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
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说实话,这本书的阅读难度是摆在那里的,它绝非午后消遣的读物。然而,正是这种挑战性,让最终的收获显得格外珍贵。我必须承认,有几处的推导过程,我不得不反复阅读,甚至需要借助外部资源来辅助理解其背后的数学基础。但高明之处在于,每当我觉得快要被那些复杂的符号和矩阵运算击溃时,作者总能及时地抛出一个精妙的几何解释或是一个贴合实际的工程应用场景来“拯救”我。这种节奏的把控,体现了作者极高的教学智慧。他深知读者的“痛点”在哪里,并提前布置了相应的“缓冲带”。尤其值得称赞的是,书中对于方法论的演进历史脉络梳理得极为清晰。它不是孤立地介绍当前最先进的技术,而是追溯了这些技术是如何从早期的粗糙近似,一步步演化到如今的精细化处理。这种历史的纵深感,使得读者能够更深刻地理解“为什么”要选择当前的工具,而不是仅仅停留在“如何”使用的层面。这对于任何想在特定领域深耕的专业人士来说,都是无价的财富。
评分从装帧设计和印刷质量来看,这本书无疑是出版界的精品之作。纸张的选择偏向哑光,有效减少了长时间阅读产生的眼部疲劳,这对于一本需要反复查阅的工具书来说至关重要。内页的图表绘制清晰锐利,即便是涉及到三维或高维空间的抽象图形,也处理得井井有条,色彩的运用克制而有效,完全服务于信息的传递,没有丝毫花哨的装饰。更值得一提的是,书中的脚注和索引系统构建得极为完善,每一次需要追溯某个概念的源头或是查找相关术语时,都能迅速定位,极大地提高了查阅效率。虽然内容本身已经足够厚重,但排版师似乎深谙“留白”的艺术,恰到好处的页边距和行距,使得整本书在视觉上保持了极佳的呼吸感,避免了信息过载带来的压迫感。总而言之,这是一部从内容到形式都体现出极高匠人精神的著作,值得每一个对该领域抱有严肃态度的学习者和研究者收入囊中,并将其作为案头的常备参考资料。
评分初读此书,我感到一种近乎“沉浸式”的学习体验。它并非那种传统的教科书,只是简单地罗列定义和定理,而是更像一位经验丰富的导师,带着你一步步构建起整个知识的殿堂。最让我印象深刻的是作者在处理“不确定性”这一核心议题时的细腻笔触。他没有用那种高高在上的说教口吻,而是通过大量的案例分析,展示了在真实世界的数据面前,理论模型是如何一步步被修正、被挑战,最终如何适应和解释现实的。那种从理论的完美假设跌入现实的泥泞,再用更强大的工具将其打磨光亮的历程,让人感同身受。其中有一章专门探讨了数据异构性对模型稳健性的影响,作者竟然引用了古典哲学中关于“一即是多,多即是一”的辩证思想作为引子,这种跨学科的融合,着实让我眼前一亮。它不仅教会了我如何进行量化分析,更重要的是,它培养了一种面对未知问题时,既要保持批判性思维,又要拥抱复杂性的哲学态度。读完这一章,我感觉自己看待数据和世界的视角都被拓宽了,不再局限于单纯的数字本身。
评分这本书的结构安排堪称典范,它成功地在广度与深度之间找到了一个近乎完美的平衡点。它没有试图涵盖所有已知的分析技术,而是专注于构建一个坚实的核心理论框架,并在该框架内进行了极其深入的挖掘。我特别喜欢作者在章节末尾设置的“反思与展望”环节。这些部分往往没有提供标准答案,而是提出了一系列开放性的、极具启发性的问题,引导读者去思考当前方法论的局限性以及未来可能的研究方向。这不仅仅是一本传授知识的书,它更像是一份邀请函,邀请读者加入到这场持续不断的学术探索之中。例如,书中对某一类模型的局限性讨论,直指当前领域内的一个“老大难”问题,作者并未回避,而是坦诚地指出了现有工具的不足,并展望了在非线性动态系统建模方面可能出现的范式转移。这种诚实和远见,极大地提升了这本书在严肃学术界的地位,让人感觉到自己正在阅读的是一份对未来研究具有指导意义的文献。
评分这本书的封面设计着实抓人眼球,那种深沉的蓝色调配上简约的字体排版,立刻给人一种专业而严谨的学术气息。我最初拿起它,是冲着那个赫然印在封脊上的宏大主题去的,希望能在这本厚厚的著作中,找到关于复杂系统建模与分析的一把万能钥匙。然而,深入阅读后我发现,它更像是一部精雕细琢的艺术品,其内容组织和逻辑推演的精妙程度,远超我的预期。作者似乎拥有将极其抽象的数学概念,用一种近乎诗意的语言阐述出来的魔力。例如,在讲解某种迭代优化算法时,他并没有陷入枯燥的公式堆砌,而是通过一个生动的类比——将参数空间想象成一个布满迷雾的山谷,而算法就是那个不懈探索的向导——瞬间将晦涩的理论变得清晰易懂。这种叙事方式,极大地降低了初学者的门槛,让人在享受阅读过程的同时,不知不觉地吸收了大量前沿的知识。我特别欣赏其中对不同理论流派之间细微差异的梳理,那种中立而深刻的洞察力,使得全书的论述显得无比扎实和全面,完全避免了任何一家独大的偏颇,为读者构建了一个广阔的知识图景。
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