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Books on the topic 'Brain functional Network'

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Published: 9 March 2023
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1

Alessandro, Treves, ed. Neural networks and brain function. Oxford: Oxford University Press, 1998.

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2

W, Thatcher Robert, ed. Functional neuroimaging: Technical foundations. San Diego: Academic Press, 1994.

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3

De Vico Fallani, Fabrizio, and Fabio Babiloni. The Graph Theoretical Approach in Brain Functional Networks. Cham: Springer International Publishing, 2010. http://dx.doi.org/10.1007/978-3-031-01644-8.

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4

1933-, Cotterill Rodney, ed. Models of brain function. Cambridge: Cambridge University Press, 1989.

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5

Baev, Konstantin V. Biological Neural Networks: Hierarchical Concept of Brain Function. Boston, MA: Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4612-4100-3.

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6

Biological neural networks: Hierarchical concept of brain function. Boston: Birkhäuser, 1998.

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7

Modeling brain function: The world of attractor neural networks. Cambridge [England]: Cambridge University Press, 1989.

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8

The metaphorical brain 2: Neural networks and beyond. New York, N.Y: Wiley, 1989.

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9

Paul, Cisek, Drew Trevor, and Kalaska John F, eds. Computational neuroscience: Theoretical insights into brain function. Amsterdam: Elsevier, 2007.

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10

E, Raichle Marcus, ed. Images of mind. New York: Scientific American Library, 1994.

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11

The social brain: Discovering the networks of the mind. New York: Basic Books, 1985.

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12

José, Hanson Stephen, and Olson Carl R, eds. Connectionist modeling and brain function: The developing interface. Cambridge, Mass: MIT Press, 1990.

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13

Elizabeth, Hillis Argye, ed. New techniques for identifying the neural substrates of language. [Hove, East Sussex: Psychology Press, 2002.

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14

Integrative and molecular approach to brain function: Proceedings of the Uehara Memorial Foundation Symposium on Integrative and Molecular Approach to Brain Function, Tokyo, 25-27 June 1996. Amsterdam: Elsevier, 1996.

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15

1947-, Kitamura Tadashi, ed. What should be computed to understand and model brain function?: From robotics, soft computing, biology and neuroscience to cognitive philosophy. xii, 309 p: ill., 2001.

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16

van, Pelt J., ed. The self-organizing brain: From growth cones to functional networks : proceedings of the 18th International Summer School of Brain Research, held at the University of Amsterdm and the Academic Medical Center (The Netherlands) from 23 to 27 August 1993. Amsterdam: Elsevier, 1994.

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17

van, Pelt J., ed. Development, dynamics, and pathology of neuronal networks: From molecules to functional circuits : proceedings of the 23rd International Summer School of Brain Research, held at the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands, from 25-29 August 2003. Amsterdam: Elsevier, 2005.

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18

A, Neugebauer, and Istituto italiano per gli studi filosofici., eds. Macromolecular interplay in brain associative mechanisms: Proceedings of the International School of Biocybernetics, Casamicciola, Napoli, Italy, 16-21 October 1995. Singapore: World Scientific, 1995.

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19

BI 2010 (2010 Toronto, Ont.). Brain informatics: International conference, BI 2010, Toronto, ON, Canada, August 28-30, 2010 : proceedings. Berlin: Springer, 2010.

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20

Functional Specialisation within the Language Network: Effects of Cortical Dysfunction. Peeters Publishers, 2007.

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21

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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22

Rubia, Katya. ADHD brain function. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198739258.003.0007.

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ADHD patients appear to have complex multisystem impairments in several cognitive-domain dissociated inferior, dorsolateral, and medial fronto-striato-parietal and frontocerebellar neural networks during inhibition, attention, working memory, and timing functions. There is emerging evidence for abnormalities in motivation and affect control regions, most prominently in ventral striatum, but also orbital/ventromedial frontolimbic areas. Furthermore, there is an immature interrelationship between hypoengaged task-positive cognitive control networks and a poorly ‘switched off’ default mode network, both of which impact performance. Stimulant medication enhances the activation of inferior frontostriatal systems, while atomoxetine appears to have more pronounced effects on the dorsal attention network. More studies are needed to understand the neurofunctional correlates of the effects of age, gender, ADHD subtypes, and comorbidities with other psychiatric conditions. The use of pattern recognition analyses applied to imaging to make individual diagnostic or prognostic predictions are promising and will be the challenge over the next decade.
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23

Papanicolaou, Andrew C. The Default Mode and Other Resting State Networks. Edited by Andrew C. Papanicolaou. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.003.

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Brain activity during rest, as measured and imaged mainly by fMRI, appears to be due to a number of simultaneously active neuronal networks. The network identified first is the default mode network, which has been used as a marker of conscious awareness in patients with compromised consciousness. In this chapter, the methods of deriving this and other resting networks are outlined, the reliability of each network is assessed, and the question of the functional significance of the default mode network including its relevance to the theory of mind and morality is addressed through a critical appraisal of the relevant literature.
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24

Gorman, Jack M. Making Connections. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190850128.003.0006.

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Although some functions, like speech and vision, can be linked to single, specific locations in the brain, complex emotions and behaviors usually involve complex interactions among brain regions. As our brains mature, these connections are shaped by our lived experiences. Scientists in basic neuroscience laboratories have traced the pathways and networks necessary for the acquisition, expression, and extinction of one emotion: fear. Brain imaging studies have shown that these same connected brain regions are activated by fear and anxiety in humans. The “fear network” includes the amygdala, hippocampus, and prefrontal cortex. Abnormalities in activity and strength of connections in the fear network are present in children and adults with anxiety disorders and depression. Brain networks that are necessary for other emotions and behaviors have been identified, so that today we look to how our brains are connected to understand our actions and emotions.
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25

Treves, Alessandro, and Edmund Rolls. Neural Networks and Brain Function. Oxford University Press, 1999.

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26

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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27

Zhou, Juan, and William W. Seeley. Brain Circuits. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190233563.003.0007.

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Each neurodegenerative disease is defined by selectively vulnerable neurons, regions, networks, and functions, as well as genetic risk factors. In the past decade, new network-sensitive neuroimaging methods have made it possible to test the notion of network-based degeneration in living humans. This chapter focuses on two common causes of dementia, Alzheimer’s disease (AD) and frontotemporal dementia (FTD), but uses these diseases to illustrate class-wide neurodegeneration principles whenever possible. It first introduces two key concepts of neurodegenerative disease selective vulnerability: onset and progression. In parallel, it addresses two distinct but related observations about neurodegenerative disease: clinico-anatomical convergence and phenotypic heterogeneity. It then examines disease onset and models of progression in more detail, based on available neuroimaging evidence. Finally, it touches on the most important frontiers in the field of network-based neurodegeneration.
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28

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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29

Papanicolaou, Andrew C. Overview of Basic Concepts. Edited by Andrew C. Papanicolaou. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.002.

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Functional brain imaging is based on a set of assumptions. A clear appreciation of those makes it possible to form reasonable opinions regarding the potential range of application and the limits of the functional neuroimaging procedures. Exposition of these basic facts and assumptions is the primary goal of this chapter. A secondary goal is the juxtaposition of the basic concepts involved in them, such as the concept of “function,” “brain mechanism,” “neuronal network,” “activity,” and “activation”; drawing, in broad outline, a description of the methods of neuroimaging, their relative spatial and temporal resolution, and the type of neurophysiological effects each of them captures and renders in images.
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30

Papanicolaou, Andrew C., and Marina Kilintari. Imaging the Networks of Language. Edited by Andrew C. Papanicolaou. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.15.

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Among the “higher” functions, language and its cerebral networks is the most intensively explored through behavioral or clinical studies and, more recently, through functional neuroimaging. From the former studies, several models (only partially congruent) have emerged during the past three centuries regarding the organization and topography of the brain mechanisms of the acoustic, phonological, semantic, syntactic, and pragmatic operations in which psycholinguists have divided the language function. The main task of this chapter is to extract from the vast functional neuroimaging literature of language reliable evidence that would be used to disconfirm the various hypotheses comprising the current language models. Most of these hypotheses concern the anatomical structures that could be considered nodes or hubs of the neuronal networks mediating the above-mentioned linguistic operations. Using the same criteria, the authors present neuroimaging evidence relevant to the issue of the neuronal mediation of sign languages, reading, and dyslexia.
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31

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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32

Abbott, David F., John S. Archer, Patrick W. Carney, David N. Vaughan, and Graeme D. Jackson, eds. Functional Brain Mapping of Epilepsy Networks: Methods and Applications. Frontiers Media SA, 2020. http://dx.doi.org/10.3389/978-2-88963-400-2.

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33

F. H. Lopes da Silva, M. A. Corner, H. B. M. Uylings, and J. van Pelt. Self-Organizing Brain: From Growth Cones to Functional Networks. Elsevier Science & Technology Books, 1994.

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34

Amit, Daniel J. Modeling Brain Function: The World of Attractor Neural Networks. Cambridge University Press, 1992.

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35

Amit, Daniel J. Modeling Brain Function: The World of Attractor Neural Networks. Cambridge University Press, 2012.

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36

Bianconi, Ginestra. Communities. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0008.

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Multilayer networks have a mesoscale structure organized in multilayer communities, spanning different layers and often revealing important functional properties of the network. In this chapter the major techniques proposed for detecting and characterizing the multilayer communities are described, including: generalized modularity, consensus clustering, multilayer infomaps, multilink communities, tensorial decomposition, Normalized Mutual Information, theta indicators. The main benefits and limitations of these approaches are discussed and revealed by analysing the results obtained on real datasets coming from sociology, technology, molecular biology and brain networks. Additionally, techniques for layer aggregation and disaggregation are here discussed. These methods are compared and commented in order to provide a general perspective on the subject.
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37

Seeck, Margitta, L. Spinelli, Jean Gotman, and Fernando H. Lopes da Silva. Combination of Brain Functional Imaging Techniques. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0046.

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Several tools are available to map brain electrical activity. Clinical applications focus on epileptic activity, although electric source imaging (ESI) and electroencephalography-coupled functional magnetic resonance imaging (EEG–fMRI) are also used to investigate non-epileptic processes in healthy subjects. While positron-emission tomography (PET) reflects glucose metabolism, strongly linked with synaptic activity, and single-photon-emission computed tomography (SPECT) reflects blood flow, fMRI (BOLD) signals have a hemodynamic component that is a surrogate signal of neuronal (synaptic) activity. The exact interpretation of BOLD signals is not completely understood; even in unifocal epilepsy, more than one region of positive or negative BOLD is often observed. Co-registration of medical images is essential to answer clinical questions, particularly for presurgical epilepsy evaluations. Multimodal imaging can yield information about epileptic foci and underlying networks. Co-registering MRI, PET, SPECT, fMRI, and ESI (or magnetic source imaging) provides information to estimate the epileptogenic zone and can help optimize surgical results.
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38

Fallani, Fabrizio, and Fabio Babiloni. Graph Theoretical Approach in Brain Functional Networks: Theory and Applications. Morgan & Claypool Publishers, 2010.

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39

Fallani, Fabrizio, and Fabio Babiloni. Graph Theoretical Approach in Brain Functional Networks: Theory and Applications. Springer International Publishing AG, 2010.

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40

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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41

Baev, Konstantin V. Biological Neural Networks: Hierarchical Concept of Brain Function. Birkhauser Verlag, 2012.

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42

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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43

The Self-Organizing Brain: From Growth Cones to Functional Networks (Progress in Brain Research). Elsevier Science, 1994.

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44

Babiloni, Fabio, Fabrizio De Vico Fallani, and Fabrizio De Vico Fallani. The Graph Theoretical Approach in Brain Functional Networks: Theory and Applications. Morgan & Claypool Publishers, 2010.

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45

Zorumski, Charles, and Eugene Rubin. Psychiatry and Clinical Neuroscience. Oxford University Press, 2012. http://dx.doi.org/10.1093/med/9780199768769.001.1.

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This resource examines recent developments in the field of network neuroscience and their potential impact on clinical psychiatry, including the way that psychiatrists are trained and interact with other medical specialties and mental health professionals. It discusses how research in neuroscience is revolutionizing how we think about psychiatric diagnosis and treatment, and how understanding how the neural networks that underlie these mental functions become dysfunctional holds great promise for devising innovative approaches to diagnosis and treatment. It covers recent advances in human functional neuroimaging, which is being used to characterize the activity of specific brain circuits at rest and during the performance of specific tasks, as well as advances in clinical neuroscience that are being coupled with expanding knowledge about genetics and cellular and synaptic neuroscience. Taken together, these advancements offer the hope of much more mechanism-based approaches to treatment in the future.
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46

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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47

Peter Aj Van Der Made. Higher Intelligence: How to Create a Functional Artificial Brain. Vivid Publishing, 2013.

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48

Carrión, Victor G., John A. Turner, and Carl F. Weems. Brain Function in Pediatric PTSD. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190201968.003.0009.

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Previous chapters established that many of the symptoms of PTSD in children and adolescents are associated with structural and functional abnormalities of fronto-limbic pathways. The current chapter reviews the scope of the book and discusses general implications that result from these findings, suggests other areas of investigation, and discusses applicability of this neuroscience research to treatment and policy. This includes a survey of current research into critical periods of brain development that may affect the trajectory of PTSD’s development, research into whole-brain networks exhibiting vulnerability to traumatic stress, and innovative treatment strategies based on these emerging theoretical frameworks. Future directions for the ever-growing field of traumatic stress science, as well as miscellaneous findings not otherwise included within this book’s framework, are discussed.
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49

Neuronal Networks in Brain Function, CNS Disorders, and Therapeutics. Elsevier, 2014. http://dx.doi.org/10.1016/c2011-0-04525-8.

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50

Blumenfeld, Hal, and Carl Faingold. Neuronal Networks in Brain Function, CNS Disorders, and Therapeutics. Elsevier Science & Technology Books, 2013.

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