Exploratory Analysis and Data Modeling in Functional Neuroimaging PDF Download
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Author: Friedrich T. Sommer
Publisher: MIT Press
ISBN: 9780262194815
Category : Computers
Languages : en
Pages : 318
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Book Description
An overview of theoretical and computational approaches to neuroimaging.
Author: Friedrich T. Sommer
Publisher: MIT Press
ISBN: 9780262194815
Category : Computers
Languages : en
Pages : 318
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Book Description
An overview of theoretical and computational approaches to neuroimaging.
Author: Hernando Ombao
Publisher: CRC Press
ISBN: 1482220989
Category : Mathematics
Languages : en
Pages : 702
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Book Description
This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.
Author: Markus Ullsperger
Publisher: Oxford University Press
ISBN: 0190451777
Category : Medical
Languages : en
Pages : 336
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Book Description
One of the major challenges in science is to study and understand the human brain. Numerous methods examining different aspects of brain functions have been developed and employed. To study systemic interactions brain networks in vivo, non-invasive methods such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been used with great success. However, each of these methods can map only certain, quite selective aspects of brain function while missing others; and the inferences on neuronal processes and information flow are often rather indirect. To overcome these shortcomings of single methods, researchers have attempted to combine methods in order to make optimal use of their advantages while compensating their disadvantages. Hence, it is not surprising that soon after the introduction of fMRI as a neuroimaging method the possibilities of combinations with EEG have been explored. This book is intended to aid researchers who plan to set up a simultaneous EEG-fMRI laboratory and those who are interested in integrating electrophysiological and hemodynamic data. As will be obvious from the different chapters, this is a dynamically developing field in which several approaches are being tested, validated and compared. Currently, there is no one best solution for all problems available, but many promising techniques are emerging. This book shall give a comprehensive overview of these techniques. In addition, it points to open questions and directions for future research.
Author: Ning Zhong
Publisher: Springer Science & Business Media
ISBN: 3642049532
Category : Computers
Languages : en
Pages : 248
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Book Description
This volume contains the papers selected for presentation at The 2009 Inter- tional Conference on Brain Informatics (BI 2009) held at Beijing University of Technology, China, on October 22–24, 2009. It was organized by the Web Int- ligence Consortium (WIC) and IEEE Computational Intelligence Society Task Force on Brain Informatics (IEEE TF-BI). The conference was held jointly with The 2009 International Conference on Active Media Technology (AMT 2009). Brain informatics (BI) has emergedas an interdisciplinaryresearch?eld that focuses on studying the mechanisms underlying the human information proce- ing system (HIPS). It investigates the essential functions of the brain, ranging from perception to thinking, and encompassing such areas as multi-perception, attention,memory,language,computation,heuristicsearch,reasoning,planning, decision-making, problem-solving, learning, discovery, and creativity. The goal of BI is to develop and demonstrate a systematic approach to achieving an integrated understanding of both macroscopic and microscopic level working principles of the brain, by means of experimental, computational, and cognitive neuroscience studies, as well as utilizing advanced Web Intelligence (WI) centric information technologies. BI represents a potentially revolutionary shift in the way that research is undertaken. It attempts to capture new forms of c- laborative and interdisciplinary work. Following this vision, new kinds of BI methods and global research communities will emerge, through infrastructure on the wisdom Web and knowledge grids that enables high speed and d- tributed, large-scale analysis and computations, and radically new ways of sh- ing data/knowledge.
Author: Zbigniew W. Ras
Publisher: Springer Science & Business Media
ISBN: 3540684158
Category : Computers
Languages : en
Pages : 275
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Book Description
This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.
Author: Marzena Kryszkiewicz
Publisher: Springer Science & Business Media
ISBN: 3540734503
Category : Computers
Languages : en
Pages : 854
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Book Description
This book constitutes the refereed proceedings of the International Conference on Rough Sets and Emerging Intelligent Systems Paradigms, RSEISP 2007, held in Warsaw, Poland in June 2007 - dedicated to the memory of Professor Zdzislaw Pawlak. The 73 revised full papers papers presented together with 2 keynote lectures and 11 invited papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on foundations of rough sets, foundations and applications of fuzzy sets, granular computing, algorithmic aspects of rough sets, rough set applications, rough/fuzzy approach, information systems and rough sets, data and text mining, machine learning, hybrid methods and applications, multiagent systems, applications in bioinformatics and medicine, multimedia applications, as well as web reasoning and human problem solving.
Author: Ning Zhong
Publisher: Springer
ISBN: 3540770283
Category : Computers
Languages : en
Pages : 526
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Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of the First WICI International Workshop on Web Intelligence meets Brain Informatics, WImBI 2006, which was held in Beijing, China, in December 2006. The workshop explores a new perspective of Web Intelligence (WI) research from the viewpoint of Brain Informatics (BI). The 26 revised full-length papers presented together with three introductory lectures have been carefully reviewed and selected.
Author: Andreas Miroslaus Wichert
Publisher: World Scientific
ISBN: 9811234078
Category : Computers
Languages : en
Pages : 641
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Book Description
This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)
Author: Irina Rish
Publisher: MIT Press
ISBN: 0262325330
Category : Computers
Languages : en
Pages : 265
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Book Description
Key approaches in the rapidly developing area of sparse modeling, focusing on its application in fields including neuroscience, computational biology, and computer vision. Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse modeling, focusing on its applications in fields including neuroscience, computational biology, and computer vision. Sparse modeling methods can improve the interpretability of predictive models and aid efficient recovery of high-dimensional unobserved signals from a limited number of measurements. Yet despite significant advances in the field, a number of open issues remain when sparse modeling meets real-life applications. The book discusses a range of practical applications and state-of-the-art approaches for tackling the challenges presented by these applications. Topics considered include the choice of method in genomics applications; analysis of protein mass-spectrometry data; the stability of sparse models in brain imaging applications; sequential testing approaches; algorithmic aspects of sparse recovery; and learning sparse latent models. Contributors A. Vania Apkarian, Marwan Baliki, Melissa K. Carroll, Guillermo A. Cecchi, Volkan Cevher, Xi Chen, Nathan W. Churchill, Rémi Emonet, Rahul Garg, Zoubin Ghahramani, Lars Kai Hansen, Matthias Hein, Katherine Heller, Sina Jafarpour, Seyoung Kim, Mladen Kolar, Anastasios Kyrillidis, Seunghak Lee, Aurelie Lozano, Matthew L. Malloy, Pablo Meyer, Shakir Mohamed, Alexandru Niculescu-Mizil, Robert D. Nowak, Jean-Marc Odobez, Peter M. Rasmussen, Irina Rish, Saharon Rosset, Martin Slawski, Stephen C. Strother, Jagannadan Varadarajan, Eric P. Xing
Author: Stephane Doncieux
Publisher: Springer Science & Business Media
ISBN: 3642151922
Category : Computers
Languages : en
Pages : 676
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Book Description
This volume constitutes the refereed proceedings of the 11th International Conference on Simulation and Adaptive Behavior, SAB 2010, held in Paris and Clos Lucé, France, in August 2010. The articles cover all main areas in animat research, including perception and motor control, action selection, motivation and emotion, internal models and representation, collective behavior, language evolution, evolution and learning. The authors focus on well-defined models, computer simulations or robotic models, that help to characterize and compare various organizational principles, architectures, and adaptation processes capable of inducing adaptive behavior in real animals or synthetic agents, the animats.
