162918 20260108075227.0 doi 10.1038/s41551-025-01445-1 sideral 144705 ART-2025-144705 eng (orcid)0000-0001-8439-151X Ibáñez, Jaime Universidad de Zaragoza Peripheral neural interfaces for reading high-frequency brain signals 2025 Access copy available to the general public Unrestricted Accurate and robust recording and decoding from the central nervous system (CNS) is essential for advances in human–machine interfacing. Technologies for direct measurements of CNS activity are limited by their resolution, sensitivity to interference and invasiveness. Motor neurons (MNs) represent the motor output layer of the CNS, receiving and sampling signals from different regions in the nervous system and generating the neural commands that control muscles. Muscle recordings and deep learning decode the spiking activity of spinal MNs in real time and with high accuracy. The input signals to MNs can be estimated from MN outputs. Here we argue that peripheral neural interfaces using muscle sensors represent a promising, non-invasive approach to estimate some of the neural activity from the CNS that reaches the MNs but does not directly modulate force production. We discuss the evidence supporting this concept and the advances needed to consolidate and test MN-based CNS interfaces in controlled and real-world settings. info:eu-repo/grantAgreement/EC/HORIZON EUROPE/101077693/EU/Extracting the Human Motor Null Space from Muscles - A new framework to measure human neural activity/ECHOES info:eu-repo/grantAgreement/EC/H2020/810346/EU/Natural Integration of Bionic Limbs via Spinal Interfacing/Natural BionicS This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 810346-Natural BionicS info:eu-repo/grantAgreement/EC/H2020/899626/EU/NIMA: Non-invasive Interface for Movement Augmentation/NIMA This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 899626-NIMA info:eu-repo/grantAgreement/ES/MICINN/PID2022-138585OA-C32 info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Zicher, Blanka Burdet, Etienne Baker, Stuart N. Mehring, Carsten Farina, Dario 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. Nature Biomedical Engineering Nature Biomedical Engineering 2157-846X 3434057 http://zaguan.unizar.es/record/162918/files/texto_completo.pdf Postprint info:eu-repo/date/embargoEnd/2025-12-27 1859773 http://zaguan.unizar.es/record/162918/files/texto_completo.jpg?subformat=icon icon Postprint info:eu-repo/date/embargoEnd/2025-12-27 oai:zaguan.unizar.es:162918 articulos driver 2026-01-07-18:55:43 ARTICLE