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.
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.
Magnetoencephalography measures the magnetic fields generated by neural currents using quantum sensors such as superconducting quantum interference devices and atomic magnetometers. Here we combine the energy resolution limit of magnetic sensing with the metabolic power available to neural currents to derive a technology-independent bound on the information capacity of MEG. The bound factorizes into geometry, metabolism, and Planck's constant, and gives an estimated maximum information rate of 2.2~Mbit/s for representative human-brain parameters. Further, we show that the externally measurable magnetic field has a finite angular bandwidth, with high multipole components being geometrically attenuated and falling below the quantum-limited noise floor. This yields an information-limited spatial scale of order 1cm and renders the accessible measurement space effectively finite-dimensional. The energy resolution limit therefore defines an information-theoretic Nyquist scale for magnetoencephalography, beyond which denser spatial sampling provides redundant measurements rather than additional recoverable information. Since the energy resolution limit also makes the noise variance grow linearly with measurement bandwidth, temporal and spatial bandwidths compete, producing a fundamental spatio-temporal trade-off. These results show how quantum-limited measurements constrain the observable complexity and information content of noninvasive brain imaging, providing a quantitative link between fundamental physics and neuroscience.
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.
The neurosciences have pioneered the use of quantum technologies for sensing and imaging the brain.Next-generation technologies promise routes towards low-cost, wearable imaging devices with high spatial and temporal resolution.Much of the progress in our understanding of the brain and our ability to assess brain health relies heavily on magnetic resonance imaging (MRI) and quantum technologies that rely on quantum properties of matter or radiation such, e.g., nuclear spin, entanglement or detection of single quanta.These technologies are undergoing a renaissance in funding and research, which has led to some very exciting developments in recent years, for example, reconstructing images, videos [1,2], and the semantics of entire sentences [3] from brain activity and fMRI data alone.The goal of this perspective is to provide a brief overview of some quantum technologies that may have an impact, for example, on the wearability, precision, and cost of these brain reading approaches.Magnetic resonance imaging (MRI) is a noninvasive approach that relies on a quantum effect whereby charged particles can have a spin and thus interact with an external magnetic field that provides information about the conformation of the spins and of the matter that we are probing.One form of MRI known as functional MRI (fMRI)-which measures brain activity by detecting small changes of blood flow in the brain-can now achieve sub-millimetre resolution, albeit typically with a 5 to 10 second time lag that results from the fact that it measures a blood oxygenation level dependent (BOLD) signal.Another noninvasive technology known as magnetoencelphagraphy (MEG) instead measures the magnetic fields generated as a result of the time-varying voltage signals at the cellular level.The quantum technology utilised here lies not in the physics of the signal itself but rather in the detection, which is typically achieved using the extreme sensitivity of superconducting quantum interference devices (SQUIDs).MEG has lower spatial resolution compared to fMRI of order 3 mm but without the BOLD time-lag.It is clear that using fMRI and MEG to image the brain at ever-finer detail is enabling a deeper understanding of how the brain operates.However, fMRI has relatively high costs that severely limit accessibility and the range of experiments is constrained by the fact that lying down in an MRI scanner is not a "natural" environment in which animals or humans operate.MEG based on SQUIDs is moderately more wearable but still expensive, mostly as a result of the experiments needing to be housed in special rooms that shield the instruments from the
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.
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.