook offer a broad overview of the subjects covered during the Workshop, including applications of multiparametric MRI to neurological diseases, multimodal combination of MRI with electrophysiology, advanced methods for the investigation of brain networks and of brain physiology, and perspectives towards brain state reading.
| Author | : Yuhui Du |
| Publisher | : Frontiers Media SA |
| Total Pages | : 288 |
| Release | : 2020-07-10 |
| Genre | : |
| ISBN | : 2889634043 |
Download Identifying Neuroimaging-Based Markers for Distinguishing Brain Disorders Book in PDF, ePub and Kindle
There has been increasing interests in exploring biomarkers from brain images, aiming to have a better understanding and a more effective diagnosis of brain disorders such as schizophrenia, bipolar disorder, schizoaffective disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer’s disease and so on. Therefore, it is important to identify disease-specific changes for distinguishing healthy controls and patients with brain disorders as well as for differentiating patients with different disorders showing similar clinical symptoms. Biomarkers can be identified from different types of brain Imaging techniques including functional magnetic resonance imaging (fMRI), structural MRI, positron emission tomography (PET), electroencephalography (EEG), and magnetoencephalography (MEG) by using statistical analysis methods. Furthermore, based on measures from brain imaging techniques, machine learning techniques can help to classify or predict disease for individual subjects. In fact, fusion of features from multiple modalities may benefit the understanding of disease mechanism and improve the classification performance. This Research Topic further explores the functional or structural alterations in brain disorders.
| Author | : Anita Meghan Sinha |
| Publisher | : |
| Total Pages | : |
| Release | : 2021 |
| Genre | : |
| ISBN | : |
Download Optimizing Statistical Methods for Connectivity Mapping in MR Neuroimaging Book in PDF, ePub and Kindle
Magnetic resonance imaging (MRI) plays an integral role in the study, diagnosis and treatment of neurological diseases. Neuroimaging analyses involve high-dimensional, large-scale data that contain rich spatial and temporal information about the dynamic and integrated systems in the brain. Therefore, it has become imperative to develop and optimize analytical approaches drawn from engineering and mathematics to more precisely model these complex patterns and interactions, which will advance our understanding of functional brain organization in health and disease. Chapter 1 provides an overview and background of MRI, with a particular focus on the use of resting-state functional magnetic resonance imaging (rs-fMRI) to capture and characterize brain connectivity. Previous work of statistical methods developed for fMRI analysis are reviewed. Chapter 2 presents an analysis of changes in functional connectivity and behavioral outcomes in patients of stroke who undergo brain-computer interface (BCI) interventional therapy. This work employs a widely used network-based inference method for fMRI analysis that serves as motivation for subsequent work to overcome statistical challenges associated with its use to more effectively model and characterize brain network dynamics and organization in a robust manner. Chapter 3 presents a novel application of differential covariance trajectory analysis as promising framework for brain network modeling using rs-fMRI data. The proposed algorithm models functional connectivity as trajectories on the manifold and employs a localization procedure to search over and identify subsets of first- and second-order differences in brain connectivity features between patients with Temporal Lobe Epilepsy (TLE) and healthy control subjects. Chapter 4 extends the work presented in the previous chapter to apply the combined differential covariance trajectory and scan statistics framework to characterize the Alzheimer's Disease connectome. We demonstrate the utility and robustness of this method to study altered brain network organization in large-scale functional networks in a different and older clinical population, which is notably of smaller sample size, where the statistical signal may be weak. Chapter 5 discusses conclusions and key takeaways of the work, along with potential future avenues of research.
