Download or read book Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging written by Catherine Elizabeth Chang and published by Stanford University. This book was released on 2011 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging written by Catherine Elizabeth Chang and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Magnetic Resonance Imaging of Healthy and Diseased Brain Networks written by Yong He and published by Frontiers Media SA. This book was released on 2015-03-05 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Handbook of MRI Pulse Sequences written by Matt A. Bernstein and published by Elsevier. This book was released on 2004-09-21 with total page 1041 pages. Available in PDF, EPUB and Kindle. Book excerpt: Magnetic Resonance Imaging (MRI) is among the most important medical imaging techniques available today. There is an installed base of approximately 15,000 MRI scanners worldwide. Each of these scanners is capable of running many different "pulse sequences", which are governed by physics and engineering principles, and implemented by software programs that control the MRI hardware. To utilize an MRI scanner to the fullest extent, a conceptual understanding of its pulse sequences is crucial. Handbook of MRI Pulse Sequences offers a complete guide that can help the scientists, engineers, clinicians, and technologists in the field of MRI understand and better employ their scanner. Explains pulse sequences, their components, and the associated image reconstruction methods commonly used in MRI Provides self-contained sections for individual techniques Can be used as a quick reference guide or as a resource for deeper study Includes both non-mathematical and mathematical descriptions Contains numerous figures, tables, references, and worked example problems

Download or read book Quantitative Magnetic Resonance Imaging written by Nicole Seiberlich and published by Academic Press. This book was released on 2020-11-18 with total page 1094 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative Magnetic Resonance Imaging is a ‘go-to’ reference for methods and applications of quantitative magnetic resonance imaging, with specific sections on Relaxometry, Perfusion, and Diffusion. Each section will start with an explanation of the basic techniques for mapping the tissue property in question, including a description of the challenges that arise when using these basic approaches. For properties which can be measured in multiple ways, each of these basic methods will be described in separate chapters. Following the basics, a chapter in each section presents more advanced and recently proposed techniques for quantitative tissue property mapping, with a concluding chapter on clinical applications. The reader will learn: The basic physics behind tissue property mapping How to implement basic pulse sequences for the quantitative measurement of tissue properties The strengths and limitations to the basic and more rapid methods for mapping the magnetic relaxation properties T1, T2, and T2* The pros and cons for different approaches to mapping perfusion The methods of Diffusion-weighted imaging and how this approach can be used to generate diffusion tensor maps and more complex representations of diffusion How flow, magneto-electric tissue property, fat fraction, exchange, elastography, and temperature mapping are performed How fast imaging approaches including parallel imaging, compressed sensing, and Magnetic Resonance Fingerprinting can be used to accelerate or improve tissue property mapping schemes How tissue property mapping is used clinically in different organs Structured to cater for MRI researchers and graduate students with a wide variety of backgrounds Explains basic methods for quantitatively measuring tissue properties with MRI - including T1, T2, perfusion, diffusion, fat and iron fraction, elastography, flow, susceptibility - enabling the implementation of pulse sequences to perform measurements Shows the limitations of the techniques and explains the challenges to the clinical adoption of these traditional methods, presenting the latest research in rapid quantitative imaging which has the possibility to tackle these challenges Each section contains a chapter explaining the basics of novel ideas for quantitative mapping, such as compressed sensing and Magnetic Resonance Fingerprinting-based approaches

Download or read book Temporal Features in Resting State fMRI Data written by Xiaoping Philip Hu and published by Frontiers Media SA. This book was released on 2021-01-20 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book fMRI Neurofeedback written by Michelle Hampson and published by Academic Press. This book was released on 2021-10-09 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: fMRI Neurofeedback provides a perspective on how the field of functional magnetic resonance imaging (fMRI) neurofeedback has evolved, an introduction to state-of-the-art methods used for fMRI neurofeedback, a review of published neuroscientific and clinical applications, and a discussion of relevant ethical considerations. It gives a view of the ongoing research challenges throughout and provides guidance for researchers new to the field on the practical implementation and design of fMRI neurofeedback protocols. This book is designed to be accessible to all scientists and clinicians interested in conducting fMRI neurofeedback research, addressing the variety of different knowledge gaps that readers may have given their varied backgrounds and avoiding field-specific jargon. The book, therefore, will be suitable for engineers, computer scientists, neuroscientists, psychologists, and physicians working in fMRI neurofeedback. Provides a reference on fMRI neurofeedback covering history, methods, mechanisms, clinical applications, and basic research, as well as ethical considerations Offers contributions from international experts—leading research groups are represented, including from Europe, Japan, Israel, and the United States Includes coverage of data analytic methods, study design, neuroscience mechanisms, and clinical considerations Presents a perspective on future translational development

Download or read book Functional magnetic resonance imaging fMRI written by Lori A. Whitten and published by RTI Press. This book was released on 2012-12-11 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sophisticated methods of neuroscience—including molecular genetics, structural and functional neuroimaging, animal models, and experimental tasks that approximate real-world behaviors in human research—have yielded important insights about typical functioning and neurobehavioral disorders. Translational neuroscience endeavors to use this knowledge to improve the human condition by developing and improving interventions for these disorders. This paper reviews the literature on the contribution of functional magnetic resonance imaging (fMRI) and two related techniques, resting-state fMRI (rs-fMRI) and real-time fMRI (rt-fMRI), to the diagnosis and treatment of behavioral problems and psychiatric disorders. It also explains how incorporating neuroscience principles and techniques into research on the prevention of substance misuse and antisocial behavior may spur advances and innovations in this important area. This article argues that fMRI’s potential contribution to these prevention efforts has yet to be fully realized, explores new ways in which the technique could be adapted to that end, highlights some of the work by researchers in the vanguard of this effort, and notes limitations of fMRI and ethical concerns the technique raises.

Download or read book Advances in Resting State Functional MRI written by Jean Chen and published by Elsevier. This book was released on 2023-07-03 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Resting-State Functional MRI: Methods, Interpretation, and Applications gives readers with basic neuroimaging experience an up-to-date and in-depth understanding of the methods, opportunities, and challenges in rs-fMRI. The book covers current knowledge gaps in rs-fMRI, including "what are biologically plausible brain networks," "how to tell what part is noise," "how to perform quality assurance on the data," "what are the spatial and temporal limits of our ability to resolve FC," and "how to best identify network features related to individual differences or disease state". This book is an ideal reference for neuroscientists, computational neuroscientists, psychologists, biomedical engineers, physicists and medical physicists. Both new and more advanced researchers alike will be able to discover new information distilled from the past decade of research to become well-versed in rs-fMRI-related topics. Presents the first book to explain the latest methods, opportunities and challenges of Resting-state Functional MRI Edited and authored by leading researchers in fMRI Includes neuroscientific and clinical applications

Download or read book Characterization of Spatial and Temporal Brain Activation Patterns in Functional Magnetic Resonance Imaging Data written by Jae-Min Lee and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: From a signal processing perspective, we expect that our two frameworks could contribute to better characterizing brain activation patterns.

Download or read book Introduction to Resting State fMRI Functional Connectivity written by Janine Bijsterbosch and published by Oxford University Press. This book was released on 2017-06-15 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spontaneous 'resting-state' fluctuations in neuronal activity offer insights into the inherent organisation of the human brain, and may provide markers for diagnosis and treatment of mental disorders. Resting state functional magnetic resonance imaging (fMRI) can be used to investigate intrinsic functional connectivity networks, which are identified based on similarities in the signal measured from different regions. From data acquisition to results interpretation, An Introduction to Resting State fMRI Functional Connectivity discusses a wide range of approaches without expecting previous knowledge of the reader, making it truly accessible to readers from a broad range of backgrounds. Supplemented with online examples to enable the reader to obtain hands-on experience working with data, the text also provides details to enhance learning for those already experienced in the field. The Oxford Neuroimaging Primers are written for new researchers or advanced undergraduates in neuroimaging to provide a thorough understanding of the ways in which neuroimaging data can be analysed and interpreted. Aimed at students without a background in mathematics or physics, this book is also important reading for those familiar with task fMRI but new to the field of resting state fMRI.

Download or read book Functional Imaging Connectome of the Human Brain and Its Associations with Biological and Behavioral Characteristics written by Chao Zhang and published by . This book was released on 2018 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Functional connectome of the human brain explores the temporal associations of different brain regions. Functional connectivity (FC) measures derived from resting state functional magnetic resonance imaging (rfMRI) characterize the brain network at rest and studies have shown that rfMRI FC is closely related to individual subject's biological and behavioral measures. In this thesis we investigate a large rfMRI dataset from the Human Connectome Project (HCP) and utilize statistical methods to facilitate the understanding of fundamental FC-behavior associations of the human brain. Our studies include reliability analysis of FC statistics, demonstration of FC spatial patterns, and predictive analysis of individual biological and behavioral measures using FC features. Covering both static and dynamic FC (sFC and dFC) characterizations, the baseline FC patterns in healthy young adults are illustrated. Predictive analyses demonstrate that individual biological and behavioral measures, such as gender, age, fluid intelligence and language scores, can be predicted using FC. While dFC by itself performs worse than sFC in prediction accuracy, if appropriate parameters and models are utilized, adding dFC features to sFC can significantly increase the predictive power. Results of this thesis contribute to the understanding of the neural underpinnings of individual biological and behavioral differences in the human brain."--Abstract.

Download or read book Magnetic Resonance Diffusion Characterization of Brain Diseases written by Ying Ding and published by Open Dissertation Press. This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Magnetic Resonance Diffusion Characterization of Brain Diseases" by 丁莹, Ying, Ding, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Magnetic resonance imaging (MRI) is a valuable imaging technique. It provides excellent soft tissue contrast and multi-parametric non-invasive imaging protocols. Among those various techniques, diffusion MRI measures the water diffusion properties of biological tissue. It is a useful tool in characterizing various brain tissue microstructures quantitatively. With its rapid development, it is emerging that subtle changes can be probed by diffusion tensor imaging (DTI) quantitation. The objectives of this doctoral work are to access the subtle microstructural alterations in rodent brains due to hemodynamic changes, fear conditioning and sleep deprivation using in vivo DTI. With the improved reproducibility and specificity achieved by using advanced post-processing and animal preparation procedures, in vivo DTI is expected to be useful to explore the underlying biological mechanisms for posttraumatic stress disorder and memory deficit following sleep loss in human. Firstly, as DTI could be influenced by the presence of water molecules in brain vasculature, for better understand the reproducibility and sensitivity of in vivo DTI measurements, conventional DTI protocol was applied to a well-controlled rat model of hypercapnia. Our data demonstrated that diffusivities increased in whole brain, gray and white matter regions in response to hypercapnia. These results indicate that in vivo DTI quantitation in brain can be interfered by vascular factors on the order of few percents. Cautions should be taken in designing and interpreting quantitative DTI studies as all DTI indices can be potentially confounded by physiologic conditions, cerebrovascular and hemodynamic characteristics. Secondly, recent DTI studies have shown detection of long-term neural plasticity weeks to months following relatively extensive periods of training in animals. However, rapid plasticity within a short period (24 hours) after learning is important for observing the time course of training-evoked changes and narrow down candidate mechanisms. Fear conditioning (FC), which typically occurs over a short timescale (in minutes), was selected as a paradigm for investigation. Using voxel-wise repeated measures analysis, FA was found to increase in amygdala and decrease in hippocampus 1-hour post-FC, and it reversed in both regions 1-day post-FC. Results indicate that DTI can detect rapid microstructural changes in brain regions known to mediate fear conditioning in vivo. DTI indices could be explored as a translational tool to capture potential early biological changes in individuals at risk for developing post-traumatic stress disorder. Thirdly, in vivo DTI was employed to access regional specific microstructural changes following rapid eye movement sleep deprivation (SD), and explore possible temporal differentiation of these changes. With voxel-base analysis, MD is found to decrease in post-SD time points in bilateral hippocampi and cerebral cortex. The distributions of these clusters exhibited differentiable layer specific patterns, which were pointing to dentate gyrus and CA1 layer in hippocampus, and parietal cortex and barrel field layers in cerebral cortex. Results indicate that in vivo DTI is capable to detect microstructural changes in specific layers and reveal temporal distinction between them. These specific layers are possibly more susceptible to sleep loss, and the temporal distinction of changes between these

Download or read book Handbook of Neuroengineering written by Nitish V. Thakor and published by Springer Nature. This book was released on 2023-02-02 with total page 3686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook serves as an authoritative reference book in the field of Neuroengineering. Neuroengineering is a very exciting field that is rapidly getting established as core subject matter for research and education. The Neuroengineering field has also produced an impressive array of industry products and clinical applications. It also serves as a reference book for graduate students, research scholars and teachers. Selected sections or a compendium of chapters may be used as “reference book” for a one or two semester graduate course in Biomedical Engineering. Some academicians will construct a “textbook” out of selected sections or chapters. The Handbook is also meant as a state-of-the-art volume for researchers. Due to its comprehensive coverage, researchers in one field covered by a certain section of the Handbook would find other sections valuable sources of cross-reference for information and fertilization of interdisciplinary ideas. Industry researchers as well as clinicians using neurotechnologies will find the Handbook a single source for foundation and state-of-the-art applications in the field of Neuroengineering. Regulatory agencies, entrepreneurs, investors and legal experts can use the Handbook as a reference for their professional work as well.​

Download or read book STUDY OF DYNAMIC FUNCTIONAL BR written by Zening Fu and published by Open Dissertation Press. This book was released on 2017-01-26 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "A Study of Dynamic Functional Brain Connectivity Using Functional Magnetic Resonance Imaging (fMRI): Method and Applications" by Zening, Fu, 傅泽宁, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Identifying the statistical interdependence (functional connectivity, FC) between brain regions using functional magnetic resonance imaging (fMRI)is an important approach towards understanding how brain system is organized. Most fMRI studies assumed temporal stationarity of FC, so that the dynamic fluctuations of FC were overlooked. Emerging evidence has shown that FC fluctuates significantly across time and such fluctuations are physiologically relevant. The objectives of this work were (1) to develop novel methods for estimating dynamic FC from non-stationary fMRI signals, and (2) to apply new methods on real-life fMRI datasets for exploring dynamic patterns of FC in tasks and at rest. In particular, new methods were introduced to tackle two key issues in dynamic FC estimation: how to adaptively select window size to estimate dynamic FC and how to estimate dynamic FC networks with sparse architecture and sparse evolution. Firstly, a local polynomial regression (LPR) method was introduced to estimate time-varying covariance (TVCOV) for the inference of dynamic FC. The asymptotic analysis of this covariance estimator was performed and then a data-driven method, intersection of confidence intervals (ICI), was adopted to adaptively determine the window size. Simulation results showed that the LPR-ICI method could achieve robust and reliable performance in estimating TVCOV, making it a powerful tool for studying the dynamic FC from fMRI signals. Secondly, the LPR-ICI method was applied to a visual task fMRI dataset for studying the changes of FC in a block-designed visual checkerboard experiment. Reliable task-related FC changes were identified among activated visual regions during the task block. The results suggested that characterizing the task-related FC dynamics might provide greater insight into condition shifts and coordination between brain regions. Thirdly, the LPR-ICI method was applied to a resting-state fMRI dataset for exploring FC dynamics across the whole brain and investigating their relationships with dynamics of local brain activities. Converging results demonstrated that resting-state FC exhibited remarkable different dynamic patterns across the brain and these dynamic patterns were significantly correlated with the dynamic patterns of brain activities. These findings suggested that the brain might bean adaptive network, in which brain activities and their FC coevolve across time. Lastly, a novel dual l0-penalized (DLP) time-varying in verse covariance estimation method was introduced for estimating sparse dynamic FC networks. This DLP method was able to estimate dynamic networks with sparse architecture and sparse evolution by minimizing a log-likelihood function regularized by two l0-penalties (to enforce sparse architecture and sparse evolution, respectively).A coordinate descent algorithm was developed for searching the local minimizers of the objective function. Extensive simulation results showed that the DLP method could achieve better performance than conventionall1-penalized methods. In summary, two newly-developed methods (LPR-ICI and DLP) could be effective tools for studying dynamic brain FC and our results have advanced the knowledge of how brain regions dynamically coordinate. This study was also clinically relevant, as the quantification of altered FC dynamics in clinical populations of neuropsyc

Download or read book Functional Brain Organization in Space and Time written by Timothy Otto Laumann and published by . This book was released on 2017 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The brain is a network functionally organized at many spatial and temporal scales. To understand how the brain processes information, controls behavior and dynamically adapts to an ever-changing environment, it is critical to have a comprehensive description of the constituent elements of this network and how relationships between these elements may change over time. Decades of lesion studies, anatomical tract-tracing, and electrophysiological recording have given insight into this functional organization. Recently, however, resting state functional magnetic resonance imaging (fMRI) has emerged as a powerful tool for whole-brain non-invasive measurement of spontaneous neural activity in humans, giving ready access to macroscopic scales of functional organization previously much more difficult to obtain. This thesis aims to harness the unique combination of spatial and temporal resolution provided by functional MRI to explore the spatial and temporal properties of the functional organization of the brain. First, we establish an approach for defining cortical areas using transitions in correlated patterns of spontaneous BOLD activity (Chapter 2). We then propose and apply measures of internal and external validity to evaluate the credibility of the areal parcellation generated by this technique (Chapter 3). In chapter 4, we extend the study of functional brain organization to a highly sampled individual. We describe the idiosyncratic areal and systems-level organization of the individual relative to a standard group-average description. Further, we develop a model describing the reliability of BOLD correlation estimates across days that accounts for relevant sources of variability. Finally, in Chapter 5, we examine whether BOLD correlations meaningfully vary over the course of single resting-state scans.

Download or read book New Advances in Magnetic Resonance Imaging written by Denis Larrivee and published by BoD – Books on Demand. This book was released on 2024-02 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: