Qsmri Achieves Noninvasive Detection of Neuronal Activity in Human Brains

Researchers are tackling the long-standing challenge of directly measuring neuronal electrical activity non-invasively in the human brain. Yongxian Qian, Ying-Chia Lin, and Seyedehsara Hejazi, alongside colleagues from the Bernard and Irene Schwartz Center for Biomedical Imaging at New York University Grossman School of Medicine, have pioneered a novel technique called quantum sensing MRI (qsMRI) , a method utilising standard MRI systems to detect the magnetic fields produced by firing neurons. This breakthrough circumvents the limitations of current neuroimaging tools like EEG, MEG, and fMRI, offering the potential for higher sensitivity and resolution in both space and time , crucially, without requiring invasive procedures. By harnessing the intrinsic magnetic properties of water molecules, qsMRI decodes neuronal activity from free induction decay signals, opening doors to a deeper understanding of brain function in both healthy individuals and those with neurological disorders.

This breakthrough exploits endogenous proton nuclear spins in water molecules as intrinsic quantum sensors, decoding time-resolved phase information from free induction decay (FID) signals to accurately infer neuronal magnetic fields, a feat previously unattainable. The team validated qsMRI through rigorous simulations, phantom experiments, and crucially, human studies both at rest and during active motor tasks, providing open experimental procedures to encourage independent verification of their findings.

The study establishes a completely novel functional imaging modality, moving beyond the blood oxygen level-dependent (BOLD) signals traditionally measured by fMRI and enabling direct interrogation of neuronal firing dynamics in both cortical and deep brain regions. qsMRI addresses the fundamental challenges of measuring neuronal activity, namely the extremely weak magnetic fields (~0.2 pT) and transient nature of action potentials (~2ms) and postsynaptic potentials (~10, 100ms), all while remaining entirely noninvasive and safe for human subjects. By leveraging the sensitivity of quantum sensors, the research overcomes the limitations of scalp EEG and MEG, which struggle with source localisation accuracy due to the distance from neuronal sources (~20mm), and the indirect measurement of neuronal activity inherent in conventional fMRI. Experiments show that qsMRI successfully decodes neuronal firing-induced magnetic fields, offering a temporal resolution sufficient to capture the rapid dynamics of neuronal communication, a significant improvement over fMRI’s ~40, 100ms resolution. The team’s approach not only provides a more direct measure of neuronal activity but also opens avenues for investigating cognitive processes and identifying disruptions caused by neurological disorders such as Alzheimer’s disease and epilepsy.
A compelling case study presented within the work highlights the potential of qsMRI for diagnosing and monitoring these conditions, suggesting a future where early detection and targeted therapies become more readily available. This first-in-human application of quantum sensing on a clinical MRI platform represents a substantial leap forward in neuroimaging technology. The research establishes a non-BOLD functional imaging modality, offering a unique perspective on brain activity and paving the way for a deeper understanding of the neural basis of cognition and its decline. Furthermore, the open availability of experimental procedures ensures that this innovative technique can be widely adopted and further refined by the scientific community, accelerating progress in neuroscience and clinical neurology, potentially revolutionising our ability to diagnose and treat brain disorders.

Decoding Neuronal Fields via qsMRI and FID signals

Scientists pioneered a novel neuroimaging technique, qsMRI, to directly detect neuronal firing-induced magnetic fields noninvasively within the living human brain. This breakthrough circumvents the limitations of existing methods like EEG, MEG, and fMRI, which struggle with trade-offs between sensitivity, spatial, and temporal resolution. The research team engineered qsMRI to exploit endogenous proton (¹H) nuclear spins in water molecules as intrinsic sensors, effectively transforming them into microscopic magnetometers within the brain. Experiments employed a clinical MRI system to decode time-resolved phase information from free induction decay (FID) signals, allowing inference of neuronal magnetic fields with unprecedented precision.

Researchers validated qsMRI through a multi-stage process beginning with detailed simulations to model expected signal characteristics, followed by phantom experiments utilising specifically designed test objects to confirm signal detection and calibration. Human studies were then conducted both at rest and during controlled motor tasks, providing crucial in vivo data for validation and refinement of the technique. The study harnessed a 3 Tesla MRI scanner and meticulously optimised pulse sequences to maximise signal-to-noise ratio and temporal resolution. Specifically, the team implemented a gradient-echo sequence with a minimum echo time of 0.5ms to capture the rapid dynamics of neuronal firing, achieving a temporal resolution capable of resolving action potentials lasting approximately 2ms and postsynaptic potentials ranging from 10, 100ms.

This innovative approach enables the interrogation of neuronal firing dynamics in both cortical and deep brain regions, previously inaccessible to non-invasive techniques. Furthermore, the team developed open experimental procedures and made data and codes available upon request, facilitating independent validation and wider adoption of qsMRI by the scientific community. A compelling case study demonstrated the potential of qsMRI for applications in neurological disorders, suggesting a pathway towards improved diagnosis and treatment strategies for conditions like Alzheimer’s disease and mild cognitive impairment. This method achieves a first-in-human application on a clinical MRI platform, establishing a non-BOLD functional imaging modality and opening new avenues for understanding the neural basis of cognition.

Neuronal firing detected via qsMRI magnetometry offers new

Scientists have achieved a breakthrough in non-invasive brain imaging with a new technique called qsMRI, directly detecting neuronal firing-induced magnetic fields using a clinical MRI system. The research team successfully measured magnetic fields generated by neuronal activity, overcoming limitations inherent in existing neuroimaging methods like EEG, MEG, and fMRI, which struggle with balancing sensitivity and resolution. Experiments revealed that qsMRI exploits the endogenous proton nuclear spins in water molecules as intrinsic sensors, decoding time-resolved phase information from free induction decay (FID) signals to infer these neuronal magnetic fields. The team estimated the magnetic field inside a firing axon, with a typical diameter of 0.1, 1.0μm, to be between 18, 182 μT during an action potential.

These estimations, derived from a single axon model, are sufficient to induce measurable phase shifts in FID signals, corresponding to 8.78°, 88.78° for proton nuclear spins at a temporal sampling interval of 0.2ms. Further simulations and phantom experiments validated the approach, demonstrating the feasibility of detecting these incredibly weak signals, as low as 0.2 nT, directly from living brain tissue. Measurements confirm that qsMRI can achieve high accuracy and precision in neuronal firing measurements under realistic noise conditions, with relative measurement errors of less than 0.07% for action potentials and less than 0.09% for postsynaptic potentials. Accuracy was quantified by comparing peak amplitudes of estimated fields with ground-truth values in simulated inputs, yielding a coefficient of variation of δ This level of precision represents a significant advancement, as conventional MRI studies have struggled to detect such weak magnetic fields, often reporting inconsistent results or focusing on extracellular space where signals rapidly decay.

The study also demonstrated a novel active localization strategy, exploiting the spatially localized sensitivity of individual coil elements to pinpoint neuronal firing sources with greater accuracy than traditional methods like scalp EEG and MEG. Tests prove qsMRI’s ability to interrogate neuronal firing dynamics in both cortical and deep brain regions, opening possibilities for applications in neurological disorders and a deeper understanding of human cognition. The breakthrough delivers a first-in-human application of this technology on a clinical MRI platform, establishing a non-BOLD functional imaging modality and paving the way for future investigations into the complexities of brain activity.

Direct neuronal activity via magnetic resonance

Scientists have developed a novel neuroimaging technique called qsMRI, which directly detects neuronal firing-induced magnetic fields using a standard clinical MRI system. This noninvasive approach utilizes the inherent magnetic properties of water molecules within the brain as sensors, decoding phase information from free induction decay signals to infer neuronal activity. Through simulations, phantom experiments, and initial human studies, both at rest and during motor tasks, researchers validated the feasibility of qsMRI and have made experimental procedures openly available for independent verification. The significance of this work lies in establishing a functional imaging modality independent of the blood-oxygen-level dependent (BOLD) signal traditionally used in fMRI. qsMRI allows for the interrogation of neuronal firing dynamics in both superficial cortical areas and deeper brain regions, potentially offering higher temporal resolution than existing methods. The authors acknowledge that further improvements in spatial resolution may be possible through refinements in coil design or radiofrequency excitation strategies. Future research will focus on community-based validation and exploring applications in understanding cognitive brain circuits, as well as clinical applications for neurological and psychiatric disorders such as epilepsy, brain tumours, depression, and bipolar disorder.