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Abstract Presurgical evaluation is still challenging for MRI‐negative epilepsy patients. As non‐invasive modalities are the easiest acceptable and economic methods in determining the epileptogenic zone, we analyzed the localization value of common non‐invasive methods in MRI‐negative epilepsy patients. In this study, we included epilepsy patients undergoing presurgical evaluation with presurgical negative MRI. MRI post‐processing was performed using a Morphometric Analysis Program (MAP) on T1‐weighted volumetric MRI. The relationship between MAP, magnetoencephalography (MEG), scalp electroencephalogram (EEG), and seizure outcomes was analyzed to figure out the localization value of different non‐invasive methods. Eighty‐six patients were included in this study. Complete resection of the MAP‐positive regions or the MEG‐positive regions was positively associated with seizure freedom (p = 0.028 and 0.007, respectively). When an area is co‐localized by MAP and MEG, the resection of the area was significantly associated with seizure freedom (p = 0.006). However, neither the EEG lateralization nor the EEG localization showed statistical association with the surgical outcome (p = 0.683 and 0.505, respectively). In conclusion, scalp EEG had a limited role in presurgical localization and predicting seizure outcome, combining MAP and MEG results can significantly improve the localization of epileptogenic lesions and have a positive association with seizure‐free outcome. Plain Language Summary Due to the lack of obvious structure abnormalities on neuroimaging examinations, the identification of epilepsy lesions in MRI‐negative epilepsy patients can be difficult. In this study, we intended to use non‐invasive examinations to explore the potential epileptic lesions in MRI‐negative epilepsy patients and to determine the results accuracy by comparing the neuroimaging results with the epilepsy surgery outcomes. A total of 86 epilepsy patients without obvious structure lesions on MRI were included, and we found that the combinations of different non‐invasive examinations and neuroimaging post‐processing methods are significantly associated with the seizure freedom results of epilepsy surgery.

Abstract Introduction There has been a growing interest in studying brain activity under naturalistic conditions. However, the relationship between individual differences in ongoing brain activity and psychological characteristics is not well understood. We investigated this connection, focusing on the association between oscillatory activity in the brain and individually characteristic dispositional traits. Given the variability of unconstrained resting states among individuals, we devised a paradigm that could harmonize the state of mind across all participants. Methods We constructed task contrasts that included focused attention (FA), self‐centered future planning, and rumination on anxious thoughts triggered by visual imagery. Magnetoencephalography was recorded from 28 participants under these 3 conditions for a duration of 16 min. The oscillatory power in the alpha and beta bands was converted into spatial contrast maps, representing the difference in brain oscillation power between the two conditions. We performed permutation cluster tests on these spatial contrast maps. Additionally, we applied penalized canonical correlation analysis (CCA) to study the relationship between brain oscillation patterns and behavioral traits. Results The data revealed that the FA condition, as compared to the other conditions, was associated with higher alpha and beta power in the temporal areas of the left hemisphere and lower alpha and beta power in the parietal areas of the right hemisphere. Interestingly, the penalized CCA indicated that behavioral inhibition was positively correlated, whereas anxiety was negatively correlated, with a pattern of high oscillatory power in the bilateral precuneus and low power in the bilateral temporal regions. This unique association was found in the anxious‐thoughts condition when contrasted with the focused‐attention condition. Conclusion Our findings suggest individual temperament traits significantly affect brain engagement in naturalistic conditions. This research underscores the importance of considering individual traits in neuroscience and offers an effective method for analyzing brain activity and psychological differences.

Key Clinical Message Cognitive impairment associated dementia is treatable non‐pharmacologically. Monitoring tools are important to provide proper treatment. The present study showed that the resting‐state brain activity measured using magnetoencephalography reflects their outcomes and captures clinical impressions better than neuropsychological assessments, which have inherent limitations such as the practice effect. Abstract Mild cognitive impairment (MCI) is a prodromal phase of dementia caused by brain diseases. Non‐pharmacological treatments are sometimes effective in improving patient's cognition and quality of life. To provide better treatments, monitoring the treatment outcomes, which is done using neuropsychological assessments, is important. However, these assessments have inherent limitations, such as practice effects. Therefore, complementary assessments are anticipated. Magnetoencephalography (MEG) is a neuroimaging technique that is sensitive to changes in brain activity associated with cognitive impairment. It represents the state of brain activity in terms of MEG spectral parameters associated with neuropsychological assessment scores. MEG spectral parameters could reasonably be used to monitor treatment outcomes without the aforementioned limitations. However, few published longitudinal reports have assessed MEG spectral parameters during the non‐pharmacological treatment period for cognitive impairment associated with dementia. In this study, we retrospectively examined the clinical records of two patients with MCI. Changes in neuropsychological assessment scores and MEG spectral parameters were qualitatively evaluated along with the patients' conditions, as described in the medical records during non‐pharmacological treatments provided for more than 2 years. The changes in neuropsychological assessment scores and MEG spectral parameters showed comparable trends, with some discrepancies. Changes in MEG spectral parameters were more consistent with the subjective reports from caregivers and medical staff in the medical records. Our results suggest that MEG is a promising tool for monitoring patient conditions during treatment.

Abstract Objective This study aimed to investigate the differences on resting‐state brain networks between the interictal epileptiform discharge (IED) group with self‐limited epilepsy with centrotemporal spikes (SeLECTS), the non‐IED group with SeLECTS, and the healthy control (HC) group. Methods Patients were divided into the IED and non‐IED group according to the presence or absence of IED during magnetoencephalography (MEG). We used Wechsler Intelligence Scale for Children, fourth edition (WISC‐IV) to assess cognition in 30 children with SeLECTS and 15 HCs. Functional networks were constructed at the whole‐brain level and graph theory (GT) analysis was used to quantify the topology of the brain network. Results The IED group had the lowest cognitive function scores, followed by the non‐IED group and then HCs. Our MEG results showed that the IED group had more dispersed functional connectivity (FC) in the 4–8 Hz frequency band, and more brain regions were involved compared to the other two groups. Furthermore, the IED group had fewer FC between the anterior and posterior brain regions in the 12–30 Hz frequency band. Both the IED group and the non‐IED group had fewer FC between the anterior and posterior brain regions in the 80–250 Hz frequency band compared to the HC group. GT analysis showed that the IED group had a higher clustering coefficient compared to the HC group and a higher degree compared to the non‐IED group in the 80–250 Hz frequency band. The non‐IED group had a lower path length in the 30–80 Hz frequency band compared to the HC group. Conclusions The study data obtained in this study suggested that intrinsic neural activity was frequency‐dependent and that FC networks of the IED group and the non‐IED group underwent changes in different frequency bands. These network‐related changes may contribute to cognitive dysfunction in children with SeLECTS.

Abstract Aim This study aimed to investigate gamma oscillations related to face processing of children with autism spectrum disorders and typically developed children using magnetoencephalography. Methods We developed stimuli that included naturalistic real‐time eye‐gaze situations between participants and their mothers. Eighteen young children with autism spectrum disorders (62−97 months) and 24 typically developed children (61−79 months) were included. The magnetoencephalography data were analyzed in the bilateral banks of the superior temporal sulcus, fusiform gyrus, and pericalcarine cortex for frequency ranges 30–59 and 61–90 Hz. The gamma oscillation normalized values were calculated to compare the face condition (children gazing at mother's face) and control measurements (baseline) using the following formula: (face − control)/(face + control). Results The results revealed significant differences in gamma oscillation normalized values in the low gamma band (30–59 Hz) in the right banks of the superior temporal sulcus, right fusiform gyrus, and right pericalcarine cortex between children with autism spectrum disorders and typically developed children. Furthermore, there were significant differences in gamma oscillation normalized values in the high gamma band (61–90 Hz) in the right banks of the superior temporal sulcus, bilateral fusiform gyrus, and bilateral pericalcarine cortex between the groups. Conclusion This report is the first magnetoencephalography study revealing atypical face processing in young children with autism spectrum disorders using relevant stimuli between participants and their mothers. Our naturalistic paradigm provides a useful assessment of social communication traits and a valuable insight into the underlying neural mechanisms in children with autism spectrum disorders.

The characterisation of resting-state networks (RSNs) using neuroimaging techniques has significantly contributed to our understanding of the organisation of brain activity. Prior work has demonstrated the electrophysiological basis of RSNs and their dynamic nature, revealing transient activations of brain networks with millisecond timescales. While previous research has confirmed the comparability of RSNs identified by electroencephalography (EEG) to those identified by magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), most studies have utilised static analysis techniques, ignoring the dynamic nature of brain activity. Often, these studies use high-density EEG systems, which limit their applicability in clinical settings. Addressing these gaps, our research studies RSNs using medium-density EEG systems (61 sensors), comparing both static and dynamic brain network features to those obtained from a high-density MEG system (306 sensors). We assess the qualitative and quantitative comparability of EEG-derived RSNs to those from MEG, including their ability to capture age-related effects, and explore the reproducibility of dynamic RSNs within and across the modalities. Our findings suggest that both MEG and EEG offer comparable static and dynamic network descriptions, albeit with MEG offering some increased sensitivity and reproducibility. Such RSNs and their comparability across the two modalities remained consistent qualitatively but not quantitatively when the data were reconstructed without subject-specific structural MRI images., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Verbal working memory (vWM) is an essential limited-capacity cognitive system that spans the fronto-parietal network and utilizes the subprocesses of encoding, maintenance, and retrieval. With the recent widespread use of noninvasive brain stimulation techniques, multiple recent studies have examined whether such stimulation may enhance cognitive abilities such as vWM, but the findings to date remain unclear in terms of both behavior and critical brain regions. In the current study, we applied high-definition direct current stimulation to the left and right parietal cortices of 39 healthy adults in three separate sessions (left anodal, right anodal, and sham). Following stimulation, participants completed a vWM task during high-density magnetoencephalography (MEG). Significant neural responses at the sensor-level were imaged using a beamformer and whole-brain ANOVAs were used to identify the specific neuromodulatory effects of the stimulation conditions on neural responses serving distinct phases of vWM. We found that right stimulation had a faciliatory effect relative to left stimulation and sham on theta oscillations during encoding in the right inferior frontal, while the opposite pattern was observed for left supramarginal regions. Stimulation also had a faciliatory effect on theta in occipital regions and alpha in temporal regions regardless of the laterality of stimulation. In summary, our data suggest that parietal HD-tDCS both facilitates and interferes with neural responses underlying both the encoding and maintenance phases of vWM. Future studies are warranted to determine whether specific tDCS parameters can be tuned to accentuate the facilitation responses and attenuate the interfering aspects., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

During aging the inter-individual variability in both the neural and behavioral functions is likely to be emphasized. Decreased competence particularly in working memory and general executive control compromises many aspects of the quality of life also within the nonclinical population. We aimed, first, to clarify the brain basis of visual working memory and inhibition during multi-stage natural-like task performance, and second, to identify associations between variation in task-related neural activity and relevant cognitive skills, namely inhibition and general working memory capacity. We recorded, using magnetoencephalography (MEG), the neural modulations associated with encoding, maintenance, and retrieval, as well as interference suppression during a visual working memory task in older adults. We quantified the neural correlates of these cognitive processes through two complementary approaches: evoked responses and oscillatory activity. Neural activity during memory retrieval and interference suppression were correlated with behavioral measures of task switching and general executive functions. Our results show that general inhibitory control induced frontocentral neural modulation across a broad range of frequencies whereas domain-specific inhibition was limited to right posterior areas. Our findings also suggest that modulations particularly in phase-locked evoked neural activity can be reliably associated with explicit measures of cognitive skills, with better inhibitory control linked with an early neural effect of distractor inhibition during retrieval. In general, we show that exploiting the inherent inter-individual variability in neural measures and behavioral markers of cognition in aging populations can help establish reliable links between specific brain functions and their behavioral manifestations., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Recently, there has been a resurgence in experimental and conceptual efforts to understand how brain rhythms can serve to organize visual information. Oscillations can provide temporal structure for neuronal processing and form a basis for integrating information across brain areas. Here, we use a bistable paradigm and a data-driven approach to test the hypothesis that oscillatory modulations associate with the integration or segregation of visual elements. Spectral signatures of perception of bound and unbound configurations of visual moving stimuli were studied using magnetoencephalography (MEG) in ambiguous and unambiguous conditions. Using a 2 × 2 design, we were able to isolate correlates from visual integration, either perceptual or stimulus-driven, from attentional and ambiguity-related activity. Two frequency bands were found to be modulated by visual integration: an alpha/beta frequency and a higher frequency gamma-band. Alpha/beta power was increased in several early visual cortical and dorsal visual areas during visual integration, while gamma-band power was surprisingly increased in the extrastriate visual cortex during segregation. This points to an integrative role for alpha/beta activity, likely from top-down signals maintaining a single visual representation. On the other hand, when more representations have to be processed in parallel gamma-band activity is increased, which is at odds with the notion that gamma oscillations are related to perceptual coherence. These modulations were confirmed in intracranial EEG recordings and partially originate from distinct brain areas. Our MEG and stereo-EEG data confirms predictions of binding mechanisms depending on low-frequency activity for long-range integration and for organizing visual processing while refuting a straightforward correlation between gamma-activity and perceptual binding. PRACTITIONER POINTS: Distinct neurophysiological signals underlie competing bistable percepts. Increased alpha/beta activity correlate with visual integration while gamma correlates with segmentation. Ambiguous percepts drive alpha/beta activity in the posterior cingulate cortex., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Regular cannabis use is associated with cortex-wide changes in spontaneous and oscillatory activity, although the functional significance of such changes remains unclear. We hypothesized that regular cannabis use would suppress spontaneous gamma activity in regions serving cognitive control and scale with task performance. Participants (34 cannabis users, 33 nonusers) underwent an interview regarding their substance use history and completed the Eriksen flanker task during magnetoencephalography (MEG). MEG data were imaged in the time-frequency domain and virtual sensors were extracted from the peak voxels of the grand-averaged oscillatory interference maps to quantify spontaneous gamma activity during the pre-stimulus baseline period. We then assessed group-level differences in spontaneous and oscillatory gamma activity, and their relationship with task performance and cannabis use metrics. Both groups exhibited a significant behavioral flanker interference effect, with slower responses during incongruent relative to congruent trials. Mixed-model ANOVAs indicated significant gamma-frequency neural interference effects in the left frontal eye fields (FEF) and left temporoparietal junction (TPJ). Further, a group-by-condition interaction was detected in the left FEF, with nonusers exhibiting stronger gamma oscillations during incongruent relative to congruent trials and cannabis users showing no difference. In addition, spontaneous gamma activity was sharply suppressed in cannabis users relative to nonusers in the left FEF and TPJ. Finally, spontaneous gamma activity in the left FEF and TPJ was associated with task performance across all participants, and greater cannabis use was associated with weaker spontaneous gamma activity in the left TPJ of the cannabis users. Regular cannabis use was associated with weaker spontaneous gamma in the TPJ and FEF. Further, the degree of use may be proportionally related to the degree of suppression in spontaneous activity in the left TPJ., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

This study assesses the reliability of resting-state dynamic causal modelling (DCM) of magnetoencephalography (MEG) under conductance-based canonical microcircuit models, in terms of both posterior parameter estimates and model evidence. We use resting-state MEG data from two sessions, acquired 2 weeks apart, from a cohort with high between-subject variance arising from Alzheimer's disease. Our focus is not on the effect of disease, but on the reliability of the methods (as within-subject between-session agreement), which is crucial for future studies of disease progression and drug intervention. To assess the reliability of first-level DCMs, we compare model evidence associated with the covariance among subject-specific free energies (i.e., the 'quality' of the models) with versus without interclass correlations. We then used parametric empirical Bayes (PEB) to investigate the differences between the inferred DCM parameter probability distributions at the between subject level. Specifically, we examined the evidence for or against parameter differences (i) within-subject, within-session, and between-epochs; (ii) within-subject between-session; and (iii) within-site between-subjects, accommodating the conditional dependency among parameter estimates. We show that for data acquired close in time, and under similar circumstances, more than 95% of inferred DCM parameters are unlikely to differ, speaking to mutual predictability over sessions. Using PEB, we show a reciprocal relationship between a conventional definition of 'reliability' and the conditional dependency among inferred model parameters. Our analyses confirm the reliability and reproducibility of the conductance-based DCMs for resting-state neurophysiological data. In this respect, the implicit generative modelling is suitable for interventional and longitudinal studies of neurological and psychiatric disorders., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Visual entrainment is a powerful and widely used research tool to study visual information processing in the brain. While many entrainment studies have focused on frequencies around 14-16 Hz, there is renewed interest in understanding visual entrainment at higher frequencies (e.g., gamma-band entrainment). Notably, recent groundbreaking studies have demonstrated that gamma-band visual entrainment at 40 Hz may have therapeutic effects in the context of Alzheimer's disease (AD) by stimulating specific neural ensembles, which utilize GABAergic signaling. Despite such promising findings, few studies have investigated the optimal parameters for gamma-band visual entrainment. Herein, we examined whether visual stimulation at 32, 40, or 48 Hz produces optimal visual entrainment responses using high-density magnetoencephalography (MEG). Our results indicated strong entrainment responses localizing to the primary visual cortex in each condition. Entrainment responses were stronger for 32 and 40 Hz relative to 48 Hz, indicating more robust synchronization of neural ensembles at these lower gamma-band frequencies. In addition, 32 and 40 Hz entrainment responses showed typical patterns of habituation across trials, but this effect was absent for 48 Hz. Finally, connectivity between visual cortex and parietal and prefrontal cortices tended to be strongest for 40 relative to 32 and 48 Hz entrainment. These results suggest that neural ensembles in the visual cortex may resonate at around 32 and 40 Hz and thus entrain more readily to photic stimulation at these frequencies. Emerging AD therapies, which have focused on 40 Hz entrainment to date, may be more effective at lower relative to higher gamma frequencies, although additional work in clinical populations is needed to confirm these findings. PRACTITIONER POINTS: Gamma-band visual entrainment has emerged as a therapeutic approach for eliminating amyloid in Alzheimer's disease, but its optimal parameters are unknown. We found stronger entrainment at 32 and 40 Hz compared to 48 Hz, suggesting neural ensembles prefer to resonate around these relatively lower gamma-band frequencies. These findings may inform the development and refinement of innovative AD therapies and the study of GABAergic visual cortical functions., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Testosterone levels sharply rise during the transition from childhood to adolescence and these changes are known to be associated with changes in human brain structure. During this same developmental window, there are also robust changes in the neural oscillatory dynamics serving verbal working memory processing. Surprisingly, whereas many studies have investigated the effects of chronological age on the neural oscillations supporting verbal working memory, none have probed the impact of endogenous testosterone levels during this developmental period. Using a sample of 89 youth aged 6-14 years-old, we collected salivary testosterone samples and recorded magnetoencephalography during a modified Sternberg verbal working memory task. Significant oscillatory responses were identified and imaged using a beamforming approach and the resulting maps were subjected to whole-brain ANCOVAs examining the effects of testosterone and sex, controlling for age, during verbal working memory encoding and maintenance. Our primary results indicated robust testosterone-related effects in theta (4-7 Hz) and alpha (8-14 Hz) oscillatory activity, controlling for age. During encoding, females exhibited weaker theta oscillations than males in right cerebellar cortices and stronger alpha oscillations in left temporal cortices. During maintenance, youth with greater testosterone exhibited weaker alpha oscillations in right parahippocampal and cerebellar cortices, as well as regions across the left-lateralized language network. These results extend the existing literature on the development of verbal working memory processing by showing region and sex-specific effects of testosterone, and are the first results to link endogenous testosterone levels to the neural oscillatory activity serving verbal working memory, above and beyond the effects of chronological age., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Abstract Introduction An increasing number of studies are using magnetoencephalography (MEG) to study dementia. Here we define a common methodological framework for MEG resting‐state acquisition and analysis to facilitate the pooling of data from different sites. Methods Two groups of patients with mild cognitive impairment (MCI, n = 84) and healthy controls (n = 84) were combined from three sites, and site and group differences inspected in terms of power spectra and functional connectivity. Classification accuracy for MCI versus controls was compared across three different types of MEG analyses, and compared with classification based on structural MRI. Results The spectral analyses confirmed frequency‐specific differences in patients with MCI, both in power and connectivity patterns, with highest classification accuracy from connectivity. Critically, site acquisition differences did not dominate the results. Discussion This work provides detailed protocols and analyses that are sensitive to cognitive impairment, and that will enable standardized data sharing to facilitate large‐scale collaborative projects.

The post-movement beta rebound has been studied extensively using magnetoencephalography (MEG) and is reliably modulated by various task parameters as well as illness. Our recent study showed that rebounds, which we generalise as "post-task responses" (PTRs), are a ubiquitous phenomenon in the brain, occurring across the cortex in theta, alpha, and beta bands. Currently, it is unknown whether PTRs following working memory are driven by transient bursts, which are moments of short-lived high amplitude activity, similar to those that drive the post-movement beta rebound. Here, we use three-state univariate hidden Markov models (HMMs), which can identify bursts without a priori knowledge of frequency content or response timings, to compare bursts that drive PTRs in working memory and visuomotor MEG datasets. Our results show that PTRs across working memory and visuomotor tasks are driven by pan-spectral transient bursts. These bursts have very similar spectral content variation over the cortex, correlating strongly between the two tasks in the alpha (R 2  = .89) and beta (R 2  = .53) bands. Bursts also have similar variation in duration over the cortex (e.g., long duration bursts occur in the motor cortex for both tasks), strongly correlating over cortical regions between tasks (R 2  = .56), with a mean over all regions of around 300 ms in both datasets. Finally, we demonstrate the ability of HMMs to isolate signals of interest in MEG data, such that the HMM probability timecourse correlates more strongly with reaction times than frequency filtered power envelopes from the same brain regions. Overall, we show that induced PTRs across different tasks are driven by bursts with similar characteristics, which can be identified using HMMs. Given the similarity between bursts across tasks, we suggest that PTRs across the cortex may be driven by a common underlying neural phenomenon., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Abstract In situations involving fatigue, the increase in fatigue levels and the apparent decrease in motivation levels are thought to suppress mental and physical performance to avoid disrupting homeostasis and aid recovery; however, the ultimate source of information on which the brain depends to perceive fatigue and/or a loss of motivation for protection remains unknown. In this study, we found that, as assessed by magnetoencephalography, electromagnetic cortical neuronal activity while performing cognitive tasks was associated with a decrease in motivation caused by the tasks in healthy participants, suggesting the possibility that the brain utilizes information that reflects the invested amount of neural activity to suppress performance. To our knowledge, this is the first report to provide clues for the missing link between neural investments and the resulting activation of the biological alarms that suppress performance.

Abstract Introduction We report the routine application of magnetoencephalography (MEG) in a memory clinic, and its value in the discrimination of patients with Alzheimer's disease (AD) dementia from controls. Methods Three hundred sixty‐six patients visiting our memory clinic underwent MEG recording. Source‐reconstructed MEG data were visually assessed and evaluated in the context of clinical findings and other diagnostic markers. We analyzed the diagnostic accuracy of MEG spectral measures in the discrimination of individual AD dementia patients (n = 40) from subjective cognitive decline (SCD) patients (n = 40) using random forest models. Results Best discrimination was obtained using a combination of relative theta and delta power (accuracy 0.846, sensitivity 0.855, specificity 0.837). The results were validated in an independent cohort. Hippocampal and thalamic regions, besides temporal‐occipital lobes, contributed considerably to the model. Discussion MEG has been implemented successfully in the workup of memory clinic patients and has value in diagnostic decision‐making.

Abstract Introduction This study was aimed to explore the relationship between neural network changes in newly diagnosed children with Benign Childhood Epilepsy with Centrotemporal Spikes (BECTS) and cognitive impairment. Methods Children's cognition was evaluated using the Wechsler Intelligence Scale for Children‐Fourth Edition (WISC‐IV). Magnetoencephalographic (MEG) data of 18 healthy children and 22 BECTS patients were recorded in order to construct a functional connectivity (FC) network, which was quantified by graph theory (GT). Results The mean age of the control group was 7.94 ± 1.89 years, and the mean age of BECTS patients was 8.14 ± 1.73 years. Our results show that the WISC‐IV index scores in the BECTS group were significantly lower than those in the control group. Besides, the FC network pattern of BECTS patients changed significantly in the 12–30, 30–80, and 250–500 Hz frequency band. The local functional connections between posterior cingulate cortex (PCC) and frontal lobe varied significantly in 12–30, 80–250, and 250–500 Hz. Our GT analysis shows that the connection strength of BECTS patients increases significantly in the 12–30 Hz frequency band, the path length decreases significantly in the 12–30 Hz and 30–80 Hz frequency bands, with the clustering coefficient decreasing significantly in the 12–30 Hz, 30–80 Hz, and 250–500 Hz frequency bands. Correlation analysis showed that the full‐scale IQ (FSIQ) was positively correlated with the 12–30 Hz clustering coefficient, verbal comprehension index (VCI) was positively correlated with the 250–500 Hz clustering coefficient, perceptual reasoning index (PRI) was positively correlated with the 12–30 Hz clustering coefficient, and perceptual reasoning index (PSI) was negatively correlated with the 12–30 Hz path length. Conclusion There is a trend of cognitive impairment in patients with early BECTS. This trend of cognitive impairment in early BECTS children may be related to the changes in the FC network pattern.

The electrophysiological basis of resting-state networks (RSN) is still under debate. In particular, no principled mechanism has been determined that is capable of explaining all RSN equally well. While magnetoencephalography (MEG) and electroencephalography are the methods of choice to determine the electrophysiological basis of RSN, no standard analysis pipeline of RSN yet exists. In this article, we compare the two main existing data-driven analysis strategies for extracting RSNs from MEG data and introduce a third approach. The first approach uses phase-amplitude coupling to determine the RSN. The second approach extracts RSN through an independent component analysis of the Hilbert envelope in different frequency bands, while the third new approach uses a singular value decomposition instead. To evaluate these approaches, we compare the MEG-RSN to the functional magnetic resonance imaging (fMRI)-RSN from the same subjects. Overall, it was possible to extract RSN with MEG using all three techniques, which matched the group-specific fMRI-RSN. Interestingly the new approach based on SVD yielded significantly higher correspondence to five out of seven fMRI-RSN than the two existing approaches. Importantly, with this approach, all networks-except for the visual network-had the highest correspondence to the fMRI networks within one frequency band. Thereby we provide further insights into the electrophysiological underpinnings of the fMRI-RSNs. This knowledge will be important for the analysis of the electrophysiological connectome., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

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., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Fluid intelligence (Gf) involves logical reasoning and novel problem-solving abilities. Often, abstract reasoning tasks like Raven's progressive matrices are used to assess Gf. Prior work has shown an age-related decline in fluid intelligence capabilities, and although many studies have sought to identify the underlying mechanisms, our understanding of the critical brain regions and dynamics remains largely incomplete. In this study, we utilized magnetoencephalography (MEG) to investigate 78 individuals, ages 20-65 years, as they completed an abstract reasoning task. MEG data was co-registered with structural MRI data, transformed into the time-frequency domain, and the resulting neural oscillations were imaged using a beamformer. We found worsening behavioral performance with age, including prolonged reaction times and reduced accuracy. MEG analyses indicated robust oscillations in the theta, alpha/beta, and gamma range during the task. Whole brain correlation analyses with age revealed relationships in the theta and alpha/beta frequency bands, such that theta oscillations became stronger with increasing age in a right prefrontal region and alpha/beta oscillations became stronger with increasing age in parietal and right motor cortices. Follow-up connectivity analyses revealed increasing parieto-frontal connectivity with increasing age in the alpha/beta frequency range. Importantly, our findings are consistent with the parieto-frontal integration theory of intelligence (P-FIT). These results further suggest that as people age, there may be alterations in neural responses that are spectrally specific, such that older people exhibit stronger alpha/beta oscillations across the parieto-frontal network during abstract reasoning tasks., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Tau rhythms are largely defined by sound responsive alpha band (~8-13 Hz) oscillations generated largely within auditory areas of the superior temporal gyri. Studies of tau have mostly employed magnetoencephalography or intracranial recording because of tau's elusiveness in the electroencephalogram. Here, we demonstrate that independent component analysis (ICA) decomposition can be an effective way to identify tau sources and study tau source activities in EEG recordings. Subjects (N = 18) were passively exposed to complex acoustic stimuli while the EEG was recorded from 68 electrodes across the scalp. Subjects' data were split into 60 parallel processing pipelines entailing use of five levels of high-pass filtering (passbands of 0.1, 0.5, 1, 2, and 4 Hz), three levels of low-pass filtering (25, 50, and 100 Hz), and four different ICA algorithms (fastICA, infomax, adaptive mixture ICA [AMICA], and multi-model AMICA [mAMICA]). Tau-related independent component (IC) processes were identified from this data as being localized near the superior temporal gyri with a spectral peak in the 8-13 Hz alpha band. These "tau ICs" showed alpha suppression during sound presentations that was not seen for other commonly observed IC clusters with spectral peaks in the alpha range (e.g., those associated with somatomotor mu, and parietal or occipital alpha). The choice of analysis parameters impacted the likelihood of obtaining tau ICs from an ICA decomposition. Lower cutoff frequencies for high-pass filtering resulted in significantly fewer subjects showing a tau IC than more aggressive high-pass filtering. Decomposition using the fastICA algorithm performed the poorest in this regard, while mAMICA performed best. The best combination of filters and ICA model choice was able to identify at least one tau IC in the data of ~94% of the sample. Altogether, the data reveal close similarities between tau EEG IC dynamics and tau dynamics observed in MEG and intracranial data. Use of relatively aggressive high-pass filters and mAMICA decomposition should allow researchers to identify and characterize tau rhythms in a majority of their subjects. We believe adopting the ICA decomposition approach to EEG analysis can increase the rate and range of discoveries related to auditory responsive tau rhythms., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Magnetoencephalography (MEG) recordings are often contaminated by interference that can exceed the amplitude of physiological brain activity by several orders of magnitude. Furthermore, the activity of interference sources may spatially extend (known as source leakage) into the activity of brain signals of interest, resulting in source estimation inaccuracies. This problem is particularly apparent when using MEG to interrogate the effects of brain stimulation on large-scale cortical networks. In this technical report, we develop a novel denoising approach for suppressing the leakage of interference source activity into the activity representing a brain region of interest. This approach leverages spatial and temporal domain projectors for signal arising from prespecified anatomical regions of interest. We apply this denoising approach to reconstruct simulated evoked response topographies to deep brain stimulation (DBS) in a phantom recording. We highlight the advantages of our approach compared to the benchmark-spatiotemporal signal space separation-and show that it can more accurately reveal brain stimulation-evoked response topographies. Finally, we apply our method to MEG recordings from a single patient with Parkinson's disease, to reveal early cortical-evoked responses to DBS of the subthalamic nucleus., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Understanding encoded languages, such as written script or Morse code, requires nonlexical and lexical processing components that act in a parallel and interactive fashion. Decoding written script-as for example in reading-is typically very fast, making the investigation of the lexical and nonlexical components and their underlying neural mechanisms challenging. In the current study, we aimed to accomplish this problem by using Morse code as a model for language decoding. The decoding of Morse code is slower and thus allows a better and more fine-grained investigation of the lexical and nonlexical components of language decoding. In the current study, we investigated the impact of various components of nonlexical decoding of Morse code using magnetoencephalography. For this purpose, we reconstructed the time-frequency responses below 40 Hz in brain regions significantly involved in Morse code decoding and word comprehension that were identified in a previous study. Event-related reduction in beta- and alpha-band power were found in left inferior frontal cortex and angular gyrus, respectively, while event-related theta-band power increase was found at frontal midline. These induced oscillations reflect working-memory encoding, long-term memory retrieval as well as demanding cognitive control, respectively. In sum, by using Morse code and MEG, we were able to identify a cortical network underlying language decoding in a time- and frequency-resolved manner., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Cognitive impairment is a major concern in clinical medicine. It is usually evaluated with neuropsychological assessments, which have inherent limitations. To compensate for them, magnetoencephalography has already come into clinical use to evaluate the level of cognitive impairment. It evaluates global changes in the frequency of resting-state brain activity, which are associated with cognitive status. However, it remains unclear what neural mechanism causes the frequency changes. To understand this, it is important to identify cortical regions that mainly contribute to these changes. We retrospectively analysed the clinical records from 310 individuals with cognitive impairment who visited the outpatient department at our hospital. The analysis included resting-state magnetoencephalography, neuropsychological assessment, and clinical diagnosis data. Regional oscillatory intensities were estimated from the magnetoencephalography data, which were statistically analysed, along with neuropsychological assessment scores, and the severity of cognitive impairment associated with clinical diagnosis. The regional oscillatory intensity covering a wide range of regions and frequencies was significantly associated with neuropsychological assessment scores and differed between healthy individuals and patients with cognitive impairment. However, these associations and differences in all conditions were overlapped by a single change in beta frequency in the left supramarginal gyrus. High frequency oscillatory intensity in the left supramarginal gyrus is associated with cognitive impairment levels among patients who were concerned about dementia. It provides new insights into cognitive status measurements using magnetoencephalography, which is expected to develop as an objective index to be used alongside traditional neuropsychological assessments., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The transition from childhood to adolescence is associated with an influx of sex hormones, which not only facilitates physical and behavioral changes, but also dramatic changes in neural circuitry. While previous work has shown that pubertal hormones modulate structural and functional brain development, few of these studies have focused on the impact that such hormones have on spontaneous cortical activity, and whether these effects are modulated by sex during this critical developmental window. Herein, we examined the effect of endogenous testosterone on spontaneous cortical activity in 71 typically-developing youth (ages 10-17 years; 32 male). Participants completed a resting-state magnetoencephalographic (MEG) recording, structural MRI, and provided a saliva sample for hormone analysis. MEG data were source-reconstructed and the power within five canonical frequency bands (delta, theta, alpha, beta, and gamma) was computed. The resulting power spectral density maps were analyzed via vertex-wise ANCOVAs to identify spatially specific effects of testosterone and sex by testosterone interactions, while covarying out age. We found robust sex differences in the modulatory effects of testosterone on spontaneous delta, beta, and gamma activity. These interactions were largely confined to frontal cortices and exhibited a stark switch in the directionality of the correlation from the low (delta) to high frequencies (beta/gamma). For example, in the delta band, greater testosterone related to lower relative power in prefrontal cortices in boys, while the reverse pattern was found for girls. These data suggest testosterone levels are uniquely related to the development of spontaneous cortical dynamics during adolescence, and such levels are associated with different developmental patterns in males and females within regions implicated in executive functioning., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Multiple sclerosis (MS) is a neurodegenerative disease characterized by neuronal and synaptic loss, resulting in an imbalance of excitatory and inhibitory synaptic transmission and potentially cognitive impairment. Current methods for measuring the excitation/inhibition (E/I) ratio are mostly invasive, but recent research combining neurocomputational modeling with measurements of local field potentials has indicated that the slope with which the power spectrum of neuronal activity captured by electro- and/or magnetoencephalography rolls off, is a non-invasive biomarker of the E/I ratio. A steeper roll-off is associated with a stronger inhibition. This novel method can be applied to assess the E/I ratio in people with multiple sclerosis (pwMS), detect the effect of medication such as benzodiazepines, and explore its utility as a biomarker for cognition. We recruited 44 healthy control subjects and 95 pwMS who underwent resting-state magnetoencephalographic recordings. The 1/f spectral slope of the neural power spectra was calculated for each subject and for each brain region. As expected, the spectral slope was significantly steeper in pwMS treated with benzodiazepines (BZDs) compared to pwMS not receiving BZDs (p = .01). In the sub-cohort of pwMS not treated with BZDs, we observed a steeper slope in cognitively impaired pwMS compared to cognitively preserved pwMS (p = .01) and healthy subjects (p = .02). Furthermore, we observed a significant correlation between 1/f spectral slope and verbal and spatial working memory functioning in the brain regions located in the prefrontal and parietal cortex. In this study, we highlighted the value of the spectral slope in MS by quantifying the effect of benzodiazepines and by putting it forward as a potential biomarker of cognitive deficits in pwMS., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Prenatal alcohol exposure (PAE), the leading known cause of childhood developmental disability, has long-lasting effects extending throughout the lifespan. It is well documented that children prenatally exposed to alcohol have difficulties inhibiting behavior and sustaining attention. Thus, the Sustained Attention to Response Task (SART), a Go/No-go paradigm, is especially well suited to assess the behavioral and neural functioning characteristics of children with PAE. In this study, we utilized neuropsychological assessment, parent/guardian questionnaires, and magnetoencephalography during SART random and fixed orders to assess characteristics of children 8-12 years old prenatally exposed to alcohol compared to typically developing children. Compared to neurotypical control children, children with a Fetal Alcohol Spectrum Disorder (FASD) diagnosis had significantly decreased performance on neuropsychological measures, had deficiencies in task-based performance, were rated as having increased Attention-Deficit/Hyperactivity Disorder (ADHD) behaviors and as having lower cognitive functioning by their caretakers, and had decreased peak amplitudes in Broadmann's Area 44 (BA44) during SART. Further, MEG peak amplitude in BA44 was found to be significantly associated with neuropsychological test results, parent/guardian questionnaires, and task-based performance such that decreased amplitude was associated with poorer performance. In exploratory analyses, we also found significant correlations between total cortical volume and MEG peak amplitude indicating that the reduced amplitude is likely related in part to reduced overall brain volume often reported in children with PAE. These findings show that children 8-12 years old with an FASD diagnosis have decreased amplitudes in BA44 during SART random order, and that these deficits are associated with multiple behavioral measures., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Cerebellar differences have long been documented in autism spectrum disorder (ASD), yet the extent to which such differences might impact language processing in ASD remains unknown. To investigate this, we recorded brain activity with magnetoencephalography (MEG) while ASD and age-matched typically developing (TD) children passively processed spoken meaningful English and meaningless Jabberwocky sentences. Using a novel source localization approach that allows higher resolution MEG source localization of cerebellar activity, we found that, unlike TD children, ASD children showed no difference between evoked responses to meaningful versus meaningless sentences in right cerebellar lobule VI. ASD children also had atypically weak functional connectivity in the meaningful versus meaningless speech condition between right cerebellar lobule VI and several left-hemisphere sensorimotor and language regions in later time windows. In contrast, ASD children had atypically strong functional connectivity for in the meaningful versus meaningless speech condition between right cerebellar lobule VI and primary auditory cortical areas in an earlier time window. The atypical functional connectivity patterns in ASD correlated with ASD severity and the ability to inhibit involuntary attention. These findings align with a model where cerebro-cerebellar speech processing mechanisms in ASD are impacted by aberrant stimulus-driven attention, which could result from atypical temporal information and predictions of auditory sensory events by right cerebellar lobule VI., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Overlapping clinical presentations in primary progressive aphasia (PPA) variants present challenges for diagnosis and understanding pathophysiology, particularly in the early stages of the disease when behavioral (speech) symptoms are not clearly evident. Divergent atrophy patterns (temporoparietal degeneration in logopenic variant lvPPA, frontal degeneration in nonfluent variant nfvPPA) can partially account for differential speech production errors in the two groups in the later stages of the disease. While the existing dogma states that neurodegeneration is the root cause of compromised behavior and cortical activity in PPA, the extent to which neurophysiological signatures of speech dysfunction manifest independent of their divergent atrophy patterns remain unknown. We test the hypothesis that nonword deficits in lvPPA and nfvPPA arise from distinct patterns of neural oscillations that are unrelated to atrophy. We use a novel structure-function imaging approach integrating magnetoencephalographic imaging of neural oscillations during a non-word repetition task with voxel-based morphometry-derived measures of gray matter volume to isolate neural oscillation abnormalities independent of atrophy. We find reduced beta band neural activity in left temporal regions associated with the late stages of auditory encoding unique to patients with lvPPA and reduced high-gamma neural activity over left frontal regions associated with the early stages of motor preparation in patients with nfvPPA. Neither of these patterns of reduced cortical oscillations was explained by cortical atrophy in our statistical model. These findings highlight the importance of structure-function imaging in revealing neurophysiological sequelae in early stages of dementia when neither structural atrophy nor behavioral deficits are clinically distinct., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)