While optically-pumped magnetometer (OPM) technology offers a number of compelling advantages over its SQUID predecessor for magnetoencephalography (MEG), many studies and viewpoints focus on issues of (i) scalp placement, with commensurate increases in sensitivity to weak magnetic fields and (ii) room temperature operation (without the need for baths of liquid helium to maintain superconducting properties of SQUIDs). This article addresses another unique and tantalizing opportunity—the ability for the OPM array to be “wearable”, and thus to move with the participant. This is critical in adoption of naturalistic paradigms that move beyond “laboratory neuroscience” toward “real world neuroscience”. It is also critically important in application to pediatric populations who cannot or will not remain still during conventional MEG scan procedures. Application to the developing infant brain will be considered as well as application to pediatric neuropsychiatric and developmental disorders, such as autism spectrum disorder. Rather than present solutions, this article will highlight the challenges faced by conventional SQUID-based cryo-MEG and explore the potential avenues for OPM-MEG to make a positive impact to the field of pediatric neuroscience.

Understanding the neurocognitive underpinnings of driving behavior in adolescents is critical to improving road safety. To address this, we established a novel paradigm linking magnetoencephalography (MEG)-recorded frequency-specific brain activity to simulated driving performance, identifying periods of increased cognitive control. However, this initial paradigm did not incorporate eye-tracking - a potentially scalable proxy for cognitive control that could be leveraged by in-vehicle driver monitoring systems. This proof-of-concept study expands our paradigm by integrating eye-tracking to identify scanning behavior metrics associated with periods of increased cognitive control validated by MEG. Typically developing adolescents (n = 11; mean age = 15.1 ± 1.5 yrs) completed three driving tasks of varying cognitive demand, and MEG frequency specific analysis confirmed periods of high (Hi) and low (Lo) cognitive control via the established biomarker of frontal midline theta (FMT). Fixation count, fixation duration, horizontal/vertical mean gaze position, saccade amplitude, and horizontal/vertical spread of search were compared between Hi vs. Lo periods of cognitive control. Task-specific differences in fixation count (p < 0.05), mean gaze position (p < 0.01), saccade amplitude (p < 0.05), and spread of search (p < 0.01) were observed between Hi compared to Lo cognitive control periods. These differences corresponded to expected task-specific changes in scanning behavior that would accompany cognitive control over behavior, suggesting a signal that eye-tracking may serve as a proxy for underlying neurocognitive processes. This integrated approach demonstrates methodological rigor and offers a promising framework for further research and informing development of in-vehicle driver monitoring systems for detecting cognitive deficits in real time, with implications for enhancing teen driver safety.

Purpose To develop a dentate nucleus (DN) segmentation tool using deep learning applied to brain MRI-based quantitative susceptibility mapping (QSM) images. Materials and Methods Brain QSM images from healthy controls and individuals with cerebellar ataxia or multiple sclerosis were collected from nine different datasets (2016-2023) worldwide for this retrospective study (ClinicalTrials.gov identifier: NCT04349514). Manual delineation of the DN was performed by experienced raters. Automated segmentation performance was evaluated against manual reference segmentations following training with several deep learning architectures. A two-step approach was used, consisting of a localization model followed by DN segmentation. Performance metrics included intraclass correlation coefficient (ICC), Dice score, and Pearson correlation coefficient. Results The training and testing datasets comprised 328 individuals (age range, 11-64 years; 171 female individuals), including 141 healthy individuals and 187 with cerebellar ataxia or multiple sclerosis. The manual tracing protocol produced reference standards with high intrarater (average ICC, 0.91) and interrater reliability (average ICC, 0.78). Initial deep learning architecture exploration indicated that the nnU-Net framework performed best. The two-step localization plus segmentation pipeline achieved a Dice score of 0.90 ± 0.03 (SD) and 0.89 ± 0.04 for left and right DN segmentation, respectively. In external testing, the proposed algorithm outperformed the current leading automated tool (mean Dice scores for left and right DN, 0.86 ± 0.04 vs 0.57 ± 0.22 [P < .001]; 0.84 ± 0.07 vs 0.58 ± 0.24 [P < .001]). The model demonstrated generalizability across datasets unseen during the training step, with automated segmentations showing high correlation with manual annotations (left DN: r = 0.74 [P < .001]; right DN: r = 0.48 [P = .03]). Conclusion The proposed model accurately and efficiently segmented the DN from brain QSM images. The model is publicly available (https://github.com/art2mri/DentateSeg). Keywords: MR Imaging, Brain/Brain Stem, Segmentation, Convolutional Neural Network, Supervised Learning, Computer Applications-3D, Volume Analysis, Image Postprocessing ClinicalTrials.gov registration no. NCT04349514 Supplemental material is available for this article. © RSNA, 2025.

OBJECTIVE:We aimed to quantify differences in the brain and spinal cord between Friedreich ataxia and controls, stratified by age and disease stage, including for the first time in young children. METHODS:TRACK-FA is the largest prospective, longitudinal, multi-modal neuroimaging study in Friedreich ataxia to date. We assessed individuals with Friedreich ataxia and controls, 5 to 42 years, at 7 sites across 4 continents. The 17 imaging primary outcome measures (POMs) were selected from metrics that showed a significant longitudinal change in previous small-scale studies. These included brain and spinal cord morphometry (structural magnetic resonance imaging [MRI]) and microstructure (diffusion MRI); brain iron levels (quantitative susceptibility mapping); and spinal cord biochemistry (magnetic resonance spectroscopy). This study is registered with ClinicalTrials.gov (NCT04349514). RESULTS:Between February 2021 and August 2023, we assessed 169 individuals with Friedreich ataxia and 95 controls. Compared to controls, individuals with Friedreich ataxia had lower volume of dentate nucleus and superior cerebellar peduncles; smaller cross-sectional area of spinal cord; lower fractional anisotropy and higher diffusivity in spinal cord and superior cerebellar peduncles; and lower total N-acetyl-aspartate/myo-inositol ratio in spinal cord. Morphometric differences in spinal cord and superior cerebellar peduncles increased dramatically with age during childhood, with rapid development in controls, but not in Friedreich ataxia. Many imaging POMs showed significant associations with clinical severity. INTERPRETATION:Our findings provide strong imaging evidence of impaired development of spinal cord and superior cerebellar peduncles during childhood in Friedreich ataxia and open the way for the use of neuroimaging biomarkers in clinical trials. ANN NEUROL 2025;98:386-397.

There is no simple blood test for autism. Consequently, much attention has been paid to identifying noninvasive biomarkers using imaging (e.g., Magnetic resonance imaging, MRI) and electrophysiological (e.g., electroencephalography, EEG and magnetoencephalography, MEG) methods. While, in general, these lack direct biological specificity, they can (in principle) provide a useful tool, or suite of tools, for diagnostic, prognostic, stratification, and response monitoring purposes.This chapter focuses on the pursuit of biomarkers using magnetoencephalography (MEG). While closely related to the more common electroencephalography (EEG), MEG offers some unique characteristics (such as improved spatial resolution, in combination with real-time temporal resolution and spectral discrimination), that might be considered impactful in the pursuit of biomarkers.Given the widely-acknowledged heterogeneity of ASD ("if you've seen one child with autism, then you've seen one child with autism"), the tide of research is perhaps shifting away from diagnostic biomarkers toward biomarkers that can help stratify patients according to some similarity in biological basis, etiology, or pathway. This approach, somewhat pragmatic, may be of benefit when designing and conducting clinical trials of putative therapeutics, or when optimally designing behavioral supports (when "therapy" may not be indicated).Ultimately, MEG-derived biomarkers, however advantageous in themselves, may likely find a place as reference in the prioritization and roll-out of candidate biomarkers established using other modalities, more accessible and available to the global community.

Background/Objectives: This study investigates the relationship between movement-related beta synchrony and primary motor cortex (M1) excitability, focusing on the time-dependent inhibition of movement. Voluntary movement induces beta frequency (13–30 Hz) event-related desynchronisation (B-ERD) in M1, followed by post-movement beta rebound (PMBR). Although PMBR is linked to cortical inhibition, its temporal relationship with motor cortical excitability is unclear. This study aims to determine whether PMBR acts as a marker for post-movement inhibition by assessing motor-evoked potentials (MEPs) during distinct phases of the beta synchrony profile. Methods: Twenty-five right-handed participants (mean age: 24 years) were recruited. EMG data were recorded from the first dorsal interosseous muscle, and TMS was applied to the M1 motor hotspot to evoke MEPs. A reaction time task was used to elicit beta oscillations, with TMS delivered at participant-specific time points based on EEG-derived beta power envelopes. MEP amplitudes were compared across four phases: B-ERD, early PMBR, peak PMBR, and late PMBR. Results: Our findings demonstrate that MEP amplitude significantly increased during B-ERD compared to rest, indicating heightened cortical excitability. In contrast, MEPs recorded during peak PMBR were significantly reduced, suggesting cortical inhibition. While all three PMBR phases exhibited reduced cortical excitability, a trend toward amplitude-dependent inhibition was observed. Conclusions: This study confirms that PMBR is linked to reduced cortical excitability, validating its role as a marker of motor cortical inhibition. These results enhance the understanding of beta oscillations in motor control and suggest that further research on altered PMBR could be crucial for understanding neurological and psychiatric disorders.

Purpose: To develop a dentate nucleus (DN) segmentation tool using deep learning (DL) applied to brain quantitative susceptibility mapping (QSM) images. Materials and Methods: Brain QSM images from 132 healthy controls and 170 individuals with cerebellar ataxia or multiple sclerosis were collected from nine different datasets worldwide for this retrospective study. Manual delineation of the DN (gray matter and white matter hilus) was first undertaken by experienced raters with a robust quality control process. Performance of automated segmentation was compared following training using several DL architectures. A two-step approach was implemented, composed of a localization model followed by DN segmentation. Results: The manual tracing protocol produced ground-truth data with high intra-rater (average ICC 0.906) and inter-rater reliability (average ICC 0.776). Initial DL architecture exploration indicated that the nnU-Net framework performed best. The two-step localization plus segmentation pipeline achieved a Dice score of 0.898±0.031 and 0.894±0.036 for left and right DN, respectively. In external validation, our algorithm outperformed the leading existing automated tool (left/right DN Dice 0.863±0.038/0.843±0.066 vs. 0.568±0.222/0.582±0.239). The model demonstrated generalizability across unseen datasets during the training step. The measures showed a superior correlation index with manual annotations and performed well in both isotropic and anisotropic QSM datasets. Conclusion: We provide a model that accurately and efficiently segments the DN from brain QSM images. The model can be readily deployed for use in observational, natural history, and treatment trials for biomarker discovery.### Competing Interest StatementTJRR is employed by Biogen, receives a salary, and is a grant recipient from Friedreich's Ataxia Research Alliance (FARA). DHS is an Itaú Unibanco SA employee and a grant recipient from Friedreich's Ataxia Research Alliance (FARA). SC received fees from Amicus for the advisory board. LAC is funded by Friedreich's Ataxia Research Alliance (FARA) and is a consultant for Biogen Pharmaceuticals. ID is funded by Friedreich's Ataxia Research Alliance (FARA). NGK is funded by Friedreich's Ataxia Research Alliance (FARA) and CHDI Foundation Inc (New York, USA). PGH is a grant recipient from Friedreich's Ataxia Research Alliance (FARA) and the National Institute of Health (NIH) P41EB027061, P30NS076408, S10OD017974. JMJ is funded by Friedreich's Ataxia Research Alliance (FARA) and National Institute of Health (NIH). CLK reports grant FWF P35887. CL received research grants from Minoryx Therapeutics, research support from Biogen Inc and is funded by Friedreich's Ataxia Research Alliance (FARA) and NIH P41 EB027061. JL is funded by Friedreich's Ataxia Research Alliance (FARA). TM reports funding from National Institute of Health (NIH) U01 NS104326. SM is funded by the Italian MUR for the project "SEE LIFE - StrEngthEning the Italian InFrastructure of Euro-bioimaging." AN is funded by the Italian Ministry of Health (RRC). KR is funded by Friedreich's Ataxia Research Alliance (FARA). SHS is industry support research for Reata, Biogen, Biohaven, Avidity Biosciences, Fulcrum therapeutics, Vertex, Arthex, PTC, Reneo, Larimar, has a consulting work for Reata, Biogen, Fulcrum, participated in speaking engagements for Biogen, MDA, Bionews, Medscape, and is funded by NIH, FDA, Muscular Dystrophy Association, Wyck Foundation, Friedreich's Ataxia Research Alliance, and National Ataxia Foundation. DT reports grants DFG, DE 2516/1-1 and TI 239/17-1. MCFJ reports funding from FAPESP (São Paulo Research Foundation). IHH reports Friedreich's Ataxia Research Alliance general research grant and NHMRC Ideas and Investigator Grants (2026191, 1184403). All other authors declare no financial or non-financial competing interests.### Funding StatementThis work was supported by the Friedreich's Ataxia Research Alliance (FARA General Research Grant) and grants from the Australian National Health and Medical Research Council (NHMRC Ideas Grant 1184403). The funding agencies did not influence the study design, data collection, or manuscript drafting.### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The ethics committee or institutional review board (IRB) respective to each project data source or site approved the use or ethics waiver for this retrospective study, and all participants provided written informed consent prior to original data collection. The TRACK-FA steering committee approved the data use, and IRB reference numbers were previously published (Monash Health Human Research Ethics Committee: RES-20-0000-139A; Children's Hospital of Philadelphia: IRB 20-017611; University of Minnesota: IRB STUDY00009047; University of Florida: IRB202000399; RWTH Aachen University: EK195/20; University of Campinas (CAAE NO): 83241318.3.1001.5404; McGill IRB Approved Project Number: 2022-8676). Ethics approval was obtained independently for the remaining studies, respectively: Ethical Committee "Carlo Romano" of the University of Naples "Federico II" (Naples A: 209/13, Naples B: 47/15), Monash University Human Research Ethics Committee (IMAGE-FRDA: 13201B, INFLAM-FRDA: 7810), and University of Minnesota IRB (1210M22281). The institutional ethics committee respective to each project approved their study (Fondazione IRCCS Istituto Neurologico "Carlo Besta": 42/2017 07/06/2017; Medical University of Graz local ethics-committee: 31-432ex18/191264-2019).I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesThe patient MRI data is not publicly available due to privacy regulations. Access can be provided upon reasonable request to scientists in accordance with our Data Use and Access Policy.

A vascularized composite tissue allotransplantation (VCA) was performed at the Children's Hospital of Philadelphia (CHOP), on an 8-year-old patient in 2015, six years after bilateral hand and foot amputation. Hand VCA resulted in reafferentation of the medial, ulnar, and radial nerves serving hand somatosensation and motor function. We used magnetoencephalography (MEG) to assess somatosensory cortical plasticity following the post-transplantation recovery of the peripheral sensory nerves of the hands. Our 2-year postoperative MEG showed that somatosensory lip representations, initially observed at "hand areas", reverted to canonical, orthotopic lip locations with recovery of post-transplant hand function. Here, we continue the assessment of motor and somatosensory responses up to 6-years post-transplant. Magnetoencephalographic somatosensory responses were recorded eight times over a six-year period following hand transplantation, using a 275-channel MEG system. Somatosensory tactile stimuli were presented to the right lower lip (all 8 visits) as well as right and left index fingers (visits 3-8) and fifth digits (visits 4-8). In addition, left and right-hand motor responses were also recorded for left index finger and right thumb (visit 8 only).During the acute recovery phase (visits 3 and 4), somatosensory responses of the digits were observed to be significantly larger and more phasic (i.e., smoother) than controls. Subsequent measures showed that digit responses maintain this atypical response profile (evoked-response magnitudes typically exceed 1 picoTesla). Orthotopic somatosensory localization of the lip, D2, and D5 was preserved. Motor beta-band desynchrony was age-typical in localization and response magnitude; however, the motor gamma-band response was significantly larger than that observed in a reference population.These novel findings show that the restoration of somatosensory input of the hands resulted in persistent and atypically large cortical responses to digit stimulation, which remain atypically large at 6 years post-transplant; there is no known perceptual correlate, and no reports of phantom pain. Normal somatosensory organization of the lip, D2, and D5 representation remain stable following post-recovery reorganization of the lip's somatosensory response.

Magnetoencephalography (MEG) is particularly well-suited to the study of human motor cortex oscillatory rhythms and motor control. However, the motor tasks studied to date are largely overly simplistic. This study describes a new approach: a novel event-based simulated drive made operational via MEG compatible driving simulator hardware, paired with differential beamformer methods to characterize the neural correlates of realistic, complex motor activity. We scanned 23 healthy individuals aged 16-23 years (mean age = 19.5, SD = 2.5; 18 males and 5 females, all right-handed) who completed a custom-built repeated trials driving scenario. MEG data were recorded with a 275-channel CTF, and a volumetric magnetic resonance imaging scan was used for MEG source localization. To validate this paradigm, we hypothesized that pedal-use would elicit expected modulation of primary motor responses beta-event-related desynchronization (B-ERD) and movement-related gamma synchrony (MRGS). To confirm the added utility of this paradigm, we hypothesized that the driving task could also probe frontal cognitive control responses (specifically, frontal midline theta [FMT]). Three of 23 participants were removed due to excess head motion (>1.5 cm/trial), confirming feasibility. Nonparametric group analysis revealed significant regions of pedal-use related B-ERD activity (at left precentral foot area, as well as bilateral superior parietal lobe: p < .01 corrected), MRGS (at medial precentral gyrus: p < .01 corrected), and FMT band activity sustained around planned braking (at bilateral superior frontal gyrus: p < .01 corrected). This paradigm overcomes the limits of previous efforts by allowing for characterization of the neural correlates of realistic, complex motor activity in terms of brain regions, frequency bands and their dynamic temporal interplay.

Epilepsy is a highly heterogeneous neurological disorder with variable etiology, manifestation, and response to treatment. It is imperative that new models of epileptiform brain activity account for this variability, to identify individual needs and allow clinicians to curate personalized care. Here, we use a hidden Markov model (HMM) to create a unique statistical model of interictal brain activity for 10 pediatric patients. We use magnetoencephalography (MEG) data acquired as part of standard clinical care for patients at the Children's Hospital of Philadelphia. These data are routinely analyzed using excess kurtosis mapping (EKM); however, as cases become more complex (extreme multifocal and/or polymorphic activity), they become harder to interpret with EKM. We assessed the performance of the HMM against EKM for three patient groups, with increasingly complicated presentation. The difference in localization of epileptogenic foci for the two methods was 7 +/- 2 mm (mean +/- SD over all 10 patients); and 94% +/- 13% of EKM temporal markers were matched by an HMM state visit. The HMM localizes epileptogenic areas (in agreement with EKM) and provides additional information about the relationship between those areas. A key advantage over current methods is that the HMM is a data-driven model, so the output is tuned to each individual. Finally, the model output is intuitive, allowing a user (clinician) to review the result and manually select the HMM epileptiform state, offering multiple advantages over previous methods and allowing for broader implementation of MEG epileptiform analysis in surgical decision-making for patients with intractable epilepsy.

BACKGROUND:The conventional focus on discrete finger movements (i.e., index finger flexion or button-box key presses) has been an effective method to study neuromotor control using magnetoencephalography (MEG). However, this approach is challenging for young children and not possible for some people with physical disability. NEW METHOD:We have developed a novel, interactive MEG compatible reach-to-target task to investigate neuromotor function, specifically for use with young children. We used an infrared touch-screen frame to detect responses to targets presented using custom software. The game can be played using a conventional computer monitor or during MEG recordings via projector. We termed this game the Target-Touch Motor Task (TTMT). RESULTS:We demonstrate that the TTMT is a feasible motor task for use with young children including children with physical impairments. TTMT response-to-target trial counts are also comparable to conventional methods. Artifacts from the touch screen, while present &gt; 100 Hz, did not affect MEG source analysis in the beta band (14-30 Hz). MEG responses during TTMT game play reveal robust cortical activity from expected areas of motor cortex as typically observed following movements of the upper limb. COMPARISON WITH EXISTING METHOD(S):The TTMT paradigm allows participation by individuals with a broad range of motor abilities on a reach-to-target' functional task rather than conventional tasks focusing on discrete finger movements. CONCLUSIONS:The TTMT is well suited for young children and successfully activates expected motor cortical areas. The TTMT opens-up new opportunities for the assessment of motor function across the lifespan, including for children with physical limitations.

IntroductionDrug development for neurodegenerative diseases such as Friedreich's ataxia (FRDA) is limited by a lack of validated, sensitive biomarkers of pharmacodynamic response in affected tissue and disease progression. Studies employing neuroimaging measures to track FRDA have thus far been limited by their small sample sizes and limited follow up. TRACK-FA, a longitudinal, multi-site, and multi-modal neuroimaging natural history study, aims to address these shortcomings by enabling better understanding of underlying pathology and identifying sensitive, clinical trial ready, neuroimaging biomarkers for FRDA.Methods200 individuals with FRDA and 104 control participants will be recruited across seven international study sites. Inclusion criteria for participants with genetically confirmed FRDA involves, age of disease onset ≤ 25 years, Friedreich's Ataxia Rating Scale (FARS) functional staging score of ≤ 5, and a total modified FARS (mFARS) score of ≤ 65 upon enrolment. The control cohort is matched to the FRDA cohort for age, sex, handedness, and years of education. Participants will be evaluated at three study visits over two years. Each visit comprises of a harmonized multimodal Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) scan of the brain and spinal cord; clinical, cognitive, mood and speech assessments and collection of a blood sample. Primary outcome measures, informed by previous neuroimaging studies, include measures of: spinal cord and brain morphometry, spinal cord and brain microstructure (measured using diffusion MRI), brain iron accumulation (using Quantitative Susceptibility Mapping) and spinal cord biochemistry (using MRS). Secondary and exploratory outcome measures include clinical, cognitive assessments and blood biomarkers.DiscussionPrioritising immediate areas of need, TRACK-FA aims to deliver a set of sensitive, clinical trial-ready neuroimaging biomarkers to accelerate drug discovery efforts and better understand disease trajectory. Once validated, these potential pharmacodynamic biomarkers can be used to measure the efficacy of new therapeutics in forestalling disease progression.Clinical trial registrationClinicalTrails.gov Identifier: NCT04349514.

Magnetoencephalography, the extracranial detection of tiny magnetic fields emanating from intracranial electrical activity of neurons, and its source modeling relation, magnetic source imaging, represent a powerful functional neuroimaging technique, able to detect and localize both spontaneous and evoked activity of the brain in health and disease. Recent years have seen an increased utilization of this technique for both clinical practice and research, in the United States and worldwide. This report summarizes current thinking, presents recommendations for clinical implementation, and offers an outlook for emerging new clinical indications.

This chapter examines clinical motor mapping with magnetoencephalography (MEG). Motor cortex functional mapping procedures were first conducted by neurosurgeons who famously stimulated their patient’s exposed brain during surgery and then systematically documented the responses observed from the activated muscles of the body. Numerous neuroimaging-based functional mapping techniques followed, such as functional magnetic resonance imaging (fMRI), transcranial magnetic stimulation (TMS), high-density electroencephalography (HD-EEG), and MEG, which are currently used to map the motor areas in relation to isolated volitional movements. The use of MEG for presurgical functional mapping has become a standard component of clinical MEG practice. Indeed, knowledge regarding the location of eloquent MEG motor representations is valuable for presurgical planning and can improve outcomes by limiting the production of postsurgical deficits of motor function. Meanwhile, source localization challenges using equivalent current dipole (ECD) models have given way to newer methods, such as beamformer spatial filters, which have been validated clinically using electrical stimulation. It should also be noted that it is becoming increasingly evident that motor cortical oscillations are changing consistently over the life span, and thus consideration of the patient’s age will likely aid the interpretation of results.

Wednesday, April 29April 14, 2020Free AccessAnterior and Posterior Visual Pathway Injury in Pediatric-Onset Multiple Sclerosis as Measured by Visual Evoked Potentials and Magnetoencephalography (4782)John Sollee, Ritobrato Datta, Amy Lavery, Geraldine Liu, Brenda Banwell, William Gaetz, and Amy WaldmanAuthors Info & AffiliationsApril 14, 2020 issue94 (15_supplement)https://doi.org/10.1212/WNL.94.15_supplement.4782 Letters to the Editor

We have previously demonstrated that pediatric-onset multiple sclerosis (POMS) negatively impacts the visual pathway as well as motor processing speed. Relationships between MS-related diffuse structural damage of gray and white matter (WM) tissue and cortical responses to visual and motor stimuli remain poorly understood. We used magnetoencephalography in 14 POMS patients and 15 age- and sex-matched healthy controls to assess visual gamma (30-80 Hz), motor gamma (60-90 Hz), and motor beta (15-30 Hz) cortical oscillatory responses to a visualmotor task. Then, 3T MRI was used to: (a) calculate fractional anisotropy (FA) of the posterior visual and corticospinal motor WM pathways and (b) quantify volume and thickness of the cuneus and primary motor cortex. Visual gamma band power was reduced in POMS and was associated with reduced FA of the optic radiations but not with loss of cuneus volume or thickness. Activity in the primary motor cortex, as measured by postmovement beta rebound amplitude associated with peak latency, was decreased in POMS, although this reduction was not predicted by structural metrics. Our findings implicate loss of WM integrity as a contributor to reduced electrical responses in the visual cortex in POMS. Future work in larger cohorts will inform on the cognitive implications of this finding in terms of visual processing function and will determine whether the progressive loss of brain volume known to occur in POMS ultimately contributes to both progressive dysfunction in such tasks as well as progressive reduction in cortical electrical responses in the visual cortex.

Autism spectrum disorder (ASD) is primarily characterized by impairments in social communication and the appearance of repetitive behaviors with restricted interests. Increasingly, evidence also points to a general deficit of motor tone and coordination in children and adults with ASD; yet the neural basis of motor functional impairment in ASD remains poorly characterized. In this study, we used magnetoencephalography (MEG) to (1) assess potential group differences between typically developing (TD) and ASD participants in motor cortical oscillatory activity observed on a simple button-press task and (2) to do so over a sufficiently broad age-range so as to capture age-dependent changes associated with development. Event-related desynchronization was evaluated in Mu (8-13 Hz) and Beta (15-30 Hz) frequency bands (Mu-ERD, Beta-ERD). In addition, post-movement Beta rebound (PMBR), and movement-related gamma (60-90 Hz) synchrony (MRGS) were also assessed in a cohort of 123 participants (63 typically developing (TD) and 59 with ASD) ranging in age from 8 to 24.9 years. We observed significant age-dependent linear trends in Beta-ERD and MRGS power with age for both TD and ASD groups; which did not differ significantly between groups. However, for PMBR, in addition to a significant effect of age, we also observed a significant reduction in PMBR power in the ASD group (p < 0.05). Post-hoc tests showed that this omnibus group difference was driven by the older cohort of children >13.2 years (p <0.001) and this group difference was not observed when assessing PMBR activity for the younger PMBR groups (ages 8-13.2 years; p = 0.48). Moreover, for the older ASD cohort, hierarchical regression showed a significant relationship between PMBR activity and clinical scores of ASD severity (Social Responsiveness Scale (SRS T scores)), after regressing out the effect of age (p < 0.05). Our results show substantial age-dependent changes in motor cortical oscillations (Beta-ERD and MRGS) occur for both TD and ASD children and diverge only for PMBR, and most significantly for older adolescents and adults with ASD. While the functional significance of PMBR and reduced PMBR signaling remains to be fully elucidated, these results underscore the importance of considering age as a factor when assessing motor cortical oscillations and group differences in children with ASD.

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that provides whole-head measures of neural activity with millisecond temporal resolution. Over the last three decades, MEG has been used for assessing brain activity, most commonly in adults. MEG has been used less often to examine neural function during early development, in large part due to the fact that infant whole-head MEG systems have only recently been developed. In this review, an overview of infant MEG studies is provided, focusing on the period from birth to three years. The advantages of MEG for measuring neural activity in infants are highlighted (See Box 1), including the ability to assess activity in brain (source) space rather than sensor space, thus allowing direct assessment of neural generator activity. Recent advances in MEG hardware and source analysis are also discussed. As the review indicates, efforts in this area demonstrate that MEG is a promising technology for studying the infant brain. As a noninvasive technology, with emerging hardware providing the necessary sensitivity, an expected deliverable is the capability for longitudinal infant MEG studies evaluating the developmental trajectory (maturation) of neural activity. It is expected that departures from neuro-typical trajectories will offer early detection and prognosis insights in infants and toddlers at-risk for neurodevelopmental disorders, thus paving the way for early targeted interventions.

Objective To assess with magnetoencephalography the developmental vs progressive character of the impairment of spinocortical proprioceptive pathways in Friedreich ataxia (FRDA). Methods Neuromagnetic signals were recorded from 16 right-handed patients with FRDA (9 female patients, mean age 27 years, mean Scale for the Assessment and Rating Of ataxia [SARA] score 22.25) and matched healthy controls while they performed right finger movements either actively or passively. The coupling between movement kinematics (i.e., acceleration) and neuromagnetic signals was assessed by the use of coherence at sensor and source levels. Such coupling, that is, the corticokinematic coherence (CKC), specifically indexes proprioceptive afferent inputs to the contralateral primary sensorimotor (cSM1) cortex. Nonparametric permutations and Spearman rank correlation test were used for statistics. Results In both groups of participants and movement conditions, significant coupling peaked at the cSM1 cortex. Coherence levels were 70% to 75% lower in patients with FRDA than in healthy controls in both movement conditions. In patients with FRDA, coherence levels correlated with genotype alteration (i.e., the size of GAA1 triplet expansion) and the age at symptom onset but not with disease duration or SARA score. Conclusion This study provides electrophysiologic evidence demonstrating that proprioceptive impairment in FRDA is mostly genetically determined and scarcely progressive after symptom onset. It also positions CKC as a reliable, robust, specific marker of proprioceptive impairment in FRDA.

Objective: Resective surgery is the most effective treatment option for patients with refractory epilepsy; however identification of patients who will benefit from epilepsy surgery remains challenging. Synthetic aperture magnetometry and excess kurtosis mapping (SAM(g2)) of magnetoencephalography (MEG) is a non-invasive tool that warrants further examination in the pediatric epilepsy population. Here, we examined the utility of MEG with SAM(g2) to determine if MEG epileptiform foci correlates with surgical outcome and to develop a predictive model incorporating MEG information to best assess likelihood of seizure improvement/freedom from resective surgery. Methods: 564 subjects who had MEG at the Children's Hospital of Philadelphia between 2010-2015 were screened. Clinical epilepsy history and prior electrographic records were extracted and reviewed and correlated with MEG findings. MEG assessments were made by both a neurologist and neuroradiologist. Predictive models were developed to assess the utility of MEG in determining Engel class at one year and five years after resective epilepsy surgery. Results: The number of MEG spike foci was highly associated with Engel class outcome at both one year and five years; however, using MEG data in isolation was not significantly predictive of 5 year surgical outcome. When combined with clinical factors; scalp EEG (single ictal onset zone), MRI (lesional or not), age and sex in a logistic regression model MEG foci was significant for Engel class outcome at both 1 year (p = 0.03) and 5 years (0.02). The percent correctly classified for Engel class at one year was 78.43% and the positive predictive value was 71.43. Significance: MEG using SAM(g2) analysis in an important non-invasive tool in the identification of those patients who will benefit most from surgery. Integrating MEG data analysis into pre-surgical evaluation can help to predict epilepsy outcome after resective surgery in the pediatric population if utilized with skilled interpretation.