Neuronal electrical activity underlies human cognition, yet its direct, noninvasive measurement in the living human brain remains a fundamental challenge. Existing neuroimaging techniques, including EEG, MEG, and 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 free induction decay (FID) 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 validation. We further present a case study demonstrating potential applications to neurological disorders. qsMRI represents a first-in-human application of quantum sensing on a clinical MRI platform, establishes a non-BOLD functional imaging modality, and enables interrogation of neuronal firing dynamics in both cortical and deep brain regions.
Neuronal electrical activity underlies human cognition, yet its direct, noninvasive measurement in the living human brain remains a fundamental challenge. Existing neuroimaging techniques, including EEG, MEG, and 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 free induction decay (FID) 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 validation. We further present a case study demonstrating potential applications to neurological disorders. qsMRI represents a first-in-human application of quantum sensing on a clinical MRI platform, establishes a non-BOLD functional imaging modality, and enables interrogation of neuronal firing dynamics in both cortical and deep brain regions.
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
The development of quantum-enhanced MRI technologies presents a novel frontier for early disease detection and continuous monitoring of human health. The magnetic resonance imaging (MRI) modality has become an essential pillar of modern healthcare systems and is the most widely used imaging technology for human health screening. It provides non-invasive and high-resolution visualisation of both anatomy and dynamics associated with diseases. Nevertheless, there are several diseases for which a MRI alone is not sufficient or highly challenging for early detection. Hence, advanced solutions are required. Quantum-enhanced MRI offers a promising path to overcome the limitations of conventional MRI by providing unprecedented enhancements to sensitivity, contrast, and spatiotemporal resolution compared with the state-of-the-art MRI. These enhancements have the potential to enable the imaging of emerging biomarkers related to several diseases such as Alzheimer’s, Parkinson’s, cardiovascular diseases, metabolic disorders and cancer at the early stage. Also, quantum-enhanced MRI provides non-intrusive monitoring frameworks that allow continuous observation of physiological parameters such as temperature, heart rate, and molecular dynamics while preserving the privacy of individuals. Such frameworks make it possible for a portable/bedside MRI system operating at ambient temperature to remotely monitor human health and wellness anywhere. Quantum-enhanced MRI is, however, still in its infancy and comes with several challenges. It is necessary to conduct a systematic literature review of quantum-enhanced MRI technologies covering its theoretical foundations, technological advances, potential clinical applications, implications for human health monitoring, existing challenges and future directions.
Quantum technology, such as the quantum computers, has attracted significant attention in recent years. In nuclear medicine, powerful and highly sensitive molecular imaging modalities such as PET (Positron Emission Tomography), SPECT (Single Photon Emission CT) and MRI (Magnetic Resonance Imaging) provide accurate morphological and functional information. Exploiting certain aspects of quantum mechanics may bring further improvements in sensitivity, spatial resolution and enable novel capabilities in the field of biomedical imaging and sensing. In this workshop, the possibilities of biomedical applications inspired by quantum technology were discussed. The following exciting topics were covered: quantum entanglement in PET, dynamic nuclear polarization toward more sensitive MRI, quantum sensors based on the229mTh nuclear clock, plans of an advanced high-energy gamma-ray source at CERN, laser-assisted radiation detection, solid-state quantum sensors such as those based on nitrogen vacancy centers in diamond, quantum sensing using cascade multi photons, and a laser-based radioactive isotope analysis.
• Using clinical MRI, researchers observed the first indications of a macroscopic quantum entangled state formed by proton spins of water molecules in the living human brain. • By introducing an entanglement witness technique—originally proposed for quantum gravity research—into neuroscience, the team discovered that entanglement signals of proton spins are surprisingly synchronized with Heartbeat-Evoked Potentials (HEPs). • The study provides strong experimental indications that human consciousness, cognition, and brain computational processes are based on non-classical quantum mechanics, confirming that the entanglement-based signals fade away when the subject falls asleep. [Quantum Biology Society] Whether human brain functions, especially consciousness and cognition, are merely the result of classical electrical and chemical signal exchanges between brain cells, or the result of computations akin to a quantum computer based on quantum mechanical principles, has been one of the hottest debates in modern science. While the dominant argument has been that quantum effects would instantly break down in a macroscopic, hot, and wet environment like the brain, a recent study directly capturing strong indications of macroscopic quantum entanglement in the living human brain is exciting the global scientific community. The paper "Experimental indications of non-classical brain functions," published entirely free of charge in the Journal of Physics Communications, contains these remarkable achievements. A research team led by Christian Matthias Kerskens and David López Pérez from the Trinity College Institute of Neuroscience (TCIN) in Dublin, Ireland, successfully conducted this groundbreaking experiment. ■ Quantum Gravity Research Techniques Open the Door to Neuroscience To detect quantum effects in the macroscopic environment of the brain responsible for cognitive functions, the researchers made an unconventional attempt by applying an entanglement witness protocol—originally proposed for quantum gravity research—to clinical magnetic resonance imaging (MRI) of a living human body. MRI measures the proton spins of bulk water in the brain; the researchers highly saturated the magnetization to minimize classical single quantum coherence (SQC) signals, selectively capturing only the target zero quantum coherence (ZQC) signals. ■ Quantum Entanglement in the Brain Synchronized with the Heartbeat The observation results were astonishing. The network of fluid spins (proton spins of bulk water) inside the brain interacted with each other, showing indications of a specific entangled state, and these entanglement-based signal bursts were surprisingly synchronized with the heartbeat-evoked potentials (HEPs) induced by the subject's heartbeat. These pulsating signals could not be explained by any existing classical MRI contrast techniques. ■ Entanglement Signals Disappear as Consciousness Fades Even more interestingly, these quantum entanglement-related signals appeared strongly only when the subjects were in a state of conscious awareness. When the subjects' consciousness faded, such as when falling asleep, the signals invariably and gradually disappeared. This is a strong experimental indication that macroscopic water proton spins related to brain physiology are mediating entanglement through unknown brain functions, further suggesting that the foundation of human brain computational processes and consciousness could be strictly non-classical. This research leaves open the possibility that the human brain operates effectively like a highly complex quantum computer, and it is expected to bring a groundbreaking paradigm shift in neuroscience, psychology, medicine, and the development of next-generation artificial intelligence in the future.
Advances in neuroimaging and genomics have enabled unprecedented insights into the biological underpinnings of neuropsychiatric disorders; however, integrating heterogeneous, high-dimensional datasets remains a significant analytical challenge. This paper explores quantum neuroinformatics for multi-modal brain imaging, focusing on the integration of functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and genomic data to model complex neuropsychiatric phenotypes. By leveraging hybrid quantum–classical machine learning frameworks, the study examines how quantum-enhanced feature mapping, probabilistic modeling, and high-dimensional optimization can improve the fusion and interpretation of multimodal datasets. The analysis evaluates the potential of quantum algorithms to capture nonlinear interactions across neural, temporal, and genetic domains, while also addressing computational and hardware limitations associated with the Noisy Intermediate-Scale Quantum (NISQ) era. The findings suggest that quantum neuroinformatics may offer a novel pathway for advancing precision psychiatry by enabling more accurate phenotypic classification, biomarker discovery, and personalized treatment strategies.
Advances in neuroimaging and genomics have enabled unprecedented insights into the biological underpinnings of neuropsychiatric disorders; however, integrating heterogeneous, high-dimensional datasets remains a significant analytical challenge. This paper explores quantum neuroinformatics for multi-modal brain imaging, focusing on the integration of functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and genomic data to model complex neuropsychiatric phenotypes. By leveraging hybrid quantum–classical machine learning frameworks, the study examines how quantum-enhanced feature mapping, probabilistic modeling, and high-dimensional optimization can improve the fusion and interpretation of multimodal datasets. The analysis evaluates the potential of quantum algorithms to capture nonlinear interactions across neural, temporal, and genetic domains, while also addressing computational and hardware limitations associated with the Noisy Intermediate-Scale Quantum (NISQ) era. The findings suggest that quantum neuroinformatics may offer a novel pathway for advancing precision psychiatry by enabling more accurate phenotypic classification, biomarker discovery, and personalized treatment strategies.