Neural activity has been shown to track hierarchical linguistic units in connected speech and these responses can be directly modulated by changes in speech intelligibility caused by spectral degradation. In the current study, we manipulate prior knowledge to increase the intelligibility of physically identical speech sentences and test the hypothesis that the tracking responses can be enhanced by this intelligibility improvement. Cortical magnetoencephalography (MEG) responses to intelligible speech followed by either the same (matched) or different (unmatched) unintelligible speech were measured in twenty-three normal hearing participants. Driven by prior knowledge, cortical coherence to “abstract” linguistic units with no accompanying acoustic cues (phrases and sentences) was enhanced relative to the unmatched condition, and was lateralized to the left hemisphere. In contrast, cortical responses coherent to word units, aligned with acoustic onsets, were bilateral and insensitive to contextual information changes. No such coherence changes were observed when prior experience was not available (unintelligible speech before intelligible speech). This dissociation suggests that cerebral responses to linguistic information are directly affected by intelligibility, which in turn are powerfully shaped by physical cues in speech. These results provide an objective and sensitive neural index of speech intelligibility, and explain why previous studies have reported no effect of prior knowledge on cortical entrainment.

Childhood apraxia of speech (CAS) is conceived as an impairment of the central motor system's ability to program multiple speech movements, resulting in inaccurate transitions between and relative timing across speech sounds. However, the extant neuroimaging evidence base is scant and inconclusive, and the neurophysiological origins of these motor planning problems remain highly underspecified. In the first magnetoencephalography study of this disorder, we measured brain activity from typically developing (TD) children (N= 19, 11 males, 8 females) and children with CAS (N= 7 males) during performance of a speech task designed to interrogate function of the speech areas of the primary sensorimotor cortex. Relative to their TD peers, our sample of children with CAS showed abnormal speech-related responses within the mu-band motor rhythm, and beamformer source reconstruction analyses specify a brain origin of this speech rhythm in the left cerebral hemisphere, within or near pre-Rolandic motor areas crucial for the planning and control of speech and oromotor movements. These results provide a new and specific candidate mechanism for the core praxic features of CAS; point to a novel and robust neurophysiological marker of typical and atypical expressive speech development; and support an emerging neuroscientific consensus which assigns a central role for programming and coordination of speech movements to the motor cortices of the precentral gyrus.

Many decades after Penfield's (Penfield W, Boldrey E. Brain 60: 389-443, 1937) classic depiction of the motor homunculus, it remains unclear how spatially contiguous and interconnected representations within human sensorimotor cortex might separate their activities to achieve the directed and precise control of distinct body regions evident in activities as different as typing and speaking. One long-standing but relatively neglected explanation draws from models of simple physical systems (like swinging pendulums) to posit that small differences in the oscillatory properties of neuronal populations (termed "frequency detuning") can result in highly effective segregation of their activities and outputs. We tested this hypothesis by comparing the peak frequencies of beta-band (13-30 Hz) motor rhythms measured in a magnetoencephalographic neuroimaging study of finger and speech movements in a group of healthy adults and a group of typically developing children. Our results confirm a peak frequency task difference (speech movement vs. hand movement) of about 1.5 Hz in the beta motor rhythms of both left and right hemispheres in adults. A comparable task difference was obtained in children for the left but not for the right hemisphere. These results provide novel support for the role of frequency detuning in the functional organization of the brain and suggest that this mechanism should play a more prominent role in current models of bodily representations and their development within the sensorimotor cortex.NEW & NOTEWORTHY This work is the first evidence for frequency detuning of an intrinsic motor rhythm in spatially contiguous regions of primary motor cortex associated with hand and speech movements, supporting a mechanism of functional segregation that has been largely overlooked by current models of motor cortex organization. Our results from children further provide the first evidence for frequency detuning in the developing brain, indicating an early-developing mechanism with later refinements of hemispheric control.

Distractor suppression allows us to remain on-task in the presence of distractions by filtering task-irrelevant information from ongoing cognitive processing and responding. Electrophysiological studies have revealed that this key feature of selective attention is a dynamic process that involves at least two distinct stages of processing. Two important aspects of these processing stages remain unclear: Whether the processing of emotional distractors at an earlier stage is automatic, as reflected in the N2/early posterior negativity (EPN) component; and what functional-anatomical brain systems are recruited in each stage. The present study addresses these issues by measuring brain activity with concurrent electroencephalography-magnetoencephalography (MEG) recordings while participants performed a combined rapid serial visual presentation and motion tracking task. Event-related potentials (ERP) showed significant effects of attentional capture and attentional modulation during two time windows marked by the N2/EPN and P3b ERP components. Source reconstruction of concurrent MEG measurements revealed activation of the left visual association cortex and anterior cingulate cortex during the N2/EPN time window, activation of the insula during the early phase of the P3b and anterior cingulate cortex activity during the later phase of the P3b. The findings provide novel evidence establishing a connection between the increased N2 response to negative pictures and the activation of the cingulate gyrus, which facilitates the suppression of distractions during demanding cognitive tasks. In addition, distinct activation patterns were observed in the insula and anterior cingulate cortex during the P3b time window, indicating that attentional control mediated by the anterior cingulate cortex operates to suppress the processing of distracting emotional stimuli. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Neuroimaging protocols for mapping of expressive speech centres employ several standard speech tasks including object naming, rhyming, and covert word production (Agarwal et al., 2019). These tasks reliably elicit activation of distributed speech centres in prefrontal, precentral and cingulate motor cortices and are widely used for presurgical mapping and in research studies of language production. In the present study we used an alternative speech protocol employing reiterated productions of simple disyllabic nonwords (VCV; Anastasopoulou et al., 2022; van Lieshout et al., 2007). Here we show that this task elicits highly focal and highly lateralised activations of speech motor control areas centred on the precentral gyrus and adjacent portions of the middle frontal gyrus. 10 healthy adults, 19 typically developing children and 7 children with CAS participated in the study. MEG scans were carried out with a whole-head MEG system consisting of 160 first-order axial gradiometers with a 50 mm baseline (Model PQ1160R-N2, KIT, Kanazawa, Japan). MEG data were acquired with analog filter settings of 0.03 Hz high-pass, 1,000 Hz low-pass, 4,000 Hz sampling rate. Measurements were carried out with participants in supine position in a magnetically shielded room (Fujihara Co. Ltd., Tokyo, Japan). Time-aligned speech acoustics were recorded in an auxiliary channel of the MEG setup at the same sample rate as the MEG recordings. Brain activity was recorded while participants produced reiterated utterances of /ipa/ and /api/, at normal and speeded rates in addition to a button press task (right index finger) to elicit activity in the hand region of sensorimotor cortex (e.g. Johnson et al., 2020). MEG data were co-registered with individual structural MRI scans obtained in a separate scanning session. Source reconstruction was performed with synthetic aperture magnetometry (SAM) beamformer implemented in Matlab (Jobst et al., 2018) and group statistics performed with permutation tests (p < 0.05). Button press map shows clusters encompassing dorsal precentral and postcentral gyri (Brodmann areas 4 and 6), corresponding to hand sensorimotor cortices. Speech map shows clusters encompassing precentral gyrus immediately ventral to hand motor cortex (BA6), and an immediately adjacent portion of the posterior middle frontal gyrus. Both button press and speech result in a robust desynchronisation restricted within a frequency band of about 13-30 Hz (beta band). Our results show that the reiterated speech task results in robust beta-band desynchronisation in a highly focal region of the precentral gyrus, located immediately ventral to the hand motor region of the precentral gyrus. In adults, speech motor -related brain activity was predominantly observed in the left hemisphere. Typically developing children, on the other hand, exhibited bilateral activation and in the case of individuals with CAS exhibited only right-hemisphere activation. Taken together the present findings provide a non-invasive and highly selective window on a crucial node of the expressive speech network that has previously been accessed only with invasive electrophysiological means and lesion studies.

Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been feasible to use both in the same experimental setup because of technical incompatibilities between the two methodologies. Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK; Alves et al., 2016), which is technically compatible with magnetoencephalography (MEG) brain scanning systems. In the present paper we describe our methodological and analytic approach for extracting brain motor activities related to key kinematic and coordination event parameters derived from time-registered MASK tracking measurements (Anastasopoulou et al., 2022). Data were collected from ten healthy adults with tracking coils on the tongue, lips, and jaw. Analyses targeted the gestural landmarks of reiterated utterances /ipa/ and /api/, produced at normal and faster rates (Anastasopoulou et al., 2022; Van Lieshout, 2007). The results show that (1) Speech sensorimotor cortex can be reliably located in peri-rolandic regions of the left hemisphere; (2) mu (8-12 Hz) and beta band (13-30 Hz) neuromotor oscillations are present in the speech signals and contain information structures that are independent of those present in higher-frequency bands; and (3) hypotheses concerning the information content of speech motor rhythms can be systematically evaluated with multivariate pattern analytic techniques. These results show that MASK provides the capability, for deriving subject-specific articulatory parameters, based on well-established and robust motor control parameters, in the same experimental setup as the MEG brain recordings and in temporal and spatial co-register with the brain data. The analytic approach described here provides new capabilities for testing hypotheses concerning the types of kinematic information that are encoded and processed within specific components of the speech neuromotor system.

Currently, electroencephalogram (EEG) is mostly analyzed in a supervised way, which requires EEG labels (e.g., EEG classification). With the ever-increasing amount of unlabeled/mislabeled EEG in neuropsychiatric disorder diagnosis, BCI, and rehabilitation, manually labeling of EEG data is a labor intensive and time-consuming process, and few labs have developed algorithms to analyze EEG in an unsupervised manner (i.e., EEG clustering). In this paper, we propose a cooperative game inspired approach to cluster multi-trial EEG data. The idea is to map multi-trial EEG clustering to the coalition formation in a cooperative game, and then identify cluster center (the EEG trial with highest Shapley value) and assign EEG trials into proper clusters based on their cross correlation-transformed Shapley values. We demonstrate the mapped EEG cooperative game is convex, and it leads to an algorithm for multi-trial EEG clustering named CoGEEGc. The CoGEEGc yields high-quality multi-trial EEG clustering with respect to intra-cluster compactness and inter-cluster scatter. We show that CoGEEGc outperforms 15 state-of-the-art EEG or time series clustering approaches through detailed experimentation on real-world multi-trial EEG datasets. Comparison against 15 methods with four theoretical properties of clustering further illustrates the superiority of CoGEEGc, as it satisfies two properties while other approaches only satisfy one.

Brain electroencephalography (EEG), the complex, weak, multivariate, nonlinear, and nonstationary time series, has been recently widely applied in neurocognitive disorder diagnoses and brain-machine interface developments. With its specific features, unlabeled EEG is not well addressed by conventional unsupervised time-series learning methods. In this article, we handle the problem of unlabeled EEG time-series clustering and propose a novel EEG clustering algorithm, that we call mwcEEGc. The idea is to map the EEG clustering to the maximum-weight clique (MWC) searching in an improved Fréchet similarity-weighted EEG graph. The mwcEEGc considers the weights of both vertices and edges in the constructed EEG graph and clusters EEG based on their similarity weights instead of calculating the cluster centroids. To the best of our knowledge, it is the first attempt to cluster unlabeled EEG trials using MWC searching. The mwcEEGc achieves high-quality clusters with respect to intracluster compactness as well as intercluster scatter. We demonstrate the superiority of mwcEEGc over ten state-of-the-art unsupervised learning/clustering approaches by conducting detailed experimentations with the standard clustering validity criteria on 14 real-world brain EEG datasets. We also present that mwcEEGc satisfies the theoretical properties of clustering, such as richness, consistency, and order independence.

Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until recently, however, it has generally not been possible to use both in the same experimental setup because of technical incompatibilities between the two methodologies. Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), which we used to derive kinematic profiles of oro-facial movements during speech. MASK was used to characterize speech kinematics in two healthy adults, and the results were compared to measurements from a separate participant with a conventional Electromagnetic Articulography (EMA) system. Analyses targeted the gestural landmarks of reiterated utterances /ipa/, /api/ and /pataka/. The results demonstrate that MASK reliably characterizes key kinematic and movement coordination parameters of speech motor control. Since these parameters are intrinsically registered in time with concurrent magnetoencephalographic (MEG) measurements of neuromotor brain activity, this methodology paves the way for innovative cross-disciplinary studies of the neuromotor control of human speech production, speech development, and speech motor disorders.

Hippocampal rhythms are important for spatial navigation. This study examined whether gender differences in human navigation performance are associated with differences in hippocampal rhythms. We measured brain activities in males and females with whole-head magnetoencephalography (MEG), while they performed a virtual Morris water maze task. Behavioural results showed clear gender differences: males were significantly faster than females; unlike males, females did not show improved navigation performance in a familiar vs. new environment. MEG results showed that the magnitudes of right hippocampal/parahippocampal theta rhythm were similar between the two groups during navigation in a new environment; however, unlike males who exhibited a significant decrease in right hippocampal/parahippocampal theta power in the familiar environment shown before, females showed no change. This result may suggest faster environmental learning in males vs. females. After navigating in the new environment during the inter-trial (ITI) rest periods, males showed significantly higher right hippocampal/parahippocampal high-gamma power than females, suggesting greater consolidation in males. Moreover, right hippocampal/parahippocampal theta power during navigation correlated with navigation performance in both genders; high-gamma power during the ITI was correlated with navigation performance only in males. These associations may provide further support for the functional importance of theta and high-gamma rhythms in navigation. Overall, this study provides new insights into the neurophysiological mechanisms underlying gender differences in spatial navigation.

Human cortical activity measured with magnetoencephalography (MEG) has been shown to track the temporal regularity of linguistic information in connected speech. In the current study, we investigate the underlying neural sources of these responses and test the hypothesis that they can be directly modulated by changes in speech intelligibility. MEG responses were measured to natural and spectrally degraded (noise-vocoded) speech in 19 normal hearing participants. Results showed that cortical coherence to "abstract" linguistic units with no accompanying acoustic cues (phrases and sentences) were lateralized to the left hemisphere and changed parametrically with intelligibility of speech. In contrast, responses coherent to words/syllables accompanied by acoustic onsets were bilateral and insensitive to intelligibility changes. This dissociation suggests that cerebral responses to linguistic information are directly affected by intelligibility but also powerfully shaped by physical cues in speech. This explains why previous studies have reported widely inconsistent effects of speech intelligibility on cortical entrainment and, within a single experiment, provided clear support for conclusions about language lateralization derived from a large number of separately conducted neuroimaging studies. Since noise-vocoded speech resembles the signals provided by a cochlear implant device, the current methodology has potential clinical utility for assessment of cochlear implant performance.

This article explores valid brain electroencephalography (EEG) selection for EEG classification with different classifiers, which has been rarely addressed in previous studies and is mostly ignored by existing EEG processing methods and applications. Importantly, traditional selection methods are not able to select valid EEG signals for different classifiers. This article focuses on a source control-based valid EEG selection to reduce the impact of invalid EEG signals and aims to improve EEG-based classification performance for different classifiers. We propose a novel centroid-based EEG selection approach named CenEEGs, which uses a scale-and-shift-invariance similarity metric to measure similarities of EEG signals and then applies a globally optimal centroid strategy to select valid EEG signals with respect to a similarity threshold. A detailed comparison with several state-of-the-art time series selection methods by using standard criteria on 8 EEG datasets demonstrates the efficacy and superiority of CenEEGs for different classifiers.

Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been possible to use both in the same experimental setup because of technical incompatibilities between the two methodologies. Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), used for the first time to obtain kinematic profiles of oro-facial movements during speech together with concurrent magnetoencephalographic (MEG) measurements of neuromotor brain activity. MASK was used to characterise speech kinematics in a healthy adult, and the results were compared to measurements from the same participant with a conventional electromagnetic articulography (EMA) setup. We also characterised speech movement kinematics with MASK in a group of ten typically developing children, aged 8-12 years. Analyses targeted the gestural landmarks of the utterances /ida/, /ila/ and reiterated productions of /pataka/. These results demonstrate that the MASK technique can be used to reliably characterise movement profiles and kinematic parameters that reflect development of speech motor control, together with MEG measurements of brain responses from speech sensorimotor cortex. This new capability sets the stage for cross-disciplinary efforts to understand the developmental neurobiology of human speech production.

In a previous study, we reported the first measurements of pre-movement and sensorimotor cortex activity in preschool age children (ages 3-5 years) using a customized pediatric magnetoencephalographic system. Movement-related activity in the sensorimotor cortex differed from that typically observed in adults, suggesting that maturation of cortical motor networks was still incomplete by late preschool age. Here we compare these earlier results to a group of school age children (ages 6-8 years) including seven children from the original study measured again two years later, and a group of adults (mean age 31.1 years) performing the same task. Differences in movement-related brain activity were observed both longitudinally within children in which repeated measurements were made, and cross-sectionally between preschool age children, school age children, and adults. Movement-related mu (8-12 Hz) and beta (15-30 Hz) oscillations demonstrated linear increases in amplitude and mean frequency with age. In contrast, movement-evoked gamma synchronization demonstrated a step-like transition from low (30-50 Hz) to high (70-90 Hz) narrow-band oscillations, and this occurred at different ages in different children. Notably, pre-movement activity ('readiness fields') observed in adults was absent in even the oldest children. These are the first direct observations of brain activity accompanying motor responses throughout early childhood, confirming that maturation of this activity is still incomplete by mid-childhood. In addition, individual children demonstrated markedly different developmental trajectories in movement-related brain activity, suggesting that individual differences need to be taken into account when studying motor development across age groups.

Recent evidence shows that hippocampal theta oscillations, usually linked to memory and navigation, are also observed during online language processing, suggesting a shared neurophysiological mechanism between language and memory. However, it remains to be established what specific roles hippocampal theta oscillations may play in language, and whether and how theta mediates the communication between the hippocampus and the perisylvian cortical areas, generally thought to support language processing. With whole-head magnetoencephalographic (MEG) recordings, the present study investigated these questions with two experiments. Using a violation paradigm, extensively used for studying neural underpinnings of different aspects of linguistic processing, we found increased theta power (4–8 ​Hz) in the hippocampal formation, when participants read a semantically incorrect vs. correct sentence ending. Such a pattern of results was replicated using different sentence stimuli in another cohort of participants. Importantly, no significant hippocampal theta power increase was found when participants read a semantically correct but syntactically incorrect sentence ending vs. a correct sentence ending. These findings may suggest that hippocampal theta oscillations are specifically linked to lexical-semantic related processing, and not general information processing in sentence reading. Furthermore, we found significantly transient theta phase coupling between the hippocampus and the left superior temporal gyrus, a hub area of the cortical network for language comprehension. This transient theta phase coupling may provide an important channel that links the memory and language systems for the generation of sentence meaning. Overall, these findings help specify the role of hippocampal theta in language, and provide a novel neurophysiological mechanism at the network level that may support the interface between memory and language.

This article explores valid brain electroencephalography (EEG) selection for EEG classification with different classifiers, which has been rarely addressed in previous studies and is mostly ignored by existing EEG processing methods and applications. Importantly, traditional selection methods are not able to select valid EEG signals for different classifiers. This article focuses on a source control-based valid EEG selection to reduce the impact of invalid EEG signals and aims to improve EEG-based classification performance for different classifiers. We propose a novel centroid-based EEG selection approach named CenEEGs, which uses a scale-and-shift-invariance similarity metric to measure similarities of EEG signals and then applies a globally optimal centroid strategy to select valid EEG signals with respect to a similarity threshold. A detailed comparison with several state-of-the-art time series selection methods by using standard criteria on 8 EEG datasets demonstrates the efficacy and superiority of CenEEGs for different classifiers.

The ability to silently hear music in the mind has been argued to be fundamental to musicality. Objective measurements of this subjective imagery experience are needed if this link between imagery ability and musicality is to be investigated. However, previous tests of musical imagery either rely on self-report, rely on melodic memory, or do not cater in range of abilities. The Pitch Imagery Arrow Task (PIAT) was designed to address these shortcomings; however, it is impractically long. In this paper, we shorten the PIAT using adaptive testing and automatic item generation. We interrogate the cognitive processes underlying the PIAT through item response modelling. The result is an efficient online test of auditory mental imagery ability (adaptive Pitch Imagery Arrow Task: aPIAT) that takes 8 min to complete, is adaptive to participant’s individual ability, and so can be used to test participants with a range of musical backgrounds. Performance on the aPIAT showed positive moderate-to-strong correlations with measures of non-musical and musical working memory, self-reported musical training, and general musical sophistication. Ability on the task was best predicted by the ability to maintain and manipulate tones in mental imagery, as well as to resist perceptual biases that can lead to incorrect responses. As such, the aPIAT is the ideal tool in which to investigate the relationship between pitch imagery ability and musicality.

Recent magnetoencephalography (MEG) studies have established that sensorimotor brain rhythms are strongly modulated during mental imagery of musical beat and rhythm, suggesting that motor regions of the brain are important for temporal aspects of musical imagery. The present study examined whether these rhythms also play a role in non-temporal aspects of musical imagery including musical pitch. Brain function was measured with MEG from 19 healthy adults while they performed a validated musical pitch imagery task and two non-imagery control tasks with identical temporal characteristics. A 4-dipole source model probed activity in bilateral auditory and sensorimotor cortices. Significantly greater β-band modulation was found during imagery compared to control tasks of auditory perception and mental arithmetic. Imagery-induced β-modulation showed no significant differences between auditory and sensorimotor regions, which may reflect a tightly coordinated mode of communication between these areas. Directed connectivity analysis in the θ-band revealed that the left sensorimotor region drove left auditory region during imagery onset. These results add to the growing evidence that motor regions of the brain are involved in the top-down generation of musical imagery, and that imagery-like processes may be involved in musical perception.

In a previous MEG study of movement-related brain activity in preschool age children, we reported that pre-movement fields and sensorimotor cortex oscillations differed from those typically observed in adults, suggesting that maturation of cortical motor networks is still incomplete by late preschool age (Cheyne et al., 2014). Here we describe the same measurements in an older group of school-aged children (6 to 8 years old) and an adult control group, in addition to repeated recordings in seven children from the original study approximately two years later. Differences were observed both longitudinally within children and between age groups. Pre-movement (readiness) fields were still not present in the oldest children, however both frequency and magnitude of movement-related mu (8-12Hz) and beta (15-30Hz) oscillations demonstrated linear increases with age. In contrast, movement-evoked gamma synchronization demonstrated a step-like transition from low (30-50 Hz) to high (70-90 Hz) narrow-band oscillations, and this occurred at different ages in different children. These data provide novel evidence of linear and non-linear changes in motor cortex oscillations and delayed development of the readiness field throughout early childhood. Individual children showed large differences in maturation of movement-related brain activity, possibly reflecting differing rates of motor development.