Magnetic resonance identification tags for ultra-flexible electrodes.

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Bibliographic Details
Title: Magnetic resonance identification tags for ultra-flexible electrodes.
Authors: Özil E; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland., Gombkoto P; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland., Apostolelli A; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.; Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK., Yasar TB; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland., Vavladeli AD; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.; Brain Research Institute, University of Zurich, Zurich, Switzerland.; University Research Priority Program (URPP), Adaptive Brain Circuits in Development and Learning, University of Zurich, Zurich, Switzerland.; Center for Microscopy and Image Analysis (ZMB), University of Zurich, Zurich, Switzerland., Marks M; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.; Division of Computing and Mathematical Sciences, Caltech, Pasadena, CA, USA.; Division of Engineering and Applied Science, Caltech, Pasadena, CA, USA., Rohr-Fukuma M; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.; Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland.; Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland., von der Behrens W; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland., Yanik MF; Neurotechnology Group, Institute of Neuroinformatics, Department of Information Technology and Electrical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland. yanik@ethz.ch.; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland. yanik@ethz.ch.
Source: Nature communications [Nat Commun] 2026 Apr 28; Vol. 17 (1). Date of Electronic Publication: 2026 Apr 28.
Publication Type: Journal Article
Journal Info: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2041-1723
DOI:10.1038/s41467-026-71887-x