脑成像
Methods in Mind 豆瓣
作者: Senior, Carl (EDT)/ Russell, Tamara (EDT)/ Gazzaniga, Michael S. (EDT) Mit Press 2006 - 6
The evolution of cognitive neuroscience has been spurred by the development of increasingly sophisticated investigative techniques to study human cognition. In Methods in Mind, experts examine the wide variety of tools available to cognitive neuroscientists, paying particular attention to the ways in which different methods can be integrated to strengthen empirical findings and how innovative uses for established techniques can be developed. The book will be a uniquely valuable resource for the researcher seeking to expand his or her repertoire of investigative techniques.
Each chapter explores a different approach. These include transcranial magnetic stimulation, cognitive neuropsychiatry, lesion studies in nonhuman primates, computational modeling, psychophysiology, single neurons and primate behavior, grid computing, eye movements, fMRI, electroencephalography, imaging genetics, magnetoencephalography, neuropharmacology, and neuroendocrinology. As mandated, authors focus on convergence and innovation in their fields; chapters highlight such cross-method innovations as the use of the fMRI signal to constrain magnetoencephalography, the use of electroencephalography (EEG) to guide rapid transcranial magnetic stimulation at a specific frequency, and the successful integration of neuroimaging and genetic analysis. Computational approaches depend on increased computing power, and one chapter describes the use of distributed or grid computing to analyze massive datasets in cyberspace. Each chapter author is a leading authority in the technique discussed.
Contributors:
Peyman Adjamian, Peter A. Bandettini, Mark Baxter, Anthony S. David, James Dobson, Ian Foster, Michael Gazzaniga, Dietmar G. Heinke, Stephen Hall, John M. Henderson, Glyn W. Humphreys, Andreas Meyer-Lindenburg, Venkata Mattay, Elisabeth A. Murray, Gina Rippon, Tamara Russell, Carl Senior, Philip Shaw, Krish D. Singh, Marc A. Sommer, Lauren Stewart, John D. Van Horn, Jens Voeckler, Vincent Walsh, Daniel R. Weinberger, Michael Wilde, Jeffrey Woodward, Robert H. Wurtz, Eun Young Yoon, Yong Zhao
Statistical Parametric Mapping 豆瓣
作者: Karl J. Friston / John T. Ashburner Academic Press 2006
Book Description
Describes the theoretical background behind Statistical Parametric Mapping and provides operational guidelines and technical details on data analysis.
Product Description
In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis.
* An essential reference and companion for users of the SPM software
* Provides a complete description of the concepts and procedures entailed by the analysis of brain images
* Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data
* Stands as a compendium of all the advances in neuroimaging data analysis over the past decade
* Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes
* Structured treatment of data analysis issues that links different modalities and models
* Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
From the Back Cover
In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis.
Key Features:
* An essential reference and companion for users of the SPM software
* Provides a complete description of the concepts and procedures entailed by the analysis of brain images
* Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data
* Stands as a compendium of all the advances in neuroimaging data analysis over the past decade
* Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes
* Structured treatment of data analysis issues that links different modalities and models
* Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
Computing Brain Activity Maps from fMRI Time-Series Images 通过功能性核磁共振时序造影计算大脑活动图谱 豆瓣
作者: Gordon E. Sarty Cambridge University Press 2006 - 11
fMRI is a very popular method for researchers and clinicians to image human brain activity in response to given mental tasks. This book presents a comprehensive review of the methods for computing activity maps, while providing an intuitive and mathematical outline of how each method works. The approaches include statistical parametric maps (SPM), hemodynamic response modeling and deconvolution, Bayesian, Fourier and nonparametric methods. The newest activity maps provide information on regional connectivity and include principal and independent component analysis, crisp and fuzzy clustering, structural equation modeling, and dynamic causal modeling. Preprocessing and experimental design issues are discussed with references made to the software available for implementing the various methods. Aimed at graduate students and researchers, it will appeal to anyone with an interest in fMRI and who is looking to expand their perspectives of this technique.