Real Time Fmri Neurofeedback Using Dynamic Causal Modeling A Resting State Analysis Of Network Connectivity Between The Dorsomedial Prefrontal Cortex And The Amygdala

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Real-time FMRI Neurofeedback Using Dynamic Causal Modeling: A Resting-state Analysis of Network Connectivity Between the Dorsomedial Prefrontal Cortex and the Amygdala

Author : Alexander Michael Peter Karner
Publisher :
ISBN 13 :
Total Pages : 42 pages
Book Rating : 4.:/5 (126 download)

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Book Synopsis Real-time FMRI Neurofeedback Using Dynamic Causal Modeling: A Resting-state Analysis of Network Connectivity Between the Dorsomedial Prefrontal Cortex and the Amygdala by : Alexander Michael Peter Karner

Download or read book Real-time FMRI Neurofeedback Using Dynamic Causal Modeling: A Resting-state Analysis of Network Connectivity Between the Dorsomedial Prefrontal Cortex and the Amygdala written by Alexander Michael Peter Karner and published by . This book was released on 2020 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Schwierigkeiten bei der Regulation von Emotionen sind mit verschiedenen psychischen Beeinträchtigungen und psychiatrischen Erkrankungen verbunden, einschließlich Depressionen, Angststörungen und posttraumatischen Belastungsstörungen. Durch Echtzeit-Neurofeedback, eine nicht-invasive Methode, welche sich unter anderem funktionelle Magnetresonanztomographie (fMRT) zunutze macht, kann die Selbstregulation von Emotionsnetzwerken im Gehirn trainiert werden, um dauerhafte Effekte zu erzielen, die zu einer Linderung der Symptome führen. Die Verbindung zwischen dem dorsomedialen präfrontalen Cortex (dmPFC) und der Amygdala stellt eine Schlüsselverbindung in der Regulation von Emotionen dar. In der vorliegenden Studie wurde mittels Dynamic Causal Modeling untersucht, ob die Auswirkungen von konnektivitätsbasiertem fMRT-Neurofeedback, durch welches gesunde TeilnehmerInnen lernten, ihre effektive Top-Down-Konnektivität zwischen dmPFC und Amygdala zu erhöhen, auf den Ruhezustand (resting-state) übertragen wurden. Die Ergebnisse der vorliegenden Studie zeigten keine Unterschiede zwischen Versuchsgruppe und Kontrollgruppe während der Ruhezustands-Scans. Unter anderem sind Einflussfaktoren wie homöostatische Regulationsmechanismen im Gehirn, sowie der Zeitabstand zwischen Neurofeedback-Training und Ruhezustands-Scans mögliche Erklärungen für das Fehlen eines Übertragungseffekts. Weitere Studien sind erforderlich, um mögliche Übertragungseffekte von Echtzeit-fMRT-Neurofeedback-Training auf den Ruhezustand zu untersuchen.*****Difficulties in the regulation of emotions are associated with various mental dysfunctions as well as psychiatric illnesses, including depression, anxiety and posttraumatic stress disorder. Through real-time functional magnetic resonance imaging (fMRI) neurofeedback, which is a relatively novel, non-invasive technique, the self-regulation of emotion networks can be trained, with the aim to achieve lasting neuromodulatory effects that lead to an alleviation of s

fMRI Neurofeedback

Author : Michelle Hampson
Publisher : Academic Press
ISBN 13 : 0128224363
Total Pages : 366 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis fMRI Neurofeedback by : Michelle Hampson

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

Mapping Psychopathology with fMRI and Effective Connectivity Analysis

Author : Baojuan Li
Publisher : Frontiers Media SA
ISBN 13 : 2889452077
Total Pages : 142 pages
Book Rating : 4.8/5 (894 download)

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Book Synopsis Mapping Psychopathology with fMRI and Effective Connectivity Analysis by : Baojuan Li

Download or read book Mapping Psychopathology with fMRI and Effective Connectivity Analysis written by Baojuan Li and published by Frontiers Media SA. This book was released on 2017-06-22 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a growing appreciation that many psychiatric (and neurological) conditions can be understood as functional disconnection syndromes – as reflected in aberrant functional integration and synaptic connectivity. This Research Topic considers recent advances in understanding psychopathology in terms of aberrant effective connectivity – as measured noninvasively using functional magnetic resonance imaging (fMRI). Recently, there has been increasing interest in inferring directed connectivity (effective connectivity) from fMRI data. Effective connectivity refers to the influence that one neural system exerts over another and quantifies the directed coupling among brain regions – and how they change with pathophysiology. Compared to functional connectivity, effective connectivity allows one to understand how brain regions interact with each other in terms of context sensitive changes and directed coupling – and therefore may provide mechanistic insights into the neural basis of psychopathology. Established models of effective connectivity include psychophysiological interaction (PPI), structural equation modeling (SEM) and dynamic causal modelling (DCM). DCM is unique because it explicitly models the interaction among brain regions in terms of latent neuronal activity. Moreover, recent advances in DCM such as stochastic and spectral DCM, make it possible to characterize the interaction between different brain regions both at rest and during a cognitive task.

Closed-loop Real-time FMRI Neurofeedback of Amygdala Training Modulates Resting-state Functional Connectivity

Author : Bingjie Cheng
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Closed-loop Real-time FMRI Neurofeedback of Amygdala Training Modulates Resting-state Functional Connectivity by : Bingjie Cheng

Download or read book Closed-loop Real-time FMRI Neurofeedback of Amygdala Training Modulates Resting-state Functional Connectivity written by Bingjie Cheng and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging

Author : Catherine Elizabeth Chang
Publisher : Stanford University
ISBN 13 :
Total Pages : 237 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging by : Catherine Elizabeth Chang

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.

Introduction to Resting State fMRI Functional Connectivity

Author : Janine Bijsterbosch
Publisher : Oxford University Press
ISBN 13 : 0192535757
Total Pages : 287 pages
Book Rating : 4.1/5 (925 download)

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Book Synopsis Introduction to Resting State fMRI Functional Connectivity by : Janine Bijsterbosch

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.

Estimating Effective Connectivity Within Brain Emotional Circuitry Using Dynamic Causal Modeling and FMRI

Author :
Publisher :
ISBN 13 :
Total Pages : 234 pages
Book Rating : 4.:/5 (879 download)

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Book Synopsis Estimating Effective Connectivity Within Brain Emotional Circuitry Using Dynamic Causal Modeling and FMRI by :

Download or read book Estimating Effective Connectivity Within Brain Emotional Circuitry Using Dynamic Causal Modeling and FMRI written by and published by . This book was released on 2014 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimating effective connectivity in human negative emotional network and inferring the best causal model reveals potentially important differences between subjects with 5-HTTLRP long- and short-allele. We estimate effective connectivity among four brain regions that are activated during the processing of facial affect, e.g., fear: left and right amygdale (L and R, respectively), caudal supragenual and rostral subgenual portions of anterior cingulate cortex (rACC and cACC, respectively). Dynamic causal modeling is used to make interences about effective connectivity. Bayesian model selection is also used for finding the best model from a set of plausible alternative models. The stimuli paradigm presents fearful facial expressions to a set of 37 subjects who have either two copies of the 5-HTTLRP long-allele or one copy of the 5-HTTLRP short-allele carriers (15 subjects of long-allele and 22 subjects of short-allele). Our results revealed that model 1 was the winning model for long-allele whereas model 7 was the winning model for short-allele individuals. The left to right amygdale connections were significantly different between long- and short-allele. Modulating factor on L [implies] R was found nonzero. The input connection to rACC could not be statistically proven nonzero. However, performance of DCM under low SNR has not been explored and validated thoroughly. A reasonable question is what levels of noise can be handled by the DVM. It is not straightforward to analytically answer this question. Therefore, simulation is an appropriate methodology to address this question. We propose the Euler method to simulate fMRI signal. Such a signal is then used to estimate the ground truth of neurodynamic parameters. Three different scenarios were studied: 1) linear, 2) bilinear, 3) nonlinear dynamic models. The results were compared to those of the SPM-generate. We considered one model for each linear and nonlinear and four models of bilinear scenarios, as the latter is largely used. For each model, simulated data were generated at 11 different noise levels and five trials were conducted for each noise level. DCM always converged when using signals generated by Euler method. Although DCM performed similarly in linear scenario fo both methods, DCM handled higher noise levels for Euler compared to SPM-generate.

STUDY OF DYNAMIC FUNCTIONAL BR

Author : Zening Fu
Publisher : Open Dissertation Press
ISBN 13 : 9781361040393
Total Pages : 150 pages
Book Rating : 4.0/5 (43 download)

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Book Synopsis STUDY OF DYNAMIC FUNCTIONAL BR by : Zening Fu

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

Temporal Features in Resting State fMRI Data

Author : Xiaoping Philip Hu
Publisher : Frontiers Media SA
ISBN 13 : 2889664082
Total Pages : 136 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Temporal Features in Resting State fMRI Data by : Xiaoping Philip Hu

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:

Resting state brain activity: Implications for systems neuroscience

Author : Vinod Menon
Publisher : Frontiers E-books
ISBN 13 : 2889190412
Total Pages : 212 pages
Book Rating : 4.8/5 (891 download)

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Book Synopsis Resting state brain activity: Implications for systems neuroscience by : Vinod Menon

Download or read book Resting state brain activity: Implications for systems neuroscience written by Vinod Menon and published by Frontiers E-books. This book was released on with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Advances in Resting-State Functional MRI-

Author : Jean Chen
Publisher : Elsevier
ISBN 13 : 0323985459
Total Pages : 382 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Advances in Resting-State Functional MRI- by : Jean Chen

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

Exploring Brain Functional Networks Using Multimodal Approaches in Awake Rodents

Author : Xu Han
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Exploring Brain Functional Networks Using Multimodal Approaches in Awake Rodents by : Xu Han

Download or read book Exploring Brain Functional Networks Using Multimodal Approaches in Awake Rodents written by Xu Han and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The brain is a highly coordinated network, consisting of a set of interconnected regions. Resting state functional magnetic resonance imaging (rsfMRI) is the predominant method used to investigate functional brain networks. It measures brain-wide resting state functional connectivity (RSFC) by estimating co-fluctuations of spontaneous brain activities between different regions. Despite significant progress, current research on brain network function using rsfMRI largely remains at the correlational and descriptive level. A comprehensive understanding of causal relationships of brain networks and how brain networks mediate behavior remains elusive. To address this issue, this dissertation comprises three studies. In the first study, the feasibility of deriving causality (i.e., directional information) in the brain network was examined by utilizing neural modulation techniques and rsfMRI. The study was carried out on a resting-state rodent model using stabilized step-function opsin (SSFO)-based optogenetics combined with rsfMRI. The impact of a localized increase of excitability on brain-wide RSFC was examined by incorporating Pearson's correlation and partial correlation analyses in a graphical model to derive both directness and directional information in connections that displayed RSFC modulations. The results showed that upon SSFO activation of the dentate gyrus (DG), there were significant changes in connectivity within several brain regions associated with the DG, particularly in the medial prefrontal cortex. Based on a causal inference model, an accuracy rate of 84%-100% was achieved when compared to the directional information obtained from anatomical tracing data. In the second study, the causal impact of inhibiting a central node in the memory network (i.e., the dorsal hippocampus) on both brain-wide RSFC and behavior was investigated by combining chemogenetics, rsfMRI, and behavior tests. The results demonstrated that the suppression of dorsal hippocampus (dHP) activity led to significant alterations in RSFC in an extended hippocampal-related brain network. Importantly, the data suggest that these changes contributed to the impaired performance observed in a memory-related test (i.e., Y-maze). In a separate research line, the development of neurovascular coupling in postnatal mice was investigated. Neurovascular coupling is the mechanism that associates neural activity with subsequent blood flow and forms the foundation of the fMRI signal. However, neurovascular coupling is not mature in neonates, hindering the interpretation of fMRI signals in young animals. In this dissertation, hemodynamic response was measured in awake mice from 10 days postnatal to adulthood (P10-P60). The data showed that the stimulation-evoked BOLD response was lower or even negative in young pups, and the time-to-peak of the BOLD signal in young mice was longer. Collectively, this dissertation established the optogenetic- and chemogenetic-fMRI systems to investigate the relationship between local region activity and RSFC modulation. It provided a way to analyze causal relationships between brain regions and determine network contributions to behavioral changes under neural modulation. It also characterized development-related neurovascular coupling.

Z Score Neurofeedback

Author : Robert W. Thatcher
Publisher : Academic Press
ISBN 13 : 0128014644
Total Pages : 405 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Z Score Neurofeedback by : Robert W. Thatcher

Download or read book Z Score Neurofeedback written by Robert W. Thatcher and published by Academic Press. This book was released on 2014-09-20 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neurofeedback is utilized by over 10,000 clinicians worldwide with new techniques and uses being found regularly. Z Score Neurofeedback is a new technique using a normative database to identify and target a specific individual’s area of dysregulation allowing for faster and more effective treatment. The book describes how to perform z Score Neurofeedback, as well as research indicating its effectiveness for a variety of disorders including pain, depression, anxiety, substance abuse, PTSD, ADHD, TBI, headache, frontal lobe disorders, or for cognitive enhancement. Suitable for clinicians as well as researchers this book is a one stop shop for those looking to understand and use this new technique. Contains protocols to implement Z score neurofeedback Reviews research on disorders for which this is effective treatment Describes advanced techniques and applications

Real-time FMRI Neurofeedback and PTSD

Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Real-time FMRI Neurofeedback and PTSD by :

Download or read book Real-time FMRI Neurofeedback and PTSD written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Posttraumatic stress disorder (PTSD) is recognized by the DSM-V as resulting from exposure to a traumatic event and the subsequent, prolonged experience of intrusive symptoms, avoidance behavior, altered cognitive functioning and hyperarousal. Current treatments often do not provide relief from symptoms and there is a need for neuro-scientifically informed interventions. Through the review of all available studies using real-time fMRI neurofeedback (rt-fMRI-NF) as a treatment for PTSD, the efficacy of this therapeutic intervention was analyzed in order to make specific recommendations for the neurofeedback protocols of future studies. Evidence demonstrated successful reduction in symptom severity and normalizing changes in aberrant neurocircuitry in several studies. The strongest results came from research investigating the use of positive emotion enhancement training (PEET) with amygdala upregulation, emotion induction and regulation training (EIRT) with posterior cingulate cortex (PCC) downregulation, and cognitive reappraisal training (CRT) with lateral prefrontal cortex (PFC) upregulation.

Evaluation and Calibration of Functional Network Modeling Methods Based on Known Anatomical Connections

Author : Debra Dawson
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (921 download)

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Book Synopsis Evaluation and Calibration of Functional Network Modeling Methods Based on Known Anatomical Connections by : Debra Dawson

Download or read book Evaluation and Calibration of Functional Network Modeling Methods Based on Known Anatomical Connections written by Debra Dawson and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Recent studies have identified large scale brain networks based on the spatio-temporal structure of spontaneous fluctuations in resting-state fMRI data. It is expected that functional connectivity based on resting-state data is reflective of- but not identical to the underlying anatomical connectivity. However, which functional connectivity analysis methods reliably predict the network structure remains unclear. Here we tested and compared network connectivity analysis methods by applying them to fMRI resting-state time-series obtained from the human visual cortex. The methods evaluated here are those previously tested against simulated data in Smith et al. (Neuroimage, 2011).To this end, we defined regions within retinotopic visual areas V1, V2, and V3 according to their eccentricity in the visual field, delineating central, intermediate, and peripheral eccentricity regions of interest (ROIs). These ROIs served as nodes in the models we study. We based our evaluation on the 'ground-truth', thoroughly studied retinotopically organized anatomical connectivity in the monkey visual cortex. For each evaluated method, we computed the fractional rate of detecting connections known to exist ('c-sensitivity'), while using a threshold of the 95th percentile of the distribution of interaction magnitudes of those connections not expected to exist. Under optimal conditions, including session duration of 68 minutes, a relatively small network consisting of 9 nodes and artifact-free regression of the global effect, each of the top methods predicted the expected connections with 75%-83% c-sensitivity. Partial Correlation performed best (PCorr; 83%), followed by Regularized Inverse Covariance (ICOV; 79%), Bayesian Network methods (BayesNet; 77%), Correlation (75%), and General Synchronization measures (75%). With decreased session duration, these top methods saw decreases in c-sensitivities, achieving 66%-78% and 60%-70% for 34 and 17 minute sessions, respectively. With a short resting-state fMRI scan of 8.5 minutes (TR = 2s), none of the methods predicted the real network well, with ICOV (53%) and PCorr (51%) performing best. With increased complexity of the network from 9 to 36 nodes, multivariate methods including PCorr and BayesNet saw a decrease in performance. However, this decrease became small when using data from a long (68 minutes) session. Artifact-free regression of the global effect significantly increased the c-sensitivity of all top-performing methods. In an overall evaluation across all tests we performed, PCorr, ICOV and BayesNet set themselves somewhat above all other methods. We propose that data-based calibration based on known anatomical connections be integrated into future network studies, in order to maximize sensitivity and reduce false positives." --

Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging

Author : Catherine Elizabeth Chang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (745 download)

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Book Synopsis Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging by : Catherine Elizabeth Chang

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.

The Neuroscience of Mindfulness Meditation

Author : Yi-Yuan Tang
Publisher : Springer
ISBN 13 : 3319463225
Total Pages : 103 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis The Neuroscience of Mindfulness Meditation by : Yi-Yuan Tang

Download or read book The Neuroscience of Mindfulness Meditation written by Yi-Yuan Tang and published by Springer. This book was released on 2017-08-09 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest neuroscience research on mindfulness meditation and provides guidance on how to apply these findings to our work, relationships, health, education and daily lives. Presenting cutting-edge research on the neurological and cognitive changes associated with its practice Tang aims to explain how it reaps positive effects and subsequently, how best to undertake and implement mindfulness practice. Mindfulness neuroscience research integrates theory and methods from eastern contemplative traditions, western psychology and neuroscience, and is based on neuroimaging techniques, physiological measures and behavioural tests. The Neuroscience of Mindfulness Meditation begins by explaining these foundations and then moves on to themes such as the impact of personality and how mindfulness can shape behaviour change, attention and self-control. Finally, the book discusses common misconceptions about mindfulness and challenges in future research endeavours. Written by an expert in the neuroscience of mindfulness this book will be valuable for scholars, researchers and practitioners in psychotherapy and the health sciences working with mindfulness, as well as those studying and working in the fields of neuroscience and neuropsychology.