Novel neural network models and architectures inspired by the human brain advance learning and adaptability in AI systems. Innovations in neurorobotics empower robots to perceive, interact with, and navigate the environment autonomously through bio-inspired algorithms. As a result, brain-computer interfaces (BCI) technology can be applied to the development of advanced prosthetics, exoskeletons, and assistive devices that restore mobility and functionality. BCI-enabled neurofeedback can be utilized for cognitive training, neurorehabilitation, and treating neurological disorders. Advancements in neural interface technologies, including brain implants and neurostimulation techniques, are imperative for seamless integration with AI systems and robots. Neural Network Technologies and Brain-Computer Interfaces: Innovations and Applications explores the latest advancements and innovations in neural network technologies and brain-computer interfaces (BCIs), highlighting their potential to revolutionize various fields, including artificial intelligence, robotics, healthcare, and virtual reality. It discusses the potential of leveraging neural networks for processing and analyzing brain signals to enhance the accuracy and speed of BCI systems. Covering topics such as BCI prediction accuracy, healthcare access barriers, and neurofinance, this book is an excellent resource for engineers, healthcare practitioners, neuroscientists, computer scientists, researchers, academicians, and more.