Handbook of Neural Engineering

  • 16h 6m
  • Metin Akay (ed)
  • John Wiley & Sons (US)
  • 2007

An important new work establishing a foundation for future developments in neural engineering

The Handbook of Neural Engineering provides theoretical foundations in computational neural science and engineering and current applications in wearable and implantable neural sensors/probes. Inside, leading experts from diverse disciplinary groups representing academia, industry, and private and government organizations present peer-reviewed contributions on the brain-computer interface, nano-neural engineering, neural prostheses, imaging the brain, neural signal processing, the brain, and neurons.

The Handbook of Neural Engineering covers:

  • Neural signal and image processing—the analysis and modeling of neural activity and EEG-related activities using the nonlinear and nonstationary analysis methods, including the chaos, fractal, and time-frequency and time-scale analysis methods—and how to measure functional, physiological, and metabolic activities in the human brain using current and emerging medical imaging technologies
  • Neuro-nanotechnology, artificial implants, and neural prosthesis—the design of multi-electrode arrays to study how the neurons of human and animals encode stimuli, the evaluation of functional changes in neural networks after stroke and spinal cord injuries, and improvements in therapeutic applications using neural prostheses
  • Neurorobotics and neural rehabilitation engineering—the recent developments in the areas of biorobotic system, biosonar head, limb kinematics, and robot-assisted activity to improve the treatment of elderly subjects at the hospital and home, as well as the interactions of the neuron chip, neural information processing, perception and neural dynamics, learning memory and behavior, biological neural networks, and neural control

About the Editor

Metin Akay is a professor of bioengineering and interim department chairman of the Harrington Department of Bioengineering at the Fulton School of Engineering, Arizona State University at Tempe. He received his Bachelor of Science and Master of Science in Electrical Engineering from the Bogazici University, Istanbul, Turkey in 1981 and 1984, respectively, and a Ph.D. from Rutgers University in 1990.

He is the author/coauthor/editor of 14 books and has given more than 50 keynote, plenary, and invited talks at international meetings including the first, second and third Latin American Conference on Biomedical Engineering in 1998, 2001, and 2004.

Dr. Akay is the founding chair of the Annual International Summer School on Biocomplexity from System, to Gene sponsored by the NSF and Dartmouth College and technically cosponsored by the IEEE EMBS, of the Satellite Conference on Emerging Technologies in Biomedical Engineering. In 2003, he was also the founding chair of the International IEEE Conference on Neural Engineering and the first chair of the steering committee of the IEEE Transaction on Computational Biology and Bioinformatics sponsored by the IEEE (CS, EMBS, NN, etc.) and non-IEEE societies. He was the invited guest editor for the special issues of Bioinformatics: Proteomics and Genomics Engineering of the Proceedings of IEEE, the most highly cited IEEE journal.

Prof. Akay is a recipient of the IEEE EMBS Service Award, an IEEE Third Millennium Medal, and the IEEE Engineering in Medicine and Biology Society Early Career Achievement Award 1997. He also received the Young Investigator Award of the Sigma Xi Society, Northeast Region in 1998 and 2000.

Dr. Akay is a fellow of Institute of Physics, senior member of the IEEE, a member of BMES, Eta Kappa, Sigma Xi, Tau Beta Pi. He also serves on the editorial or advisory board of several international journals including the IEEE T-BME, IEEE T-NSRE, IEEE T-ITIB, Proceedings of IEEE, Journal of Neural Engineering, NIH Neural Engineering and Bioengineering partnership study sections and several NSF review panels.

In this Book

  • Optimal Signal Processing for Brain – Machine Interfaces
  • Modulation of Electrophysiological Activity in Neural Networks—Toward A Bioartificial Living System
  • Estimation of Posterior Probabilities with Neural Networks—Application to Microcalcification Detection in Breast Cancer Diagnosis
  • Identification of Central Auditory Processing Disorders by Binaurally Evoked Brainstem Responses
  • Functional Characterization of Adaptive Visual Encoding
  • Deconvolution of Overlapping Auditory Brainstem Responses Obtained at High Stimulus Rates
  • Autonomic Cardiac Modulation at Sinoatrial and Atrioventricular Nodes—observations and Models
  • Neural Networks and Time–Frequency Analysis of Surface Electromyographic Signals for Muscle Cerebral Control
  • Multiresolution Fractal Analysis of Medical Images
  • Methods for Neural-Network-Based Segmentation of Magnetic Resonance Images
  • High-Resolution Eeg and Estimation of Cortical Activity for Brain–Computer Interface Applications
  • Estimation of Cortical Sources Related to Short-Term Memory in Humans with High-Resolution Eeg Recordings and Statistical Probability Mapping
  • Exploring Semantic Memory Areas by Functional MRI
  • Restoration of Movement By Implantable Neural Motor Prostheses
  • Hybrid Olfactory Biosensor Using Multichannel Electroantennogram—Design and Application
  • Reconfigurable Retina-Like Preprocessing Platform for Cortical Visual Neuroprostheses
  • Biomimetic Integration of Neural And Acoustic Signal Processing
  • Retinal Image and Phosphene Image: an Analogy
  • Brain-Implantable Biomimetic Electronics As Neural Prostheses To Restore Lost Cognitive Function
  • Advances in Retinal Neuroprosthetics
  • Towards A Cultured Neural Probe—Patterning of Networks and Their Electrical Activity
  • Spike Superposition Resolution in Multichannel Extracellular Neural Recordings—A Novel Approach
  • Toward A Button-Sized 1024-Site Wireless Cortical Microstimulating Array
  • Practical Considerations in Retinal Neuroprosthesis Design
  • Interfacing Neural and Artificial Systems—From Neuroengineering to Neurorobotics
  • Neurocontroller for Robot Arms Based on Biologically Inspired Visuomotor Coordination Neural Models
  • Muscle Synergies for Motor Control
  • Robots with Neural Building Blocks
  • Decoding Sensory Stimuli from Populations of Neurons—Methods for Long-Term Longitudinal Studies
  • Model of Mammalian Visual System with Optical Logic Cells
  • Cns Reorganization During Sensory-Supported Treadmill Training
  • Independent Component Analysis of Surface Emg for Detection of Single motoneurons Firing in Voluntary Isometric Contraction
  • Recent Advances in Composite Aep Eeg Indices for Estimating Hypnotic Depth During General Anesthesia
  • Eng Recording Amplifier Configurations for Tripolar Cuff Electrodes
  • Cable Equation Model for Myelinated Nerve Fiber
  • Bayesian Networks for Modeling Cortical Integration
  • Normal and Abnormal Auditory Information Processing Revealed by Nonstationary Signal Analysis of Eeg
  • Probing Oscillatory Visual Dynamics at the Perceptual Level
  • Nonlinear Approaches to Learning And Memory
  • Single-Trial Analysis of Eeg for Enabling Cognitive User Interfaces
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