Brain Technology in Augmented Cognition: Current and Future Trends informs engineers interested in human-computer interaction about the current state of augmented cognition. Its scope includes recent advances in electroencephalography (EEG), neural network, and brain-computer interface (BCI) brain technologies.
The title explores in detail each technological approach to augmented cognition and offers conclusions to them, summarizing the work and their respective futures. Augmented cognition research often includes the use of brain technology, and this book addresses advances in augmented cognition and its applications. It details recent uses of EEG, neural networks, and BCI in the field and how they may augment user, researcher, and practitioner cognition. Focusing on the use of EEG for eye-tracking, neural network logic, and the BCI application of motor-imagery (MI) and discussing challenges and opportunities relevant to such applications, the title is a useful introduction to the subject matter.
This is an engaging read for any student, researcher or academic in the fields of engineering, augmented cognition, human-computer interaction and human factors/ergonomics who will learn the basics and key concepts of augmented cognition through this simple and straightforward title.
Brain Technology in Augmented Cognition: Current and Future Trends informs engineers interested in human-computer interaction about the current state of augmented cognition. Its scope includes recent advances in electroencephalography (EEG), neural network, and brain-computer interface (BCI) brain technologies.
Preface
About the Author
Acknowledgments
Introduction
Chapter 1: How Can Brain Technology Augment Cognition?
1.1 Introduction
1.2 Brain Technologies and the Mind
1.3 Three Case Examples
Chapter 2: Electroencephalography (EEG)
2.1 From Neural Activity to Augmented Cognition
2.2 Measuring Individual Cognitive Differences
2.3 EEG in General
Chapter 3: Neural Network (NN)
3.1 Brain Simulation to Augment Cognition
3.2 Artificial versus Biological Neural Networks (ANNs vs. BNNs)
3.3 EEG and Deep Convolutional NNs (DCNNs)
3.4 Related Topics
Chapter 4: Brain-Computer Interface (BCI)
4.1 A Whole-body Approach to Augmented Cognition
4.2 Augmented Embodied Cognition
4.3 From Brain to Body and Mind
4.4 Medical Hope (and Promise)
Chapter 5: Exploring a Combinatory Approach
5.1 Synthesis (Theory and Technology)
5.2 Computational Neurosciences Augmented Mind-brain
5.3 Augmented Brain, Mind, and Body
Conclusion
References
Index
Suraj Sood is an augmented cognition researcher with a decade of experience in human-computer interaction. He completed his Bachelor of Arts at the University of California, Santa Barbara, majoring in Psychology and Philosophy, and his Doctorate of Philosophy at the University of West Georgia in Psychology: Consciousness & Society. He has served as a session chair for Human-Computer Interaction International Conferences Augmented Cognition in 2019, 2021, and 2022. He has been on Augmented Cognitions Program Board since 2019. His research in HCI focuses on theory-building and simulation, drawing from psychology, philosophy, and computer science.
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