Neural Interfaces

AVINASH SINGH, Senior Lecturer, School of Computer Science and Australian AI Institute, Faculty of Engineering and Information Technology, University of Technology Sydney.

• About the Author xviiPreface xixAcknowledgments xxiAcronyms xxiiiAbout the Companion Website xxixIntroduction xxxiBrain, Wires, and Waves xxxv1 Origins, Evolution, and Inspiration 11.1 Conceptual Foundations Before BCI 11.2 Scientific Milestones of the 20th Century 31.3 Key Historical Milestones in Acquisition and Methods 81.4 Summary 142 Cognitive Neuroscience Foundations 172.1 Brain Organization and Anatomy 182.2 The Brain in BCI: Structures and Signal Sources 212.3 Cognitive Functions in BCI 302.4 Neural Correlates: The "HOW" of Cognitive Decoding 342.5 Summary 353 Acquisition and Stimulation Technology 373.1 Invasive and Noninvasive Acquisition Technologies in BCI 373.2 Summary 534 Translational Brain–Computer Interfaces: Bridging Research to Practice 554.1 Clinical and Neuroscientific Foundations of Translational BCI 554.2 Real-world Deployment of BCI Systems 574.3 Bridging Theory and Application in Translational BCI 59x Contents4.4 Summary 685 Automated Signal Processing for Neural Interfaces 715.1 From Traditional to Automated Signal Processing 715.2 Preprocessing and Artifact Handling 725.3 Feature Extraction for Neural Interfaces 785.4 Multimodal Signal Processing Considerations 885.5 Software Ecosystem for Signal Processing in Brain–Computer Interface (BCIs) 895.6 Relevance to Real-world BCI Applications 935.7 Summary 946 Machine Learning and Generative AI for Neural Decoding 956.1 ML Methods for Neural Data Analysis 956.2 Applications of Generative AI in Neural Interfaces 1116.3 From Decoding to Intelligent Interaction 1166.4 Summary 1177 Innovative Environment and Tools 1197.1 Gamified Environment 1207.2 AR, VR, and MR Environment 1267.3 Take-home Experiments 1287.4 Summary 1348 Applications of Brain–Computer Interfaces 1358.1 Medical 1358.2 Entertainment 1408.3 Workplace 1448.4 Neural Interface Applications Beyond BCIs 1468.5 Summary 1489 Enhancing Human Capabilities with Neural Interfaces 1519.1 Speech and Mental Imagery in BCI 1519.2 Neuroadaptive BCI 1569.3 Natural BCI 1589.4 Multimodality and Multitasking in BCI 1619.5 Summary 16210 Neuroethics 16310.1 Responsible Technology Development 16310.2 Public and Social Perception of BCI Technology 16610.3 Identity, Agency, and Personhood 16710.4 Mental Privacy and Cognitive Liberty 16810.5 Neural Data Governance 16810.6 Commercialization and Corporate Power 16910.7 Neuroethical Guidelines 17010.8 Practical Implementation 17210.9 Examples 17210.10 Summary 17511 Challenges of Current Neural Interface Technology 17711.1 Data Acquisition and Stimulation Challenge 17711.2 Technological Challenge 18011.3 Ethical Challenge 18211.4 Design Challenge 18311.5 Standardization and Interoperability Challenge 18411.6 Reliability, Robustness, and Real-world Deployment Challenge 18511.7 Usability and Human Factors Challenge 18611.8 Calibration and Training Challenge 18611.9 Long-term Safety and Physiological Impact Challenge 18611.10 Psychological and Cognitive Load Challenge 187Contents xv11.11 Social Acceptance and Trust Challenge 18711.12 Summary 18812 Envisioning the Future of Brain–Computer Interfaces 18912.1 The Near Future: Practical Expectations for BCIs 19012.2 Foundational Milestones in BCI Technology 19212.3 Innovations Needed and Looking Ahead 19512.4 Beyond the Horizon: The Next 50 Years of BCI 19712.5 Summary 202References 203Index 217