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Author: Catherine Elizabeth Chang
Publisher: Stanford University
ISBN:
Category :
Languages : en
Pages : 237
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Book Description
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: Catherine Elizabeth Chang
Publisher: Stanford University
ISBN:
Category :
Languages : en
Pages : 237
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Book Description
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: Catherine Elizabeth Chang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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: Yong He
Publisher: Frontiers Media SA
ISBN: 2889194353
Category : Brain
Languages : en
Pages : 366
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Book Description
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: Xiaoping Philip Hu
Publisher: Frontiers Media SA
ISBN: 2889664082
Category : Science
Languages : en
Pages : 136
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Book Description
Author: Federico Giove
Publisher: Frontiers Media SA
ISBN: 2889455548
Category :
Languages : en
Pages : 150
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Book Description
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: Lori A. Whitten
Publisher: RTI Press
ISBN:
Category : Medical
Languages : en
Pages : 36
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Book Description
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.
Author: Alex Fornito
Publisher: Frontiers E-books
ISBN: 288919051X
Category :
Languages : en
Pages : 132
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Book Description
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: Janine Bijsterbosch
Publisher: Oxford University Press
ISBN: 0192535749
Category : Medical
Languages : en
Pages : 157
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Book Description
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.
Author: Vinod Menon
Publisher: Frontiers E-books
ISBN: 2889190412
Category :
Languages : en
Pages : 212
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Book Description
Research on resting state brain activity using fMRI offers a novel approach for understanding brain organization at the systems level. Resting state fMRI examines spatial synchronization of intrinsic fluctuations in blood-oxygenation-level-dependent (BOLD) signals arising from neuronal and synaptic activity that is present in the absence of overt cognitive information processing. Since the discovery of coherent spontaneous fluctuations within the somatomotor system (Biswal, et al. 1995), a growing number of studies have shown that many of the brain areas engaged during various cognitive tasks also form coherent large-scale brain networks that can be readily identified using resting state fMRI. These studies are beginning to provide new insights into the functional architecture of the human brain. This Research Topic will synthesize current knowledge about resting state brain activity and discuss their implications for understanding brain function and dysfunction from a systems neuroscience perspective. This topic will also provide perspectives on important conceptual and methodological questions that the field needs to address in the next years. In addition to invited reviews and perspectives, we solicit research articles on theoretical, experimental and clinical questions related to the nature, origins and functions of resting state brain activity.
Author: Jae-Min Lee
Publisher:
ISBN:
Category : Brain
Languages : en
Pages :
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Book Description
From a signal processing perspective, we expect that our two frameworks could contribute to better characterizing brain activation patterns.
