Neural Engineering,9780306486098

Neural Engineering

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Edition: CD
ISBN13: 9780306486098
ISBN10: 0306486091
Format: Hardcover
Pub. Date: 2005-01-30
Publisher(s): Springer Verlag
List Price: $156.45

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Summary

About the Series: Bioelectric Engineering presents state-of-the-art discussions on modern biomedical engineering with respect to applications of electrical engineering and information technology in biomedicine. This focus affirms Springer's commitment to publishing important reviews of the broadest interest to biomedical engineers, bioengineers, and their colleagues in affiliated disciplines. Recent volumes have covered modeling and imaging of bioelectric activity, neural engineering, biosignal processing, bionanotechnology, among other topics. Key Features of this Volume: Neural Engineering (Bioelectric Engineering Volume 3) contains reviews and discussions of contemporary and relevant topics by leading investigators in the field. It is intended to serve as a textbook at the graduate and advanced undergraduate level in a bioengineering curriculum. The topics include: '¬" Neural Prostheses '¬" Neural Interfacing '¬" Neural Robotics '¬" Functional Neural Stimulation '¬" Neural Imaging '¬" Neural Computation '¬" Neural Networks '¬" Neural System Identification and Prediction '¬" Retinal Neuroengineering This principles and applications approach to neural engineering is essential reading for all academics, biomedical engineers, neuroscientists, neurophysiologists, and industry professionals wishing to take advantage of the latest and greatest in this emerging field. About the Editor: Bin He, PhD., IEEE Fellow, is a leading figure in the field of bioelectric engineering. An internationally recognized scientist with numerous publications, Dr. He has served as the President of the International Society of Bioelectromagnetism and as an Associate or Guest Editor for nine international journals in the field of biomedical engineering. Dr. He is currently Professor of Biomedical Engineering at the University of Minnesota.

Author Biography

Bin He, PhD., is a leading figure in the field of bioelectric engineering. An internationally recognized scientist with numerous publications, Dr. He has served as the President of the International Society of Bioelectromagnetism and as an Associate or Guest Editor for nine international journals in the field of biomedical engineering. Dr. He is currently Professor of Biomedical Engineering, Electrical Engineering, and Neuroscience at the University of Minnesota.

Table of Contents

Sensory Neural Prostheses
1(48)
Philip R. Troyk
Stuart F. Cogan
Introduction
1(1)
Fundamentals of Sensory Neural Prostheses
2(2)
Electrodes for Neural Stimulation
4(17)
Charge Injection Processes and Coatings
6(5)
Fabrication of Neural Stimulating Electrodes
11(7)
Reactions of Neural Tissue to Stimulating Electrodes
18(3)
Transcutaneous Coupling of Power and Telemetry
21(7)
Inductive Links
21(3)
Generating the Transmitter Coil Current
24(2)
Data Telemetry
26(2)
Techniques for Driving Electrodes
28(7)
A Model for a Stimulating Microelectrode
28(3)
Imbalances in Electrode Current Waveforms
31(1)
Constant-Current Electronic Circuits
32(3)
Applications
35(14)
Cochlear Implants
35(3)
Visual Prostheses
38(11)
Interfacing Neural Tissue With Microsystems
49(36)
Ph. A. Passeraub
N. V. Thakor
Introduction
49(1)
Neural Microsystems
50(9)
Background
50(2)
Function Block Diagram
52(4)
Neural Microsystems Configurations
56(3)
Generic Methods to Interface Microsystem and Neural Tissue
59(16)
How to Interface Electrical Signals in Neural Microsystems
59(4)
How to Interface Chemical Signals in Neural Microsystems
63(3)
How to Interface Other Types of Signals in Neural Microsystems
66(2)
How to Set the Interface Position in Neural Microsystems
68(6)
How to Supply Nutrients, O2, and Stable Temperature in Neural Microsystems
74(1)
Example of Neural Microsystem Development
75(3)
Concluding Remarks
78(7)
Brain-Computer Interface
85(38)
Anirudh Vallabhaneni
Tao Wang
Bin He
Introduction
85(1)
What is BCI
85(1)
History of BCI
86(1)
Components of a BCI System
86(3)
Functional Components
87(1)
Feedback
88(1)
Signal Acquisition
89(4)
Invasive Techniques
89(4)
Noninvasive Techniques
93(1)
Feature Extraction and Translation
93(20)
Types of Signals
95(5)
Training
100(2)
Signal Processing and Feature Extraction Techniques
102(4)
Translation Techniques
106(1)
Extraction and Translation in Action: A Case Study on Classification of Motor Imagery Tasks
107(6)
Typical BCI Systems
113(3)
BCI Development
116(7)
Neurorobotics
123(34)
Karen A. Moxon
Introduction
123(3)
Directly Interfacing with the Brain
126(4)
Representation of Information in the Brain
126(2)
Coding Strategies of Ensembles of Single Neurons
128(1)
Decoding the Neural Signal
129(1)
Neurorobotic Control
130(10)
Feasibility of Neurorobotic Control
130(6)
Neurorobotic Control as Tool for Investigating Neural Coding Strategies
136(2)
Neurorobotic Control as a Therapeutic Device
138(2)
Hardware Requirements for Neurorobotic Control
140(9)
The Neural Interface
142(2)
Signal Conditioning
144(2)
Neurorobotic Control Algorithms
146(2)
Packaging and Telemetry
148(1)
New Directions for a Neurorobotic Control
149(8)
Electrical Stimulation of the Neuromuscular System
157(36)
Dominique M. Durand
Warren M. Grill
Robert Kirsch
Introduction
157(1)
Mechanisms of Excitation of Applied Electrical Fields
158(10)
Anatomy and Physiology
158(1)
Electric Fields in Volume Conductors
159(5)
Effects of Applied Electric Fields on Transmembrane Potentials
164(4)
Electrode-Tissue Interface
168(6)
Regulated Voltage and Regulated Current Stimulation
169(1)
Tissue Damage
170(2)
Effect of Waveform
172(2)
Neuromuscular Prostheses
174(11)
Recruitment Properties
175(2)
Electrodes for Muscle Stimulation
177(2)
Upper Extremity Applications
179(1)
Lower Extremity Applications
180(3)
Bladder Prostheses
183(2)
Conclusions
185(8)
Neural Signal Processing
193(28)
Donna L. Hudson
Maurice E. Cohen
Overview
193(1)
Biological Foundations and History
193(1)
Biological Foundations
193(1)
Central Nervous System
194(1)
Analysis of Signals from Single Neurons
194(4)
Neuron Models
196(1)
Neurotransmitters
197(1)
Action Potential Detection
197(1)
Implanted Electrodes
197(1)
Time Series Analysis
198(8)
Properties of Time Series
198(1)
Correlation and Covariance Functions for Stationary Processes
198(1)
Correlation and Covariance Functions for Nonstationary Processes
199(1)
Fourier Analysis
199(1)
Power Spectral Density Functions
200(1)
Wavelet Analysis
200(4)
Chaotic Analysis
204(1)
Linear versus Nonlinear Analysis
205(1)
Biomedical Signals
205(1)
Peripheral Neural Signals
206(1)
Signal Processing in the CNS
207(3)
EEG Analysis
207(2)
Preprocessing
209(1)
Signal Analysis
209(1)
Higher-Order Modeling
210(1)
Neural Signal Analysis and Disease
210(2)
Epilepsy
210(1)
Parkinson's
211(1)
Huntington's
211(1)
Alzheimer's
211(1)
Differentiation of Types of Dementia
211(1)
Higher-Order Decision Models
212(3)
Case Study: Diagnosis of Dementia
212(3)
Frontiers of Neural Signal Processing
215(6)
Electrophysiological Neuroimaging
221(42)
Bin He
Jie Lian
Introduction
221(5)
The Generation and Measurement of the EEG
221(1)
Spatial and Temporal Resolution of the EEG
222(1)
EEG Forward Problem and Inverse Problem
223(1)
Head Volume Conductor Models and Source Models
223(2)
Electrical Potentials in a Concentric Three-Sphere Volume Conductor Model
225(1)
Dipole Source Localization
226(4)
Equivalent Current Dipole Models
226(1)
EEG-based Dipole Source Localization
227(2)
Constrained Dipole Source Localization
229(1)
Distributed Source Imaging
230(9)
Distributed Source Models
232(1)
Linear Inverse Filters
233(3)
Regularization Parameters
236(3)
Two-Dimensional Cortical Imaging Technique
239(10)
Concept of Cortical Imaging Technique
239(1)
Cortical Current Imaging
240(3)
Cortical Potential Imaging
243(3)
Multimodal Integration
246(3)
Surface Laplacian
249(1)
Three-Dimensional Brain Electric Source Imaging
249(5)
Challenges of 3D Neuroimaging
249(1)
Inverse Problem of the 3D Neuroimaging
250(1)
3D Brain Electric Source Models
251(1)
Nonlinear Inverse Problem
252(2)
Discussion
254(9)
Mechanisms of Cortical Computation
263(26)
Leif H. Finkel
Diego Contreras
Introduction
263(4)
Learning and Synaptic Plasticity
267(3)
Spike-Based Computation
270(3)
Spatiotemporal Pattern Recognition
273(5)
Neuronal Firing Characteristics
278(2)
Time Constraints on Cortical Computation
280(1)
Putting It All Together
281(4)
Conclusions
285(4)
Computational Neural Networks
289(44)
Dongming Xu
Bryan Davis
Mustafa Ozturk
Liping Deng
Mark Skowronski
John G. Harris
Walter J. Freeman
Jose C. Principe
Introduction
289(1)
Review of Dynamical Systems Analysis
290(2)
Linear Time-Invariant Systems and Their Qualitative Behavior
290(1)
Nonlinear Systems
291(1)
Bifurcations
291(1)
Poincare-Bendixon Theorem
292(1)
The Olfactory System as a Distributed Neural Network of Coupled Oscillators
292(17)
The Hierarchy Structure of Freeman's Model
292(2)
Dynamic Analysis of a Reduced KII Set
294(15)
Digital Simulation of the Freeman Model
309(8)
Digital Implementation Approaches
309(4)
Quantitative Performance Analysis
313(4)
The Reduced KII Network as an Associative Memory
317(5)
Designing the Excitatory Interconnections of the KII Network
319(1)
Training the KII Interconnection Weights with Oja's Rule
319(1)
Examples
320(2)
Hardware Implementation in Analog VLSI
322(5)
Input Stage
323(1)
Nonlinear Function
323(2)
Second-order Dynamics
325(1)
Chip Measurement Results
325(1)
Comparison of Digital Simulation and Hardware Design
326(1)
Conclusions
327(6)
Circuit Models for Neural Information Processing
333(34)
Ting Ma
Ying-Ying Gu
Yuan-Ting Zhang
Introduction
333(1)
Circuit Models for Single Neurons
333(11)
A Simple Circuit Model for Passive Neuronal Membranes
334(2)
Equivalent Circuit Model for Active Neurons
336(4)
Compartment Model
340(4)
Models for Neuronal Rate Coding
344(10)
An Integrate-and-Fire Circuit Model
344(3)
Integral Pulse Frequency Modulation (IPFM) Model
347(7)
Modeling Rate-Intensity Function in an Auditory Periphery
354(7)
Biophysics of Auditory Periphery
355(1)
IHC Model and Rate-Intensity Function
356(5)
Conclusion
361(6)
Neural System Identification
367(22)
Garrett B. Stanley
Introduction
367(1)
System Identification
368(5)
Dynamical Systems
368(1)
Estimation
369(4)
Representations of Neuronal Activity
373(3)
Spike Times
373(2)
Firing Rate
375(1)
Neuronal Variability
375(1)
Neuronal Encoding in the Visual Pathway
376(4)
Estimation of the STRF
377(1)
Adaptive Estimation
378(2)
Nonlinear Encoding in the Somatosensory Pathway
380(3)
The Impulse Response and Nonlinear Encoding
381(2)
Neural Control of Cardiac Function
383(2)
Input-Driven Threshold Model
384(1)
Summary
385(4)
Seizure Prediction in Epilepsy
389(32)
Wim van Drongelen
Hyong C. Lee
Kurt E. Hecox
Introduction
389(3)
Processes Underlying the Electroencephalogram
392(1)
Electrographic Seizure Activity
393(4)
Time Series Analysis and Application in Eeg
397(10)
Linear Methods
398(1)
Nonlinear Methods
398(8)
Multichannel-Based Methods
406(1)
Surrogate Time Series
406(1)
Evaluation and Future Directions
407(5)
Appendix 1: C Function to Calculate Maximum Likelihood Kolmogorov Entropy
412(3)
Appendix 2: Matlab Scripts to Create Figures 12.2 and 12.5
415(6)
Retinal Bioengineering
421(64)
Robert A. Linsenmeier
Introduction
421(1)
The Neural Structure and Function of the Retina
422(10)
Photoreceptors
422(3)
Retinal Circuits
425(2)
Receptive Fields
427(3)
Eccentricity and Acuity
430(2)
Vasculature of the Retina
432(1)
Major Retinal Diseases
433(4)
Retinitis Pigmentosa
433(1)
Macular Degeneration
434(1)
Glaucoma
435(1)
Diabetic Retinopathy
436(1)
Vascular Occlusive Disease
437(1)
Retinal Detachment
437(1)
Engineering Contributions to Understanding Retinal Physiology and Pathophysiology
437(28)
Photoreceptor Models
438(5)
Postreceptor ERG Analyses
443(3)
Ganglion Cell Models
446(11)
Models of the Retinal Microenvironment
457(8)
Engineering Contributions to Treatment of Retinal Diseases---Visual Prostheses
465(10)
Visual Prostheses
465(1)
Design Goals
466(2)
Subretinal and Epiretinal Prostheses
468(3)
Biocompatibility
471(1)
Coupling of Prostheses to Neurons
472(3)
Vascular Issues
475(1)
Opportunities
475(10)
Index 485

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