Download or read book Generative AI for brain imaging and brain network construction written by Shuqiang Wang and published by Frontiers Media SA. This book was released on 2023-10-05 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fundamentals of Brain Network Analysis written by Alex Fornito and published by Academic Press. This book was released on 2016-03-04 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain
Download or read book Functional and structural brain network construction representation and application written by Mingxia Liu and published by Frontiers Media SA. This book was released on 2023-04-06 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning and Interpretation in Neuroimaging written by Georg Langs and published by Springer. This book was released on 2012-11-11 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning.
Download or read book The Relevance of the Time Domain to Neural Network Models written by A. Ravishankar Rao and published by Springer Science & Business Media. This book was released on 2011-09-18 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: A significant amount of effort in neural modeling is directed towards understanding the representation of information in various parts of the brain, such as cortical maps [6], and the paths along which sensory information is processed. Though the time domain is integral an integral aspect of the functioning of biological systems, it has proven very challenging to incorporate the time domain effectively in neural network models. A promising path that is being explored is to study the importance of synchronization in biological systems. Synchronization plays a critical role in the interactions between neurons in the brain, giving rise to perceptual phenomena, and explaining multiple effects such as visual contour integration, and the separation of superposed inputs. The purpose of this book is to provide a unified view of how the time domain can be effectively employed in neural network models. A first direction to consider is to deploy oscillators that model temporal firing patterns of a neuron or a group of neurons. There is a growing body of research on the use of oscillatory neural networks, and their ability to synchronize under the right conditions. Such networks of synchronizing elements have been shown to be effective in image processing and segmentation tasks, and also in solving the binding problem, which is of great significance in the field of neuroscience. The oscillatory neural models can be employed at multiple scales of abstraction, ranging from individual neurons, to groups of neurons using Wilson-Cowan modeling techniques and eventually to the behavior of entire brain regions as revealed in oscillations observed in EEG recordings. A second interesting direction to consider is to understand the effect of different neural network topologies on their ability to create the desired synchronization. A third direction of interest is the extraction of temporal signaling patterns from brain imaging data such as EEG and fMRI. Hence this Special Session is of emerging interest in the brain sciences, as imaging techniques are able to resolve sufficient temporal detail to provide an insight into how the time domain is deployed in cognitive function. The following broad topics will be covered in the book: Synchronization, phase-locking behavior, image processing, image segmentation, temporal pattern analysis, EEG analysis, fMRI analyis, network topology and synchronizability, cortical interactions involving synchronization, and oscillatory neural networks. This book will benefit readers interested in the topics of computational neuroscience, applying neural network models to understand brain function, extracting temporal information from brain imaging data, and emerging techniques for image segmentation using oscillatory networks
Download or read book Machine learning methods for human brain imaging written by Fatos Tunay Yarman Vural and published by Frontiers Media SA. This book was released on 2023-03-29 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Brain inspired Machine Learning and Computation for Brain Behavior Analysis written by Rong Chen and published by Frontiers Media SA. This book was released on 2021-04-16 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Human Brain and Artificial Intelligence written by Yueming Wang and published by Springer Nature. This book was released on 2021-04-07 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Human Brain and Artificial Intelligence, HBAI 2020, held in conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic HBAI 2020 was held in the year 2021 and transferred into virtual format. The 11 full papers presented were carefully reviewed and selected from 12 submissions. The papers present most recent research in the fields of brain-inspired computing, brain-machine interfaces, computational neuroscience, brain-related health, neuroimaging, cognition and behavior, learning, and memory, neuron modulation, and closed-loop brain stimulation.
Download or read book Advanced Machine Learning Approaches for Brain Mapping written by Dajiang Zhu and published by Frontiers Media SA. This book was released on 2024-04-10 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain mapping is dedicated to using brain imaging techniques such as MRI, CT, PET, EEG, and fNIRS to understand the brain anatomy, structure, and function, and how it contributes to cognition, behavior, and deficits of brain diseases. Recently, machine learning is in a stage of rapid development, and various new technologies are continuously introduced into the field, from traditional approaches
Download or read book Advanced Computational Intelligence Methods for Processing Brain Imaging Data written by Kaijian Xia and published by Frontiers Media SA. This book was released on 2022-11-09 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Building Organizational Resilience With Neuroleadership written by Saluja, Shefali and published by IGI Global. This book was released on 2024-04-04 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's landscape of leadership and management, a pressing issue confronts professionals at all levels. Traditional leadership paradigms, including emotional intelligence, are proving insufficient in meeting the demands of the dynamic professional environment. Leaders, both aspiring and experienced, grapple with the challenge of establishing deeper, more meaningful connections in both personal and professional spheres. What exacerbates this issue is the lack of awareness regarding the untapped potential residing at the intersection of neuroscience, cognitive psychology, and social sciences. Building Organizational Resilience With Neuroleadership serves as a beacon of knowledge and a solution to this enduring challenge. This thought-provoking book embarks on an illuminating journey through the emerging field of neuroleadership, seamlessly integrating insights from neuroscience, cognitive psychology, and leadership studies. It offers a comprehensive solution, meticulously crafted for academic scholars, researchers, management students, and seasoned professionals who aspire to transcend their leadership abilities. This groundbreaking book propels emotional intelligence to new heights, empowering leaders to forge more profound connections within their teams and organizations. By unraveling the neural underpinnings of effective leadership, it equips readers with the tools to recognize and manage emotions, thereby fostering authenticity in their interactions. It also reveals the profound influence of neurons, encouraging both budding and seasoned leaders to embrace the extraordinary role of brain functions in shaping magnetic organizational cultures and teams. By bringing together the collaborative efforts of pioneering researchers, social scientists, and behavioral experts, a wholistic solution is prepared within the pages of this text.
Download or read book Reshaping CyberSecurity With Generative AI Techniques written by Jhanjhi, Noor Zaman and published by IGI Global. This book was released on 2024-09-13 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: The constantly changing digital environment of today makes cybersecurity an ever-increasing concern. With every technological advancement, cyber threats become more sophisticated and easily exploit system vulnerabilities. This unending attack barrage exposes organizations to data breaches, financial losses, and reputational harm. The traditional defense mechanisms, once dependable, now require additional support to keep up with the dynamic nature of modern attacks. Reshaping CyberSecurity With Generative AI Techniques offers a transformative solution to the pressing cybersecurity dilemma by harnessing the power of cutting-edge generative AI technologies. Bridging the gap between artificial intelligence and cybersecurity presents a paradigm shift in defense strategies, empowering organizations to safeguard their digital assets proactively. Through a comprehensive exploration of generative AI techniques, readers gain invaluable insights into how these technologies can be leveraged to mitigate cyber threats, enhance defense capabilities, and reshape the cybersecurity paradigm.
Download or read book Computational and Network Modeling of Neuroimaging Data written by Kendrick Kay and published by Elsevier. This book was released on 2024-06-17 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuroimaging is witnessing a massive increase in the quality and quantity of data being acquired. It is widely recognized that effective interpretation and extraction of information from such data requires quantitative modeling. However, modeling comes in many diverse forms, with different research communities tackling different brain systems, different spatial and temporal scales, and different aspects of brain structure and function. Computational and Network Modeling of Neuroimaging Data provides an authoritative and comprehensive overview of the many diverse modeling approaches that have been fruitfully applied to neuroimaging data. This book gives an accessible foundation to the field of computational and network modeling of neuroimaging data and is suitable for graduate students, academic researchers, and industry practitioners who are interested in adopting or applying model-based approaches in neuroimaging. - Provides an authoritative and comprehensive overview of major modeling approaches to neuroimaging data - Written by experts, the book's chapters use a common structure to introduce, motivate, and describe a specific modeling approach used in neuroimaging - Gives insights into the similarities and differences across different modeling approaches - Analyses details of outstanding research challenges in the field
Download or read book Understanding Brain Networks in Rats and Humans written by Zhiwei Ma and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Our knowledge of human brain organization has been significantly advanced since the advent of resting-state functional magnetic resonance imaging (rsfMRI), which measures resting state functional connectivity (RSFC) between brain regions. However, the parallel effort in rodents is still sparse, which impedes the progress not only in comparative functional neuroanatomy but also in translational studies of different brain disorders. In this dissertation, we first established a reproducible RSFC-based functional atlas in the awake rat brain, which exhibited high regional specialization. We then constructed a whole-brain functional brain network based on this atlas. We revealed that this network shared similar topological features with the human brain, and further investigated its integrational feature by identifying functional brain hubs. Using the connectivity patterns of these functional parcels as references, we then discovered reproducible spatiotemporal dynamic patterns of spontaneous brain activity in the awake rat brain. Furthermore, we investigated brain network using cortical myelination-based structural covariance across 881 subjects from the Human Connectome Project. Cortical myelination covariance was found to be highly reproducible, and its correlation with RSFC was relatively uniform within each resting-state brain network, but could vary considerably across them. Particularly, this correlation was appreciably stronger in sensory and motor networks than in cognitive and polymodal association networks. Taken together, the studies in this dissertation characterized specialization, integration and spatiotemporal dynamic properties in the awake rat brain, and also discovered the unique network-specific relationship between RSFC and myelination covariance of the human brain. All these new concepts and methodologies established here in healthy subjects can be used for further investigations of brain in diseases.
Download or read book Functional Brain Network Analysis Based on Unsupervised Deep Learning written by Qinglin Dong and published by . This book was released on 2019 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the neuroimaging and brain mapping communities, researchers have proposed a variety of computational methods and tools to learn functional brain network (FBN), such as general linear models (GLM), independent component analysis (ICA) and sparse dictionary learning (SDL). Recently, deep learning has attracted much attention in the fields of machine learning and data mining, and it has been proven that deep learning approach has superb representation power over traditional shallow models. In this research, three deep models, which are volumetric sparse deep belief networks (VS-DBN), neural architecture search based DBN (NAS-DBN) and recurrent autoencoder (RAE), were designed to explore representations of fMRI volumes. The quantitative analysis showed that these deep models have promising capability in learning meaningful FBNs and revealed novel insights into the organizational architecture of human brain.
Download or read book Handbook of Neuroengineering written by Nitish V. Thakor and published by Springer Nature. This book was released on 2023-02-02 with total page 3686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook serves as an authoritative reference book in the field of Neuroengineering. Neuroengineering is a very exciting field that is rapidly getting established as core subject matter for research and education. The Neuroengineering field has also produced an impressive array of industry products and clinical applications. It also serves as a reference book for graduate students, research scholars and teachers. Selected sections or a compendium of chapters may be used as “reference book” for a one or two semester graduate course in Biomedical Engineering. Some academicians will construct a “textbook” out of selected sections or chapters. The Handbook is also meant as a state-of-the-art volume for researchers. Due to its comprehensive coverage, researchers in one field covered by a certain section of the Handbook would find other sections valuable sources of cross-reference for information and fertilization of interdisciplinary ideas. Industry researchers as well as clinicians using neurotechnologies will find the Handbook a single source for foundation and state-of-the-art applications in the field of Neuroengineering. Regulatory agencies, entrepreneurs, investors and legal experts can use the Handbook as a reference for their professional work as well.
Download or read book Deep learning techniques and their applications to the healthy and disordered brain during development through adulthood and beyond written by Amir Shmuel and published by Frontiers Media SA. This book was released on 2023-02-07 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt:
