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arXiv:2511.06401 · Physical Review Research

Metabolic quantum limit to the information capacity of magnetoencephalography

E. Gkoudinakis, S. Li, I. K. Kominis

physics.bio-phphysics.comp-phquant-phSubmitted Nov 9, 2025• Announced Nov 11, 2025• 0 citations• Revised Mar 4, 2026 (v2)
v1 · Nov 9, 2025v2 · Mar 4, 2026v3 · Jun 11, 2026
arXivHTMLPDF

Abstract

Magnetoencephalography, the noninvasive measurement of magnetic fields produced by brain activity, utilizes quantum sensors such as superconducting quantum interference devices and atomic magnetometers. Combining the energy resolution limit of magnetic sensing with the brain's metabolic power, we derive a technology-independent bound on the information capacity of such measurements. Depending only on geometry, neural metabolism, and Planck's constant, this bound yields a maximum information rate of 2.2~Mbit/s for the human brain. We also show that the measurable magnetic field has a finite angular bandwidth. Higher multipole components are geometrically suppressed and fall below the quantum-limited noise floor, limiting the spatial complexity of neural current patterns encoded in the external field. Because the energy resolution limit implies noise variance grows linearly with bandwidth, temporal and spatial bandwidths compete, establishing a fundamental spatio-temporal trade-off. These results unravel the fundamental limits of noninvasive brain imaging, and may inspire the synthesis of neuroscience with modern quantum technology.

Journal reference
Physical Review RESEARCH 8, 023267 (2026)
DOI
10.1103/kqxb-y7p9
Comments
8 pages, 1 figure

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Magnetoencephalography, the noninvasive measurement of magnetic fields produced by brain activity, utilizes quantum sensors such as superconducting quantum interference devices and atomic magnetometers. Combining the energy resolution limit of magnetic sensing with the brain's metabolic power, we derive a technology-independent bound on the information capacity of such measurements. Depending only on geometry, neural metabolism, and Planck's constant, this bound yields a maximum information rate of 2.2~Mbit/s for the human brain. We also show that the measurable magnetic field has a finite angular bandwidth. Higher multipole components are geometrically suppressed and fall below the quantum-limited noise floor, limiting the spatial complexity of neural current patterns encoded in the external field. Because the energy resolution limit implies noise variance grows linearly with bandwidth, temporal and spatial bandwidths compete, establishing a fundamental spatio-temporal trade-off. These results unravel the fundamental limits of noninvasive brain imaging, and may inspire the synthesis of neuroscience with modern quantum technology.
Magnetoencephalography, the noninvasive measurement of magnetic fields produced by brain activity, utilizes quantum sensors like superconducting quantum interference devices or atomic magnetometers. Here we derive a fundamental, technology-independent bound on the information that such measurements can convey. Using the energy resolution limit of magnetic sensing together with the brain's metabolic power, we obtain a universal expression for the maximum information rate, which depends only on geometry, metabolism, and Planck's constant, and the numerical value of which is 2.6 Mbit/s. At the high bandwidth limit we arrive at a bound scaling linearly with the area of the current source boundary. We thus demonstrate a biophysical holographic bound for metabolically powered information conveyed by the magnetic field. For the geometry and metabolic power of the human brain the geometric bound is 6.6 Gbit/s.
Significance Energy resolution per bandwidth E R is a cross-technology figure of merit that quantifies the combined spatial, temporal, and field resolution of a magnetic sensor. Today’s best-developed magnetometer technologies, including superconducting quantum interference devices, spin-exchange relaxation-free Rb vapors, and nitrogen-vacancy centers in diamond, are limited by quantum noise to E R ≳ ℏ . Meanwhile, important sensing applications, e.g., noninvasive discrimination of individual brain events, would be enabled by E R < ℏ . This situation has motivated proposals for sensors operating by new physical principles. Our result, E R = 0.075 ( 16 ) ℏ , far beyond the best possible performance of established sensor technologies, confirms the potential of this class of proposed sensors. The result opens horizons for condensed matter, neuroscience, and tests of fundamental physics.
It was recently demonstrated that a multitude of realizations of several magnetic sensing technologies satisfy the energy resolution limit, which connects a quantity composed by the variance of the magnetic field estimate, the sensor volume and the measurement time, and having units of action, with ℏ. A first-principles derivation of this limit is still elusive. We here present such a derivation based on quantum thermodynamic arguments. We show that the energy resolution limit is a result of quantum thermodynamic work necessarily associated with quantum measurement and Landauer erasure, the work being exchanged with the magnetic field. We apply these considerations to atomic magnetometers, diamond magnetometers, and SQUIDs, spanning an energy resolution from 10^{0}ℏ to 10^{7}ℏ. This connection between quantum thermodynamics and magnetometry can help advance quantum sensing technologies towards even more sensitive devices.
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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.