Neuromorphic computing aims to replicate the structure and function of neural circuits in electronic hardware, offering an alternative to traditional computer architectures. This approach promises high computational efficiency with reduced power consumption, essential for advancing neurotechnology applications.

Theoretical neuroscience provides the foundation for developing and deploying neurotechnologies by elucidating the organizational principles of the mind and brain. This field bridges empirical neuroscience and technology through computational models that predict and explain brain functions.

Neuromorphic control integrates neuromorphic computing with robotics, creating systems that interact with the real world through sensors and effectors. This field is crucial for developing soft robotics that emulate the compliance and dynamic configuration of biological bodies.

Neuroinformatics develops tools and methods for analyzing and controlling brain-derived artifacts, fostering coherence and synergy between neuroscience and neurotechnology. This field focuses on creating integrated systems and multi-scale brain models to guide technological development.

Neuroprosthetics involves creating devices that interface with the brain to restore or enhance neural functions. This field exemplifies neurotechnology by combining brain state sensing, signal processing, and functional modulation to achieve therapeutic outcomes.

Clinical neurotechnology focuses on integrating intervention and monitoring systems into digital brain health pipelines for patient care. This domain aims to revolutionize healthcare delivery through advanced, patient-specific neurotechnologies.

Neurometaphysics explores the philosophical, ethical, and legal implications of neurotechnology, emphasizing the need for interdisciplinary analyses. This field addresses the broader impact of neurotechnologies on society and human capabilities.