Biology subjects

De Tiege, X.

Publications and source records attributed to De Tiege, X..

At least 19 recordsLinked to original sources

bioRxiv2026

Multi-parametric spectral modeling disentangles synaptic kinetics and neural excitability from non-invasive electrophysiological recordings

Spectral modeling of electrophysiological recordings enables non-invasive characterization of neural excitability. However, current approaches rely on a single spectral index, limiting insight into the multiple biophysical processes underlying excitation-inhibition balance. Here, we introduce a biologically informed, multi-parametric spectral analysis that disentangles neural excitability and synaptic kinetics from recordings. As a proof of concept, we demonstrate that this approach captures signatures of hyperexcitability and glutamate reuptake dysfunction characteristic of Alzheimer's disease.

neuroscience↗

bioRxiv2026

Glymphatic Imaging in Multiple Sclerosis: Microstructural Constraints on DTI-ALPS and Clinical Relevance of gBOLD-CSF Coupling in Relation to Sleep and Disability

The glymphatic system is the waste clearance pathway in the central nervous system. Although its dysfunction has been associated with several neurological disorders, its role in multiple sclerosis (MS) remains poorly understood. This system is thought to be particularly active during sleep, yet the relationship between sleep metrics and MRI-derived markers of glymphatic activity has been scarcely explored. In this study, we aimed to perform a multimodal magnetic resonance imaging (MRI) assessment of glymphatic function in MS and investigate its association with sleep parameters, clinical disability, disease duration and MRI-derived structural markers. The study included 22 patients (34.3{+/-}10.1 years; 16 female) with relapsing-remitting MS and 26 healthy controls (32.2{+/-}5.7 years; 18 female), all of whom underwent 3.0 Tesla MRI. Glymphatic function was assessed using diffusion tensor image analysis along the perivascular space (DTI-ALPS) index and global blood-oxygen-level-dependent (BOLD) signal-cerebrospinal fluid (CSF) coupling. In addition, sleep micro- and macrostructural features, clinical disability, disease duration, along with mean diffusivity (MD), lateral ventricular, choroid plexus volumes and lesion load were evaluated. Patients showed reduced DTI-ALPS index, though this difference became only a trend after controlling for MD. No significant group differences were observed in global BOLD signal-CSF coupling. However, in patients, the weaker coupling was associated with longer total sleep time, lower arousal index, greater disability and lateral ventricle enlargement, whereas the DTI-ALPS index showed no significant correlations with any of the measures. Together, these findings challenge the assumption that DTI-ALPS can serve as a reliable marker of glymphatic function in demyelinating diseases such as MS, where disease-related alterations in white matter microstructure can confound diffusion-based measures. In contrast, gBOLD-CSF coupling showed associations with sleep, clinical disability and structural changes in patients, despite the absence of a significant group-level difference. This finding suggests that gBOLD-CSF coupling may capture individual variability in glymphatic-related dynamics relevant to sleep and the clinical expression of MS.

neuroscience↗

bioRxiv2026

Assessment of sensorimotor cortical beta oscillations from peripheral electromyography and force recordings

The beta oscillations of the human primary sensorimotor cortex (SM1) play a crucial role in regulating motor and cognitive behavior in health and disease. However, their assessment relies on costly and complex neuroimaging techniques, limiting scalability and translational applications. We present a novel method for assessing beta oscillations from easily obtained peripheral electromyography and force recordings. We show that movement-induced modulations in SM1 beta oscillations can be assessed from the electromyography or force recordings of a contracted contralateral hand muscle. We demonstrate the fidelity of this method in young and elderly healthy participants and in Parkinsons disease patients. We also demonstrate that the resting-state SM1 beta interhemispheric coupling can be assessed from an interhand coupling between the electromyography or force of contracted homologous hand muscles. This methodology enables scalable and cost-effective investigations of beta oscillations for all fields of human neuroscience and for the development of accessible disease/therapeutic markers.

neuroscience↗

bioRxiv2026

Theta-band brain synchronization supports the immediate and post-sleep dynamics of memory recall in children

Memory engrams emerge from dynamic, coordinated interactions among synchronized functional brain networks. Yet, how these networks are selectively reactivated upon cued recall and gradually (re)organized over time, especially through sleep, remains poorly understood. Using magnetoencephalography (MEG), sleep electroencephalography (EEG) and behavioral measures, we investigated the spatiotemporal neural dynamics of cued recall memory during immediate and post-sleep (i.e., 90-minute post-learning nap) recall sessions in school-aged children. Results showed that immediate recall engaged a temporally ordered sequence of theta-band phase synchronization across two transiently synchronized networks: an early (150-350 ms) network involving the ventral visual pathway and left medial temporal lobe (MTL), followed by a later (550-750 ms) network encompassing the bilateral MTL and widespread neocortical associative regions. Post-sleep recall was associated, relative to wakefulness, with strengthened theta-band phase synchronization between the left MTL and widespread bilateral neocortical regions in a similar late window (450-650 ms). Post-sleep theta-band synchronization and memory gains in performance positively correlated with slow oscillation-spindle coupling during the post-learning nap. Altogether, these findings highlight oscillatory and spatiotemporal dynamics of memory recall networks and suggest that sleep, possibly driven by slow-oscillation-spindle coupling mechanisms, supports the efficient reinstatement of memory traces in the developing brain.

neuroscience↗

bioRxiv2026

Signal space beamforming for gain- and geometry-independent interference suppression in wearable MEG

Optically pumped magnetometers (OPMs) for wearable magnetoencephalography (MEG) offer substantial flexibility compared to cryogenic MEG, but they also introduce new challenges related to environmental noise and movement artefacts. State-of-the-art denoising techniques such as signal space separation require not only dense OPM arrays but also the fine calibration of sensor gain and geometry. This may complicate their use in complex experimental situations involving uncooperative patients or subjects such as newborns or fetuses, where OPM positioning may be unstable or plain unknown. To address this limitation, we introduce signal space beamforming (SSB), a version of beamforming applied to sensor signals and designed to suppress interferences independently of sensor gain and geometry. We show that SSB operates via a trade-off between noise suppression and neural signal preservation that is controlled by a single soft-threshold parameter, which we calibrated using phantom measurements. We then validated the effectiveness of SSB across several datasets. Using interictal OPM-MEG recordings in epileptic patients, SSB successfully cleaned signals while preserving epileptiform discharges. Moving onto cutting-edge early neurodevelopmental OPM-MEG recordings, SSB allowed to recover auditory evoked responses in newborns and fetuses similar to previous findings but with more streamlined preprocessing and higher response amplitude in the case of the fetal data. We contend that SSB provides a pragmatic solution to exploit OPM-MEG data recorded in challenging conditions where geometry-dependent methods cannot be used, opening new frontiers for pioneering clinical and fundamental applications of the OPM technology.

neuroscience↗

bioRxiv2025

Can you feel what I am saying? Speech-based vibrotactile stimulation enhances the cortical tracking of attended speech in a multi-talker background

In environments with multiple talkers, humans can tune in to a speaker of interest while ignoring competing voices. In such conditions, however, auditory cortices track the attended speech envelope rhythms (cortical tracking of speech, CTS) less accurately than in quiet, hindering intelligibility. Visual speech cues (e.g., lip movements) can enhance this CTS, but it remains unclear whether other non-auditory sensory cues, such as tactile input, provide comparable benefits through similar neural mechanisms. Here, using magnetoencephalography, we quantified syllabic (4-8 Hz) and phrasal (<1 Hz) CTS while participants attended to connected speech alone, together with synchronous or asynchronous speech-based vibrations, or with the corresponding speaker video, in both quiet and a multi-talker background noise. We hypothesized that, in noise, speech-based vibrotactile stimulation improves comprehension by enhancing CTS and modulating auditory-seeded functional brain connectivity with extra-auditory neocortical brain areas. Results revealed that synchronous vibrotactile stimulation improved comprehension in multi-talker noise and increased syllabic CTS at right auditory cortex, with this CTS increase magnitude correlating with comprehension performance. Audio-tactile CTS enhancement was accompanied by stronger beta-band auditory cortex connectivity with ipsilateral angular and ventral inferior temporal gyri, alongside reduced alpha-band coupling with the precuneus. These findings suggest that vibrotactile input can support speech-in-noise processing by impacting both local auditory cortical activity and auditory-seeded long-range functional connectivity.

neuroscience↗

bioRxiv2025

Fetal magnetoencephalography based on optically pumped magnetometers

The fetus in the third trimester of gestation has already the remarkable capacity to process external sensory information in utero. So far, investigations of fetal brain responses to sensory information have mostly relied on cryogenic magnetoencephalography (MEG), which is suitable to record fetal brain activity and is not much affected by layers of maternal tissues. Nevertheless, this solution is extremely expensive and limited to a couple of laboratories worldwide. In this work, we took advantage of the next generation cryogenic-free MEG, that is MEG based on optically pumped magnetometers (OPM), to develop a system that could record both fetal and newborn brain responses to auditory stimulation in a longitudinal design. Twenty-one pregnant women in their late third trimester of gestation (35-40 weeks of gestational age) were exposed to sequences of 500 Hz tones. Fetal brain activity was recorded using a wearable belt equipped with OPM sensors arranged on the womens abdomen based on fetal head position. Results revealed that fetal OPM-MEG successfully recorded significant evoked brain responses to auditory stimuli that peaked ~300 ms post-stimulus at the group level. A similar auditory paradigm was performed with on-scalp OPM-MEG in 14 one-month-old infants, with 9 participants common to both timepoints. Infant responses showed a significant latency decrease compared to the fetal ones in terms of magnetometers; a decrease that did not reach significance level for virtual gradiometers. This work demonstrates the ability of OPM-MEG to non-invasively record fetal brain responses to external sensory stimuli. It paves the way for a wider use of fetal MEG to investigate fetal cognition and positions OPM-MEG as the most promising lifespan-compliant solution for monitoring early brain development.

neuroscience↗

bioRxiv2025

Association between theta-band resting-state functional connectivity and declarative memory abilities in children

Declarative memory formation critically relies on the synchronization of brain oscillations in the theta (4-8 Hz) frequency band within specific brain networks. The development of this capacity is closely linked to the functional organization of these networks already at rest. However, the relationship between theta-band resting-state functional connectivity and declarative memory abilities remains unexplored in children. Here, using magnetoencephalography, we examined the association between declarative memory performance and pre-learning resting-state functional connectivity across frequency bands in 32 school-aged children. Declarative memory was assessed as the percentage of correct retrieval of 50 new associations between non-objects and magical functions, while resting-state functional connectivity was measured through power envelope correlation of the theta, alpha, low and high beta frequency bands. We found that stronger theta-band resting-state functional connectivity within occipito-temporo-frontal networks correlated with better declarative memory retrieval, while no correlation was observed in the alpha and beta frequency bands. These findings suggest that the functional brain architecture at rest, specifically involving theta-band oscillations, supports declarative memory in children. This mechanism may facilitate the subsequent rapid transformation of sensory input into visuo-semantic representations, highlighting the critical role of theta-band connectivity in early cognitive development.

neuroscience↗

bioRxiv2024

A Novel, Robust, and Portable Platform for Magnetoencephalography using Optically Pumped Magnetometers

Magnetoencephalography (MEG) measures brain function via assessment of magnetic fields generated by neural currents. Conventional MEG uses superconducting sensors, which place significant limitations on performance, practicality, and deployment; however, the field has been revolutionised in recent years by the introduction of optically-pumped-magnetometers (OPMs). OPMs enable measurement of the MEG signal without cryogenics, and consequently the conception of OPM-MEG systems which ostensibly allow increased sensitivity and resolution, lifespan compliance, free subject movement, and lower cost. However, OPM-MEG remains in its infancy with limitations on both sensor and system design. Here, we report a new OPM-MEG design with miniaturised and integrated electronic control, a high level of portability, and improved sensor dynamic range (arguably the biggest limitation of existing instrumentation). We show that this system produces equivalent measures when compared to an established instrument; specifically, when measuring task-induced beta-band, gamma-band and evoked neuro-electrical responses, source localisations from the two systems were highly comparable and temporal correlation was >0.7 at the individual level and >0.9 for groups. Using an electromagnetic phantom, we demonstrate improved dynamic range by running the system in background fields up to 8 nT. We show that the system is effective in gathering data during free movement (including a sitting-to-standing paradigm) and that it is compatible with simultaneous electroencephalography (EEG - the clinical standard). Finally, we demonstrate portability by moving the system between two laboratories. Overall, our new system is shown to be a significant step forward for OPM-MEG technology and offers an attractive platform for next generation functional medical imaging.

neuroscience↗

bioRxiv2023

Extending the applicability of optically pumped magnetoencephalography toward early human life

Characterizing the early development of the human brain is critical from both fundamental and clinical perspectives. However, existing neuroimaging techniques are either not well suited to infants or have limited spatial or temporal resolution. The advent of optically pumped magnetometers (OPMs) has revolutionized magnetoencephalography (MEG) by enabling wearable and thus more naturalistic recordings while maintaining excellent sensitivity and spatiotemporal resolution. Nevertheless, its adaptation to studying neural activity in infancy poses several challenges. In this work, we present an original close-to-scalp OPM-MEG setup that successfully recorded brain responses to sounds in newborns. We exposed one-month-old infants to continuous streams of tones and observed significant evoked responses, which peaked [~]250 ms poststimulus at bilateral auditory cortices. When tones were presented at a steady fixed pace with an oddball tone every fourth tone, significant neural responses were found both at the frequency of the standard tones (3 Hz) and of the oddball tones (0.75 Hz). The latter reflects the ability of the newborn brain to detect auditory change and synchronize to regular auditory patterns. Additional analyses support the added value of triaxial OPMs to increase the number of channels on small heads. Finally, OPM-MEG responses were validated with those obtained from the same participants using an adult-sized cryogenic MEG. This study demonstrates the applicability of OPM-MEG to study early postnatal periods; a crucial step towards future OPM investigations of typical and pathological early brain development.

neuroscience↗

bioRxiv2023

Motor learning- and consolidation-related resting state fast and slow brain dynamics across wake and sleep

Learning and consolidation of motor skills dynamically evolve both online during practice and offline after training. We investigated, using magnetoencephalography, the neural dynamics underpinning motor learning and its consolidation in relation to sleep during resting-state periods shortly after the end of learning (short-term boost window, within 30 min) and at more delayed time scales (silent 4h and next day 24h windows) with an intermediate nap or wakefulness after the boost window. Resting-state neural dynamics in brain networks were investigated at fast (sub-second) and slower (supra-second) timescales using Hidden Markov modelling (HMM) and resting-state functional connectivity (rsFC), respectively, as well as their relationship with the evolution of motor performance. HMM results show that fast dynamic activities in a Temporal/Sensorimotor state network predict individual motor performance achievements, suggesting a trait-like association between rapidly recurrent neural patterns and motor behaviour. Short, post-training re-exposure to the task modulated fast and slow network characteristics during the boost but not in the silent window. These short practice-related induction effects were observed again on the next day, to a reduced extent as compared to the boost window. Daytime naps did not significantly modulate memory consolidation both at behavioural and neural levels. These results emphasise the critical role of the transient boost window in motor learning and subsequent memory consolidation processes and provide further insights into the relationship between the multiscale neural dynamics of brain networks, motor learning, and consolidation.

neuroscience↗

bioRxiv2023

Towards the automated detection of interictal epileptiform discharges with magnetoencephalography

The analysis of clinical magnetoencephalography (MEG) in patients with epilepsy traditionally relies on the visual identification of interictal epileptiform discharges (IEDs), which is time consuming and dependent on (subjective) human criteria. Data-driven approaches enabling both spatial and temporal localization of epileptic spikes would represent a major leap forward in clinical MEG practice. Here, we explore the ability of Independent Components Analysis (ICA) and Hidden Markov Modeling (HMM) to automatically detect and localize IEDs. Combined with kurtosis mapping, we developed a fully automated identification of epileptiform independent components (ICs) or HMM states. We tested our pipeline on MEG recordings at rest from 10 school-age children with either focal or multifocal epilepsy and compared results with the traditional MEG analysis performed by an experienced clinical magnetoencephalographer. In patients with focal epilepsy, both ICA- and HMM-based pipelines successfully detected visually identified IEDs with high sensitivity, but also revealed low-amplitude IEDs unidentified by the visual detection. Success was more mitigated in patients with multifocal epilepsy, as our automated pipeline missed IED activity associated with some foci--an issue that could be alleviated by post-hoc manual selection of epileptiform ICs or HMM states. Therefore, IED detection based on ICA or HMM represents an efficient way to identify spike localization and timing, with heightened sensitivity to IEDs compared to visual MEG signal inspection and requiring minimal input from clinical practitioners.

neuroscience↗

bioRxiv2023

Functional identification of language-responsive channels in individual participants in MEG investigations

Making meaningful inferences about the functional architecture of the language system requires the ability to refer to the same neural units across individuals and studies. Traditional brain imaging approaches align and average brains together in a common space. However, lateral frontal and temporal cortices, where the language system resides, is characterized by high structural and functional inter-individual variability, which reduces the sensitivity and functional resolution of group-averaging analyses. This issue is compounded by the fact that language areas lay in close proximity to regions of other large-scale networks with different functional profiles. A solution inspired by visual neuroscience is to identify language areas functionally in each individual brain using a localizer task (e.g., a language comprehension task). This approach has proven productive in fMRI, yielding a number of robust and replicable findings about the language system. Here, we extend this approach to MEG. Across two experiments (one in Dutch speakers, n=19; one in English speakers, n=23), we examined neural responses to the processing of sentences and a control condition (nonword sequences). In both the time and frequency domains, we demonstrated that the topography of neural responses to language is spatially stable within individuals but varies across individuals. Consequently, analyses that take this inter-individual variability into account are characterized by greater sensitivity, compared to the group-level analyses. In summary, similar to fMRI, functional identification within individuals yields benefits in MEG, thus opening the door to future investigations of language processing including questions where whole-brain coverage and temporal resolution are both critical.

neuroscience↗

bioRxiv2022

Do intrinsic functional networks reflect interacting brain rhythms? Assessing the power bias in MEG amplitude connectivity at rest

The oscillatory nature of intrinsic brain networks is largely taken for granted in the systems neuroscience community. However, the hypothesis that brain rhythms--and by extension transient bursting oscillations--underlie functional networks has not been demonstrated per se. Electrophysiological measures of functional connectivity are indeed affected by the power bias, which may lead to artefactual observations of spectrally specific network couplings not genuinely driven by neural oscillations, bursting or not. We investigate this crucial question by introducing a unique combination of a rigorous mathematical analysis of the power bias in frequency-dependent amplitude connectivity with a neurobiologically informed model of cerebral background noise based on hidden Markov modeling of resting-state magnetoencephalography (MEG). We demonstrate that the power bias may be corrected by a suitable renormalization depending nonlinearly on the signal-to-noise ratio, with noise identified as non-bursting oscillations. Applying this correction preserves the spectral content of amplitude connectivity, definitely proving the importance of brain rhythms in intrinsic functional networks. Our demonstration highlights a dichotomy between spontaneous oscillatory bursts underlying network couplings and non-bursting oscillations acting as background noise but whose function remains unsettled. Significance statementBrain rhythms are paramount electrophysiological correlates of human cerebral activity as they coordinate neurons across distinct brain areas and establish neural synchronization. Spontaneous cortical oscillations, and particularly transient "bursts" of oscillations, also appear as the main electrophysiological subtrate of intrinsic functional brain networks. However, we argue that this oscillatory theory of brain networks, despite being widely accepted, should be requestioned due to a critical bias in electrophysiological measures of network connectivity. Here, we combined mathematical and neurobiological modeling techniques with magnetoencephalography recordings to set this theory on firm and rigorous grounds. Key to our analysis are scarcely studied non-bursting cortical oscillations. Although their precise function remains elusive, our results reveal that dissociating bursting and non-bursting oscillations is fundamental to the rigorous interpretation of electrophysiological network connectivity.

neuroscience↗

bioRxiv2022

Cortical tracking of lexical speech units in a multi-talker background is immature in school-aged children

Children have more difficulty perceiving speech in noise than adults. Whether these difficulties relate to 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 acoustic 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, and 2 phrases formed a sentence, 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, cortical tracking of linguistic units was lower for all units in conditions without noise, and similarly impacted by the addition of babble noise for phrase and sentence units. Critically, when there was noise, adults increased the cortical tracking of monosyllabic words in the inferior frontal gyri 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 identification of lexical but not supra-lexical linguistic units. HighlightsO_LIChildren track the hierarchical linguistic units of clear speech devoid of prosody C_LIO_LIThis cortical tracking is left-hemisphere dominant as the adult brain C_LIO_LIBabble noise reduces cortical tracking of sentences in children and adults C_LIO_LIUnlike adults, children are not able to enhance cortical tracking of words in noise C_LI

neuroscience↗

bioRxiv2022

Neurodevelopmental oscillatory basis of speech processing in noise

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 to 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. TeaserThe neural signature of speech processing in silence and noise features multiple behaviorally relevant developmental milestones

neuroscience↗

bioRxiv2021

The role of reading experience in atypical cortical tracking of speech and speech-in-noise in dyslexia

Dyslexia is a frequent developmental disorder in which reading acquisition is delayed and that is usually associated with difficulties understanding speech in noise. At the neuronal level, children with dyslexia were reported to display abnormal cortical tracking of speech (CTS) at phrasal rate. Here, we aimed to determine if abnormal tracking is a cause or a consequence of dyslexia and if it is modulated by the severity of dyslexia or the presence of acoustic noise. We included 26 school-age children with dyslexia, 26 age-matched controls and 26 reading-level matched controls. All were native French speakers. Childrens brain activity was recorded with magnetoencephalography while they listened to continuous speech in noiseless and multiple noise conditions. CTS values were compared between groups, conditions and hemispheres, and also within groups, between children with best and worse reading performance. Syllabic CTS was significantly reduced in the right superior temporal gyrus in children with dyslexia compared with controls matched for age but not for reading level. Among children with dyslexia, phrasal CTS tended to lateralize to the left hemisphere in severe dyslexia and lateralized to the right hemisphere in children with mild dyslexia and in all control groups. Finally, phrasal CTS was lower in children with dyslexia compared with age-matched controls, but only in informational noise conditions. No such effect was seen in comparison with reading-level matched controls. Overall, our results confirmed the finding of altered neuronal basis of speech perception in noiseless and babble noise conditions in dyslexia compared with age-matched peers. However, the absence of alteration in comparison with reading-level matched controls suggests that such alterations are a consequence of reduced reading experience rather than a cause of dyslexia. HighlightsO_LIThe cortical tracking of speech (CTS) was assessed in dyslexia and proper controls C_LIO_LIPhrasal CTS and its resistance to noise were altered in dyslexia C_LIO_LISuch alterations were not found in comparison with controls matched for reading level C_LIO_LIThe severity of dyslexia modulated the hemispheric lateralization of phrasal CTS C_LI

neuroscience↗

bioRxiv2021

Spectro-temporal neural dynamics during sentence completion

This magnetoencephalography (MEG) study aimed at characterizing the spectro-temporal dynamics of brain oscillatory activity elicited by sentence completion (SC). For that purpose, we adapted a version of the SC experimental paradigm typically used in functional magnetic resonance imaging to MEG investigation constraints. Twenty right-handed healthy young adults underwent MEG recordings while they were sequentially presented with short sentences divided in three parts: the first two giving context and the last requiring completion. MEG data were then analysed using a prior-free, non-parametric statistical approach with stringent control of the family-wise error rate. We identified three successive significant neural response patterns associated with distinct spatial and spectro-temporal characteristics: (i) an early (<300 ms) bioccipital 4-10-Hz event-related synchronization (ERS); (ii) an intermediate (at about 400 ms) 8-30-Hz event-related desynchronization (ERD) in an extended semantic network involving the ventral language stream as well as bilateral posterior nodes of the default mode network (DMN) in both hemispheres; (iii) a late (>800 ms) 8-30 Hz ERD involving the left dorsal language stream. Furthermore, the left component of the ventral language stream displayed prolonged ERD after 800 ms compared to the right which showed signs of inhibition in the form of ERS. Overall, this study elucidates the dynamics of the recruitment of the language network that accompany SC and the spectro-temporal signature of an extended semantic network. This MEG adaptation of an SC paradigm also paves the way for novel approaches in presurgical language mapping and may help to understand the neural underpinnings of the alterations of sentence completion in various neurologic disorders affecting language.

neuroscience↗