English

Quantum Sensing MRI for Noninvasive Detection of Neuronal Electrical Activity in Human Brains

Medical Physics 2026-03-17 v2 Quantum Physics

Abstract

Neuronal electrical activity underlies human cognition including perception, attention, memory, language, and decision-making. Yet its direct, noninvasive measurement in the living human brain remains a fundamental challenge. Existing neuroimaging techniques, including electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI), are limited by trade-offs in sensitivity and spatial or temporal resolution. Here we propose quantum sensing MRI (qsMRI), a noninvasive approach that enables direct detection of neuronal firing-induced magnetic fields using a clinical MRI system. qsMRI exploits endogenous proton (1H) nuclear spins in water molecules as intrinsic quantum sensors and decodes time-resolved phase information from the free induction decay signals to infer neuronal magnetic fields. We validate qsMRI through simulations, phantom experiments, and human studies at rest and during motor tasks, and provide open experimental procedures to facilitate independent rigorous validation. We further present a case study demonstrating potential applications to neurological disorders. qsMRI represents, to our knowledge, the first-in-human application of quantum sensing on a clinical MRI platform and may lay the foundation for a non-BOLD functional imaging modality capable of probing neuronal firing dynamics in both cortical and deep brain regions.

Keywords

Cite

@article{arxiv.2601.16423,
  title  = {Quantum Sensing MRI for Noninvasive Detection of Neuronal Electrical Activity in Human Brains},
  author = {Yongxian Qian and Ying-Chia Lin and Seyedehsara Hejazi and Kamri Clarke and Kennedy Watson and Xingye Chen and Nahbila-Malikha Kumbella and Justin Quimbo and Abena Dinizulu and Simon Henin and Yulin Ge and Arjun Masurkar and Anli Liu and Yvonne W. Lui and Fernando E. Boada},
  journal= {arXiv preprint arXiv:2601.16423},
  year   = {2026}
}

Comments

26 pages, 8 figures, 2 tables, and Supplementary Information