Abstract
This disclosure introduces an innovative concept for an implantable artificial intelligence (AI) neural interface designed to restore functional connectivity between a transplanted human head (or brain) and the recipient body by bridging the severed spinal cord. The system features a bi-directional neural implant equipped with AI-driven signal decoding, encoding, and adaptive learning capabilities, enabling both motor control and sensory feedback across the disconnection. Core components include neural sensor arrays, a machine-learning processor, stimulation modules, and optional regenerative and drug delivery systems. This approach addresses the longstanding barrier of neural reconnection in full head transplantation and holds promise for applications in spinal cord injury, advanced prosthetics, and neuro-integrated exoskeletons. By combining bioelectronics, neuroscience, and adaptive AI, the proposal lays the foundation for achieving effective brain-body integration in extreme medical scenarios.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Karelias, George, "“Innovative Methodology for Full Human Head Transplantation: A Multidisciplinary Surgical and Neurological Approach”", Technical Disclosure Commons, (May 12, 2025)
https://www.tdcommons.org/dpubs_series/8117