Moving magnetoencephalography towards real-world applications with a wearable system

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

Epilepsy can be defined as a dysfunction of the brain network, and each type of epilepsy involves different brain-network changes that are implicated differently in the control and propagation of interictal or ictal discharges. Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice. An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tractography, diffusion kurtosis imaging-based fiber tractography, fiber ball imaging-based tractography, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, molecular imaging, and functional ultrasound imaging have been extensively used to delineate epileptic networks. In this review, we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy, and extensively analyze the imaging mechanisms, advantages, limitations, and clinical application ranges of each technique. A greater focus on emerging advanced technologies, new data analysis software, a combination of multiple techniques, and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

A novel method for highly linear gradient coil design based on stream function

BACKGROUND

Magnetoencephalography (MEG) and magnetic resonance imaging (MRI) are non-invasive imaging techniques that offer effective means for disease diagnosis. A more straightforward and optimized method is presented for designing gradient coils which are pivotal parts of the above imaging systems.

PURPOSE

A novel design method based on stream function combining an optimization algorithm is proposed to obtain highly linear gradient coil.

METHODS

Two-dimensional Fourier expansion of the current field on the surface where the coil is located and the equipotential line of the expansion term superposition according to the number of turns of the coil are used to represent the coil shape. Particle swarm optimization is utilized to optimize the coil shape while linearity and field uniformity are used as parameters to evaluate the coil performance. Through this method, the main parameters such as input current distribution region, coil turns, desired magnetic field strength, expansion order and iteration times can be combined in a given solution space to optimize coil design.

RESULTS

Simulation results show that the maximum linearity spatial deviation of the designed bi-planar x-gradient coil compared with that of target field method is reduced from 14% to 0.54%, and that of the bi-planar z-gradient coil is reduced from 8.98% to 0.52%. Similarly, that of the cylindrical x-gradient coil is reduced from 2% to 0.1%, and that of the cylindrical z-gradient coil is reduced from 0.87% to 0.45%. The similar results are found in the index of inhomogeneity error. Moreover, it has also been verified experimentally that the result of measured magnetic field is consist with simulated result.

CONCLUSIONS

The proposed method provides a straightforward way that simplifies the design process and improves the linearity of designed gradient coil, which could be beneficial to realize better magnetic field in engineering applications.

Healable and Conductive Two-Dimensional Sulfur Iodide for High-Rate Sodium Batteries

Self-healing functional materials can repair cracks and damage inside the battery, ensuring the stability of the battery material structure. This feature minimizes performance degradation during the charging and discharging processes, improving the efficiency and stability of the battery. Here, we have developed a novel healing conductive two-dimensional sulfur iodide (SI4) composite cathode. This process integrates both sulfur and iodine compounds into carbon nanocages, forming a SI4@C core-shell structure. This cathode design improves electrical conductivity and repairability, facilitates rapid activation, and ensures structural integrity, resulting in a typical Na-SI4 battery with high capacity and an exceptionally long cycle life. At 10.0 A g-1, the capacity of the Na-SI4 battery can still reach 217.4 mAh g-1 after more than 500 cycles, and the capacity decay rate per cycle is only 0.06%. In addition, the cathode exhibits a cascade redox reaction involving S and I, contributing to its high capacity. The in situ growth of a carbon shell further enhances the conductivity and structural robustness of the entire cathode. The flexibility and bendability of SI4@C-carbon cloth make it applicable for flexible electronic devices, providing more possibilities for battery design. The strategy of engineering a two-dimensional self-healing structure to construct a superior cathode is expected to be widely applied to other electrode materials. This study provides a new pathway for designing novel binary-conversion-type sodium-ion batteries with excellent long-term cycling performance.

Source localization comparison and combination of OPM-MEG and fMRI to detect sensorimotor cortex responses

BACKGROUND AND OBJECTIVES

The exploration of various neuroimaging techniques have become focal points within the field of neuroscience research. Magnetoencephalography based on optically pumped magnetometers (OPM-MEG) has shown significant potential to be the next generation of functional neuroimaging with the advantages of high signal intensity and flexible sensor arrangement. In this study, we constructed a 31-channel OPM-MEG system and performed a preliminary comparison of the temporal and spatial relationship between magnetic responses measured by OPM-MEG and blood-oxygen-level-dependent signals detected by functional magnetic resonance imaging (fMRI) during a grasping task.

METHODS

For OPM-MEG, the β-band (15-30 Hz) oscillatory activities can be reliably detected across multiple subjects and multiple session runs. To effectively localize the inhibitory oscillatory activities, a source power-spectrum ratio-based imaging method was proposed. This approach was compared with conventional source imaging methods, such as minimum norm-type and beamformer methods, and was applied in OPM-MEG source analysis. Subsequently, the spatial and temporal responses at the source-level between OPM-MEG and fMRI were analyzed.

RESULTS

The effectiveness of the proposed method was confirmed through simulations compared to benchmark methods. Our demonstration revealed an average spatial separation of 10.57 ± 4.41 mm between the localization results of OPM-MEG and fMRI across four subjects. Furthermore, the fMRI-constrained OPM-MEG localization results indicated a more focused imaging extent.

CONCLUSIONS

Taken together, the performance exhibited by OPM-MEG positions it as a potential instrument for functional surgery assessment.

Real-time motion-enabling positron emission tomography of the brain of upright ambulatory humans

BACKGROUND

Mobile upright PET devices have the potential to enable previously impossible neuroimaging studies. Currently available options are imagers with deep brain coverage that severely limit head/body movements or imagers with upright/motion enabling properties that are limited to only covering the brain surface.

METHODS

In this study, we test the feasibility of an upright, motion-compatible brain imager, our Ambulatory Motion-enabling Positron Emission Tomography (AMPET) helmet prototype, for use as a neuroscience tool by replicating a variant of a published PET/fMRI study of the neurocorrelates of human walking. We validate our AMPET prototype by conducting a walking movement paradigm to determine motion tolerance and assess for appropriate task related activity in motor-related brain regions. Human participants (n = 11 patients) performed a walking-in-place task with simultaneous AMPET imaging, receiving a bolus delivery of F18-Fluorodeoxyglucose.

RESULTS

Here we validate three pre-determined measure criteria, including brain alignment motion artifact of less than <2 mm and functional neuroimaging outcomes consistent with existing walking movement literature.

CONCLUSIONS

The study extends the potential and utility for use of mobile, upright, and motion-tolerant neuroimaging devices in real-world, ecologically-valid paradigms. Our approach accounts for the real-world logistics of an actual human participant study and can be used to inform experimental physicists, engineers and imaging instrumentation developers undertaking similar future studies. The technical advances described herein help set new priorities for facilitating future neuroimaging devices and research of the human brain in health and disease.

Tracking the neurodevelopmental trajectory of beta band oscillations with optically pumped magnetometer-based magnetoencephalography

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - optically pumped magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

Metasurface-based optical system for miniaturization of atomic magnetometers

Recent research has focused on miniaturizing atomic devices like magnetometers and gyroscopes for quantum precision measurements, leading to energy savings and broader application. This paper presents the design and validation of metasurface-based optical elements for atomic magnetometers' optical paths. These include highly efficient half-wave plates, polarizers, circular polarization generators, polarization-preserving reflectors, and polarizing beam splitters. These components, compatible with semiconductor manufacturing, offer a promising solution for creating ultra-thin, compact atomic devices.

Concurrent spinal and brain imaging with optically pumped magnetometers

BACKGROUND

The spinal cord and its interactions with the brain are fundamental for movement control and somatosensation. However, brain and spinal electrophysiology in humans have largely been treated as distinct enterprises, in part due to the relative inaccessibility of the spinal cord. Consequently, there is a dearth of knowledge on human spinal electrophysiology, including the multiple pathologies that affect the spinal cord as well as the brain.

NEW METHOD

Here we exploit recent advances in the development of wearable optically pumped magnetometers (OPMs) which can be flexibly arranged to provide coverage of both the spinal cord and the brain in relatively unconstrained environments. This system for magnetospinoencephalography (MSEG) measures both spinal and cortical signals simultaneously by employing custom-made scanning casts.

RESULTS

We evidence the utility of such a system by recording spinal and cortical evoked responses to median nerve stimulation at the wrist. MSEG revealed early (10 - 15 ms) and late (>20 ms) responses at the spinal cord, in addition to typical cortical evoked responses (i.e., N20).

COMPARISON WITH EXISTING METHODS

Early spinal evoked responses detected were in line with conventional somatosensory evoked potential recordings.

CONCLUSION

This MSEG system demonstrates the novel ability for concurrent non-invasive millisecond imaging of brain and spinal cord.

A user-friendly visual brain-computer interface based on high-frequency steady-state visual evoked fields recorded by OPM-MEG

Objective. Magnetoencephalography (MEG) shares a comparable time resolution with electroencephalography. However, MEG excels in spatial resolution, enabling it to capture even the subtlest and weakest brain signals for brain-computer interfaces (BCIs). Leveraging MEG's capabilities, specifically with optically pumped magnetometers (OPM-MEG), proves to be a promising avenue for advancing MEG-BCIs, owing to its exceptional sensitivity and portability. This study harnesses the power of high-frequency steady-state visual evoked fields (SSVEFs) to build an MEG-BCI system that is flickering-imperceptible, user-friendly, and highly accurate.Approach.We have constructed a nine-command BCI that operates on high-frequency SSVEF (58-62 Hz with a 0.5 Hz interval) stimulation. We achieved this by placing the light source inside and outside the magnetic shielding room, ensuring compliance with non-magnetic and visual stimulus presentation requirements. Five participants took part in offline experiments, during which we collected six-channel multi-dimensional MEG signals along both the vertical (Z-axis) and tangential (Y-axis) components. Our approach leveraged the ensemble task-related component analysis algorithm for SSVEF identification and system performance evaluation.Main Results.The offline average accuracy of our proposed system reached an impressive 92.98% when considering multi-dimensional conjoint analysis using data from both theZandYaxes. Our method achieved a theoretical average information transfer rate (ITR) of 58.36 bits min-1with a data length of 0.7 s, and the highest individual ITR reached an impressive 63.75 bits min-1.Significance.This study marks the first exploration of high-frequency SSVEF-BCI based on OPM-MEG. These results underscore the potential and feasibility of MEG in detecting subtle brain signals, offering both theoretical insights and practical value in advancing the development and application of MEG in BCI systems.

Noise Reduction and Localization Accuracy in a Mobile Magnetoencephalography System

Magnetoencephalography (MEG) non-invasively provides important information about human brain electrophysiology. The growing use of optically pumped magnetometers (OPM) for MEG, as opposed to fixed arrays of cryogenic sensors, has opened the door for innovation in system design and use cases. For example, cryogenic MEG systems are housed in large, shielded rooms to provide sufficient space for the system dewar. Here, we investigate the performance of OPM recordings inside of a cylindrical shield with a 1 × 2 m2 footprint. The efficacy of shielding was measured in terms of field attenuation and isotropy, and the value of post hoc noise reduction algorithms was also investigated. Localization accuracy was quantified for 104 OPM sensors mounted on a fixed helmet array based on simulations and recordings from a bespoke current dipole phantom. Passive shielding attenuated the vector field magnitude to 50.0 nT at direct current (DC), to 16.7 pT/√Hz at power line, and to 71 fT/√Hz (median) in the 10-200 Hz range. Post hoc noise reduction provided an additional 5-15 dB attenuation. Substantial field isotropy remained in the volume encompassing the sensor array. The consistency of the isotropy over months suggests that a field nulling solution could be readily applied. A current dipole phantom generating source activity at an appropriate magnitude for the human brain generated field fluctuations on the order of 0.5-1 pT. Phantom signals were localized with 3 mm localization accuracy, and no significant bias in localization was observed, which is in line with performance for cryogenic and OPM MEG systems. This validation of the performance of a small footprint MEG system opens the door for lower-cost MEG installations in terms of raw materials and facility space, as well as mobile imaging systems (e.g., truck-based). Such implementations are relevant for global adoption of MEG outside of highly resourced research and clinical institutions.

Four-channel optically pumped magnetometer for a magnetoencephalography sensor array

We present a novel four-channel optically pumped magnetometer (OPM) for magnetoencephalography that utilizes a two-color pump/probe scheme on a single optical axis. We characterize its performance across 18 built sensor modules. The new sensor implements several improvements over our previously developed sensor including lower vapor-cell operating temperature, improved probe-light detection optics, and reduced optical power requirements. The sensor also has new electromagnetic field coils on the sensor head which are designed using stream-function-based current optimization. We detail the coil design methodology and present experimental characterization of the coil performance. The magnetic sensitivity of the sensor is on average 12.3 fT/rt-Hz across the 18 modules while the average gradiometrically inferred sensitivity is about 6.0 fT/rt-Hz. The sensor 3-dB bandwidth is 100 Hz on average. The on-sensor coil performance is in good agreement with the simulations.

Infant neuroscience: how to measure brain activity in the youngest minds

The functional properties of the infant brain are poorly understood. Recent advances in cognitive neuroscience are opening new avenues for measuring brain activity in human infants. These include novel uses of existing technologies such as electroencephalography (EEG) and magnetoencephalography (MEG), the availability of newer technologies including functional near-infrared spectroscopy (fNIRS) and optically pumped magnetometry (OPM), and innovative applications of functional magnetic resonance imaging (fMRI) in awake infants during cognitive tasks. In this review article we catalog these available non-invasive methods, discuss the challenges and opportunities encountered when applying them to human infants, and highlight the potential they may ultimately hold for advancing our understanding of the youngest minds.

Automatic Estimation of the Interference Subspace Dimension Threshold in the Subspace Projection Algorithms of Magnetoencephalography Based on Evoked State Data

A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference (external) subspace matrix of these algorithms is the key to balancing the denoising effect and the degree of signal distortion. However, most current methods for estimating the dimension threshold rely on experience, such as observing the signal waveforms and spectrum, which may render the results too subjective and lacking in quantitative accuracy. Therefore, this study proposes a method to automatically estimate a suitable threshold. Time-frequency transformations are performed on the evoked state data to obtain the neural signal of interest and the noise signal in a specific time-frequency band, which are then used to construct the objective function describing the degree of noise suppression and signal distortion. The optimal value of the threshold in the selected range is obtained using the weighted-sum method. Our method was tested on two classical subspace projection algorithms using simulation and two sensory stimulation experiments. The thresholds estimated by the proposed method enabled the algorithms to achieve the best waveform recovery and source location error. Therefore, the threshold selected in this method enables subspace projection algorithms to achieve the best balance between noise removal and neural signal preservation in subsequent MEG analyses.

From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications

Magnetoencephalography (MEG) is a non-invasive technique that can precisely capture the dynamic spatiotemporal patterns of the brain by measuring the magnetic fields arising from neuronal activity along the order of milliseconds. Observations of brain dynamics have been used in cognitive neuroscience, the diagnosis of neurological diseases, and the brain-computer interface (BCI). In this study, we outline the basic principle, signal processing, and source localization of MEG, and describe its clinical applications for cognitive assessment, the diagnoses of neurological diseases and mental disorders, preoperative evaluation, and the BCI. This review not only provides an overall perspective of MEG, ranging from practical techniques to clinical applications, but also enhances the prevalent understanding of neural mechanisms. The use of MEG is expected to lead to significant breakthroughs in neuroscience.

Long-baseline quantum sensor network as dark matter haloscope

Ultralight dark photons constitute a well-motivated candidate for dark matter. A coherent electromagnetic wave is expected to be induced by dark photons when coupled with Standard-Model photons through kinetic mixing mechanism, and should be spatially correlated within the de Broglie wavelength of dark photons. Here we report the first search for correlated dark-photon signals using a long-baseline network of 15 atomic magnetometers, which are situated in two separated meter-scale shield rooms with a distance of about 1700 km. Both the network's multiple sensors and the shields large size significantly enhance the expected dark-photon electromagnetic signals, and long-baseline measurements confidently reduce many local noise sources. Using this network, we constrain the kinetic mixing coefficient of dark photon dark matter over the mass range 4.1 feV-2.1 peV, which represents the most stringent constraints derived from any terrestrial experiments operating over the aforementioned mass range. Our prospect indicates that future data releases may go beyond the astrophysical constraints from the cosmic microwave background and the plasma heating.

Sub-Doppler spectroscopy of the Cs atom 6S1/2-7P1/2 transition at 459 nm in a microfabricated vapor cell

We report on the characterization of sub-Doppler resonances detected by probing the 6S1/2 - 7P1/2 transition of the Cs atom at 459 nm in a microfabricated vapor cell. The dependence of the sub-Doppler resonance (linewidth, amplitude) on some key experimental parameters, including the laser intensity and the cell temperature, is investigated. These narrow atomic resonances are of interest for high-resolution spectroscopy and instrumentation and may constitute the basis of a high-stability microcell optical standard.

A Multivariate analysis on evoked components of Chinese semantic congruity: an OP-MEG study with EEG

The application of wearable magnetoencephalography using optically-pumped magnetometers has drawn extensive attention in the field of neuroscience. Electroencephalogram system can cover the whole head and reflect the overall activity of a large number of neurons. The efficacy of optically-pumped magnetometer in detecting event-related components can be validated through electroencephalogram results. Multivariate pattern analysis is capable of tracking the evolution of neurocognitive processes over time. In this paper, we adopted a classical Chinese semantic congruity paradigm and separately collected electroencephalogram and optically-pumped magnetometer signals. Then, we verified the consistency of optically-pumped magnetometer and electroencephalogram in detecting N400 using mutual information index. Multivariate pattern analysis revealed the difference in decoding performance of these two modalities, which can be further validated by dynamic/stable coding analysis on the temporal generalization matrix. The results from searchlight analysis provided a neural basis for this dissimilarity at the magnetoencephalography source level and the electroencephalogram sensor level. This study opens a new avenue for investigating the brain's coding patterns using wearable magnetoencephalography and reveals the differences in sensitivity between the two modalities in reflecting neuron representation patterns.

The neurodevelopmental trajectory of beta band oscillations: an OPM-MEG study

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - Optically Pumped Magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

Using optically pumped magnetometers to replicate task-related responses in next generation magnetoencephalography

Optically pumped magnetometers (OPMs) offer a new wearable means to measure magnetoencephalography (MEG) signals, with many advantages compared to conventional systems. However, OPMs are an emerging technology, thus characterizing and replicating MEG recordings is essential. Using OPM-MEG and SQUID-MEG, this study investigated evoked responses, oscillatory power, and functional connectivity during emotion processing in 20 adults, to establish replicability across the two technologies. Five participants with dental fixtures were included to assess the validity of OPM-MEG recordings in those with irremovable metal. Replicable task-related evoked responses were observed in both modalities. Similar patterns of oscillatory power to faces were observed in both systems. Increased connectivity was found in SQUID-versus OPM-MEG in an occipital and parietal anchored network. Notably, high quality OPM-MEG data were retained in participants with metallic fixtures, from whom no useable data were collected using conventional MEG.

Gradient phase and amplitude errors in atomic magnetic gradiometers for biomagnetic imaging systems

The cross-axis projection error (CAPE) caused by residual magnetic fields has recently attracted widespread attention. In this study, we propose a more specific theoretical model and expand the CAPE in gradient measurements. We first report that differences in relaxation rate and residual magnetic field between optically pumped magnetometers (OPMs) introduce a significant error term in the output of OPM gradiometers, referred to as the gradient phase error. Furthermore, when the longitudinal field compensation is inadequate, the interaxial response interference of a single OPM is prominent, resulting in an amplitude distortion of the signal. This is further amplified in the gradiometer configuration, introducing the gradient amplitude error. Our experiments demonstrated that the efficacy of mitigating common-mode noise of OPM gradiometers was significantly impaired when existing the gradient errors. In addition, a simulation with a magnetoencephalography (MEG) system illustrated an induced source localization error of exceeding 2 cm, severely compromising the localization accuracy of OPM-MEG systems.

A Novel, Robust, and Portable Platform for Magnetoencephalography using Optically Pumped Magnetometers

Magnetoencephalography (MEG) measures brain function via assessment of magnetic fields generated by neural currents. Conventional MEG uses superconducting sensors, which place significant limitations on performance, practicality, and deployment; however, the field has been revolutionised in recent years by the introduction of optically-pumped-magnetometers (OPMs). OPMs enable measurement of the MEG signal without cryogenics, and consequently the conception of 'OPM-MEG' systems which ostensibly allow increased sensitivity and resolution, lifespan compliance, free subject movement, and lower cost. However, OPM-MEG remains in its infancy with limitations on both sensor and system design. Here, we report a new OPM-MEG design with miniaturised and integrated electronic control, a high level of portability, and improved sensor dynamic range (arguably the biggest limitation of existing instrumentation). We show that this system produces equivalent measures when compared to an established instrument; specifically, when measuring task-induced beta-band, gamma-band and evoked neuro-electrical responses, source localisations from the two systems were highly comparable and temporal correlation was >0.7 at the individual level and >0.9 for groups. Using an electromagnetic phantom, we demonstrate improved dynamic range by running the system in background fields up to 8 nT. We show that the system is effective in gathering data during free movement (including a sitting-to-standing paradigm) and that it is compatible with simultaneous electroencephalography (EEG - the clinical standard). Finally, we demonstrate portability by moving the system between two laboratories. Overall, our new system is shown to be a significant step forward for OPM-MEG technology and offers an attractive platform for next generation functional medical imaging.

From cryogenic to on-scalp magnetoencephalography for the evaluation of paediatric epilepsy

Magnetoencephalography (MEG) is a neurophysiological technique based on the detection of brain magnetic fields. Whole-head MEG systems typically house a few hundred sensors requiring cryogenic cooling in a rigid one-size-fits-all (commonly adult-sized) helmet to keep a thermal insulation space. This leads to an increased brain-to-sensor distance in children, because of their smaller head circumference, and decreased signal-to-noise ratio. MEG allows detection and localization of interictal and ictal epileptiform discharges, and pathological high frequency oscillations, as a part of the presurgical assessment of children with refractory focal epilepsy, where electroencephalography is not contributive. MEG can also map the eloquent cortex before surgical resection. MEG also provides insights into the physiopathology of both generalized and focal epilepsy. On-scalp recordings based on cryogenic-free sensors have demonstrated their use in the field of childhood focal epilepsy and should become a reference technique for diagnosing epilepsy in the paediatric population. WHAT THIS PAPER ADDS: Magnetoencephalography (MEG) contributes to the diagnosis and understanding of paediatric epilepsy. On-scalp MEG recordings demonstrate some advantages over cryogenic MEG.

An advance in novel intelligent sensory technologies: From an implicit-tracking perspective of food perception

Food sensory evaluation mainly includes explicit and implicit measurement methods. Implicit measures of consumer perception are gaining significant attention in food sensory and consumer science as they provide effective, subconscious, objective analysis. A wide range of advanced technologies are now available for analyzing physiological and psychological responses, including facial analysis technology, neuroimaging technology, autonomic nervous system technology, and behavioral pattern measurement. However, researchers in the food field often lack systematic knowledge of these multidisciplinary technologies and struggle with interpreting their results. In order to bridge this gap, this review systematically describes the principles and highlights the applications in food sensory and consumer science of facial analysis technologies such as eye tracking, facial electromyography, and automatic facial expression analysis, as well as neuroimaging technologies like electroencephalography, magnetoencephalography, functional magnetic resonance imaging, and functional near-infrared spectroscopy. Furthermore, we critically compare and discuss these advanced implicit techniques in the context of food sensory research and then accordingly propose prospects. Ultimately, we conclude that implicit measures should be complemented by traditional explicit measures to capture responses beyond preference. Facial analysis technologies offer a more objective reflection of sensory perception and attitudes toward food, whereas neuroimaging techniques provide valuable insight into the implicit physiological responses during food consumption. To enhance the interpretability and generalizability of implicit measurement results, further sensory studies are needed. Looking ahead, the combination of different methodological techniques in real-life situations holds promise for consumer sensory science in the field of food research.

On a framework of data assimilation for hyperparameter estimation of spiking neuronal networks

When handling real-world data modeled by a complex network dynamical system, the number of the parameters is often much more than the size of the data. Therefore, in many cases, it is impossible to estimate these parameters and the exact value of each parameter is frequently less interesting than the distribution of the parameters. In this paper, we aim to estimate the distribution of the parameters in the mesoscopic neuronal network model from the macroscopic experimental data, for example, the BOLD (blood oxygen level dependent) signal. Herein, we assume that the parameters of the neurons and synapses are inhomogeneous but independently and identically distributed from certain distributions with unknown hyperparameters. Thus, we estimate these hyperparameters of the distributions of the parameters, instead of estimating the parameters themselves. We formulate this problem under the framework of data assimilation and hierarchical Bayesian method and present an efficient method named Hierarchical Data Assimilation (HDA) to conduct the statistical inference on the neuronal network model with the BOLD signal data simulated by the hemodynamic model. We consider the Leaky Integral-Fire (LIF) neuronal networks with four synapses and show that the proposed algorithm can estimate the BOLD signals and the hyperparameters with high preciseness. In addition, we discuss the influence on the performance of the algorithm configuration and the LIF network model setup.

Adaptive multipole models of optically pumped magnetometer data

Multipole expansions have been used extensively in the Magnetoencephalography (MEG) literature for mitigating environmental interference and modelling brain signal. However, their application to Optically Pumped Magnetometer (OPM) data is challenging due to the wide variety of existing OPM sensor and array designs. We therefore explore how such multipole models can be adapted to provide stable models of brain signal and interference across OPM systems. Firstly, we demonstrate how prolate spheroidal (rather than spherical) harmonics can provide a compact representation of brain signal when sampling on the scalp surface with as few as 100 channels. We then introduce a type of orthogonal projection incorporating this basis set. The Adaptive Multipole Models (AMM), which provides robust interference rejection across systems, even in the presence of spatially structured nonlinearity errors (shielding factor is the reciprocal of the maximum fractional nonlinearity error). Furthermore, this projection is always stable, as it is an orthogonal projection, and will only ever decrease the white noise in the data. However, for array designs that are suboptimal for spatially separating brain signal and interference, this method can remove brain signal components. We contrast these properties with the more typically used multipole expansion, Signal Space Separation (SSS), which never reduces brain signal amplitude but is less robust to the effect of sensor nonlinearity errors on interference rejection and can increase noise in the data if the system is sub-optimally designed (as it is an oblique projection). We conclude with an empirical example utilizing AMM to maximize signal to noise ratio (SNR) for the stimulus locked neuronal response to a flickering visual checkerboard in a 128-channel OPM system and demonstrate up to 40 dB software shielding in real data.

Capacitive Bionic Magnetic Sensors Based on One-Step Biointerface Preparation

Magnetic biomolecule-based bionic magnetic field sensors are anticipated to open up novel pathways for magnetic field detection. The detection range and accuracy of current bionic magnetic field sensors are limited, and little work is based on the capacitive response principle. We successfully developed a biochemical interface with an extralarge target-receptor size ratio, which can be manufactured in a single step for weak magnetic field detection across a wide frequency range, and we used electrochemical capacitance as a magnetic field change conduction strategy. The thickness-controllable nanoscale bovine serum albumin/graphene layer on an indium tin oxide working electrode combines with the one-step preparation method to immobilize the MagR/Cry4 complex. This capacitive bionic magnetic sensor can achieve the detection range of 0-120 mT. This biointerface design strategy obtains the further improvement of the performance of this bionic magnetic field sensor. Furthermore, the biointerface construction and optimization methodology in this proposal has potential applications in the design of other medical biosensors.

Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study

When planning for epilepsy surgery, multiple potential sites for resection may be identified through anatomical imaging. Magnetoencephalography (MEG) using optically pumped sensors (OP-MEG) is a non-invasive functional neuroimaging technique which could be used to help identify the epileptogenic zone from these candidate regions. Here we test the utility of a-priori information from anatomical imaging for differentiating potential lesion sites with OP-MEG. We investigate a number of scenarios: whether to use rigid or flexible sensor arrays, with or without a-priori source information and with or without source modelling errors. We simulated OP-MEG recordings for 1309 potential lesion sites identified from anatomical images in the Multi-centre Epilepsy Lesion Detection (MELD) project. To localise the simulated data, we used three source inversion schemes: unconstrained, prior source locations at centre of the candidate sites, and prior source locations within a volume around the lesion location. We found that prior knowledge of the candidate lesion zones made the inversion robust to errors in sensor gain, orientation and even location. When the reconstruction was too highly restricted and the source assumptions were inaccurate, the utility of this a-priori information was undermined. Overall, we found that constraining the reconstruction to the region including and around the participant's potential lesion sites provided the best compromise of robustness against modelling or measurement error.

The role of magnetoencephalography in preoperative localization and postoperative outcome prediction in patients with posterior cortical epilepsy

OBJECTIVE

We aimed to explore the value of magnetoencephalography in the presurgical evaluation of patients with posterior cortex epilepsy.

METHODS

A total of 39 patients with posterior cortex epilepsy (PCE) and intact magnetoencephalography (MEG) images were reviewed from August 2019 to July 2022. MEG dipole clusters were classified into single clusters, multiple clusters, and scatter dipoles based on tightness criteria. The association of the surgical outcome with MEG dipole classifications was evaluated using Fisher's exact tests.

RESULTS

Among the 39 cases, there were 24 cases of single clusters (61.5%), nine cases of multiple clusters (23.1%), and six cases of scattered dipoles (15.4%). Patients with single dipole clusters were more likely to become seizure-free. Among single dipole cluster cases (n = 24), complete MEG dipole resection yielded a more favorable surgical outcome than incomplete resection (83.3% vs. 16.7%, p = 0.007). Patients with concordant MRI and MEG findings achieved a significantly more favorable surgical outcome than discordant patients (66.7% vs. 33.3%, p = 0.044), especially in single dipole cluster patients (87.5% vs. 25.0%, p = 0.005).

SIGNIFICANCE

MEG can provide additional valuable information regarding surgical candidate selection, epileptogenic zone localization, electrode implantation schedule, and final surgical planning in patients with posterior cortex epilepsy.

Libet's legacy: A primer to the neuroscience of volition

The neuroscience of volition is an emerging subfield of the brain sciences, with hundreds of papers on the role of consciousness in action formation published each year. This makes the state-of-the-art in the discipline poorly accessible to newcomers and difficult to follow even for experts in the field. Here we provide a comprehensive summary of research in this field since its inception that will be useful to both groups. We also discuss important ideas that have received little coverage in the literature so far. We systematically reviewed a set of 2220 publications, with detailed consideration of almost 500 of the most relevant papers. We provide a thorough introduction to the seminal work of Benjamin Libet from the 1960s to 1980s. We also discuss common criticisms of Libet's method, including temporal introspection, the interpretation of the assumed physiological correlates of volition, and various conceptual issues. We conclude with recent advances and potential future directions in the field, highlighting modern methodological approaches to volition, as well as important recent findings.

Brain-computer interface in critical care and rehabilitation

This comprehensive review explores the broad landscape of brain-computer interface (BCI) technology and its potential use in intensive care units (ICUs), particularly for patients with motor impairments such as quadriplegia or severe brain injury. By employing brain signals from various sensing techniques, BCIs offer enhanced communication and motor rehabilitation strategies for patients. This review underscores the concept and efficacy of noninvasive, electroencephalogram-based BCIs in facilitating both communicative interactions and motor function recovery. Additionally, it highlights the current research gap in intuitive "stop" mechanisms within motor rehabilitation protocols, emphasizing the need for advancements that prioritize patient safety and individualized responsiveness. Furthermore, it advocates for more focused research that considers the unique requirements of ICU environments to address the challenges arising from patient variability, fatigue, and limited applicability of current BCI systems outside of experimental settings.

Non-rigid-registration-based positioning and labelling of triaxial OPMs on a flexible cap for wearable magnetoencephalography

BACKGROUND

Recent advances in highly sensitive miniaturized optically pumped magnetometers (OPMs) have enabled the development of wearable magnetoencephalography (MEG) offering great flexibility in experimental setting. The OPM array for wearable MEG is typically attached to a flexible cap and exhibits a variable spatial layout across different subjects, which imposes challenges concerning the efficient positioning and labelling of OPMs.

NEW METHOD

A pair of reflective markers are affixed to each triaxial OPM sensor above its cable to determine its location and sensitive axes. A non-rigid registration of optically digitized marker locations with a pre-labelled template of marker locations is performed to map newly digitized markers to OPMs.

RESULTS

The positioning and labelling of 66 OPM sensors could be completed within 35 s. Across ten experiments, all OPMs were accurately labelled, and the mean test-retest errors were 0.48 mm for sensor locations and 0.20 degree for sensitive axes. By combining six OPMs' positions with their respective recordings, magnetic dipoles inside a phantom were located with a mean error of 5.5 mm, and the best fitted dipole for MEG with auditory stimuli presented was located on a subject's primary auditory cortex.

COMPARISON WITH EXISTING METHODS

The proposed method reduces the reliance on error-prone and laborious manual operations inherent in existing methods, therefore significantly improving the efficiency of OPM positioning and labelling on a flexible cap.

CONCLUSION

We developed a method for the precise and rapid positioning and labelling triaxial OPMs on a flexible cap, thereby facilitating the practical implementation of wearable OPM-MEG.

Enzymatic Reactions Observed with Zero- and Low-Field Nuclear Magnetic Resonance

We demonstrate that enzyme-catalyzed reactions can be observed in zero- and low-field NMR experiments by combining recent advances in parahydrogen-based hyperpolarization methods with state-of-the-art magnetometry. Specifically, we investigated two model biological processes: the conversion of fumarate into malate, which is used in vivo as a marker of cell necrosis, and the conversion of pyruvate into lactate, which is the most widely studied metabolic process in hyperpolarization-enhanced imaging. In addition to this, we constructed a microfluidic zero-field NMR setup to perform experiments on microliter-scale samples of [1-13C]fumarate in a lab-on-a-chip device. Zero- to ultralow-field (ZULF) NMR has two key advantages over high-field NMR: the signals can pass through conductive materials (e.g., metals), and line broadening from sample heterogeneity is negligible. To date, the use of ZULF NMR for process monitoring has been limited to studying hydrogenation reactions. In this work, we demonstrate this emerging analytical technique for more general reaction monitoring and compare zero- vs low-field detection.

On the clinical utility of on-scalp MEG: A modeling study of epileptic activity source estimation

OBJECTIVE

Epilepsy surgery requires localization of the seizure onset zone (SOZ). Today this can only be achieved by intracranial electroencephalography (iEEG). The iEEG electrode placement is guided by findings from non-invasive modalities that cannot themselves detect SOZ-generated initial seizure activity. On scalp magnetoencephalography (osMEG), with sensors placed on the scalp, demonstrates higher sensitivity than conventional MEG (convMEG) and could potentially detect early seizure activity. Here, we modeled EEG, convMEG and osMEG to compare the modalities' ability to localize SOZ activity and to detect epileptic spikes.

METHODS

We modeled seizure propagation within ten epileptic networks located in the mesial and lateral temporal lobe; basal, dorsal, central and frontopolar frontal lobe; parietal and occipital lobe as well as insula and cingulum. The networks included brain regions often involved in focal epilepsy. 128-channel osMEG, convMEG, EEG and combined osMEG + EEG and convMEG + EEG were modeled, and the SOZ source estimation accuracy was quantified and compared using Student's t-test.

RESULTS

OsMEG was significantly (p-value <0.01) better than both convMEG and EEG at detecting the earliest SOZ-generated seizure activity and epileptic spikes, and better at localizing seizure activity from all epileptic networks (p < 0.01).

CONCLUSIONS

Our modeling results clearly show that osMEG has an unsurpassed potential to detect both epileptic spikes and seizure activity from all simulated anatomical sites.

SIGNIFICANCE

No clinically available non-invasive technique can detect SOZ activity from all brain regions. Our study indicates that osMEG has the potential to become an important clinical tool, improving both non-invasive SOZ localization and iEEG electrode placement accuracy.

Can cognitive neuroscience solve the lab-dilemma by going wild?

Reproducibility, measurability, and refutability are the foundation of the scientific method applied to empirical work. In the study of animal and human behavior, experimental protocols conducted in the lab are the most reliable means by which scientists can operationalize behaviors using controlled and parameterized setups. However, whether observations in the lab fully generalize in the real world remain legitimately disputed. The notion of "experimental design" was originally intended to ensure the generalizability of experimental findings to real-world situations. Experiments in the wild are more frequently explored and significant technological advances have been made allowing mobile neuroimaging. Yet some methodological limitations remain when testing scientific hypotheses in ecological conditions. Herein, we discuss the limitations of inferential processes derive from empirical observations in the wild. The multi-causal property of an ecological situation often lacks controls, and this major concern may prevent the replication and the reliability of behavioral observations. We discuss the epistemological and historical grounds of the induction process for behavioral and cognitive neurosciences and provide some possible heuristics for In situ experimental designs compatible with psychophysics in the wild.

Helium Optically Pumped Magnetometers Can Detect Epileptic Abnormalities as Well as SQUIDs as Shown by Intracerebral Recordings

Magnetoencephalography based on superconducting quantum interference devices (SQUIDs) has been shown to improve the diagnosis and surgical treatment decision for presurgical evaluation of drug-resistant epilepsy. Still, its use remains limited because of several constraints such as cost, fixed helmet size, and the obligation of immobility. A new generation of sensors, optically pumped magnetometers (OPMs), could overcome these limitations. In this study, we validate the ability of helium-based OPM (4He-OPM) sensors to record epileptic brain activity thanks to simultaneous recordings with intracerebral EEG [stereotactic EEG (SEEG)]. We recorded simultaneous SQUIDs-SEEG and 4He-OPM-SEEG signals in one patient during two sessions. We show that epileptic activities on intracerebral EEG can be recorded by OPMs with a better signal-to noise ratio than classical SQUIDs. The OPM sensors open new venues for the widespread application of magnetoencephalography in the management of epilepsy and other neurologic diseases and fundamental neuroscience.

Role of optically pumped magnetometers in presurgical epilepsy evaluation: Commentary of the American Clinical Magnetoencephalography Society

One of the major challenges of modern epileptology is the underutilization of epilepsy surgery for treatment of patients with focal, medication resistant epilepsy (MRE). Aggravating this distressing failure to deliver optimum care to these patients is the underuse of proven localizing tools, such as magnetoencephalography (MEG), a clinically validated, non-invasive, neurophysiological method used to directly measure and localize brain activity. A sizable mass of published evidence indicates that MEG can improve identification of surgical candidates and guide pre-surgical planning, increasing the yield of SEEG and improving operative outcomes. However, despite at least 10 common, evidence supported, clinical scenarios in MRE patients where MEG can offer non-redundant information and improve the pre-surgical evaluation, it is regularly used by only a minority of USA epilepsy centers. The current state of the art in MEG sensors employs SQUIDs, which require cooling with liquid helium to achieve superconductivity. This sensor technology has undergone significant generational improvement since whole head MEG scanners were introduced around in 1990s, but still has limitations. Further advances in sensor technology which may make ME G more easily accessible and affordable have been eagerly awaited, and development of new techniques should be encouraged. Of late, optically pumped magnetometers (OPMs) have received considerable attention, even prompting some potential acquisitions of new MEG systems to be put on hold, based on a hope that OPMs will usher in a new generation of MEG equipment and procedures. The development of any new clinical test used to guide intracranial EEG monitoring and/or surgical planning must address several specific issues. The goal of this commentary is to recognize the current state of OPM technology and to suggest a framework for it to advance in the clinical realm where it can eventually be deemed clinically valuable to physicians and patients. The American Clinical MEG Society (ACMEGS) strongly supports more advanced and less expensive technology and looks forward to continuing work with researchers to develop new sensors and clinical devices which will improve the experience and outcome for patients, and perhaps extend the role of MEG. However, currently, there are no OPM devices ready for practical clinical use. Based on the engineering obstacles and the clinical tradeoffs to be resolved, the assessment of experts suggests that there will most likely be another decade relying solely on "frozen SQUIDs" in the clinical MEG field.

Disorganized Communication and Social Dysfunction in Schizophrenia: Emerging Concepts and Methods

PURPOSE OF REVIEW

In this review, we embrace the emerging field of second-person neuroscience to address disorganization in schizophrenia. We argue that the focus of interest for disorganization is the interpersonal space where shared mental processes ('social mind') occur based on the bio-behavioural synchrony between two (or more) interacting people. We lay out several bio-behavioural measures that can capture the component parts of this process. In particular, we highlight the real-time imaging technology of hyperscanning that enables multi-person analysis of naturalistic social interaction. We illustrate how these measures can be used in empirical studies by posing disorganization as a problem of interpersonal processing.

RECENT FINDINGS

Traditionally, disorganized speech and behaviour have been studied as the product of hidden cognitive processes ('private mind'). A dysfunction in these processes was attributed to the brain afflicted by the illness ('brain-bound mechanisms'). But this approach has contributed to challenges in measuring and quantifying disorganization. Consequently, the single-brain focus has not provided satisfactory clarity or led to effective treatments for persistent social dysfunction in schizophrenia. Social dysfunction is a core feature of schizophrenia. This dysfunction arises from disorganized interpersonal interaction that typifies the social profile of affected individuals. We outline challenges in employing several emerging concepts and methods and how they can be addressed to investigate the mechanisms of social dysfunction in schizophrenia.

The emergence of non-cryogenic quantum magnetic sensors: Synergistic advancement in magnetography together with SQUID

Emerging non-superconductor quantum magnetic sensors, such as optically pumped magnetometer, fluxgate, magnetic tunnel junction, and diamond nitrogen-vacancy center, are approaching the performance of superconductor quantum interference devices (SQUIDs). These sensors are enabling magnetography for human bodies and brain-computer interface. Will they completely replace the SQUID magnetography in the near future?

In Situ Study of the Magnetic Field Gradient Produced by a Miniature Bi-Planar Coil for Chip-Scale Atomic Devices

The miniaturization of quantum sensors is a popular trend for the development of quantum technology. One of the key components of these sensors is a coil which is used for spin modulation and manipulation. The bi-planar coils have the advantage of producing three-dimensional magnetic fields with only two planes of current confinement, whereas the traditional Helmholtz coils require three-dimensional current distribution. Thus, the bi-planar coils are compatible with the current micro-fabrication process and are quite suitable for the compact design of the chip-scale atomic devices that require stable or modulated magnetic fields. This paper presents a design of a miniature bi-planar coil. Both the magnetic fields produced by the coils and their inhomogeneities were designed theoretically. The magnetic field gradient is a crucial parameter for the coils, especially for generating magnetic fields in very small areas. We used a NMR (Nuclear Magnetic Resonance) method based on the relaxation of 131Xe nuclear spins to measure the magnetic field gradient in situ. This is the first time that the field inhomogeneities of the field of such small bi-planar coils have been measured. Our results indicate that the designed gradient caused error is 0.08 for the By and the Bx coils, and the measured gradient caused error using the nuclear spin relaxation method is 0.09±0.02, suggesting that our method is suitable for measuring gradients. Due to the poor sensitivity of our magnetometer under a large Bz bias field, we could not measure the Bz magnetic field gradient. Our method also helps to improve the gradients of the miniature bi-planar coil design, which is critical for chip-scale atomic devices.

SERF-like magnetometry in room-temperature environment

We demonstrate an atomic magnetometry using amplitude-modulated pumping and hyperfine repumping techniques in a paraffin-coated cell. By exploiting the constructive interference between spins polarized by the pump beam and an additional repump beam, we observe a three-fold increase in the amplitude of magnetic resonance, along with a reduction in linewidth by approximately two times. The implementation of the repump beam effectively narrows the linewidth, demonstrating successful suppression of spin-exchange relaxation. This reduction in relaxation rate, combined with the enhanced signal, significantly improves the sensitivity of the magnetometer. Consequently, our technique offers a promising approach for achieving SERF-like magnetometry with sub-fT-level sensitivity in Earth-field range and room-temperature environment.

Single-trial classification of evoked responses to auditory tones using OPM- and SQUID-MEG

Objective.Optically pumped magnetometers (OPMs) are emerging as a near-room-temperature alternative to superconducting quantum interference devices (SQUIDs) for magnetoencephalography (MEG). In contrast to SQUIDs, OPMs can be placed in a close proximity to subject's scalp potentially increasing the signal-to-noise ratio and spatial resolution of MEG. However, experimental demonstrations of these suggested benefits are still scarce. Here, to compare a 24-channel OPM-MEG system to a commercial whole-head SQUID system in a data-driven way, we quantified their performance in classifying single-trial evoked responses.Approach.We measured evoked responses to three auditory tones in six participants using both OPM- and SQUID-MEG systems. We performed pairwise temporal classification of the single-trial responses with linear discriminant analysis as well as multiclass classification with both EEGNet convolutional neural network and xDAWN decoding.Main results.OPMs provided higher classification accuracies than SQUIDs having a similar coverage of the left hemisphere of the participant. However, the SQUID sensors covering the whole helmet had classification scores larger than those of OPMs for two of the tone pairs, demonstrating the benefits of a whole-head measurement.Significance.The results demonstrate that the current OPM-MEG system provides high-quality data about the brain with room for improvement for high bandwidth non-invasive brain-computer interfacing.

Machine learning assisted vector atomic magnetometry

Multiparameter sensing such as vector magnetometry often involves complex setups due to various external fields needed in explicitly connecting one measured signal to one parameter. Here, we propose a paradigm of indirect encoding for vector atomic magnetometry based on machine learning. We encode the three-dimensional magnetic-field information in the set of four simultaneously acquired signals associated with the optical rotation of a laser beam traversing the atomic sample. The map between the recorded signals and the vectorial field information is established through a pre-trained deep neural network. We demonstrate experimentally a single-shot all optical vector atomic magnetometer, with a simple scalar-magnetometer design employing only one elliptically-polarized laser beam and no additional coils. Magnetic field amplitude sensitivities of about 100 [Formula: see text] and angular sensitivities of about [Formula: see text] (for a magnetic field of around 140 nT) are derived from the neural network. Our approach can reduce the complexity of the architecture of vector magnetometers, and may shed light on the general design of multiparameter sensing.

Free-induction-decay magnetic field imaging with a microfabricated Cs vapor cell

Magnetic field imaging is a valuable resource for signal source localization and characterization. This work reports an optically pumped magnetometer (OPM) based on the free-induction-decay (FID) protocol, that implements microfabricated cesium (Cs) vapor cell technology to visualize the magnetic field distributions resulting from various magnetic sources placed close to the cell. The slow diffusion of Cs atoms in the presence of a nitrogen (N2) buffer gas enables spatially independent measurements to be made within the same vapor cell by translating a 175 μm diameter probe beam over the sensing area. For example, the OPM was used to record temporal and spatial information to reconstruct magnetic field distributions in one and two dimensions. The optimal magnetometer sensitivity was estimated to be 0.43 pT/H z within a Nyquist limited bandwidth of 500 Hz. Furthermore, the sensor's dynamic range exceeds the Earth's field of approximately 50 μT, which provides a framework for magnetic field imaging in unshielded environments.

Light-narrowed parametric resonance magnetometer with the fundamental sensitivity beyond the spin-exchange limit

In the field of biomagnetic measurements, one of the most important recent challenges is to perform measurements in a magnetically unshielded environment. This first requires that atomic magnetometers can operate in a finite magnetic field, and have enough high sensitivity. To meet these requirements, we develop a light-narrowed parametric resonance (LPR) magnetometer. By adding a modulation magnetic field to the large longitudinal magnetic field, our LPR magnetometer can measure small transverse magnetic fields with an intrinsic sensitivity of 3.5 fT/Hz1/2 in a longitudinal magnetic field of μT range. Moreover, we have also demonstrated that in contrast to the previous light-narrowed scalar magnetometers, our LPR magnetometer has the potential to achieve higher sensitivity. Because in our case spin-exchange relaxation suppression by using light narrowing can lead to an improvement of fundamental sensitivity limit regardless of which quantum noise is dominant, and hence the fundamental sensitivity is no longer limited by spin-exchange, and approaches the fundamental limit set by the spin-exchange and spin-destruction cross sections.

Can neuroscience enlighten the philosophical debate about free will?

Free will has been at the heart of philosophical and scientific discussions for many years. However, recent advances in neuroscience have been perceived as a threat to the commonsense notion of free will as they challenge two core requirements for actions to be free. The first is the notion of determinism and free will, i.e., decisions and actions must not be entirely determined by antecedent causes. The second is the notion of mental causation, i.e., our mental state must have causal effects in the physical world, in other words, actions are caused by conscious intention. We present the classical philosophical positions related to determinism and mental causation, and discuss how neuroscience could shed a new light on the philosophical debate based on recent experimental findings. Overall, we conclude that the current evidence is insufficient to undermine free will.

Real-time, model-based magnetic field correction for moving, wearable MEG

Most neuroimaging techniques require the participant to remain still for reliable recordings to be made. Optically pumped magnetometer (OPM) based magnetoencephalography (OP-MEG) however, is a neuroimaging technique which can be used to measure neural signals during large participant movement (approximately 1 m) within a magnetically shielded room (MSR) (Boto et al., 2018; Seymour et al., 2021). Nevertheless, environmental magnetic fields vary both spatially and temporally and OPMs can only operate within a limited magnetic field range, which constrains participant movement. Here we implement real-time updates to electromagnetic coils mounted on-board of the OPMs, to cancel out the changing background magnetic fields. The coil currents were chosen based on a continually updating harmonic model of the background magnetic field, effectively implementing homogeneous field correction (HFC) in real-time (Tierney et al., 2021). During a stationary, empty room recording, we show an improvement in very low frequency noise of 24 dB. In an auditory paradigm, during participant movement of up to 2 m within a magnetically shielded room, introduction of the real-time correction more than doubled the proportion of trials in which no sensor saturated recorded outside of a 50 cm radius from the optimally-shielded centre of the room. The main advantage of such model-based (rather than direct) feedback is that it could allow one to correct field components along unmeasured OPM axes, potentially mitigating sensor gain and calibration issues (Borna et al., 2022).

Beyond simple laboratory studies: Developing sophisticated models to study rich behavior

Psychology and neuroscience are concerned with the study of behavior, of internal cognitive processes, and their neural foundations. However, most laboratory studies use constrained experimental settings that greatly limit the range of behaviors that can be expressed. While focusing on restricted settings ensures methodological control, it risks impoverishing the object of study: by restricting behavior, we might miss key aspects of cognitive and neural functions. In this article, we argue that psychology and neuroscience should increasingly adopt innovative experimental designs, measurement methods, analysis techniques and sophisticated computational models to probe rich, ecologically valid forms of behavior, including social behavior. We discuss the challenges of studying rich forms of behavior as well as the novel opportunities offered by state-of-the-art methodologies and new sensing technologies, and we highlight the importance of developing sophisticated formal models. We exemplify our arguments by reviewing some recent streams of research in psychology, neuroscience and other fields (e.g., sports analytics, ethology and robotics) that have addressed rich forms of behavior in a model-based manner. We hope that these "success cases" will encourage psychologists and neuroscientists to extend their toolbox of techniques with sophisticated behavioral models - and to use them to study rich forms of behavior as well as the cognitive and neural processes that they engage.

Neurophysiological alterations in mice and humans carrying mutations in APP and PSEN1 genes

BACKGROUND

Studies in animal models of Alzheimer's disease (AD) have provided valuable insights into the molecular and cellular processes underlying neuronal network dysfunction. Whether and how AD-related neurophysiological alterations translate between mice and humans remains however uncertain.

METHODS

We characterized neurophysiological alterations in mice and humans carrying AD mutations in the APP and/or PSEN1 genes, focusing on early pre-symptomatic changes. Longitudinal local field potential recordings were performed in APP/PS1 mice and cross-sectional magnetoencephalography recordings in human APP and/or PSEN1 mutation carriers. All recordings were acquired in the left frontal cortex, parietal cortex, and hippocampus. Spectral power and functional connectivity were analyzed and compared with wildtype control mice and healthy age-matched human subjects.

RESULTS

APP/PS1 mice showed increased absolute power, especially at higher frequencies (beta and gamma) and predominantly between 3 and 6 moa. Relative power showed an overall shift from lower to higher frequencies over almost the entire recording period and across all three brain regions. Human mutation carriers, on the other hand, did not show changes in power except for an increase in relative theta power in the hippocampus. Mouse parietal cortex and hippocampal power spectra showed a characteristic peak at around 8 Hz which was not significantly altered in transgenic mice. Human power spectra showed a characteristic peak at around 9 Hz, the frequency of which was significantly reduced in mutation carriers. Significant alterations in functional connectivity were detected in theta, alpha, beta, and gamma frequency bands, but the exact frequency range and direction of change differed for APP/PS1 mice and human mutation carriers.

CONCLUSIONS

Both mice and humans carrying APP and/or PSEN1 mutations show abnormal neurophysiological activity, but several measures do not translate one-to-one between species. Alterations in absolute and relative power in mice should be interpreted with care and may be due to overexpression of amyloid in combination with the absence of tau pathology and cholinergic degeneration. Future studies should explore whether changes in brain activity in other AD mouse models, for instance, those also including tau pathology, provide better translation to the human AD continuum.

Microscopic-scale magnetic recording of brain neuronal electrical activity using a diamond quantum sensor

Quantum sensors using solid state qubits have demonstrated outstanding sensitivity, beyond that possible using classical devices. In particular, those based on colour centres in diamond have demonstrated high sensitivity to magnetic field through exploiting the field-dependent emission of fluorescence under coherent control using microwaves. Given the highly biocompatible nature of diamond, sensing from biological samples is a key interdisciplinary application. In particular, the microscopic-scale study of living systems can be possible through recording of temperature and biomagnetic field. In this work, we use such a quantum sensor to demonstrate such microscopic-scale recording of electrical activity from neurons in fragile living brain tissue. By recording weak magnetic field induced by ionic currents in mouse corpus callosum axons, we accurately recover signals from neuronal action potential propagation while demonstrating in situ pharmacology. Our sensor allows recording of the electrical activity in neural circuits, disruption of which can shed light on the mechanisms of disease emergence. Unlike existing techniques for recording activity, which can require potentially damaging direct interaction, our sensing is entirely passive and remote from the sample. Our results open a promising new avenue for the microscopic recording of neuronal signals, offering the eventual prospect of microscopic imaging of electrical activity in the living mammalian brain.