Review outlines architectural frameworks for bidirectional neural communication in human-device interfaces, highlighting pathways for integrating human and artificial intelligence.
Key Points
To synthesize the theoretical and methodological frameworks of brain–computer interfaces viewed as closed-loop, bidirectional communication networks.
Surveyed foundational communication theory and architectural design principles for brain–computer interface (BCI) systems.
Categorized key technological subsystems, including brain-to-computer (B2C), computer-to-brain (C2B), and multiuser operational models.
Synthesized technical barriers and design requirements across signal processing, bidirectional feedback loops, and multiuser synchronization.
Identified emerging technical frontiers involving the fusion of human and artificial intelligence, wireless communication networks, and metaverse integration.