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Books on the topic 'Brain functional Network'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

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

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2

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

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3

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

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4

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

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5

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

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6

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

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7

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

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8

Elizabeth, Hillis Argye, ed. New techniques for identifying the neural substrates of language. Psychology Press, 2002.

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9

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

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10

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. Elsevier, 2005.

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11

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. Elsevier, 1994.

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12

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. World Scientific, 1995.

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13

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

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14

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

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15

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 networ

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16

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 app

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17

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, hip

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18

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; i

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19

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

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20

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: o

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21

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

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22

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

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23

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 o

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24

Ribary, Urs, Alex L. MacKay, Alexander Rauscher, 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, bioc

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25

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 dat

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26

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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27

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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28

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

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29

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

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30

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 func

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31

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

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32

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

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33

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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34

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 h

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35

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) activ

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36

Andrews-Hanna, Jessica R. The brain's default network: Anatomy, function, and consequence of disruption. 2009.

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37

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

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38

Baev, Konstantin V. Biological Neural Networks: Hierarchical Concept of Brain Function. Island Press, 1998.

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39

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

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40

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

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41

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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42

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

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43

Fox, Kieran C. R. Neural Origins of Self-Generated Thought. Edited by Kalina Christoff and Kieran C. R. Fox. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190464745.013.1.

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Functional magnetic resonance imaging (fMRI) has begun to narrow down the neural correlates of self-generated forms of thought, with current evidence pointing toward central roles for the default, frontoparietal, and visual networks. Recent work has linked the arising of thoughts more specifically to default network activity, but the limited temporal resolution of fMRI has precluded more detailed conclusions about where in the brain self-created mental content is generated and how this is achieved. This chapter argues that the unparalleled spatiotemporal resolution of intracranial electrophysi

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44

Anderson, James A. The Brain Works by Logic. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780199357789.003.0007.

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Brains and computers were twins separated at birth. In 1943, it was known that action potentials were all or none, approximating TRUE or FALSE. In that year, Walter Pitts and Warren McCulloch wrote a paper suggesting that neurons were computing logic functions and that networks of such neurons could compute any finite logic function. This was a bold and exciting large-scale theory of brain function. Around the same time, the first digital computer, the ENIAC, was being built. The McCulloch-Pitts work was well known to the scientists building ENIAC. The connection between them appeared explicit

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45

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

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46

Fox, Kieran C. R., and Manesh Girn. Neural Correlates of Self-Generated Imagery and Cognition Throughout the Sleep Cycle. Edited by Kalina Christoff and Kieran C. R. Fox. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190464745.013.16.

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Humans have been aware for thousands of years that sleep comes in many forms, accompanied by different kinds of mental content. This chapter reviews the first-person report literature on the frequency and type of content experienced in various stages of sleep, showing that different sleep stages are dissociable at the subjective level. It then relates these subjective differences to the growing literature differentiating the various sleep stages at the neurophysiological level, including evidence from electrophysiology, neurochemistry, and functional neuroimaging. The authors suggest that ther

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47

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 exhibi

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48

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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49

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

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50

Baev, Konstantin V. Biological Neural Networks: The Hierarchical Concept of Brain Function. Birkhauser, 2011.

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