Neural vs Neuromorphic Interfaces: Where Are We Standing?
Daniela Rana, Natalia Babushkina, Martina Gini, A. Cáceres, Hangyu Li, Vanessa Maybeck, Valeria Criscuolo, Dirk Mayer, Marcello Ienca, Simon Musall, Viviana Rincón Montes, Andreas Offenhäusser, Francesca Santoro
Abstract
Neuromorphic interfaces represent a transformative frontier in neural engineering, enabling seamless communication between the nervous system and external devices through biologically inspired computing architectures. These systems offer promising avenues for diagnosing and treating neurological disorders by emulating the brain's computational strategies. Neural devices, including sensors and stimulators, monitor or modulate neural activity, playing a pivotal role in deciphering brain function and neuropathologies. Yet, clinical translation remains limited due to persistent challenges such as foreign body responses, low signal-to-noise ratios, and constraints in real-time data processing. Recent breakthroughs in neuromorphic hardware, neural recording, and stimulation technologies are addressing these challenges, paving the way for more adaptive and efficient brain-machine interfaces and neuroprosthetics. This review highlights the emerging class of neurohybrid interfaces, where neuromorphic systems might be integrated to enhance bidirectional neural communication. It emphasizes novel material strategies engineered for seamless neural interfacing and their incorporation into advanced neuromorphic chip architectures capable of real-time signal processing and closed-loop feedback. Furthermore, this review explores cutting-edge neuromorphic biointerfaces and evaluates the technological, biological, and ethical challenges involved in their clinical deployment. By bridging materials science, neuroscience, and neuromorphic engineering, these systems hold the potential to redefine the landscape of neurotechnology.