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Statistical Signal Processing for Neuroscience and Neurotechnology

Statistical Signal Processing for Neuroscience and Neurotechnology

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Contents

Table of Contents

Statistical Signal Processing for Neuroscience and Neurotechnology

Table of contents

About the Editor

About the Contributors

Chapter 1. Introduction

Chapter 2. Detection and Classification of Extracellular Action Potential Recordings

Chapter 3. Information-Theoretic Analysis of Neural Data

Chapter 4. Identification of Nonlinear Dynamics in Neural Population Activity

Chapter 5. Graphical Models of Functional and Effective Neuronal Connectivity

Chapter 6. State Space Modeling of Neural Spike Train and Behavioral Data

Chapter 7. Neural Decoding for Motor and Communication Prostheses

Chapter 8. Inner Products for Representation and Learning in the Spike Train Domain

Chapter 9. Signal Processing and Machine Learning for Single-Trial Analysis of Simultaneously Acquired EEG and fMRI

Chapter 10. Statistical Pattern Recognition and Machine Learning in BrainComputer Interfaces

Chapter 11. Prediction of Muscle Activity from Cortical Signals to Restore Hand Grasp in Subjects with Spinal Cord Injury

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Statistical Signal Processing for Neuroscience and Neurotechnology Edited by Karim G. Oweiss