Brain-machine Interface Engineering

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Morgan & Claypool Publishers, 2007 - Medical - 234 pages
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Brain-Machine Interaction provides a unique framework for understanding the motivation and techniques of applying signal processing methodologies to brain-machine interaction (BMI) design and experimentation. Each chapter begins with a historical perspective and motivating example illustrating the need for this approach in BMI design. Included in each chapter is a list of assumptions associated with each methodological choice and the impact on BMI performance. To validate and advance the state-of-the-art of BMI modeling design, model performance is discussed and how the proposed model represents the neural-to-motor mappings. Finally, the feasibility of building BMIs (technical and practical aspects) is developed in the context of digital computational hardware.
 

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Contents

Introduction to Neural Interfaces
1
Foundations of Neuronal Representations
21
InputOutput BMI Models
57
Regularization Techniques for BMI Models
99
Neural Decoding Using Generative BMI Models
141
Adaptive Algorithms for Point Processes
173
BMI Systems
197
Author Biography
233
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