The magnetoencephalogram (MEG) based on array optically pumped magnetometers (OPMs) has the potential of replacing conventional cryogenic superconducting quantum interference device. Phase synchronization is a common method for measuring brain oscillations and functional connectivity. Verifying the feasibility and fidelity of OPM-MEG in measuring phase synchronization will help its widespread application in the study of aforementioned neural mechanisms. The analysis method on source-level time series can weaken the influence of instantaneous field spread effect. In this paper, the OPM-MEG was used for measuring the evoked responses of 20Hz rhythmic and arrhythmic median nerve stimulation, and the inter-trial phase synchronization (ITPS) and inter-reginal phase synchronization (IRPS) of primary somatosensory cortex (SI) and secondary somatosensory cortex (SII) were analysed. The results find that under rhythmic condition, the evoked responses of SI and SII show continuous oscillations and the effect of resetting phase. The values of ITPS and IRPS significantly increase at the stimulation frequency of 20Hz and its harmonic of 40Hz, whereas the arrhythmic stimulation does not exhibit this phenomenon. Moreover, in the initial stage of stimulation, the ITPS and IRPS values are significantly higher at Mu rhythm in the rhythmic condition compared to arrhythmic. In conclusion, the results demonstrate the ability of OPM-MEG in measuring phase pattern and functional connectivity on source-level, and may also prove beneficial for the study on the mechanism of rhythmic stimulation therapy for rehabilitation.

The human brain undergoes tremendous changes during the first decade of life. The susceptibility of the immature central nervous system to factors such as adverse environments and genetic factors is attributed to its plasticity. Neurodevelopmental disorders (NDDs) occur once the immature brain veers off the typical developmental trajectory. However, little is known about the neurophysiological traits of atypically developing children because it is challenging for them to remain still during recording. Magnetoencephalography (MEG) is a noninvasive neuroimaging technique with high-spatiotemporal resolution. An ultralow magnetic field produced by neural electrical activity can be detected using a highly sensitive whole-head magnetometer array. Current cryogenic SQUID-MEG combined with individual MRI has shown great potential in reflecting neural activity under resting states and during tasks. MEG instrumentation for children is expected to be an effective tool for investigating brain dynamics, which provides neuropsychological evidence for atypical development in communication ability. In this paper, the advantages of pediatric MEG in neurodevelopmental disorder studies are discussed first and compared with those of several noninvasive functional imaging modalities. Existing commercial pediatric MEG systems are summarized based on their respective characteristics and parameters. State-of-the-art newly emerging sensing techniques based on spin-exchange relaxation-free (SERF) along with their application in detecting infants' brain responses are introduced. Recent discoveries on MEG biomarkers in children with NDDs are then summarized concerning disorders that have comorbidities in communication, such as specific language impairment (SLI), autism spectrum disorders (ASD), dyslexia and stuttering. Progress on multimodality research and total-field wearable SERF magnetometers offers insight into the neuropsychological substrates of communication disorders.

Multivariate pattern analysis (MVPA) has played an extensive role in interpreting brain activity, which has been applied in studies with modalities such as functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). The advent of wearable MEG systems based on optically pumped magnetometers (OPMs), i.e., OP-MEG, has broadened the application of bio-magnetism in the realm of neuroscience. Nonetheless, it also raises challenges in temporal decoding analysis due to the unique attributes of OP-MEG itself. The efficacy of decoding performance utilizing multimodal fusion, such as MEG-EEG, also remains to be elucidated. In this regard, we investigated the impact of several factors, such as processing methods, models and modalities, on the decoding outcomes of OP-MEG. Our findings indicate that the number of averaged trials, dimensionality reduction (DR) methods, and the number of cross-validation folds significantly affect the decoding performance of OP-MEG data. Additionally, decoding results vary across modalities and fusion strategy. In contrast, decoder type, resampling frequency, and sliding window length exert marginal effects. Furthermore, we introduced mutual information (MI) to investigate how information loss due to OP-MEG data processing affect decoding accuracy. Our study offers insights for linear decoding research using OP-MEG and expand its application in the fields of cognitive neuroscience.

Time–frequency parameterization for oscillations in specific frequency bands reflects the dynamic changes in the brain. It is related to cognitive behavior and diseases and has received significant attention in neuroscience. However, many studies do not consider the impact of the aperiodic noise and neural activity, including their time-varying fluctuations. Some studies are limited by the low resolution of the time–frequency spectrum and parameter-solved operation. Therefore, this paper proposes super-resolution time–frequency periodic parameterization of (transient) oscillation (STPPTO). STPPTO obtains a super-resolution time–frequency spectrum with Superlet transform. Then, the time–frequency representation of oscillations is obtained by removing the aperiodic component fitted in a time-resolved way. Finally, the definition of transient events is used to parameterize oscillations. The performance of this method is validated on simulated data and its reliability is demonstrated on magnetoencephalography. We show how it can be used to explore and analyze oscillatory activity under rhythmic stimulation.

The spontaneous oscillations within the brain are intimately linked to the hierarchical structures of the cortex, as evidenced by the cross-cortical gradient between parametrized spontaneous oscillations and cortical locations. Despite the significance of both peak frequency and peak time in characterizing these oscillations, limited research has explored the relationship between peak time and cortical locations. And no studies have demonstrated that the cross-cortical gradient can be measured by optically pumped magnetometer-based magnetoencephalography (OPM-MEG). Therefore, the cross-cortical gradient of parameterized spontaneous oscillation was analyzed for oscillations recorded by OPM-MEG using restricted maximum likelihood estimation with a linear mixed-effects model. It was validated that OPM-MEG can measure the cross-cortical gradient of spontaneous oscillations. Furthermore, results demonstrated the difference in the cross-cortical gradient between spontaneous oscillations during eye-opening and eye-closing conditions. The methods and conclusions offer potential to integrate electrophysiological and structural information of the brain, which contributes to the analysis of oscillatory fluctuations across the cortex recorded by OPM-MEG.