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Objective: To investigate cortical oscillations during a sentence completion task (SC) using magnetoencephalography (MEG), focusing on the semantic control network (SCN), its leftward asymmetry, and the effects of semantic control load., Methods: Twenty right-handed adults underwent MEG while performing SC, consisting of low cloze (LC: multiple responses) and high cloze (HC: single response) stimuli. Spectrotemporal power modulations as event-related synchronizations (ERS) and desynchronizations (ERD) were analyzed: first, at the whole-brain level; second, in key SCN regions, posterior middle/inferior temporal gyri (pMTG/ITG) and inferior frontal gyri (IFG), under different semantic control loads., Results: Three cortical response patterns emerged: early (0-200 ms) theta-band occipital ERS; intermediate (200-700 ms) semantic network alpha/beta-band ERD; late (700-3000 ms) dorsal language stream alpha/beta/gamma-band ERD. Under high semantic control load (LC), pMTG/ITG showed prolonged left-sided engagement (ERD) and right-sided inhibition (ERS). Left IFG exhibited heightened late (2500-2550 ms) beta-band ERD with increased semantic control load (LC vs. HC)., Conclusions: SC involves distinct cortical responses and depends on the left IFG and asymmetric engagement of the pMTG/ITG for semantic control., Significance: Future use of SC in neuromagnetic preoperative language mapping and for understanding the pathophysiology of language disorders in neurological conditions., (Copyright © 2024 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Voluntary motor control is thought to be predicated on the ability to efficiently integrate and process somatosensory afferent information. However, current approaches in the field of motor control have not factored in objective markers of how the brain tracks incoming somatosensory information. Here, we asked whether motor performance relates to such markers obtained with an analysis of the coupling between peripheral kinematics and cortical oscillations during continuous movements, best known as corticokinematic coherence (CKC). Motor performance was evaluated by measuring both gross and fine motor skills using the Box and Blocks Test (BBT) and the Purdue Pegboard Test (PPT), respectively, and with a biomechanics measure of coordination. A total of 61 participants completed the BBT, while equipped with electroencephalography and electromyography, and the PPT. We evaluated CKC, from the signals collected during the BBT, as the coherence between movement rhythmicity and brain activity, and coordination as the cross-correlation between muscle activity. CKC at movements' first harmonic was positively associated with BBT scores ( r  = 0.41, p  = 0.001), and alone showed no relationship with PPT scores ( r  = 0.07, p  = 0.60), but in synergy with BBT scores, participants with lower PPT scores had higher CKC than expected based on their BBT score. Coordination was not associated with motor performance or CKC ( p  > 0.05). These findings demonstrate that cortical somatosensory processing in the form of strengthened brain-peripheral coupling is specifically associated with better gross motor skills and thus may be considered as a valuable addition to classical tests of proprioception acuity., (Copyright © 2024 Mongold et al.)

Objective: To assess the effects to functional connectivity (FC) caused by lesions related to spastic diplegic cerebral palsy (CP) in children and adolescents using multiple imaging modalities., Methods: We used resting state magnetoencephalography (MEG) envelope signals in alpha, beta and gamma ranges and resting state functional magnetic resonance imaging (fMRI) signals to quantify FC between selected sensorimotor regions of interest (ROIs) in 11 adolescents with spastic diplegic cerebral palsy and 24 typically developing controls. Motor performance of the hands was quantified with gross motor, fine motor and kinesthesia tests., Results: In fMRI, participants with CP showed enhanced FC within posterior parietal regions; in MEG, they showed enhanced interhemispheric FC between sensorimotor regions and posterior parietal regions both in alpha and lower beta bands. There was a correlation between the kinesthesia score and fronto-parietal connectivity in the control population., Conclusions: CP is associated with enhanced FC in sensorimotor network. This difference is not correlated with hand coordination performance. The effect of the lesion is likely not fully captured by temporal correlation of ROI signals., Significance: Brain lesions can show as increased temporal correlation of activity between remote brain areas. We suggest this effect is likely separate from typical physiological correlates of functional connectivity., (Copyright © 2023 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Contextual information triggers predictions about the content ("what") of environmental stimuli to update an internal generative model of the surrounding world. However, visual information dynamically changes across time, and temporal predictability ("when") may influence the impact of internal predictions on visual processing. In this magnetoencephalography (MEG) study, we investigated how processing feature specific information ("what") is affected by temporal predictability ("when"). Participants (N = 16) were presented with four consecutive Gabor patches (entrainers) with constant spatial frequency but with variable orientation and temporal onset. A fifth target Gabor was presented after a longer delay and with higher or lower spatial frequency that participants had to judge. We compared the neural responses to entrainers where the Gabor orientation could, or could not be temporally predicted along the entrainer sequence, and with inter-entrainer timing that was constant (predictable), or variable (unpredictable). We observed suppression of evoked neural responses in the visual cortex for predictable stimuli. Interestingly, we found that temporal uncertainty increased expectation suppression. This suggests that in temporally uncertain scenarios the neurocognitive system invests less resources in integrating bottom-up information. Multivariate pattern analysis showed that predictable visual features could be decoded from neural responses. Temporal uncertainty did not affect decoding accuracy for early visual responses, with the feature specificity of early visual neural activity preserved across conditions. However, decoding accuracy was less sustained over time for temporally jittered than for isochronous predictable visual stimuli. These findings converge to suggest that the cognitive system processes visual features of temporally predictable stimuli in higher detail, while processing temporally uncertain stimuli may rely more heavily on abstract internal expectations., Competing Interests: Declaration of Competing Interest The author(s) declare(s) that there is no conflict of interest regarding the publication of this article., (Copyright © 2021. Published by Elsevier Inc.)

During continuous speech listening, brain activity tracks speech rhythmicity at frequencies matching with the repetition rate of phrases (0.2-1.5 Hz), words (2-4 Hz) and syllables (4-8 Hz). Here, we evaluated the applicability of wearable MEG based on optically-pumped magnetometers (OPMs) to measure such cortical tracking of speech (CTS). Measuring CTS with OPMs is a priori challenging given the complications associated with OPM measurements at frequencies below 4 Hz, due to increased intrinsic interference and head movement artifacts. Still, this represents an important development as OPM-MEG provides lifespan compliance and substantially improved spatial resolution compared with classical MEG. In this study, four healthy right-handed adults listened to continuous speech for 9 min. The radial component of the magnetic field was recorded simultaneously with 45-46 OPMs evenly covering the scalp surface and fixed to an additively manufactured helmet which fitted all 4 participants. We estimated CTS with reconstruction accuracy and coherence, and determined the number of dominant principal components (PCs) to remove from the data (as a preprocessing step) for optimal estimation. We also identified the dominant source of CTS using a minimum norm estimate. CTS estimated with reconstruction accuracy and coherence was significant in all 4 participants at phrasal and word rates, and in 3 participants (reconstruction accuracy) or 2 (coherence) at syllabic rate. Overall, close-to-optimal CTS estimation was obtained when the 3 (reconstruction accuracy) or 10 (coherence) first PCs were removed from the data. Importantly, values of reconstruction accuracy (~0.4 for 0.2-1.5-Hz CTS and ~0.1 for 2-8-Hz CTS) were remarkably close to those previously reported in classical MEG studies. Finally, source reconstruction localized the main sources of CTS to bilateral auditory cortices. In conclusion, t his study demonstrates that OPMs can be used for the purpose of CTS assessment. This finding opens new research avenues to unravel the neural network involved in CTS across the lifespan and potential alterations in, e.g., language developmental disorders. Data also suggest that OPMs are generally suitable for recording neural activity at frequencies below 4 Hz provided PCA is used as a preprocessing step; 0.2-1.5-Hz being the lowest frequency range successfully investigated here., Competing Interests: Declaration of Competing Interest E.B. and M.J.B. are directors of Cerca Magnetics Limited, a newly established spin-out company whose aim is to commercialize aspects of OPM-MEG technology, including the bi-planar coils used for field nulling. E.B., M.J.B., R.B., N.H. and R.M.H. hold founding equity in Cerca Magnetics Limited., (Copyright © 2021. Published by Elsevier Inc.)

The linearly constrained minimum variance beamformer is frequently used to reconstruct sources underpinning neuromagnetic recordings. When reconstructions must be compared across conditions, it is considered good practice to use a single, "common" beamformer estimated from all the data at once. This is to ensure that differences between conditions are not ascribable to differences in beamformer weights. Here, we investigate the localization accuracy of such a common beamformer. Based on theoretical derivations, we first show that the common beamformer leads to localization errors in source reconstruction. We then turn to simulations in which we attempt to reconstruct a (genuine) source in a first condition, while considering a second condition in which there is an (interfering) source elsewhere in the brain. We estimate maps of mislocalization and assess statistically the difference between "standard" and "common" beamformers. We complement our findings with an application to experimental MEG data. The results show that the common beamformer may yield significant mislocalization. Specifically, the common beamformer may force the genuine source to be reconstructed closer to the interfering source than it really is. As the same applies to the reconstruction of the interfering source, both sources are pulled closer together than they are. This observation was further illustrated in experimental data. Thus, although the common beamformer allows for the comparison of conditions, in some circumstances it introduces localization inaccuracies. We recommend alternative approaches to the general problem of comparing conditions., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6-9 years), young adults (18-34 years) and healthy elders (53-78 years). The effects of age on static resting-state functional brain integration were assessed using band-limited power envelope correlation, whereas those on transient functional brain dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (1) a strengthening of functional integration within and between resting-state networks and (2) an increased temporal stability of transient (100-300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamic stability within the primary visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging. These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.

In this article, we present the clinical indications and advances in the use of magnetoencephalography to map the primary sensorimotor (SM1) cortex in neurosurgical patients noninvasively. We emphasize the advantages of magnetoencephalography over sensorimotor mapping using functional magnetic resonance imaging. Recommendations to the referring physicians and the clinical magnetoencephalographers to achieve appropriate sensorimotor cortex mapping using magnetoencephalography are proposed. We finally provide some practical advice for the use of corticomuscular coherence, cortico-kinematic coherence, and mu rhythm suppression in this indication. Magnetoencephalography should now be considered as a method of reference for presurgical functional mapping of the sensorimotor cortex.

How the human brain uses self-generated auditory information during speech production is rather unsettled. Current theories of language production consider a feedback monitoring system that monitors the auditory consequences of speech output and an internal monitoring system, which makes predictions about the auditory consequences of speech before its production. To gain novel insights into underlying neural processes, we investigated the coupling between neuromagnetic activity and the temporal envelope of the heard speech sounds (i.e., cortical tracking of speech) in a group of adults who 1) read a text aloud, 2) listened to a recording of their own speech (i.e., playback), and 3) listened to another speech recording. Reading aloud was here used as a particular form of speech production that shares various processes with natural speech. During reading aloud, the reader's brain tracked the slow temporal fluctuations of the speech output. Specifically, auditory cortices tracked phrases (<1 ​Hz) but to a lesser extent than during the two speech listening conditions. Also, the tracking of words (2-4 ​Hz) and syllables (4-8 ​Hz) occurred at parietal opercula during reading aloud and at auditory cortices during listening. Directionality analyses were then used to get insights into the monitoring systems involved in the processing of self-generated auditory information. Analyses revealed that the cortical tracking of speech at <1 ​Hz, 2-4 ​Hz and 4-8 ​Hz is dominated by speech-to-brain directional coupling during both reading aloud and listening, i.e., the cortical tracking of speech during reading aloud mainly entails auditory feedback processing. Nevertheless, brain-to-speech directional coupling at 4-8 ​Hz was enhanced during reading aloud compared with listening, likely reflecting the establishment of predictions about the auditory consequences of speech before production. These data bring novel insights into how auditory verbal information is tracked by the human brain during perception and self-generation of connected speech., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Magnetoencephalography (MEG) has been used in conjunction with resting-state functional connectivity (rsFC) based on band-limited power envelope correlation to study the intrinsic human brain network organization into resting-state networks (RSNs). However, the limited availability of current MEG systems hampers the clinical applications of electrophysiological rsFC. Here, we directly compared well-known RSNs as well as the whole-brain rsFC connectome together with its state dynamics, obtained from simultaneously-recorded MEG and high-density scalp electroencephalography (EEG) resting-state data. We also examined the impact of head model precision on EEG rsFC estimation, by comparing results obtained with boundary and finite element head models. Results showed that most RSN topographies obtained with MEG and EEG are similar, except for the fronto-parietal network. At the connectome level, sensitivity was lower to frontal rsFC and higher to parieto-occipital rsFC with MEG compared to EEG. This was mostly due to inhomogeneity of MEG sensor locations relative to the scalp and significant MEG-EEG differences disappeared when taking relative MEG-EEG sensor locations into account. The default-mode network was the only RSN requiring advanced head modeling in EEG, in which gray and white matter are distinguished. Importantly, comparison of rsFC state dynamics evidenced a poor correspondence between MEG and scalp EEG, suggesting sensitivity to different components of transient neural functional integration. This study therefore shows that the investigation of static rsFC based on the human brain connectome can be performed with scalp EEG in a similar way than with MEG, opening the avenue to widespread clinical applications of rsFC analyses., (Copyright © 2020. Published by Elsevier Inc.)

Electroencephalographic and magnetoencephalographic data have characterized two types of brain-body interactions observed during various types of motor actions, "corticokinematic" and "corticomuscular" coupling. Here, we review the literature on these interactions in healthy individuals, discuss several open debates, and outline current limitations and directions for future research. Corticokinematic coupling (commonly referred to as corticokinematic coherence) probes the relationship between activity of sensorimotor network nodes and various movement-related signals (e.g., speed, velocity, acceleration). It is mainly driven by movement rhythmicity during active, passive, and observed dynamic motor actions. It typically predominates at the primary sensorimotor cortex contralateral to the moving limb, occurs at movement frequency and its harmonics, and predominantly reflects the cortical processing of proprioceptive feedback driven by movement rhythmicity in a broad range of dynamic motor actions. Corticomuscular coupling (commonly referred to as corticomuscular coherence) probes the interaction between sensorimotor cortical rhythms and electromyographic (EMG) activity that mainly occurs during steady isometric muscle contraction. We will here focus on the ~20-Hz coupling that is observed during weak isometric contraction and is linked to the modulation of the descending motor command by the ~20-Hz sensorimotor rhythm. This review argues that corticokinematic and corticomuscular couplings have different neural bases. Corticokinematic coupling is mainly driven by afferent signals, while corticomuscular coupling is mainly (but not solely) driven by efferent signals. This distinction should be considered when investigating interactions between brain and body movements., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The human brain is functionally organized into large-scale neural networks that are dynamically interconnected. Multiple short-lived states of resting-state functional connectivity (rsFC) identified transiently synchronized networks and cross-network integration. However, little is known about the way brain couplings covary as rsFC states wax and wane. In this magnetoencephalography study, we explore the synchronization structure among the spontaneous interactions of well-known resting-state networks (RSNs). To do so, we extracted modes of dynamic coupling that reflect rsFC synchrony and analyzed their spatio-temporal features. These modes identified transient, sporadic rsFC changes characterized by the widespread integration of RSNs across the brain, most prominently in the β band. This is in line with the metastable rsFC state model of resting-state dynamics, wherein our modes fit as state transition processes. Furthermore, the default-mode network (DMN) stood out as being structured into competitive cross-network couplings with widespread DMN-RSN interactions, especially among the β-band modes. These results substantiate the theory that the DMN is a core network enabling dynamic global brain integration in the β band., (Copyright © 2019 Elsevier Inc. All rights reserved.)

During connected speech listening, brain activity tracks speech rhythmicity at delta (∼0.5 Hz) and theta (4-8 Hz) frequencies. Here, we compared the potential of magnetoencephalography (MEG) and high-density electroencephalography (EEG) to uncover such speech brain tracking. Ten healthy right-handed adults listened to two different 5-min audio recordings, either without noise or mixed with a cocktail-party noise of equal loudness. Their brain activity was simultaneously recorded with MEG and EEG. We quantified speech brain tracking channel-by-channel using coherence, and with all channels at once by speech temporal envelope reconstruction accuracy. In both conditions, speech brain tracking was significant at delta and theta frequencies and peaked in the temporal regions with both modalities (MEG and EEG). However, in the absence of noise, speech brain tracking estimated from MEG data was significantly higher than that obtained from EEG. Furthemore, to uncover significant speech brain tracking, recordings needed to be ∼3 times longer in EEG than MEG, depending on the frequency considered (delta or theta) and the estimation method. In the presence of noise, both EEG and MEG recordings replicated the previous finding that speech brain tracking at delta frequencies is stronger with attended speech (i.e., the sound subjects are attending to) than with the global sound (i.e., the attended speech and the noise combined). Other previously reported MEG findings were replicated based on MEG but not EEG recordings: 1) speech brain tracking at theta frequencies is stronger with attended speech than with the global sound, 2) speech brain tracking at delta frequencies is stronger in noiseless than noisy conditions, and 3) when noise is added, speech brain tracking at delta frequencies dampens less in the left hemisphere than in the right hemisphere. Finally, sources of speech brain tracking reconstructed from EEG data were systematically deeper and more posterior than those derived from MEG. The present study demonstrates that speech brain tracking is better seen with MEG than EEG. Quantitatively, EEG recordings need to be ∼3 times longer than MEG recordings to uncover significant speech brain tracking. As a consequence, MEG appears more suited than EEG to pinpoint subtle effects related to speech brain tracking in a given recording time., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Prediction has been proposed to be a fundamental neurocognitive mechanism. However, its role in language comprehension is currently under debate. In this magnetoencephalography study we aimed to find evidence of word-form phonological pre-activation and to characterize the oscillatory mechanisms supporting this. Participants were presented firstly with a picture of an object, and then, after a delay (fixed or variable), they heard the corresponding word. Target words could contain a phoneme substitution, and participants' task was to detect mispronunciations. Word-initial phonemes were either fricatives or plosives, generating two experimental conditions (expect-fricative and expect-plosive). In the pre-word interval, significant differences (α = 0.05) emerged between conditions both for fixed and variable delays. Source reconstruction of this effect showed a brain-wide network involving several frequency bands, including bilateral superior temporal areas commonly associated with phonological processing, in a theta range. These results show that phonological representations supported by the theta band may be active before word onset, even under temporal uncertainty. However, in the evoked response just prior to the word, differences between conditions were apparent under variable- but not fixed-delays. This suggests that additional top-down mechanisms sensitive to phonological form may be recruited when there is uncertainty in the signal.

In the field of neuroimaging, researchers often resort to contrasting parametric maps to identify differences between conditions or populations. Unfortunately, contrast patterns mix effects related to amplitude and location differences and tend to peak away from sources of genuine brain activity to an extent that scales with the smoothness of the maps. Here, we illustrate this mislocation problem on source maps reconstructed from magnetoencephalographic recordings and propose a novel, dedicated location-comparison method. In realistic simulations, contrast mislocation was on average ∼10 mm when genuine sources were placed at the same location, and was still above 5 mm when sources were 20 mm apart. The dedicated location-comparison method achieved a sensitivity of ∼90% when inter-source distance was 12 mm. Its benefit is also illustrated on real brain-speech entrainment data. In conclusion, contrasts of parametric maps provide precarious information for source location. To specifically address the question of location difference, one should turn to dedicated methods as the one proposed here., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

To gain fundamental knowledge on how the brain controls motor actions, we studied in detail the interplay between MEG signals from the primary sensorimotor (SM1) cortex and the contraction force of 17 healthy adult humans (7 females, 10 males). SM1 activity was coherent at ∼20 Hz with surface electromyogram (as already extensively reported) but also with contraction force. In both cases, the effective coupling was dominant in the efferent direction. Across subjects, the level of ∼20 Hz coherence between cortex and periphery positively correlated with the "burstiness" of ∼20 Hz SM1 (Pearson r ≈ 0.65) and peripheral fluctuations ( r ≈ 0.9). Thus, ∼20 Hz coherence between cortex and periphery is tightly linked to the presence of ∼20 Hz bursts in SM1 and peripheral activity. However, the very high correlation with peripheral fluctuations suggests that the periphery is the limiting factor. At frequencies <3 Hz, both SM1 signals and ∼20 Hz SM1 envelope were coherent with both force and its absolute change rate. The effective coupling dominated in the efferent direction between (1) force and the ∼20 Hz SM1 envelope and (2) the absolute change rate of the force and SM1 signals. Together, our data favor the view that ∼20 Hz coherence between cortex and periphery during isometric contraction builds on the presence of ∼20 Hz SM1 oscillations and needs not rely on feedback from the periphery. They also suggest that effective cortical proprioceptive processing operates at <3 Hz frequencies, even during steady isometric contractions. SIGNIFICANCE STATEMENT Accurate motor actions are made possible by continuous communication between the cortex and spinal motoneurons, but the neurophysiological basis of this communication is poorly understood. Using MEG recordings in humans maintaining steady isometric muscle contractions, we found evidence that the cortex sends population-level motor commands that tend to structure according to the ∼20 Hz sensorimotor rhythm, and that it dynamically adapts these commands based on the <3 Hz fluctuations of proprioceptive feedback. To our knowledge, this is the first report to give a comprehensive account of how the human brain dynamically handles the flow of proprioceptive information and converts it into appropriate motor command to keep the contraction force steady., (Copyright © 2017 Bourguignon et al.)

Objective: Corticokinematic coherence (CKC) is the coupling between magnetoencephalographic (MEG) signals and limb kinematics during fast movements. Our objective was to assess the robustness of CKC-based identification of the primary sensorimotor (SM1) cortex of subjects producing strong magnetic artifacts when the MEG signals were cleaned with temporal signal space separation (tSSS)., Methods: We recorded MEG during active and passive forefinger movements and during median-nerve stimulation in the following conditions: (1) artifact-free, (2) a magnetic wire attached to the scalp at C3 location, and (3) a magnetic wire attached behind the lower central incisors. Data were pre-processed with tSSS and analyzed using standard CKC methods, somatosensory evoked fields (SEFs), and dipole modeling., Result: Artifacts were effectively suppressed by tSSS, enabling successful identification of the SM1 cortex in all subjects based on CKC and SEFs. The sources were in artifact conditions ∼5 mm away from the sources identified in artifact-free conditions., Conclusion: tSSS suppressed artifacts strongly enough to enable reliable identification of the SM1 cortex on the basis of CKC mapping, with localization accuracy comparable to SEF-based mapping., Significance: The results suggest that CKC can be used for SM1 cortex identification and for studies of proprioception even in patients implanted with magnetic material., (Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Spatial leakage effects are particularly confounding for seed-based investigations of brain networks using source-level electroencephalography (EEG) or magnetoencephalography (MEG). Various methods designed to avoid this issue have been introduced but are limited to particular assumptions about its temporal characteristics. Here, we investigate the usefulness of a model-based geometric correction scheme (GCS) to suppress spatial leakage emanating from the seed location. We analyze its properties theoretically and then assess potential advantages and limitations with simulated and experimental MEG data (resting state and auditory-motor task). To do so, we apply Minimum Norm Estimation (MNE) for source reconstruction and use variation of error parameters, statistical gauging of spatial leakage correction and comparison with signal orthogonalization. Results show that the GCS has a local (i.e., near the seed) effect only, in line with the geometry of MNE spatial leakage, and is able to map spatially all types of brain interactions, including linear correlations eliminated after signal orthogonalization. Furthermore, it is robust against the introduction of forward model errors. On the other hand, the GCS can be affected by local overcorrection effects and seed mislocation. These issues arise with signal orthogonalization too, although significantly less extensively, so the two approaches complement each other. The GCS thus appears to be a valuable addition to the spatial leakage correction toolkits for seed-based FC analyses in source-projected MEG/EEG data., (© 2015 Wiley Periodicals, Inc.)

Cortex-muscle coherence (CMC) reflects coupling between magnetoencephalography (MEG) and surface electromyography (sEMG), being strongest during isometric contraction but absent, for unknown reasons, in some individuals. We used a novel nonmagnetic high-density sEMG (HD-sEMG) electrode grid (36 mm × 12 mm; 60 electrodes separated by 3 mm) to study effects of sEMG recording site, electrode derivation, and rectification on the strength of CMC. Monopolar sEMG from right thenar and 306-channel whole-scalp MEG were recorded from 14 subjects during 4-min isometric thumb abduction. CMC was computed for 60 monopolar, 55 bipolar, and 32 Laplacian HD-sEMG derivations, and two derivations were computed to mimic "macroscopic" monopolar and bipolar sEMG (electrode diameter 9 mm; interelectrode distance 21 mm). With unrectified sEMG, 12 subjects showed statistically significant CMC in 91-95% of the HD-sEMG channels, with maximum coherence at ∼25 Hz. CMC was about a fifth stronger for monopolar than bipolar and Laplacian derivations. Monopolar derivations resulted in most uniform CMC distributions across the thenar and in tightest cortical source clusters in the left rolandic hand area. CMC was 19-27% stronger for HD-sEMG than for "macroscopic" monopolar or bipolar derivations. EMG rectification reduced the CMC peak by a quarter, resulted in a more uniformly distributed CMC across the thenar, and provided more tightly clustered cortical sources than unrectifed sEMGs. Moreover, it revealed CMC at ∼12 Hz. We conclude that HD-sEMG, especially with monopolar derivation, can facilitate detection of CMC and that individual muscle anatomy cannot explain the high interindividual CMC variability., (Copyright © 2015 the American Physiological Society.)

Magnetoencephalographic (MEG) signals recorded from the primary sensorimotor (SM1) cortex are coherent with kinematics of both active and passive finger movements. The coherence mainly reflects movement-related proprioceptive afference to the cortex. Here we describe a novel MEG-compatible stimulator to generate computer-controlled passive finger and toe movements that can be used as stimuli in functional brain-imaging experiments. The movements are produced by pneumatic artificial muscle (PAM), elastic actuator that shortens with increasing air pressure. To test the applicability of the stimulator to functional brain-imaging, 4-min trains of passive repetitive 5-mm flexion-extension movements of the right and left index finger and the right hallux were produced at 3Hz while the subject's brain activity was measured with whole-scalp MEG and finger or toe kinematics with an accelerometer. In all ten subjects studied, statistically significant coherence (up to 0.78) occurred between the accelerometer and MEG signals at the movement frequency or its first harmonic. Sources of coherent activity were in the contralateral hand or foot SM1 cortices. Movement-evoked fields elicited with intermittent movements of the right index finger (once every 3.2-4.0s; mean±SD peak response latency 88±25ms) were co-located with the respective coherent sources. We further moved the right index finger at 3, 6, and 12Hz (movement ranges 5, 3, and 2mm, respectively), and analyzed the first 1, 2, and 4-min epochs of data. One minute of data was sufficient to locate the left hand area of the SM1 cortex at all movement frequencies. Sound-induced spurious coherence was reliably ruled out in a control experiment. Our novel movement stimulator thus provides a robust and reliable tool to track proprioceptive afference to the cortex and to locate the SM1 cortex., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Functional connectivity studies conducted at the group level using magnetoencephalography (MEG) suggest that resting state networks (RSNs) emerge from the large-scale envelope correlation structure within spontaneous oscillatory brain activity. However, little is known about the consistency of MEG RSNs at the individual level. This paper investigates the inter- and intra-subject variability of three MEG RSNs (sensorimotor, auditory and visual) using seed-based source space envelope correlation analysis applied to 5 min of resting state MEG data acquired from a 306-channel whole-scalp neuromagnetometer (Elekta Oy, Helsinki, Finland) and source projected with minimum norm estimation. The main finding is that these three MEG RSNs exhibit substantial variability at the single-subject level across and within individuals, which depends on the RSN type, but can be reduced after averaging over subjects or sessions. Over- and under-estimations of true RSNs variability are respectively obtained using template seeds, which are potentially mislocated due to inter-subject variations, and a seed optimization method minimizing variability. In particular, bounds on the minimal number of subjects or sessions required to obtain highly consistent between- or within-subject averages of MEG RSNs are derived. Furthermore, MEG RSN topography positively correlates with their mean connectivity at the inter-subject level. These results indicate that MEG RSNs associated with primary cortices can be robustly extracted from seed-based envelope correlation and adequate averaging. MEG thus appears to be a valid technique to compare RSNs across subjects or conditions, at least when using the current methods.

Learning the functional properties of objects is a core mechanism in the development of conceptual, cognitive and linguistic knowledge in children. The cerebral processes underlying these learning mechanisms remain unclear in adults and unexplored in children. Here, we investigated the neurophysiological patterns underpinning the learning of functions for novel objects in 10-year-old healthy children. Event-related fields (ERFs) were recorded using magnetoencephalography (MEG) during a picture-definition task. Two MEG sessions were administered, separated by a behavioral verbal learning session during which children learned short definitions about the "magical" function of 50 unknown non-objects. Additionally, 50 familiar real objects and 50 other unknown non-objects for which no functions were taught were presented at both MEG sessions. Children learned at least 75% of the 50 proposed definitions in less than one hour, illustrating children's powerful ability to rapidly map new functional meanings to novel objects. Pre- and post-learning ERFs differences were analyzed first in sensor then in source space. Results in sensor space disclosed a learning-dependent modulation of ERFs for newly learned non-objects, developing 500-800 msec after stimulus onset. Analyses in the source space windowed over this late temporal component of interest disclosed underlying activity in right parietal, bilateral orbito-frontal and right temporal regions. Altogether, our results suggest that learning-related evolution in late ERF components over those regions may support the challenging task of rapidly creating new semantic representations supporting the processing of the meaning and functions of novel objects in children.

Objective: To assess the interictal epileptic discharges (IEDs) detection rate of magnetoencephalography (MEG) recordings performed in a new light-weight magnetic shielding (LMSR) concept in a large group of consecutive patients with presumed mesiotemporal lobe epilepsy (MTLE)., Methods: Thirty-eight patients (23 women; age range: 6-63 years) with presumed MTLE were prospectively studied. MEG investigations were performed with the 306-channel Elekta Neuromag® MEG-system installed in a normal hospital environment into a LMSR (MaxShield, Elekta Oy). Equivalent current dipoles (ECD, g/% > 80%) corresponding to epileptic events were fitted to each patient's spherical head model at IEDs onset and peak and then superimposed on the patient's co-registered MRI., Results: IEDs were observed in 26 out of 38 patients (68.4%). Temporal ECDs were mesial in 14 patients, anterior in 23 patients and posterior in 8 patients. Interestingly, in 6 patients, ECDs fitted at spike-onset were localized in the hippocampus while at the peak of the spike, they had an anterior temporal location., Conclusions: MEG using LMSR provides adequate signal to noise ratio (SNR) to allow reliable detection and localization of single epileptic abnormalities on continuous MEG data in 68% of patients with presumed MTLE. Moreover, mesial temporal epileptic sources were detected in 54% of patients with abnormal MEG. The SNR of MEG data acquired using the LMSR is therefore suitable for the non-invasive localization of epileptic foci in patients with MTLE. The use of LMSR, which are cheaper and smaller than conventional MSR, should facilitate the development of MEG in clinical environments., (Copyright © 2011 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.)

Reading epilepsy (RE) is an idiopathic reflex epilepsy syndrome characterized by perioral myoclonic jerks (PMJs) during reading associated with left-dominant frontotemporal spike-wave discharges (SWDs). To better understand the pathophysiology of this syndrome, we studied a 45-year-old patient using magnetic source imaging (MSI). The patient underwent two whole-head magnetoencephalography (MEG) recordings (Elekta Neuromag Oy) within 2 months while reading aloud. Forty-two SWDs associated with PMJs were recorded and averaged with respect to SWDs peak power. Epileptic discharges were then reconstructed using conventional equivalent current dipoles (ECDs) modeling, distributed sources sLORETA modeling, and beamformer approach. These methods identified two brain sources located in the left supplementary motor cortex (SMC) and the left primary sensorimotor face area (PSMFA). The spatiotemporal pattern of the sources was characterized by a cross-talk between these two brain regions, with an initial source in the left SMC. This MSI investigation suggests that RE-PMJs are associated with reading-induced activation of hyperexcitable neurons in the left SMC, followed by secondary propagation to the left PSMFA producing the myoclonus., (Wiley Periodicals, Inc. © 2011 International League Against Epilepsy.)

We present a novel method, corticokinematic coherence (CKC), for functional mapping of the motor cortex by computing coherence between cortical magnetoencephalographic (MEG) signals and the kinematics of voluntary movements. Ten subjects performed self-paced flexion-extensions of the right-hand fingers at about 3 Hz, with a three-axis accelerometer attached to the index finger. Cross-correlogram and coherence spectra were computed between 306 MEG channels and the accelerometer signals. In all subjects, accelerometer and coherence spectra showed peaks around 3-5 Hz and 6-10 Hz, corresponding to the movement frequencies. The coherence was statistically significant (P<0.05) in all subjects, with sources at the hand area of the primary motor cortex contralateral to the movement. CKC appears to be a promising and robust method for reliable and convenient functional mapping of the human motor cortex., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Due to technical constraints, magnetoencephalography (MEG) is challenging in vagus nerve stimulation (VNS) patients. This study evaluates (1) the feasibility of MEG in VNS patients and (2) the added value of MEG in their presurgical evaluation (PE). Ten VNS patients were studied by MEG using the spatiotemporal signal space separation (tSSS) method. Equivalent current dipoles (ECD) were classified "clustered"/"scattered". It was evaluated whether MEG (1) confirmed localisation of the hypothesized epileptogenic zone (HEZ), (2) improved delineation of the HEZ, or (3) identified 1 out of multiple HEZs. Finally it was evaluated whether adding MEG to the PE improved patient management by changing or supporting the hypothesis. In 7/10 patients, tSSS allowed to obtain interpretable MEG data, with interictal epileptiform discharges in 6/7. ECD clustered within 1 lobe in 4/6; confirming the localisation of the HEZ in 2/4 and improving delineation of the HEZ in 2/4. When ECD clustered within 2 lobes (1/6) or were scattered (1/6), MEG could not identify 1 out of multiple HEZs. In 2 patients, MEG changed management to invasive video-EEG monitoring (IVEM) and resective surgery (RS). In 4 patients, MEG further supported the management; IVEM in 2/4 and unsuitability for RS in 2/4. So far IVEM, performed in 2, resulted into RS. This study demonstrates the feasibility of MEG in VNS patients. MEG changed management in 20% and further supported the proposed management in 40% illustrating the clinical value of MEG in the PE of VNS patients., (2010 Elsevier B.V. All rights reserved.)

Magnetoencephalography (MEG) is a functional cerebral imaging technique that non-invasively records extracranial magnetic fields generated by the electrical activity of the brain. Magnetic source imaging (MSI) is a combination of MEG and coregistered magnetic resonance imaging (MRI) that is increasingly being used in the non-invasive presurgical evaluation of patients with refractory partial epilepsy to localize the magnetic correlate of interictal epileptiform discharges. This paper reviews the basics of MEG and MSI, briefly describes the characteristics of the MEG system installed at the ULB-Hôpital Erasme and then summarises the available data on the contribution of MSI to the presurgical work-up of refractory partial epilepsy.

This study investigates whether movement kinematics modulates similarly the rolandic α and β rhythm amplitude during executed and observed goal-directed hand movements. It also assesses if this modulation relates to the corticokinematic coherence (CKC), which is the coupling observed between cortical activity and movement kinematics during such motor actions. Magnetoencephalography (MEG) signals were recorded from 11 right-handed healthy subjects while they performed or observed an actor performing the same repetitive hand pinching action. Subjects’ and actor’s forefinger movements were monitored with an accelerometer. Coherence was computed between acceleration signals and the amplitude of α (8-12 Hz) or β (15-25 Hz) oscillations. The coherence was also evaluated between source-projected MEG signals and their β amplitude. Coherence was mainly observed between acceleration and the amplitude of β oscillations at movement frequency within bilateral primary sensorimotor (SM1) cortex with no difference between executed and observed movements. Cross-correlation between the amplitude of β oscillations at the SM1 cortex and movement acceleration was maximal when acceleration was delayed by ~ 100 ms, both during movement execution and observation. Coherence between source-projected MEG signals and their β amplitude during movement observation and execution was not significantly different from that during rest. This study shows that observing others’ actions engages in the viewer’s brain similar dynamic modulations of SM1 cortex β rhythm as during action execution. Results support the view that different neural mechanisms might account for this modulation and CKC. These two kinematic-related phenomena might help humans to understand how observed motor actions are actually performed. [ABSTRACT FROM AUTHOR]

Summary Aims of the study This study investigates the effect of movement rate on the coupling between cortical magnetoencephalographic (MEG) signals and the kinematics of repetitive active finger movements, i.e., the corticokinematic coherence (CKC). Material and methods CKC was evaluated in ten right-handed healthy adults performing repetitive flexion–extension of the right-hand fingers in three different movement rate conditions: slow (∼1 Hz, duration: 11 min), medium (∼2 Hz, duration: 5 min) and fast (∼3 Hz, duration: 3 min). Neuromagnetic signals were recorded with a whole-scalp-covering MEG (Elekta Oy) and index acceleration was monitored with a 3-axis accelerometer. Coherent sources were estimated on the time-course of the cross-correlogram using equivalent current dipole (ECD) modeling. Results Significant coherence was found at movement frequency or its first harmonics in all subjects and movement conditions. ECDs clustered at the primary sensorimotor cortex contralateral to hand movements. Movement rate had no effect on the coherence levels and the location of coherent sources. Conclusions This study demonstrates that the movement rate does not affect coherence levels and CKC source location during active finger movements. This finding has direct implications for CKC functional mapping applications and studies investigating the pathophysiology of central nervous disorders affecting proprioceptive pathways. [ABSTRACT FROM AUTHOR]

Abstract: Corticokinematic coherence (CKC) refers to coupling between magnetoencephalographic (MEG) brain activity and hand kinematics. For voluntary hand movements, CKC originates mainly from the primary sensorimotor (SM1) cortex. To learn about the relative motor and sensory contributions to CKC, we recorded CKC from 15 healthy subjects during active and passive right index-finger movements. The fingertip was either touching or not touching table, resulting in active-touch, active-no-touch, passive-touch, and passive-no-touch conditions. The kinematics of the index-finger was measured with a 3-axis accelerometer. Beamformer analysis was used to locate brain activations for the movements; somatosensory-evoked fields (SEFs) elicited by pneumatic tactile stimulation of the index finger served as a functional landmark for cutaneous input. All active and passive movements resulted in statistically significant CKC at the movement frequency (F0) and its first harmonic (F1). The main CKC sources at F0 and F1 were in the contralateral SM1 cortex with no spatial differences between conditions, and distinct from the SEF sources. At F1, the coherence was by two thirds stronger for passive than active movements, with no difference between touch vs. no-touch conditions. Our results suggest that the CKC occurring during repetitive finger movements is mainly driven by somatosensory, primarily proprioceptive, afferent input to the SM1 cortex, with negligible effect of cutaneous input. [Copyright &y& Elsevier]