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. We addressed this issue by using simultaneous MEG/EEG recordings at rest and comparing 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 differed both spatially and temporally. Microstates tend to exhibit spatio-temporal locality, 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.
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. Children's 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.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.