Exploratory Analysis and Data Modeling in Functional Neuroimaging (Hardcover)
暫譯: 功能性神經影像學中的探索性分析與數據建模 (精裝版)

Friedrich T. Sommer, Andrzej Wichert

  • 出版商: MIT
  • 出版日期: 2002-12-02
  • 售價: $1,500
  • 語言: 英文
  • 頁數: 352
  • 裝訂: Hardcover
  • ISBN: 0262194813
  • ISBN-13: 9780262194815
  • 相關分類: Data Science
  • 立即出貨

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商品描述

Description:

Functional imaging tools such as fMRI (functional magnetic resonance imaging), PET (positron emission tomography), EEG (electro-encephalogram), and MEG (magneto-encephalogram) allow researchers to record activity in the working brain and draw inferences about how the brain functions. This book provides a survey of theoretical and computational approaches to neuroimaging, including inferential, exploratory, and causal methods of data analysis; theories of cerebral function; and biophysical and computational models of neural nets. It also emphasizes the close relationships between different approaches, for example, between causal data analysis and biophysical modeling, and between functional theories and computational models.

Friedrich T. Sommer is Scientist at the Redwood Neuroscience Institute, Menlo Park, CA.

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Table of Contents:

Series Foreword vii
Foreword
Manfred Spitzer
ix
Preface xiii
1. Theories, Data Analysis, and Simulation Models in Neuroimaging--An Overview
Friedrich T. Sommer, Judith A. Hirsch and Andrzej Wichert
1
I. fMRI Data Analysis and Experimental Design 15
2. Exploratory Analysis of fMRI Data by Fuzzy Clustering--Philosophy, Strategy, Tactics, Implementation
Ray Somorjai and Mark Jarmasz
17
3. Testing Competing Hypotheses about Single Trial fMRI
Lars Kai Hansen, Archana Purushotham and Seong-Gi Kim
49
4. Deterministic and Stochastic Features of fMRI Data: Implications for Data Averaging
Martin J. McKeown
63
5. Exploratory Analysis of Event-Related fMRI Demonstrated in a Working Memory Study
Andrzej Wichert, Henrik Walter, Jo Grothe, Birgit Abler and Friedrich T. Sommer
77
6. Functional Magnetic Resonance Imaging Adaptation: A Technique for Studying the Properties of Neuronal Networks
Andreas S. Tolias, Zoe Kourtzi and Nikos K. Logothetis
109
II. EGM/MEG Data Analysis 127
7. Independent Components of Magnetoencephalography: Localization
Akaysha C. Tang and Barak A. Pearlmutter
129
8. Blind Decomposition of Multimodal Evoked Responses and DC Fields
Ricardo Vigário, Andreas Ziehe, Matthias M. Müller, Gerd Wübbeler, Lutz Trahms, Bruno-Marcel Mackert, Gabriel Curio, Veikko Jousmäki, Jaakko Särelä and Erkki Oja
163
III. Combination EEG/MEG and fMRI 193
9. Having Your Voxels and Timing Them Too?
Scott Makeig, Tzyy-Ping Jung and Terrence J. Sejnowski
195
10. Recording of Evoked Potentials during Functional MRI
Frithjof Kruggel and Christoph S. Herrmann
209
IV. Models Integrating Neurophysiology and Functional Imaging 229
11. Synthetic PET Imaging for Grasping: From Primate Neurophysiology to Human Behavior
Michael A. Arbib, Andrew H. Fagg and Scott T. Grafton
231
12. The Use of Large-Scale Modeling for Interpreting Human Brain Imaging Experiments
M-A. Tagamets and Barry Horwitz
251
13. Large-Scale Networks in Learning Analyzed with Partial Least Squares
Hemanth P. Nair and Francisco Gonzalez-Lima
273
Index 295

商品描述(中文翻譯)

描述:
功能性影像工具如 fMRI(功能性磁共振成像)、PET(正子發射斷層掃描)、EEG(腦電圖)和 MEG(磁腦圖)使研究人員能夠記錄工作中的大腦活動,並推斷大腦的功能。本書提供了神經影像學的理論和計算方法的概述,包括推論性、探索性和因果性數據分析方法;大腦功能理論;以及神經網絡的生物物理和計算模型。它還強調不同方法之間的密切關係,例如因果數據分析與生物物理建模之間的關係,以及功能理論與計算模型之間的關係。

Friedrich T. Sommer 是加州門洛帕克的紅木神經科學研究所的科學家。

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目錄:
系列前言
前言
Manfred Spitzer
前言
1. 神經影像學中的理論、數據分析和模擬模型概述
Friedrich T. Sommer, Judith A. Hirsch 和 Andrzej Wichert
I. fMRI 數據分析與實驗設計
2. 透過模糊聚類進行 fMRI 數據的探索性分析——哲學、策略、戰術、實施
Ray Somorjai 和 Mark Jarmasz
3. 測試單次試驗 fMRI 的競爭假設
Lars Kai Hansen, Archana Purushotham 和 Seong-Gi Kim
4. fMRI 數據的確定性和隨機性特徵:對數據平均的影響
Martin J. McKeown
5. 在工作記憶研究中展示的事件相關 fMRI 的探索性分析
Andrzej Wichert, Henrik Walter, Jo Grothe, Birgit Abler 和 Friedrich T. Sommer
6. 功能性磁共振成像適應:研究神經網絡特性的技術
Andreas S. Tolias, Zoe Kourtzi 和 Nikos K. Logothetis
II. EGM/MEG 數據分析
7. 磁腦圖的獨立成分:定位
Akaysha C. Tang 和 Barak A. Pearlmutter
8. 多模態誘發反應和 DC 場的盲分解
Ricardo Vigário, Andreas Ziehe, Matthias M. Müller, Gerd Wübbeler, Lutz Trahms, Bruno-Marcel Mackert, Gabriel Curio, Veikko Jousmäki, Jaakko Särelä 和 Erkki Oja
III. 結合 EEG/MEG 和 fMRI
9. 你能擁有你的體素並同時計時嗎?
Scott Makeig, Tzyy-Ping Jung 和 Terrence J. Sejnowski
10. 在功能性 MRI 中記錄誘發電位
Frithjof Kruggel 和 Christoph S. Herrmann
IV. 整合神經生理學和功能影像的模型
11. 用於抓取的合成 PET 成像:從靈長類動物神經生理學到人類行為
Michael A. Arbib, Andrew H. Fagg 和 Scott T. Grafton
12. 大規模建模在解釋人腦影像實驗中的應用
M-A. Tagamets 和 Barry Horwitz
13. 用部分最小平方分析學習中的大規模網絡
Hemanth P. Nair 和 Francisco Gonzalez-Lima
索引