Children have more difficulty perceiving speech in noise than adults. Whether this difficulty relates to an immature processing of prosodic or linguistic elements of the attended speech is still unclear. To address the impact of noise on linguistic processing per se, we assessed how babble noise impacts the cortical tracking of intelligible speech devoid of prosody in school-aged children and adults. Twenty adults and twenty children (7-9 years) listened to synthesized French monosyllabic words presented at 2.5 Hz, either randomly or in 4-word hierarchical structures wherein 2 words formed a phrase at 1.25 Hz, and 2 phrases formed a sentence at 0.625 Hz, with or without babble noise. Neuromagnetic responses to words, phrases and sentences were identified and source-localized. Children and adults displayed significant cortical tracking of words in all conditions, and of phrases and sentences only when words formed meaningful sentences. In children compared with adults, the cortical tracking was lower for all linguistic units in conditions without noise. In the presence of noise, the cortical tracking was similarly reduced for sentence units in both groups, but remained stable for phrase units. Critically, when there was noise, adults increased the cortical tracking of monosyllabic words in the inferior frontal gyri and supratemporal auditory cortices but children did not. This study demonstrates that the difficulties of school-aged children in understanding speech in a multi-talker background might be partly due to an immature tracking of lexical but not supra-lexical linguistic units

Humans' extraordinary ability to understand speech in noise relies on multiple processes that develop with age. Using magnetoencephalography (MEG), we characterize the underlying neuromaturational basis by quantifying how cortical oscillations in 144 participants (aged 5-27 years) track phrasal and syllabic structures in connected speech mixed with different types of noise. While the extraction of prosodic cues from clear speech was stable during development, its maintenance in a multi-talker background matured rapidly up to age 9 and was associated with speech comprehension. Furthermore, while the extraction of subtler information provided by syllables matured at age 9, its maintenance in noisy backgrounds progressively matured until adulthood. Altogether, these results highlight distinct behaviorally relevant maturational trajectories for the neuronal signatures of speech perception. In accordance with grain-size proposals, neuromaturational milestones are reached increasingly late for linguistic units of decreasing size, with further delays incurred by noise.

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.

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.

In multitalker backgrounds, the auditory cortex of adult humans tracks the attended speech stream rather than the global auditory scene. Still, it is unknown whether such preferential tracking also occurs in children whose speech-in-noise (SiN) abilities are typically lower compared with adults. We used magnetoencephalography (MEG) to investigate the frequency-specific cortical tracking of different elements of a cocktail party auditory scene in 20 children (age range, 6–9 years; 8 females) and 20 adults (age range, 21–40 years; 10 females). During MEG recordings, subjects attended to four different 5 min stories, mixed with different levels of multitalker background at four signal-to-noise ratios (SNRs; noiseless, +5, 0, and −5 dB). Coherence analysis quantified the coupling between the time courses of the MEG activity and attended speech stream, multitalker background, or global auditory scene, respectively. In adults, statistically significant coherence was observed between MEG signals originating from the auditory system and the attended stream at <1, 1–4, and 4–8 Hz in all SNR conditions. Children displayed similar coupling at <1 and 1–4 Hz, but increasing noise impaired the coupling more strongly than in adults. Also, children displayed drastically lower coherence at 4–8 Hz in all SNR conditions. These results suggest that children's difficulties to understand speech in noisy conditions are related to an immature selective cortical tracking of the attended speech streams. Our results also provide unprecedented evidence for an acquired cortical tracking of speech at syllable rate and argue for a progressive development of SiN abilities in humans.

Using a continuous listening task, we evaluated the coupling between the listener's cortical activity and the temporal envelopes of different sounds in a multitalker auditory scene using magnetoencephalography and corticovocal coherence analysis. Neuromagnetic signals were recorded from 20 right-handed healthy adult humans who listened to five different recorded stories (attended speech streams), one without any multitalker background (No noise) and four mixed with a “cocktail party” multitalker background noise at four signal-to-noise ratios (5, 0, −5, and −10 dB) to produce speech-in-noise mixtures, here referred to as Global scene. Coherence analysis revealed that the modulations of the attended speech stream, presented without multitalker background, were coupled at ∼0.5 Hz to the activity of both superior temporal gyri, whereas the modulations at 4–8 Hz were coupled to the activity of the right supratemporal auditory cortex. In cocktail party conditions, with the multitalker background noise, the coupling was at both frequencies stronger for the attended speech stream than for the unattended Multitalker background. The coupling strengths decreased as the Multitalker background increased. During the cocktail party conditions, the ∼0.5 Hz coupling became left-hemisphere dominant, compared with bilateral coupling without the multitalker background, whereas the 4–8 Hz coupling remained right-hemisphere lateralized in both conditions. The brain activity was not coupled to the multitalker background or to its individual talkers. The results highlight the key role of listener's left superior temporal gyri in extracting the slow ∼0.5 Hz modulations, likely reflecting the attended speech stream within a multitalker auditory scene.

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.

Using magnetoencephalography (MEG), this study investigates the spatio-temporal dynamics of the multilevel cortical processing of somatosensory change detection. Neuromagnetic signals of 16 healthy adult subjects (7 females and 9 males, mean age 29 ± 3 years) were recorded using whole-scalp-covering MEG while they underwent an oddball paradigm based on simple standard (right index fingertip tactile stimulation) and deviant (simultaneous right index fingertip and middle phalanx tactile stimulation) stimuli gathered into sequences to create and then deviate from stimulus patterns at multiple (local vs. global) levels of complexity. Five healthy adult subjects (3 females and 2 males, mean age 31, 6 ± 2 years) also underwent a similar oddball paradigm in which standard and deviant stimuli were flipped. Local deviations led to a somatosensory mismatch response peaking at 55-130 ms post-stimulus onset with a cortical generator located at the contralateral secondary somatosensory (cSII) cortex. The mismatch response was independent of the deviant stimuli physical characteristics. Global deviants led to a P300 response with cortical sources located bilaterally at temporo-parietal junction (TPJ) and supplementary motor area (SMA). The posterior parietal cortex (PPC) and the SMA were found to generate a contingent magnetic variation (CMV) attributed to top-down expectations. Amplitude of mismatch responses were modulated by top-down expectations and correlated with both the magnitude of the CMV and the P300 amplitude at the right TPJ. These results provide novel empirical evidence for a unified sensory novelty detection system in the human brain by linking detection of salient sensory stimuli in personal and extra-personal spaces to a common framework of multilevel cortical processing.

Humans and other animal species are endowed with the ability to sense, represent, and mentally manipulate the number of items in a set without needing to count them. One central hypothesis is that this ability relies on an automated functional system dedicated to numerosity, the perception of the discrete numerical magnitude of a set of items. This system has classically been associated with intraparietal regions, however accumulating evidence in favor of an early visual number sense calls into question the functional role of parietal regions in numerosity processing. Targeting specifically numerosity among other visual features in the earliest stages of processing requires high temporal and spatial resolution. We used frequency-tagged magnetoencephalography to investigate the early automatic processing of numerical magnitudes and measured the steady-state brain responses specifically evoked by numerical and other visual changes in the visual scene. The neuromagnetic responses showed implicit discrimination of numerosity, total occupied area, and convex hull. The source reconstruction corresponding to the implicit discrimination responses showed common and separate sources along the ventral and dorsal visual pathways. Occipital sources attested the perceptual salience of numerosity similarly to both other implicitly discriminable visual features. Crucially, we found parietal responses uniquely associated with numerosity discrimination, showing automatic processing of numerosity in the parietal cortex, even when not relevant to the task. Taken together, these results provide further insights into the functional roles of parietal and occipital regions in numerosity encoding along the visual hierarchy.

This magnetoencephalography (MEG) study investigates how procedural sequence learning performance is related to prior brain resting-state functional connectivity (rsFC), and to what extent sequence learning induces rapid changes in brain rsFC in school-aged children. Procedural learning was assessed in 30 typically developing children (mean age ± SD: 9.99 years ± 1.35) using a serial reaction time task (SRTT). During SRTT, participants touched as quickly and accurately as possible a stimulus sequentially or randomly appearing in one of the quadrants of a touchscreen. Band-limited power envelope correlation (brain rsFC) was applied to MEG data acquired at rest pre- and post-learning. Correlation analyses were performed between brain rsFC and sequence-specific learning or response time indices. Stronger pre-learning interhemispheric rsFC between inferior parietal and primary somatosensory/motor areas correlated with better subsequent sequence learning performance and faster visuomotor response time. Faster response time was associated with post-learning decreased rsFC within the dorsal extra-striate visual stream and increased rsFC between temporo-cerebellar regions. In school-aged children, variations in functional brain architecture at rest within the sensorimotor network account for interindividual differences in sequence learning and visuomotor performance. After learning, rapid adjustments in functional brain architecture are associated with visuomotor performance but not sequence learning skills.

This magnetoencephalography study investigates how ageing modulates the relationship between pre-learning resting-state functional connectivity (rsFC) and subsequent learning. Neuromagnetic resting-state activity was recorded 5 min before motor sequence learning in 14 young (19-30 years) and 14 old (66-70 years) participants. We used a seed-based beta-band power envelope correlation approach to estimate rsFC maps, with the seed located in the right primary sensorimotor cortex. In each age group, the relation between individual rsFC and learning performance was investigated using Pearson's correlation analyses. Our results show that rsFC is predictive of subsequent motor sequence learning but involves different cross-network interactions in the two age groups. In young adults, decreased coupling between the sensorimotor network and the cortico-striato-cerebellar network is associated with better motor learning, whereas a similar relation is found in old adults between the sensorimotor, the dorsal-attentional and the DMNs. Additionally, age-related correlational differences were found in the dorsolateral prefrontal cortex, known to subtend attentional and controlled processes. These findings suggest that motor skill learning depends-in an age-dependent manner-on subtle interactions between resting-state networks subtending motor activity on the one hand, and controlled and attentional processes on the other hand.

Decreased neural plasticity is observed with healthy ageing in the primary sensorimotor (SM1) cortex thought to participate in motor learning and memory consolidation processes. In the present magnetoencephalography study, the post-training reorganization of resting-state functional connectivity (rsFC) and its relation with motor learning and early consolidation in 14 young (19-30 years) and 14 old (66-70 years) healthy participants were investigated. At the behavioral level, participants were trained on a motor sequence learning task then retested 20-30 min later for transient offline gains in performance. Using a sensorimotor seed-based approach, rsFC relying on beta band power envelope correlation was estimated immediately before and 10 min after the learning episode. Post-training changes in rsFC (from before to after learning) were correlated with motor learning performance and with the offline improvement in performance within the hour after learning. Young and old participants exhibited differential patterns of sensorimotor-related rsFC, bearing specific relationships with motor learning and consolidation. Our findings suggest that rsFC changes following learning reflect the offline processing of the new motor skill and contribute to the early memory consolidation within the hour after learning. Furthermore, differences in post-training changes in rsFC between young and old participants support the hypothesis that ageing modulates the neural circuits underlying the learning of a new motor skill and the early subsequent consolidation stages.

Behavioral evidence shows that sleep is crucial for the consolidation of declarative memories in children as in adults. However, the underlying cerebral mechanisms remain virtually unexplored. Using magnetoencephalography, we investigated in children (8.0-12.5years) the impact of sleep (90-minute nap) on the neurophysiological processes underlying the creation and consolidation of novel associations between unknown objects and their functions. Learning-dependent changes in brain activity were observed within hippocampal and parahippocampal regions, followed by sleep-dependent changes in the prefrontal cortex, whereas no equivalent change was observed after a similar period of wakeful rest. Hence, our results show that in school-age children a 90-minute daytime nap after learning is sufficient to trigger the reorganization of memory-related brain activity toward prefrontal areas, where it incorporates into pre-existing semantic knowledge. This functional reorganization process in children is similar to that observed in adults but occurs at a much faster rate, which may contribute to the development of the impressive learning skills that characterize childhood.

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.

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.

The aim of this study was to investigate the age-related changes in resting-state neurometabolic connectivity from childhood to adulthood (6-50 years old). Fifty-four healthy adult subjects and twenty-three pseudo-healthy children underwent [(18) F]-fluorodeoxyglucose positron emission tomography at rest. Using statistical parametric mapping (SPM8), age and age squared were first used as covariate of interest to identify linear and non-linear age effects on the regional distribution of glucose metabolism throughout the brain. Then, by selecting voxels of interest (VOI) within the regions showing significant age-related metabolic changes, a psychophysiological interaction (PPI) analysis was used to search for age-induced changes in the contribution of VOIs to the metabolic activity in other brain areas. Significant linear or non-linear age-related changes in regional glucose metabolism were found in prefrontal cortices (DMPFC/ACC), cerebellar lobules, and thalamo-hippocampal areas bilaterally. Decreases were found in the contribution of thalamic, hippocampal, and cerebellar regions to DMPFC/ACC metabolic activity as well as in the contribution of hippocampi to preSMA and right IFG metabolic activities. Increases were found in the contribution of the right hippocampus to insular cortex and of the cerebellar lobule IX to superior parietal cortex metabolic activities. This study evidences significant linear or non-linear age-related changes in regional glucose metabolism of mesial prefrontal, thalamic, mesiotemporal, and cerebellar areas, associated with significant modifications in neurometabolic connectivity involving fronto-thalamic, fronto-hippocampal, and fronto-cerebellar networks. These changes in functional brain integration likely represent a metabolic correlate of age-dependent effects on sensory, motor, and high-level cognitive functional networks.

State modeling of whole-brain electroencephalography (EEG) or magnetoencephalography (MEG) allows to investigate transient, recurring neurodynamical events. Two widely-used techniques are the microstate analysis of EEG signals and hidden Markov modeling (HMM) of MEG power envelopes. Both reportedly lead to similar state lifetimes on the 100 ms timescale, suggesting a common neural basis. To investigate whether microstates and power envelope HMM states describe the same neural dynamics, we used simultaneous MEG/EEG recordings at rest and compared the spatial signature and temporal activation dynamics of microstates and power envelope HMM states obtained separately from EEG and MEG. Results showed that microstates and power envelope HMM states differ both spatially and temporally. Microstates reflect sharp events of neural synchronization, whereas power envelope HMM states disclose network-level activity with 100-200 ms lifetimes. Further, MEG microstates do not correspond to the canonical EEG microstates but are better interpreted as split HMM states. On the other hand, both MEG and EEG HMM states involve the (de)activation of similar functional networks. Microstate analysis and power envelope HMM thus appear sensitive to neural events occurring over different spatial and temporal scales. As such, they represent complementary approaches to explore the fast, sub-second scale bursting electrophysiological dynamics in spontaneous human brain activity.

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.

The default-mode network (DMN) and its principal core hubs in the posterior midline cortices (PMC), i.e., the precuneus and the posterior cingulate cortex, play a critical role in the human brain structural and functional architecture. Because of their centrality, they are affected by a wide spectrum of brain disorders, e.g., Alzheimer's disease. Non-invasive electrophysiological techniques such as magnetoencephalography (MEG) are crucial to the investigation of the neurophysiology of the DMN and its alteration by brain disorders. However, MEG studies relying on band-limited power envelope correlation diverge in their ability to identify the PMC as a part of the DMN in healthy subjects at rest. Since these works were based on different MEG recording systems and different source reconstruction pipelines, we compared DMN functional connectivity estimated with two distinct MEG systems (Elekta, now MEGIN, and CTF) and two widely used reconstruction algorithms (Minimum Norm Estimation and linearly constrained minimum variance Beamformer). Our results identified the reconstruction method as the critical factor influencing PMC functional connectivity, which was significantly dampened by the Beamformer. On this basis, we recommend that future electrophysiological studies on the DMN should rely on Minimum Norm Estimation (or close variants) rather than on the classical Beamformer. Crucially, based on analytic knowledge about these two reconstruction algorithms, we demonstrated with simulations that this empirical observation could be explained by the existence of a spontaneous linear, approximately zero-lag synchronization structure between areas of the DMN or among multiple sources within the PMC. This finding highlights a novel property of the neural dynamics and functional architecture of a core human brain network at rest.

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.

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.

Network theory and inverse modeling are two standard tools of applied physics, whose combination is needed when studying the dynamical organization of spatially distributed systems from indirect measurements. However, the associated connectivity estimation may be affected by spatial leakage, an artifact of inverse modeling that limits the interpretability of network analysis. This paper investigates general analytical aspects pertaining to this issue. First, the existence of spatial leakage is derived from the topological structure of inverse operators. Then the geometry of spatial leakage is modeled and used to define a geometric correction scheme, which limits spatial leakage effects in connectivity estimation. Finally, this new approach for network analysis is compared analytically to existing methods based on linear regressions, which are shown to yield biased coupling estimates.

Background Magnetoencephalography (MEG) is an established method used to detect and localize focal interictal epileptiform discharges (IEDs). Current MEG systems house hundreds of cryogenic sensors in a rigid, one-size-fits-all helmet, which results in several limitations, particularly in children. Purpose To determine if on-scalp MEG based on optically pumped magnetometers (OPMs) alleviates the main limitations of cryogenic MEG. Materials and Methods In this prospective single-center study conducted in a tertiary university teaching hospital, participants underwent cryogenic (102 magnetometers, 204 planar gradiometers) and on-scalp (32 OPMs) MEG. The two modalities for the detection and localization of IEDs were compared. The t test was used to compare IED amplitude and signal-to-noise ratio (SNR). Distributed source modeling was performed on OPM-based and cryogenic MEG data. Results Five children (median age, 9.4 years [range, 5-11 years]; four girls) with self-limited idiopathic (n = 3) or refractory (n = 2) focal epilepsy were included. IEDs were identified in all five children with comparable sensor topographies for both MEG devices. IED amplitudes were 2.3 (7.2 of 3.1) to 4.6 (3.2 of 0.7) times higher (P < .001) with on-scalp MEG, and the SNR was 27% (16.7 of 13.2) to 60% (12.8 of 8.0) higher (P value range: .001-.009) with on-scalp MEG in all but one participant (P = .93), whose head movements created pronounced motion artifacts. The neural source of averaged IEDs was located at approximately 5 mm (n = 3) or higher (8.3 mm, n = 1; 15.6 mm, n = 1) between on-scalp and cryogenic MEG. Conclusion Despite the limited number of sensors and scalp coverage, on-scalp magnetoencephalography (MEG) based on optically pumped magnetometers helped detect interictal epileptiform discharges in school-aged children with epilepsy with a higher amplitude, higher signal-to-noise ratio, and similar localization value compared with conventional cryogenic MEG.

The pathophysiology of cognitive dysfunction in multiple sclerosis (MS) is still unclear. This magnetoencephalography (MEG) study investigates the impact of MS on brain resting-state functional connectivity (rsFC) and its relationship to disability and cognitive impairment. We investigated rsFC based on power envelope correlation within and between different frequency bands, in a large cohort of participants consisting of 99 MS patients and 47 healthy subjects. Correlations were investigated between rsFC and outcomes on disability, disease duration and 7 neuropsychological scores within each group, while stringently correcting for multiple comparisons and possible confounding factors. Specific dysconnections correlating with MS-induced physical disability and disease duration were found within the sensorimotor and language networks, respectively. Global network-level reductions in within- and cross-network rsFC were observed in the default-mode network. Healthy subjects and patients significantly differed in their scores on cognitive fatigue and verbal fluency. Healthy subjects and patients showed different correlation patterns between rsFC and cognitive fatigue or verbal fluency, both of which involved a shift in patients from the posterior default-mode network to the language network. Introducing electrophysiological rsFC in a regression model of verbal fluency and cognitive fatigue in MS patients significantly increased the explained variance compared to a regression limited to structural MRI markers (relative thalamic volume and lesion load). This MEG study demonstrates that MS induces distinct changes in the resting-state functional brain architecture that relate to disability, disease duration and specific cognitive functioning alterations. It highlights the potential value of electrophysiological intrinsic rsFC for monitoring the cognitive impairment in patients with MS.

The Free and Cued Selective Reminding Test (FCSRT) is a largely validated neuropsychological test for the identification of amnestic syndrome from the early stage of Alzheimer's disease (AD). Previous electrophysiological data suggested a slowing down of the alpha rhythm in the AD-continuum as well as a key role of this rhythmic brain activity for episodic memory processes. This study therefore investigates the link between alpha brain activity and alterations in episodic memory as assessed by the FCSRT. For that purpose, 37 patients with altered FCSRT performance underwent a comprehensive neuropsychological assessment, supplemented by 18F-fluorodeoxyglucose positron emission tomography/structural magnetic resonance imaging (18FDG-PET/MR), and 10 min of resting-state magnetoencephalography (MEG). The individual alpha peak frequency (APF) in MEG resting-state data was positively correlated with patients' encoding efficiency as well as with the efficacy of semantic cues in facilitating patients' retrieval of previous stored word. The APF also correlated positively with patients' hippocampal volume and their regional glucose consumption in the posterior cingulate cortex. Overall, this study demonstrates that alterations in the ability to learn and store new information for a relatively short-term period are related to a slowing down of alpha rhythmic activity, possibly due to altered interactions in the extended mnemonic system. As such, a decreased APF may be considered as an electrophysiological correlate of short-term episodic memory dysfunction accompanying pathological aging.

Impaired speech perception in noise despite normal peripheral auditory function is a common problem in young adults. Despite a growing body of research, the pathophysiology of this impairment remains unknown. This magnetoencephalography study characterizes the cortical tracking of speech in a multi-talker background in a group of highly selected adult subjects with impaired speech perception in noise without peripheral auditory dysfunction. Magnetoencephalographic signals were recorded from 13 subjects with impaired speech perception in noise (six females, mean age: 30 years) and matched healthy subjects while they were listening to 5 different recordings of stories merged with a multi-talker background at different signal to noise ratios (No Noise, +10, +5, 0 and -5 dB). The cortical tracking of speech was quantified with coherence between magnetoencephalographic signals and the temporal envelope of (i) the global auditory scene (i.e. the attended speech stream and the multi-talker background noise), (ii) the attended speech stream only and (iii) the multi-talker background noise. Functional connectivity was then estimated between brain areas showing altered cortical tracking of speech in noise in subjects with impaired speech perception in noise and the rest of the brain. All participants demonstrated a selective cortical representation of the attended speech stream in noisy conditions, but subjects with impaired speech perception in noise displayed reduced cortical tracking of speech at the syllable rate (i.e. 4-8 Hz) in all noisy conditions. Increased functional connectivity was observed in subjects with impaired speech perception in noise in Noiseless and speech in noise conditions between supratemporal auditory cortices and left-dominant brain areas involved in semantic and attention processes. The difficulty to understand speech in a multi-talker background in subjects with impaired speech perception in noise appears to be related to an inaccurate auditory cortex tracking of speech at the syllable rate. The increased functional connectivity between supratemporal auditory cortices and language/attention-related neocortical areas probably aims at supporting speech perception and subsequent recognition in adverse auditory scenes. Overall, this study argues for a central origin of impaired speech perception in noise in the absence of any peripheral auditory dysfunction.

Children with developmental coordination disorder (DCD) present lower abilities to acquire and execute coordinated motor skills. DCD is frequently associated with visual perceptual (with or without motor component) impairments. This magnetoencephalography (MEG) study compares the brain resting-state functional connectivity (rsFC) and spectral power of children with and without DCD. 29 children with DCD and 28 typically developing (TD) peers underwent 2 × 5 min of resting-state MEG. Band-limited power envelope correlation and spectral power were compared between groups using a functional connectome of 59 nodes from eight resting-state networks. Correlation coefficients were calculated between fine and gross motor activity, visual perceptual and visuomotor abilities measures on the one hand, and brain rsFC and spectral power on the other hand. Nonparametric statistics were used. Significantly higher rsFC between nodes of the visual, attentional, frontoparietal, default-mode and cerebellar networks was observed in the alpha (maximum statistics, p = .0012) and the low beta (p = .0002) bands in children with DCD compared to TD peers. Lower visuomotor performance (copying figures) was associated with stronger interhemispheric rsFC within sensorimotor areas and power in the cerebellum (right lobule VIII). Children with DCD showed increased rsFC mainly in the dorsal extrastriate visual brain system and the cerebellum. However, this increase was not associated with their coordinated motor/visual perceptual abilities. This enhanced functional brain connectivity could thus reflect a characteristic brain trait of children with DCD compared to their TD peers. Moreover, an interhemispheric compensatory process might be at play to perform visuomotor task within the normative range.

Objectives: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is considered to have potential neuroinvasiveness that might lead to acute brain disorders or contribute to respiratory distress in patients with coronavirus disease 2019 (COVID-19). This study investigates the occurrence of structural brain abnormalities in non-survivors of COVID-19 in a virtopsy framework. Methods: In this prospective, monocentric, case series study, consecutive patients who fulfilled the following inclusion criteria benefited from an early postmortem structural brain MRI: death <24 hours, SARS-CoV-2 detection on nasopharyngeal swab specimen, chest CT scan suggestive of COVID-19, absence of known focal brain lesion, and MRI compatibility. Results: Among the 62 patients who died of COVID-19 from March 31, 2020, to April 24, 2020, at our institution, 19 decedents fulfilled the inclusion criteria. Parenchymal brain abnormalities were observed in 4 decedents: subcortical microbleeds and macrobleeds (2 decedents), cortico-subcortical edematous changes evocative of posterior reversible encephalopathy syndrome (PRES; 1 decedent), and nonspecific deep white matter changes (1 decedent). Asymmetric olfactory bulbs were found in 4 other decedents without downstream olfactory tract abnormalities. No brainstem MRI signal abnormality was observed. Conclusions: Postmortem brain MRI demonstrates hemorrhagic and PRES-related brain lesions in non-survivors of COVID-19. SARS-CoV-2-related olfactory impairment seems to be limited to olfactory bulbs. Brainstem MRI findings do not support a brain-related contribution to respiratory distress in COVID-19.

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: This prospective, bicentre, blinded, intention to treat study assessed the clinical added value of magnetic source imaging (MSI) in the presurgical evaluation of patients with refractory focal epilepsy (RFE). Methods: 70 consecutive patients with RFE (42 men; mean age 31.5 years, range 3-63) from two Belgian centres were prospectively included. All patients underwent conventional non-invasive presurgical evaluation (CNIPE) and a whole head magnetoencephalography recording (Elekta Neuromag). Equivalent current dipoles corresponding to interictal epileptiform discharges (IED) were fitted in the patients' spherical head model and coregistered on their MRI to produce MSI results. Results of CNIPE were first discussed blinded to the MSI results in respective multidisciplinary epilepsy surgery meetings to determine the presumed localisation of the epileptogenic zone and to set surgical or additional presurgical plans. MSI results were then discussed multidisciplinarily. MSI influence on the initial management plan was assessed. Results: Based on CNIPE, 21 patients had presumed extratemporal epilepsy, 38 had presumed temporal epilepsy and 11 had undetermined localisation epilepsy. MSI showed IED in 52 patients (74.5%) and changed the initial management in 15 patients (21%). MSI related changes were significantly more frequent in patients with presumed extratemporal or undetermined localisation epilepsy compared with patients with presumed temporal epilepsy (p≤0.001). These changes had a clear impact on clinical management in 13% of all patients. Conclusion: MSI is a clinically relevant, non-invasive neuroimaging technique for the presurgical evaluation of patients with refractory focal epilepsy and, particularly, in patients with presumed extratemporal and undetermined localisation epilepsy.