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Books on the topic 'Functional connectivity'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 September 2024

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1

Nikitchenko, Maxim V. Inference of functional neural connectivity and convergence acceleration methods. [New York, N.Y.?]: [publisher not identified], 2013.

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2

Pastore, Vito Paolo. Estimating Functional Connectivity and Topology in Large-Scale Neuronal Assemblies. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-59042-0.

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3

Hinkle, William. Neural Mechanisms Mediating the Effects of Food Cues and Acute Exercise: A functional Magnetic Resonance Imaging and Functional Connectivity Investigation. [New York, N.Y.?]: [publisher not identified], 2013.

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4

Pantazatos, Spiro. Large-scale Functional Connectivity in the Human Brain Reveals Fundamental Mechanisms of Cognitive, Sensory and Emotion Processing in Health and Psychiatric Disorders. [New York, N.Y.?]: [publisher not identified], 2014.

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5

International Business Machines Corporation. International Technical Support Organization, ed. Communications server for z/OS V1R9 TCP/IP implementation: Base functions, connectivity, and routing. Poughkeepsie, N.Y: IBM Corporation, International Technical Support Organization, 2008.

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6

International Business Machines Corporation. International Technical Support Organization, ed. IBM Z/Os V1r11 Communications Server Tcp/Ip implementation: Basic functions, connectivity, and routing. [Poughkeepsie, NY]: IBM, International Technical Support Organization, 2010.

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7

International Business Machines Corporation. International Technical Support Organization, ed. IBM z/OS V1R13 Communications Server TCP/IP implementation: Base functions, connectivity, and routing. [Poughkeepsie, NY?]: IBM Corporation, International Technical Support Organization, 2012.

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8

International Business Machines Corporation. International Technical Support Organization, ed. IBM z/OS V1R10 Communications Server TCP/IP Implementation: Base functions, connectivity, and routing. [United States?]: IBM, International Technical Support Organization, 2009.

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9

Borzyh, Stanislav. Pananthropea. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1218149.

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The monograph is dedicated to the supercontinent Pananthropea, which was created by the efforts of people, and therefore is named in his honor. It consists of all purely geographical continents, as well as all land areas, representing a single organism that functions exactly as a whole, but at the same time divided by nature itself. The relevance of this approach is shown as follows, as described in the three chapters of the text. First, it demonstrates the physical connectivity of all regions of our planet with each other, which is expressed in a change in the logic of the topology, today planted and controlled by man. Secondly, the presence of this huge and unbroken array is evidenced by the biological component of the world economy, which we have also transformed to suit our needs, thereby redrawing the natural course of affairs in this area and turning it into a global one. Third, the same is true of the cultural domain of our life, which at some point became universal, which again was achieved for the sake of our goals and interests, as a result of which we are all now members of a single interconnected association. It is of interest to both specialists and a wide audience and will be useful for us to understand both ourselves and the reality that we have constructed.
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10

Soriano-Mas, Carles, and Ben J. Harrison. Brain Functional Connectivity in OCD. Edited by Christopher Pittenger. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228163.003.0024.

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This chapter provides an overview of studies assessing alterations in brain functional connectivity in obsessive-compulsive disorder (OCD) as assessed by functional magnetic resonance imaging (fMRI). Although most of the reviewed studies relate to the analysis of resting-state fMRI data, the chapter also reviews studies that have combined resting-state with structural or task-based approaches, as well as task-based studies in which the analysis of functional connectivity was reported. The main conclusions to be drawn from this review are that patients with OCD consistently demonstrate altered patterns of brain functional connectivity in large-scale “frontostriatal” and “default mode” networks, and that the heterogeneity of OCD symptoms is likely to partly arise via distinct modulatory influences on these networks by broader disturbances of affective, motivational, and regulatory systems. The variable nature of some findings across studies as well as the influence of medications on functional connectivity measures is also discussed.
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11

Heinbockel, Thomas. Connectivity and Functional Specialization in the Brain. IntechOpen, 2021.

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12

M, Smith Stephen, Janine Bijsterbosch, and Christian F. Beckmann. Introduction to Resting State fMRI Functional Connectivity. Oxford University Press, 2017.

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13

Nieto-Castanon, Alfonso. Handbook of Functional Connectivity Magnetic Resonance Imaging Methods in CONN. Hilbert Press, 2020.

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14

Pillai, Jay J. Functional Connectivity, an Issue of Neuroimaging Clinics of North America. Elsevier - Health Sciences Division, 2017.

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15

Rocca, Maria Assunta. Functional Connectivity of the Human Brain: From Mechanisms to Clinical Applications. Elsevier Science & Technology Books, 2024.

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16

Dodel, Silke. Data driven analysis of brain activity and functional connectivity in fMRI. 2002.

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17

Rocca, Maria Assunta. Functional Connectivity of the Human Brain: From Mechanisms to Clinical Applications. Elsevier Science & Technology, 2024.

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18

Stamatakis, Emmanuel A., Eleni Orfanidou, and Andrew C. Papanicolaou. Functional Magnetic Resonance Imaging. Edited by Andrew C. Papanicolaou. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.7.

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Functional magnetic resonance imaging (fMRI) is the most frequently used functional neuroimaging method and the one that accounts for most of the neuroimaging literature. It measures the blood oxygen level-dependent (BOLD) signal in different parts of the brain during rest and during task-induced activation of functional networks mediating basic and higher functions. A basic understanding of the various instruments and techniques of recording the hemodynamic responses of different brain regions and the manner in which we establish activation and connectivity patterns out of these responses is necessary for an appreciation of the contemporary functional neuroimaging literature. To facilitate such an understanding is the purpose of this chapter.
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19

Ramani, Ramachandran, ed. Functional MRI. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190297763.001.0001.

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Functional MRI with BOLD (Blood Oxygen Level Dependent) imaging is one of the commonly used modalities for studying brain function in neuroscience. The underlying source of the BOLD fMRI signal is the variation in oxyhemoglobin to deoxyhemoglobin ratio at the site of neuronal activity in the brain. fMRI is mostly used to map out the location and intensity of brain activity that correlate with mental activities. In recent years, a new approach to fMRI was developed that is called resting-state fMRI. The fMRI signal from this method does not require the brain to perform any goal-directed task; it is acquired with the subject at rest. It was discovered that there are low-frequency fluctuations in the fMRI signal in the brain at rest. The signals originate from spatially distinct functionally related brain regions but exhibit coherent time-synchronous fluctuations. Several of the networks have been identified and are called resting-state networks. These networks represent the strength of the functional connectivity between distinct functionally related brain regions and have been used as imaging markers of various neurological and psychiatric diseases. Resting-state fMRI is also ideally suited for functional brain imaging in disorders of consciousness and in subjects under anesthesia. This book provides a review of the basic principles of fMRI (signal sources, acquisition methods, and data analysis) and its potential clinical applications.
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20

Pastore, Vito Paolo. Estimating Functional Connectivity and Topology in Large-Scale Neuronal Assemblies: Statistical and Computational Methods. Springer International Publishing AG, 2021.

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21

Pastore, Vito Paolo. Estimating Functional Connectivity and Topology in Large-Scale Neuronal Assemblies: Statistical and Computational Methods. Springer International Publishing AG, 2020.

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22

Orozco, Jonathan Garst. LEARNING-RELATED CHANGES IN THE FUNCTIONAL CONNECTIVITY WITHIN THE ZEBRA FINCH SONG-CONTROL CIRCUIT. 2014.

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23

Konrad, Kerstin, Adriana Di Martino, and Yuta Aoki. Brain volumes and intrinsic brain connectivity in ADHD. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198739258.003.0006.

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Neuroimaging studies have increased our understanding of the neurobiological underpinnings of ADHD. Structural brain imaging studies demonstrate widespread changes in brain volumes, in particular in frontal-striatal-cerebellar networks. Based on the widespread nature of structural and functional brain abnormalities, approaches able to capture the organizing principles of large-scale neural systems have been used in ADHD. These include diffusion magnetic resonance imaging (MRI) and resting state functional MRI (R-fMRI). Complementary to findings of volumetric studies, diffusion investigations have reported structural connectivity abnormalities in frontal-striatal-cerebellar networks. In parallel, R-fMRI studies point towards abnormalities in the interaction of multiple networks, extending the functional territory of explorations beyond cognitive and motor control. In the future, a deep phenotypic characterization beyond diagnostic categories combined with longitudinal study designs and novel analytical approaches will accelerate the pace towards clinical translations of neuroimaging to improve the detection and prediction of neural trajectories and treatment response in ADHD.
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24

Hannula, Deborah E., and Melissa C. Duff. Hippocampus from Cells to Systems: Structure, Connectivity, and Functional Contributions to Memory and Flexible Cognition. Springer International Publishing AG, 2017.

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25

Hannula, Deborah E., and Melissa C. Duff. The Hippocampus from Cells to Systems: Structure, Connectivity, and Functional Contributions to Memory and Flexible Cognition. Springer, 2018.

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26

Bestmann, Sven, Christian C. Ruff, Jon Driver, and Felix Blankenburg. Concurrent TMS and functional magnetic resonance imaging: methods and current advances. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0036.

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Transcranial magnetic stimulation is used for a wide range of applications in cognitive, clinical, and neuroscience. However, the precise physiological mechanisms by which TMS influences brain function are only partially understood. Combining TMS with functional magnetic resonance imaging (fMRI) provides a more complete picture of the neural underpinnings of TMS effects. This article gives an overview of methodology and technical aspects concerned with combining TMS with fMRI. Furthermore, it explains the challenges involved with the combination of TMS with fMRI and proposes solutions to the same. It also focuses on recent applications of concurrent TMS-fMRI. Combining TMS with fMRI may allow a new noninvasive probe technique for the human brain. TMS-fMRI can be used to compare TMS-evoked effective connectivity in health and disease. It can potentially be used to investigate connectivity changes during different states, with different degrees of involvement for interconnected brain regions during different tasks.
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27

Paus, Tomáš. Combining brain imaging with brain stimulation: causality and connectivity. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0034.

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This article establishes the concept of a methodological approach to combine brain imaging with brain stimulation. Transcranial magnetic stimulation (TMS) is a tool that allows perturbing neural activity, in time and space, in a noninvasive manner. This approach allows the study of the brain-behaviour relationship. Under certain circumstances, the influence of one region on other, called the effective connectivity, can be measured. Functional connectivity is the extent of correlation in brain activity measured across a number of spatially distinct brain regions. This tool of connectivity can be applied to any dataset acquired with brain-mapping tools. However, its interpretation is complex. Also, the technical complexity of the combined studies needs to be resolved. Future studies may benefit from focusing on neurochemical transmission in specific neural circuits and on temporal dynamics of cortico-cortical interactions.
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28

Papanicolaou, Andrew C., ed. The Oxford Handbook of Functional Brain Imaging in Neuropsychology and Cognitive Neurosciences. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764228.001.0001.

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A large part of the contemporary literature involves functional neuroimaging. Yet few readers are sufficiently familiar with the various imaging methods, their capabilities and limitations, to appraise it correctly. To fulfill that need is the purpose of this Handbook, which consists of an accessible description of the methods and their clinical and research applications. The Handbook begins with an overview of basic concepts of functional brain imaging, magnetoencephalography and the use of magnetic source imaging (MSI), positron emission tomography (PET), diffusion tensor imaging (DTI), and transcranial magnetic stimulation (TMS). The authors then discuss the various research applications of imaging, such as white matter connectivity; the function of the default mode network; the possibility and the utility of imaging of consciousness; the search for mnemonic traces of concepts the mechanisms of the encoding, consolidation, and retrieval of memories; executive functions and their neuroanatomical mechanisms; voluntary actions, human will and decision-making; motor cognition; language and the mechanisms of affective states and pain. The final chapter discusses the uses of functional neuroimaging in the presurgical mapping of the brain.
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29

Ribary, Urs, Alex L. MacKay, Alexander Rauscher, Christine M. Tipper, Deborah E. Giaschi, Todd S. Woodward, Vesna Sossi, et al. Emerging neuroimaging technologies: Toward future personalized diagnostics, prognosis, targeted intervention, and ethical challenges. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198786832.003.0002.

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The human brain is a fine-tuned and balanced structural, functional, and dynamic electrochemical system. Any alterations, from slight slowing of partial brain networks to severe disruptions in structural, functional, and dynamic connectivity across local and large-scale brain networks will result in slight to severe changes in cognitive ability, awareness, and consciousness. Using future noninvasive technologies, the common goal is to relate typical or atypical resting-state, sensory-motor functions, cognition, and consciousness to underlying typical or altered quantified brain structure, biochemistry, pathways, functional brain networks, and connectivity. This will pose enormous ethical challenges of quantitative diagnostic and prognostic strategies in future neurologic and psychiatric clinical practice.
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30

Zito, Giancarlo, Takashi Hanakawa, Luca Berdondini, Lorenzo Masia, and Lorenzo Natale, eds. Challenging the Functional Connectivity Disruption in Neurodegenerative Diseases: New Therapeutic Perspectives through Non-Invasive Neuromodulation and Cutting-Edge Technologies. Frontiers Media SA, 2018. http://dx.doi.org/10.3389/978-2-88945-593-5.

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31

Brennan, Brian P., and Scott L. Rauch. Functional Neuroimaging Studies in Obsessive-Compulsive Disorder: Overview and Synthesis. Edited by Christopher Pittenger. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228163.003.0021.

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Studies using functional neuroimaging have played a critical role in the current understanding of the neurobiology of obsessive-compulsive disorder (OCD). Early studies using positron emission tomography (PET) identified a core cortico-striatal-thalamo-cortical circuit that is dysfunctional in OCD. Subsequent studies using behavioral paradigms in conjunction with functional magnetic resonance imaging (fMRI) have provided additional information about the neural substrates underlying specific psychological processes relevant to OCD. More recently, studies utilizing resting state fMRI have identified abnormal functional connectivity within intrinsic brain networks including the default mode and frontoparietal networks in OCD patients. Although these studies, as a whole, clearly substantiate the model of cortico-striatal-thalamo-cortical circuit dysfunction in OCD and support the continued investigation of neuromodulatory treatments targeting these brain regions, there is also growing evidence that brain regions outside this core circuit, particularly frontoparietal regions involved in cognitive control processes, may also play a significant role in the pathophysiology of OCD.
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32

Maggiore, Valeria Della. Large-scale plasticity: Learning-related changes in brain activity and functional connectivity associated with adaptation to distortion of visual feedback. 2003.

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33

Roberts, Timothy P. L., and Luke Bloy. Neuroimaging in Pediatric Psychiatric Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0060.

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Noninvasive imaging and electrophysiological techniques have been developed to probe specific aspects of brain function and dysfunction, providing exquisite spatial maps of functional centers and temporal characteristics. The evolution of these techniques has advanced from single-modality methods identifying functional localization, specialization and segregation, through real-time measures of neuronal activity, toward multimodality integration of structural, functional, and spectro-temporal approaches. While these have an immediate impact in conditions where physical brain lesions are evident (e.g., brain tumor and stroke), making a commensurate contribution within neuropsychiatry is more complex. Nonetheless, by combining concepts of morphology, neurochemistry, neural signal propagation, and regional connectivity, there appears to be ample opportunity to contribute not only to the diagnosis of patients with mental illness but to the stratification and subtyping across behavioral phenotypes and, ultimately, to patient management. Here we present an overview of the most common noninvasive neuroimaging methodologies and their applications to pediatric neurodevelopmental disorders.
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34

Newman, Jennifer, and Charles R. Marmar. Executive Function in Post-Traumatic Stress Disorder. Edited by Charles B. Nemeroff and Charles R. Marmar. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190259440.003.0015.

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This chapter discusses the role of executive function in post-traumatic stress disorder (PTSD), which is far from fully understood. Deficits are subtle and findings are often inconsistent. Impairments have been related to worsening of psychological symptoms, functioning, and quality of life. They can also negatively impact treatment. Functional imaging shows that neurocognitive deficits in PTSD may be related to an imbalance in brain connectivity, where emotion processing is enhanced and control is reduced. Structural findings show abnormalities in brain regions involved in higher-level functions. However, findings are often discrepant. Factors related to these inconclusive results are considered, including developmental course, premorbid functioning, and comorbidities such as traumatic brain injury, depression, substance use, attention deficit hyperactivity disorder, health behaviors, and medical concerns. Treatment implications, limitations of this work, and future directions are presented. The aim of future research is to advance scientific understanding of PTSD, neurocognitive impairments, and related conditions, with the goal of improving outcomes for those who encounter trauma.
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35

Robbins, T. W. Integrating the neurobiological and neuropsychological dimensions of autism. Oxford University Press, 2015. http://dx.doi.org/10.1093/med:psych/9780198523499.003.0002.

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This chapter discusses the integration of the neurobiological and neuropsychological dimensions of autism. It includes a survey of the major neural theories of autism (medial temporal lobe hypothesis, the cerebellar hypothesis, the frontostriatal hypothesis, and evidence from neuroimaging and neuropsychology), and a summary of research suggestions (neuroimaging in a cognitive context, functional connectivity from neuroimaging, and cluster analysis of autistic symptoms).
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36

Wilde, Elisabeth A., Kareem W. Ayoub, and Asim F. Choudhri. Diffusion Tensor Imaging. Edited by Andrew C. Papanicolaou. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.10.

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Diffusion tensor imaging (DTI) is a method of specifying and visualizing the functional integrity of white matter tracts that contribute to the functional and structural connectivity among different brain regions through the examination of water diffusion through tissue. It has gained rapid popularity in the past two decades, particularly for elucidating the process of normal white matter development and the effects of aging on it, as well as providing some insights into the possible neuroanatomical correlates of numerous psychiatric and neurologic disorders. This chapter outlines the instrumentation and the procedures employed in deriving estimates of the functional integrity of anatomical connections in the brain, and issues regarding the reliability and validity of the different DTI procedures are systematically addressed.
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37

Chen, Robert, and john rothwell. Cortical Connectivity: Brain Stimulation for Assessing and Modulating Cortical Connectivity and Function. Springer, 2012.

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38

Chen, Robert, and john rothwell. Cortical Connectivity: Brain Stimulation for Assessing and Modulating Cortical Connectivity and Function. Springer, 2014.

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39

Chen, Robert, and john rothwell. Cortical Connectivity: Brain Stimulation for Assessing and Modulating Cortical Connectivity and Function. Springer London, Limited, 2012.

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40

Bandettini, Peter A., and Hanzhang Lu. Magnetic Resonance Methodologies. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0008.

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Magnetic resonance imaging is a noninvasive tool for assessing brain anatomy, perfusion, metabolism, and function with precision. In this chapter, the basics and the most cutting edge examples of MRI-based measures are described. The first is measurement of cerebral perfusion, including the latest techniques involving spin-labelling as well as the tracking of exogenous contrast agents. Functional MRI is then discussed, along with some of the cutting edge methodology that has yet to make it into routine clinical practice. Next, resting state fMRI is described, a powerful technique whereby the entire brain connectivity can be established. Diffusion-based MRI techniques are useful for diagnosing brain trauma as well as understanding the structural connections in healthy and pathological brains. Spectroscopy is able to make spatially specific and metabolite-specific assessment of brain metabolism. The chapter ends with an overview of structural imaging with MRI, highlighting the developing field of morphometry and its potential for differentially assessing individual brains.
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41

Michel, Christoph M., and Bin He. EEG Mapping and Source Imaging. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0045.

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This chapter describes methods to analyze the scalp electric field recorded with multichannel electroencephalography (EEG). With advances in high-density EEG, systems now allow fast and easy recording from 64 to 256 channels simultaneously. Pattern-recognition algorithms can characterize the topography of scalp electric fields and detect changes in topography over time and between experimental or clinical conditions. Methods for estimating the sources underlying the recorded scalp potential maps have increased the spatial resolution of EEG. The use of anatomical information in EEG source reconstruction has increased the precision of EEG source localization. Algorithms of functional connectivity applied to the source space allow determination of communication between large-scale brain networks in certain frequencies and identification of the directionality of this information flow and detection of crucial drivers in these networks. These methods have boosted the use of EEG as a functional neuroimaging method in experimental and clinical applications.
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42

Gardner, Andrew, Grant L. Iverson, Paul van Donkelaar, Philip N. Ainslie, and Peter Stanwell. Magnetic Resonance Spectroscopy, Diffusion Tensor Imaging, and Transcranial Doppler Ultrasound Following Sport-Related Concussion. Edited by Ruben Echemendia and Grant L. Iverson. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199896585.013.12.

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Sport-related concussion has been referred to as a functional rather than a structural injury with neurometabolic and microstructural alterations reported in several studies. Accordingly, conventional neuroimaging techniques, such as computed tomography (CT) and structural magnetic resonance imaging (MRI), have limited value beyond ruling out structural injury such as a contusion or hemorrhage. This chapter presents a review of three neuroimaging techniques that offer insight into the connectivity and neurometabolic consequences of concussion. A number of studies have now been published using magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI)/diffusion-weighted imaging, and transcranial Doppler ultrasound (TCD) with varying findings. The results of these studies will be presented, together with current and possible future application of these techniques within the field of sport-related concussion.
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43

Heckers, Stephan, Neil Woodward, and Dost Öngür. Neuroimaging of Psychotic Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0014.

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Neuroimaging of psychotic disorders began in the 1970s with studies of brain structure, followed by studies of blood flow, glucose metabolism, and receptor chemistry. More recently, studies of functional activation, connectivity, and neurotransmission have been added. The widespread availability of MRI has liberated researchers from the constraints of postmortem research and the limitations of inferring brain abnormalities through neurochemical effects in plasma or urine. Neuroimaging researchers aim to establish diagnostic markers, explain abnormal mental states, test anatomical and neurochemical models, and study the association of risk genes with brain abnormalities. Most studies have been cross-sectional and limited in size. But the ability to assess patients longitudinally and with large-scale study designs will ensure a prominent position for this research domain in the study of psychotic disorders.
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44

Hanajima, Ritsuko, and Yoshikazu Ugawa. Paired-pulse measures. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0011.

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This article reviews the physiology and application of the currently available paired-pulse protocols. Paired-pulse transcranial magnetic stimulation (TMS) techniques study the modulation of human motor cortical excitability. Paired-pulse experiments are designed to give insight into the nature of the cortical circuitry activated by TMS. Changes in motor cortical excitability produced by the conditioning pulse are estimated by changes in the size of the conditioned motor-evoked potential (MEP). It is possible to identify specific abnormalities in the balance between inhibitory and facilitatory processes, even if the pathology lies in abnormal afferent signalling to the motor cortex rather than in the motor cortex itself. The conclusion that emerges from the studies on interhemispheric interactions is that it is now possible by means of TMS protocols to chart long-range functional interhemispheric connectivity of remote areas of the human brain.
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45

Ilmoniemi, Risto J., and Jari Karhu. TMS and electroencephalography: methods and current advances. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0037.

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Electroencephalography (EEG) combined with transcranial magnetic stimulation (TMS) provides detailed real-time information about the state of the cortex. EEG requires only two to four electrodes and can be a part of most TMS studies. When used with magnetic resonance imaging (MRI) based targeting and conductor modelling, the TMS-EEG combination is a sophisticated brain-mapping tool. This article explains the mechanisms of TMS-evoked EEG. It describes the technique of recording TMS evoked EEG and the possible challenges for the same. Furthermore, it describes possible solutions to these challenges. By varying the TMS intensities, interstimulus intervals, induced current direction, and cortical targets, a rich spectrum of functional information can be obtained. Cortical excitability and connectivity can be studied directly by combining TMS with EEG or other brain-imaging methods, not only in motor, but also nonmotor, areas.
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46

Hoftman, Gil D., and Dean F. Salisbury. Neurobiology of Schizophrenia. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199331505.003.0005.

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Schizophrenia is a brain disease with unknown etiology; a variety of neurodevelopmental mechanisms contribute to its pathogenesis. In this chapter, we review some of the most salient neurobiological findings that seem to be linked with the pathophysiology of psychosis generally and schizophrenia specifically. Several important findings have been made from neuroimaging and neuropathology, including reduced whole-brain volume, enlarged ventricles, and decreased cortical gray matter. Abnormalities in the prefrontal cortex, such as decreased dendritic spine density, are particularly important for cognitive and negative symptoms in schizophrenia. Functional imaging suggests that patterns of activation may be closely linked to symptom clusters. We will review neurotransmitter abnormalities, especially dopamine but also glutamate and GABA, and relevant circuitry and connectivity problems related to pathology. Finally, we will discuss genetics and heritability, and the challenges of identifying relevant loci in such a complex disorder.
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47

Pittenger, Christopher. The Neurobiology of Tic Disorders and Obsessive-Compulsive Disorder. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0065.

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Obsessive-compulsive disorder (OCD) and Tourette syndrome (TS), along with other tic disorders, involve pathophysiological alterations in the cortico-striatal circuitry. Both are neurodevelopmental conditions, although OCD can also have adult onset. They are frequently comorbid and often run together in families. Recent genetic studies suggest shared risk factors, especially in the case of early-onset OCD. Because of these shared characteristics, they are treated together here. Structural and functional neuroimaging studies are refining our understanding of the abnormalities in corticostriatal connectivity that accompany symptomatology; in the case of TS, these have been accompanied by exciting observations in postmortem tissue that are beginning to connect observed anatomical and network abnormalities to underlying cellular substrates. Finally, recent advances in animal modeling of pathophysiology have allowed testing of specific etiological hypotheses and have established several systems in which more precise mechanistic studies of pathophysiology are now proceeding.
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48

Wendling, Fabrice, Marco Congendo, and Fernando H. Lopes da Silva. EEG Analysis. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0044.

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This chapter addresses the analysis and quantification of electroencephalographic (EEG) and magnetoencephalographic (MEG) signals. Topics include characteristics of these signals and practical issues such as sampling, filtering, and artifact rejection. Basic concepts of analysis in time and frequency domains are presented, with attention to non-stationary signals focusing on time-frequency signal decomposition, analytic signal and Hilbert transform, wavelet transform, matching pursuit, blind source separation and independent component analysis, canonical correlation analysis, and empirical model decomposition. The behavior of these methods in denoising EEG signals is illustrated. Concepts of functional and effective connectivity are developed with emphasis on methods to estimate causality and phase and time delays using linear and nonlinear methods. Attention is given to Granger causality and methods inspired by this concept. A concrete example is provided to show how information processing methods can be combined in the detection and classification of transient events in EEG/MEG signals.
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49

Ramirez, Dennis. Default Mode Network Dmn: Structural Connectivity, Impairments and Role in Daily Activities (Neuroscience Research Progress). Nova Science Publishers, Inc., 2015.

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50

South, Mikle, John D. Herrington, and Sarah J. Paterson. Neuroimaging in Autism Spectrum Disorders. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199744312.003.0003.

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This chapter reviews several major themes in the neuroimaging of ASDs to date (see summary of representative themes in Table 3.1), including substantial and essential contributions from the modular framework. The chapter begins, however, with a discussion of several challenges related to the diversity of ASDs in terms of factors such as age, level of functioning, and symptom presentation. Progress in the ability to identify more homogenous subgroups, based on targeted phenotypic measures, opens the door to link neuroimaging with genetics findings and also with treatment outcome data. This should lead to better understanding of both the causes of ASDs and the best approaches to intervention. The chapter is divided according to two broad, related themes related to social information processing and cognitive factors in ASDs. Within these themes, the chapter considers evidence from both structural and functional imaging studies as well as relatively newer approaches to connectivity, including diffusion tensor imaging. The primary focus of this chapter is on research utilizing functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Although several early neuroimaging studies utilized positron emission tomography scanning, these studies are rare now and are not addressed in depth. New techniques such as near-infrared spectroscopy suggest tremendous promise for noninvasive imaging of expanded age groups and severity levels of ASDs; however, these studies are also few in number and are touched on only briefly.
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