Interactions between posterior gamma and frontal alpha/beta oscillations during imagined actions

Emotion Induction Modulates Neural Dynamics Related to the Originality of Ideational Creativity

Emotions remarkably impact our creative minds; nevertheless, a comprehensive mapping of their underlying neural mechanisms remains elusive. Therefore, we examined the influence of emotion induction on ideational originality and its associated neural dynamics. Participants were randomly presented with three short videos with sad, neutral, and happy content. After each video, ideational originality was evaluated using the alternate uses task. Both happy and sad inductions significantly enhanced ideational originality relative to the neutral induction condition. However, no significant difference was observed in ideational originality between the happy and sad emotion inductions. Associated neural dynamics were assessed through EEG time-frequency (TF) power and phase-amplitude coupling (PAC) analyses. Our findings suggest that emotional states elicit distinct TF and PAC profiles associated with ideational originality. Relative to baseline, gamma activity was enhanced after the neutral induction and more enhanced after the induction of a happy emotion but reduced after the induction of sad emotion 2-4 s after starting the task. Our functional connectivity couplings suggest that inducing happy and sad emotions may influence the working memory and attentional system differently, leading to varying effects on associated processing modes. Inducing a happy emotion may result in decreased neural activity and processing of rich information in working memory for exploring more original ideas through cognitive flexibility. In contrast, inducing a sad emotion may enhance neural activity and increase coupling within the attention system to exploit and select fewer original ideas through cognitive persistence.

The gamma rhythm as a guardian of brain health

Gamma oscillations in brain activity (30-150 Hz) have been studied for over 80 years. Although in the past three decades significant progress has been made to try to understand their functional role, a definitive answer regarding their causal implication in perception, cognition, and behavior still lies ahead of us. Here, we first review the basic neural mechanisms that give rise to gamma oscillations and then focus on two main pillars of exploration. The first pillar examines the major theories regarding their functional role in information processing in the brain, also highlighting critical viewpoints. The second pillar reviews a novel research direction that proposes a therapeutic role for gamma oscillations, namely the gamma entrainment using sensory stimulation (GENUS). We extensively discuss both the positive findings and the issues regarding reproducibility of GENUS. Going beyond the functional and therapeutic role of gamma, we propose a third pillar of exploration, where gamma, generated endogenously by cortical circuits, is essential for maintenance of healthy circuit function. We propose that four classes of interneurons, namely those expressing parvalbumin (PV), vasointestinal peptide (VIP), somatostatin (SST), and nitric oxide synthase (NOS) take advantage of endogenous gamma to perform active vasomotor control that maintains homeostasis in the neuronal tissue. According to this hypothesis, which we call GAMER (GAmma MEdiated ciRcuit maintenance), gamma oscillations act as a 'servicing' rhythm that enables efficient translation of neural activity into vascular responses that are essential for optimal neurometabolic processes. GAMER is an extension of GENUS, where endogenous rather than entrained gamma plays a fundamental role. Finally, we propose several critical experiments to test the GAMER hypothesis.

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

Objective. Traditionally known for its involvement in emotional processing, the amygdala's involvement in motor control remains relatively unexplored, with sparse investigations into the neural mechanisms governing amygdaloid motor movement and inhibition. This study aimed to characterize the amygdaloid beta-band (13-30 Hz) power between 'Go' and 'No-go' trials of an arm-reaching task.Approach. Ten participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a direct reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-correctedZtests were used to assess significant modulations of beta power between the Response and fixation (baseline) phases in the 'Go' and 'No-go' conditions.Main results. In the 'Go' condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p⩽ 0.0499). In the 'No-go' condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the response phase (p⩽ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the 'Go' and 'No-go' conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders.Significance.This study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.

Neural correlates of motor imagery and execution in real-world dynamic behavior: evidence for similarities and differences

A large body of evidence shows that motor imagery and action execution behaviors result from overlapping neural substrates, even in the absence of overt movement during motor imagery. To date it is unclear how neural activations in motor imagery and execution compare for naturalistic whole-body movements, such as walking. Neuroimaging studies have not directly compared imagery and execution during dynamic walking movements. Here we recorded brain activation with mobile EEG during walking compared to during imagery of walking, with mental counting as a control condition. We asked 24 healthy participants to either walk six steps on a path, imagine taking six steps, or mentally count from one to six. We found beta and alpha power modulation during motor imagery resembling action execution patterns; a correspondence not found performing the control task of mental counting. Neural overlap occurred early in the execution and imagery walking actions, suggesting activation of shared action representations. Remarkably, a distinctive walking-related beta rebound occurred both during action execution and imagery at the end of the action suggesting that, like actual walking, motor imagery involves resetting or inhibition of motor processes. However, we also found that motor imagery elicits a distinct pattern of more distributed beta activity, especially at the beginning of the task. These results indicate that motor imagery and execution of naturalistic walking involve shared motor-cognitive activations, but that motor imagery requires additional cortical resources.

Active and Passive Cycling Decrease Subthalamic β Oscillations in Parkinson's Disease

BACKGROUND

Preserved cycling capabilities in patients with Parkinson's disease, especially in those with freezing of gait are still poorly understood. Previous research with invasive local field potential recordings in the subthalamic nucleus has shown that cycling causes a stronger suppression of β oscillations compared to walking, which facilitates motor continuation.

METHODS

We recorded local field potentials from 12 patients with Parkinson's disease (six without freezing of gait, six with freezing of gait) who were bilaterally implanted with deep brain stimulation electrodes in the subthalamic nucleus. We investigated β (13-30 Hz) and high γ (60-100 Hz) power during both active and passive cycling with different cadences and compared patients with and without freezing of gait. The passive cycling experiment, where a motor provided a fixed cadence, allowed us to study the effect of isolated sensory inputs without physical exercise.

RESULTS

We found similarly strong suppression of pathological β activity for both active and passive cycling. In contrast, there was stronger high γ band activity for active cycling. Notably, the effects of active and passive cycling were all independent of cadence. Finally, β suppression was stronger for patients with freezing of gait, especially during passive cycling.

CONCLUSIONS

Our results provide evidence for a link between proprioceptive input during cycling and β suppression. These findings support the role of continuous external sensory input and proprioceptive feedback during rhythmic passive cycling movements and suggest that systematic passive mobilization might hold therapeutic potential. © 2023 International Parkinson and Movement Disorder Society.

Neural Synchrony and Network Dynamics in Social Interaction: A Hyper-Brain Cell Assembly Hypothesis

Mounting neurophysiological evidence suggests that interpersonal interaction relies on continual communication between cell assemblies within interacting brains and continual adjustments of these neuronal dynamic states between the brains. In this Hypothesis and Theory article, a Hyper-Brain Cell Assembly Hypothesis is suggested on the basis of a conceptual review of neural synchrony and network dynamics and their roles in emerging cell assemblies within the interacting brains. The proposed hypothesis states that such cell assemblies can emerge not only within, but also between the interacting brains. More precisely, the hyper-brain cell assembly encompasses and integrates oscillatory activity within and between brains, and represents a common hyper-brain unit, which has a certain relation to social behavior and interaction. Hyper-brain modules or communities, comprising nodes across two or several brains, are considered as one of the possible representations of the hypothesized hyper-brain cell assemblies, which can also have a multidimensional or multilayer structure. It is concluded that the neuronal dynamics during interpersonal interaction is brain-wide, i.e., it is based on common neuronal activity of several brains or, more generally, of the coupled physiological systems including brains.

Synchronised neural signature of creative mental imagery in reality and augmented reality

Creativity, transforming imaginative thinking into reality, is a mental imagery simulation in essence. It can be incorporeal, concerns sophisticated and/or substantial thinking, and involves objects. In the present study, a mental imagery task consisting of creating a scene using familiar (FA) or abstract (AB) physical or virtual objects in real (RMI) and augmented reality (VMI) environments, and an execution task involving effectively creating a scene in augmented reality (VE), were utilised. The beta and gamma neural oscillations of healthy participants were recorded via a 32 channel wireless 10/20 international EGG system. In real and augmented environments and for both the mental imagery and execution tasks, the participants displayed a similar cortico-cortical neural signature essentially based on synchronous vs asynchronous beta and gamma oscillatory activities between anterior (i.e. frontal) and posterior (i.e. parietal, occipito-parietal and occipito-temporal) areas bilaterally. The findings revealed a transient synchronised neural architecture that appears to be consistent with the hypothesis according to which, creativity, because of its inherent complexity, cannot be confined to a single brain area but engages various interconnected networks.

Parietal Gamma Band Oscillation Induced by Self-Hand Recognition

Physiological studies have shown that self-body images receive unique recognition processing in a wide range of brain areas, from the frontal lobe to the parietal-occipital cortex. Event-related potential (ERP) studies have shown that the self-referential effect on the image of a hand increases P300 components, but such studies do not evaluate brain oscillatory activity. In this study, we aimed to discover the self-specific brain electrophysiological activity in relation to hand images. ERPs on the fronto-parietal midline were elicited by a three-stimulus visual oddball task using hand images: the self-hand, another hand (most similar to the self-hand), and another hand (similar to the self-hand). We analyzed ERP waveform and brain oscillatory activity by simple averaging and time-frequency analysis. The simple averaging analysis found no significant differences between the responses for the three stimulus tasks in all time windows. However, time-frequency analysis showed that self-hand stimuli elicited high gamma ERS in 650–900 ms at the Cz electrode compared to other hand stimuli. Our results show that brain activity specific to the self-referential process to the self-hand image was reflected in the long latency gamma band activity in the mid-central region. This high gamma-band activity at the Cz electrode may be similar to the activity of the mirror neuron system, which is involved in hand motion.

Intra-individual behavioural and neural signatures of audience effects and interactions in a mirror-game paradigm

We often perform actions while observed by others, yet the behavioural and neural signatures of audience effects remain understudied. Performing actions while being observed has been shown to result in more emphasized movements in musicians and dancers, as well as during communicative actions. Here, we investigate the behavioural and neural mechanisms of observed actions in relation to individual actions in isolation and interactive joint actions. Movement kinematics and EEG were recorded in 42 participants (21 pairs) during a mirror-game paradigm, while participants produced improvised movements alone, while observed by a partner, or by synchronizing movements with the partner. Participants produced largest movements when being observed, and observed actors and dyads in interaction produced slower and less variable movements in contrast with acting alone. On a neural level, we observed increased mu suppression during interaction, as well as to a lesser extent during observed actions, relative to individual actions. Moreover, we observed increased widespread functional brain connectivity during observed actions relative to both individual and interactive actions, suggesting increased intra-individual monitoring and action-perception integration as a result of audience effects. These results suggest that observed actors take observers into account in their action plans by increasing self-monitoring; on a behavioural level, observed actions are similar to emergent interactive actions, characterized by slower and more predictable movements.

Are alpha and beta oscillations spatially dissociated over the cortex in context-driven spoken-word production?

Decreases in oscillatory alpha‐ and beta‐band power have been consistently found in spoken‐word production. These have been linked to both motor preparation and conceptual‐lexical retrieval processes. However, the observed power decreases have a broad frequency range that spans two “classic” (sensorimotor) bands: alpha and beta. It remains unclear whether alpha‐ and beta‐band power decreases contribute independently when a spoken word is planned. Using a re‐analysis of existing magnetoencephalography data, we probed whether the effects in alpha and beta bands are spatially distinct. Participants read a sentence that was either constraining or non‐constraining toward the final word, which was presented as a picture. In separate blocks participants had to name the picture or score its predictability via button press. Irregular‐resampling auto‐spectral analysis (IRASA) was used to isolate the oscillatory activity in the alpha and beta bands from the background 1‐over‐f spectrum. The sources of alpha‐ and beta‐band oscillations were localized based on the participants’ individualized peak frequencies. For both tasks, alpha‐ and beta‐power decreases overlapped in left posterior temporal and inferior parietal cortex, regions that have previously been associated with conceptual and lexical processes. The spatial distributions of the alpha and beta power effects were spatially similar in these regions to the extent we could assess it. By contrast, for left frontal regions, the spatial distributions differed between alpha and beta effects. Our results suggest that for conceptual‐lexical retrieval, alpha and beta oscillations do not dissociate spatially and, thus, are distinct from the classical sensorimotor alpha and beta oscillations.

It remains unclear whether the consistently found alpha‐ and beta‐band power decreases in spoken‐word production support a single operation or contribute independently. Using novel methodology, we probed whether the alpha and beta bands are distinct from an anatomical perspective. We found anatomical overlap in the left posterior temporal and inferior parietal cortex, whereas for the left frontal region, the spatial overlap was limited. Our results suggest that for conceptual‐lexical retrieval, alpha and beta oscillations do not dissociate and, thus, are distinct from the classical sensorimotor alpha and beta.

Neural mechanism by which physical fatigue sensation suppresses physical performance: a magnetoencephalography study

The right dorsolateral prefrontal cortex (DLPFC) has been proposed to be the brain region regulating performance through fatigue sensation in fatigue, but direct evidence has been lacking for right DLPFC activation when physical performance is suppressed in the presence of fatigue sensation. We examined whether the right DLPFC is activated when physical performance is suppressed by remembering a physical fatigue sensation. Eighteen healthy male volunteers participated. They performed a rest session followed by a handgrip session to induce physical fatigue sensation. Then, they were instructed to remember the state of the right hand with (i.e., the target condition) and without (i.e., the control condition) fatigue sensation as experienced in the handgrip and rest sessions, respectively while performing motor imagery of maximum handgrip of the right hand. Neural activity during both conditions was recorded using magnetoencephalography. The level of fatigue sensation was higher in the target condition than in the control condition. Decreases of handgrip strength and beta band power in the right Brodmann's area 46 were observed in the target condition, suggesting that the right DLPFC is involved in the regulation of physical performance through fatigue sensation. These findings may help elucidate the neural mechanisms regulating performance under fatigue conditions.

The Role of Iconic Gestures in Speech Comprehension: An Overview of Various Methodologies

Iconic gesture-speech integration is a relatively recent field of investigation with numerous researchers studying its various aspects. The results obtained are just as diverse. The definition of iconic gestures is often overlooked in the interpretations of results. Furthermore, while most behavioral studies have demonstrated an advantage of bimodal presentation, brain activity studies show a diversity of results regarding the brain regions involved in the processing of this integration. Clinical studies also yield mixed results, some suggesting parallel processing channels, others a unique and integrated channel. This review aims to draw attention to the methodological variations in research on iconic gesture-speech integration and how they impact conclusions regarding the underlying phenomena. It will also attempt to draw together the findings from other relevant research and suggest potential areas for further investigation in order to better understand processes at play during speech integration process.

Space-Time-Frequency Multi-Sensor Analysis for Motor Cortex Localization Using Magnetoencephalography

Brain source imaging and time frequency mapping (TFM) are commonly used in magneto/electro encephalography (M/EEG) imaging. However, these methods suffer from important limitations. Source imaging is based on an ill-posed inverse problem leading to instability of source localization solutions, has a limited capacity to localize high frequency oscillations and loses its robustness for induced responses (ill-defined trigger). The drawback of TFM is that it involves independent analysis of signals from a number of frequency bands, and from co-localized sensors. In the present article, a regression-based multi-sensor space-time-frequency analysis (MSA) approach, which integrates co-localized sensors and/or multi-frequency information, is proposed. To estimate task-specific brain activations, MSA uses cross-validated, shifted, multiple Pearson correlation, calculated from the time-frequency transformed brain signal and the binary signal of stimuli. The results are projected from the sensor space onto the cortical surface. To assess MSA performance, the proposed method was compared to the weighted minimum norm estimate (wMNE) source imaging method, in terms of spatial selectivity and robustness against an ill-defined trigger. Magnetoencephalography (MEG) recordings were performed in fourteen subjects during two motor tasks: finger tapping and elbow flexion/extension. In particular, our results show that the MSA approach provides good localization performance when compared to wMNE and statistically significant improvement of robustness against ill-defined trigger.

Use of Both Eyes-Open and Eyes-Closed Resting States May Yield a More Robust Predictor of Motor Imagery BCI Performance

Motor-imagery brain-computer interface (MI-BCI) is a technique that manipulates external machines using brain activities, and is highly useful to amyotrophic lateral sclerosis patients who cannot move their limbs. However, it is reported that approximately 15–30% of users cannot modulate their brain signals, which results in the inability to operate motor imagery BCI systems. Thus, advance prediction of BCI performance has drawn researchers’ attention, and some predictors have been proposed using the alpha band’s power, as well as other spectral bands’ powers, or spectral entropy from resting state electroencephalography (EEG). However, these predictors rely on a single state alone, such as the eyes-closed or eyes-open state; thus, they may often be less stable or unable to explain inter-/intra-subject variability. In this work, a modified predictor of MI-BCI performance that considered both brain states (eyes-open and eyes-closed resting states) was investigated with 41 online MI-BCI session datasets acquired from 15 subjects. The results showed that our proposed predictor and online MI-BCI classification accuracy were positively and highly significantly correlated (r = 0.71, p < 0.1 × 10 − 7 ), which indicates that the use of multiple brain states may yield a more robust predictor than the use of a single state alone.

Performing the hand laterality judgement task does not necessarily require motor imagery

When people judge the laterality of rotated hand images, that is they perform the laterality judgement task (LJT), they are thought to use motor imagery. However, recent studies have suggested that its completion does not necessarily require the use of motor imagery. In this study, we investigated whether and how many people preferentially use motor imagery to perform the LJT in 37 healthy adults. We assessed the presence of behavioural features associated with motor imagery at the individual level, namely, the linear angle-response time (RT) relationship and the biomechanical constraints effect in the LJT and in the same-different judgement task (SDJT), in which people are not thought to use motor imagery. We found that at most 50% of participants showed both behavioural features in the palmar view condition of the LJT. Moreover, this proportion did not differ from that in the dorsal view condition of the LJT or that in both view conditions of the SDJT. These results demonstrate that a motor imagery-based strategy is not universally and specifically used to perform the LJT. Therefore, previous results of the LJT, in particular, regarding the biomechanical constraints effect, should be reinterpreted in light of our findings.

Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system

This study uses electrocorticography in humans to assess how alpha- and beta-band rhythms modulate excitability of the sensorimotor cortex during psychophysically-controlled movement imagery. Both rhythms displayed effector-specific modulations, tracked spectral markers of action potentials in the local neuronal population, and showed spatially systematic phase relationships (traveling waves). Yet, alpha- and beta-band rhythms differed in their anatomical and functional properties, were weakly correlated, and traveled along opposite directions across the sensorimotor cortex. Increased alpha-band power in the somatosensory cortex ipsilateral to the selected arm was associated with spatially-unspecific inhibition. Decreased beta-band power over contralateral motor cortex was associated with a focal shift from relative inhibition to excitation. These observations indicate the relevance of both inhibition and disinhibition mechanisms for precise spatiotemporal coordination of movement-related neuronal populations, and illustrate how those mechanisms are implemented through the substantially different neurophysiological properties of sensorimotor alpha- and beta-band rhythms.

Spatiotemporal Oscillatory Patterns During Working Memory Maintenance in Mild Cognitive Impairment and Subjective Cognitive Decline

Working memory (WM) is a crucial cognitive process and its disruption is among the earliest symptoms of Alzheimer’s disease. While alterations of the neuronal processes underlying WM have been evidenced in mild cognitive impairment (MCI), scarce literature is available in subjective cognitive decline (SCD). We used magnetoencephalography during a WM task performed by MCI [Formula: see text], SCD [Formula: see text] and healthy elders [Formula: see text] to examine group differences during the maintenance period (0–4000[Formula: see text]ms). Data were analyzed using time–frequency analysis and significant oscillatory differences were localized at the source level. Our results indicated significant differences between groups, mainly during the early maintenance (250–1250[Formula: see text]ms) in the theta, alpha and beta bands and in the late maintenance (2750–3750[Formula: see text]ms) in the theta band. MCI showed lower local synchronization in fronto-temporal cortical regions in the early theta–alpha window relative to controls [Formula: see text] and SCD [Formula: see text], and in the late theta window relative to controls [Formula: see text] and SCD [Formula: see text]. Early theta–alpha power was significantly correlated with memory scores [Formula: see text] and late theta power was correlated with task performance [Formula: see text] and functional activity scores [Formula: see text]. In the early beta window, MCI showed reduced power in temporo-posterior regions relative to controls [Formula: see text] and SCD [Formula: see text]. Our results may suggest that these alterations would reflect that memory-related networks are damaged.

Functional brain connectivity in a rodent seizure model of autistic-like behavior

OBJECTIVE

There is increasing evidence that Autism Spectrum Disorder (ASD) is a disorder of functional connectivity with both human and rodent studies demonstrating alterations in connectivity. Here, we hypothesized that early-life seizures (ELS) in rats would interrupt normal brain connectivity and result in autistic-like behavior (ALB).

METHODS

Following 50 seizures, adult rats were tested in the social interaction and social novelty tests and then underwent qualitative and quantitative intracranial electroencephalography (EEG) monitoring in the medial prefrontal cortex (PFC) and the hippocampal subfields, CA3 and CA1.

RESULTS

Rats with ELS showed deficits in social interaction and novelty, and compared with control, rats had marked increases in coherence within the hippocampus (CA3-CA1) and between the hippocampus and PFC during the awake and sleep states indicating hyperconnectivity. In addition, sleep spindle density was significantly reduced in rats with ELS. There were no differences in voltage correlations and power spectral densities between the ELS and control rats in any bandwidths.

CONCLUSION

Taken together, these findings indicate that ELS can result in ALB and alter functional connectivity as measured by coherence and sleep spindle density. These findings implicate altered connectivity as a robust neural signature for ALB following ELS.

Feasibility of Eye Tracking Assisted Vestibular Rehabilitation Strategy Using Immersive Virtual Reality

OBJECTIVES

Even though vestibular rehabilitation therapy (VRT) using head-mounted display (HMD) has been highlighted recently as a popular virtual reality platform, we should consider that HMD itself do not provide interactive environment for VRT. This study aimed to test the feasibility of interactive components using eye tracking assisted strategy through neurophysiologic evidence.

METHODS

HMD implemented with an infrared-based eye tracker was used to generate a virtual environment for VRT. Eighteen healthy subjects participated in our experiment, wherein they performed a saccadic eye exercise (SEE) under two conditions of feedback-on (F-on, visualization of eye position) and feedback-off (F-off, non-visualization of eye position). Eye position was continuously monitored in real time on those two conditions, but this information was not provided to the participants. Electroencephalogram recordings were used to estimate neural dynamics and attention during SEE, in which only valid trials (correct responses) were included in electroencephalogram analysis.

RESULTS

SEE accuracy was higher in the F-on than F-off condition (P=0.039). The power spectral density of beta band was higher in the F-on condition on the frontal (P=0.047), central (P=0.042), and occipital areas (P=0.045). Beta-event-related desynchronization was significantly more pronounced in the F-on (-0.19 on frontal and -0.22 on central clusters) than in the F-off condition (0.23 on frontal and 0.05 on central) on preparatory phase (P=0.005 for frontal and P=0.024 for central). In addition, more abundant functional connectivity was revealed under the F-on condition.

CONCLUSION

Considering substantial gain may come from goal directed attention and activation of brain-network while performing VRT, our preclinical study from SEE suggests that eye tracking algorithms may work efficiently in vestibular rehabilitation using HMD.

Sex differences in early sensorimotor processing for speech discrimination

Sensorimotor activity in speech perception tasks varies as a function of context, cognitive load, and cognitive ability. This study investigated listener sex as an additional variable. Raw EEG data were collected as 21 males and 21 females discriminated /ba/ and /da/ in quiet and noisy backgrounds. Independent component analyses of data from accurately discriminated trials identified sensorimotor mu components with characteristic alpha and beta peaks from 16 members of each sex. Time-frequency decompositions showed that in quiet discrimination, females displayed stronger early mu-alpha synchronization, whereas males showed stronger mu-beta desynchronization. Findings indicate that early attentional mechanisms for speech discrimination were characterized by sensorimotor inhibition in females and predictive sensorimotor activation in males. Both sexes showed stronger early sensorimotor inhibition in noisy discrimination conditions versus in quiet, suggesting sensory gating of the noise. However, the difference in neural activation between quiet and noisy conditions was greater in males than females. Though sex differences appear unrelated to behavioral accuracy, they suggest that males and females exhibit early sensorimotor processing for speech discrimination that is fundamentally different, yet similarly adaptable to adverse conditions. Findings have implications for understanding variability in neuroimaging data and the male prevalence in various neurodevelopmental disorders with inhibitory dysfunction.

The neural oscillatory markers of phonetic convergence during verbal interaction

During a conversation, the neural processes supporting speech production and perception overlap in time and, based on context, expectations and the dynamics of interaction, they are also continuously modulated in real time. Recently, the growing interest in the neural dynamics underlying interactive tasks, in particular in the language domain, has mainly tackled the temporal aspects of turn-taking in dialogs. Besides temporal coordination, an under-investigated phenomenon is the implicit convergence of the speakers toward a shared phonetic space. Here, we used dual electroencephalography (dual-EEG) to record brain signals from subjects involved in a relatively constrained interactive task where they were asked to take turns in chaining words according to a phonetic rhyming rule. We quantified participants' initial phonetic fingerprints and tracked their phonetic convergence during the interaction via a robust and automatic speaker verification technique. Results show that phonetic convergence is associated to left frontal alpha/low-beta desynchronization during speech preparation and by high-beta suppression before and during listening to speech in right centro-parietal and left frontal sectors, respectively. By this work, we provide evidence that mutual adaptation of speech phonetic targets, correlates with specific alpha and beta oscillatory dynamics. Alpha and beta oscillatory dynamics may index the coordination of the "when" as well as the "how" speech interaction takes place, reinforcing the suggestion that perception and production processes are highly interdependent and co-constructed during a conversation.

Causal Shannon-Fisher Characterization of Motor/Imagery Movements in EEG

The electroencephalogram (EEG) is an electrophysiological monitoring method that allows us to glimpse the electrical activity of the brain. Neural oscillations patterns are perhaps the best salient feature of EEG as they are rhythmic activities of the brain that can be generated by interactions across neurons. Large-scale oscillations can be measured by EEG as the different oscillation patterns reflected within the different frequency bands, and can provide us with new insights into brain functions. In order to understand how information about the rhythmic activity of the brain during visuomotor/imagined cognitive tasks is encoded in the brain we precisely quantify the different features of the oscillatory patterns considering the Shannon–Fisher plane H×F. This allows us to distinguish the dynamics of rhythmic activities of the brain showing that the Beta band facilitate information transmission during visuomotor/imagined tasks.

The Functional Alterations in Top-Down Attention Streams of Parkinson's disease Measured by EEG

Early and moderate Parkinson’s disease patients seem to have attention dysfunctions manifested differentially in separate attention streams: top-down and bottom-up. With a focus on the neurophysiological underpinnings of such differences, this study evaluated source-localized regional activity and functional connectivity of regions in the top-down and bottom-up streams as well as any discordance between the two streams. Resting state electroencephalography was used for 36 Parkinson’s disease patients and 36 healthy controls matched for age and gender. Parkinson’s disease patients showed disproportionally higher bilateral gamma activity in the bottom-up stream and higher left alpha2 connectivity in the top-down stream when compared to age-matched controls. An additional cross-frequency coupling analysis showed that Parkinson’s patients have higher alpha2-gamma coupling in the right posterior parietal cortex, which is part of the top-down stream. Higher coupling in this region was also associated with lower severity of motor symptoms in Parkinson’s disease. This study provides evidence that in Parkinson’s disease, the activity in gamma frequency band and connectivity in alpha2 frequency band is discordant between top-down and bottom-up attention streams.

Cortical Oscillatory Mechanisms Supporting the Control of Human Social-Emotional Actions

The human anterior prefrontal cortex (aPFC) is involved in regulating social-emotional behavior, presumably by modulating effective connectivity with downstream parietal, limbic, and motor cortices. Regulating that connectivity might rely on theta-band oscillations (4-8 Hz), a brain rhythm known to create overlapping periods of excitability between distant regions by temporally releasing neurons from inhibition. Here, we used MEG to understand how aPFC theta-band oscillations implement control over prepotent social-emotional behaviors; that is, the control over automatically elicited approach and avoidance actions. Forty human male participants performed a social approach-avoidance task in which they approached or avoided visually displayed emotional faces (happy or angry) by pulling or pushing a joystick. Approaching angry and avoiding happy faces (incongruent condition) requires rapid application of cognitive control to override prepotent habitual action tendencies to approach appetitive and to avoid aversive situations. In the time window before response delivery, trial-by-trial variations in aPFC theta-band power (6 Hz) predicted reaction time increases during emotional control and were inversely related to beta-band power (14-22 Hz) over parietofrontal cortex. In sensorimotor areas contralateral to the moving hand, premovement gamma-band rhythms (60-90 Hz) were stronger during incongruent than congruent trials, with power increases phase locked to peaks of the aPFC theta-band oscillations. These findings define a mechanistic relation between cortical areas involved in implementing rapid control over human social-emotional behavior. The aPFC may bias neural processing toward rule-driven actions and away from automatic emotional tendencies by coordinating tonic disinhibition and phasic enhancement of parietofrontal circuits involved in action selection.SIGNIFICANCE STATEMENT Being able to control social-emotional behavior is crucial for successful participation in society, as is illustrated by the severe social and occupational difficulties experienced by people suffering from social motivational disorders such as social anxiety. In this study, we show that theta-band oscillations in the anterior prefrontal cortex (aPFC), which are thought to provide temporal organization for neural firing during communication between distant brain areas, facilitate this control by linking aPFC to parietofrontal beta-band and sensorimotor gamma-band oscillations involved in action selection. These results contribute to a mechanistic understanding of cognitive control over automatic social-emotional action and point to frontal theta-band oscillations as a possible target of rhythmic neurostimulation techniques during treatment for social anxiety.

Abnormal Resting-State Quantitative Electroencephalogram in Children With Central Auditory Processing Disorder: A Pilot Study

In this study, we showed an abnormal resting-state quantitative electroencephalogram (QEEG) pattern in children with central auditory processing disorder (CAPD). Twenty-seven children (16 male, 11 female; mean age = 10.7 years) with CAPD and no symptoms of other developmental disorders, as well as 23 age- and sex-matched, typically developing children (TDC, 11 male, 13 female; mean age = 11.8 years) underwent examination of central auditory processes (CAPs) and QEEG evaluation consisting of two randomly presented blocks of “Eyes Open” (EO) or “Eyes Closed” (EC) recordings. Significant correlations between individual frequency band powers and CAP tests performance were found. The QEEG studies revealed that in CAPD relative to TDC there was no effect of decreased delta absolute power (1.5–4 Hz) in EO compared to the EC condition. Furthermore, children with CAPD showed increased theta power (4–8 Hz) in the frontal area, a tendency toward elevated theta power in EO block, and reduced low-frequency beta power (12–15 Hz) in the bilateral occipital and the left temporo-occipital regions for both EO and EC conditions. Decreased middle-frequency beta power (15–18 Hz) in children with CAPD was observed only in the EC block. The findings of the present study suggest that QEEG could be an adequate tool to discriminate children with CAPD from normally developing children. Correlation analysis shows relationship between the individual EEG resting frequency bands and the CAPs. Increased power of slow waves and decreased power of fast rhythms could indicate abnormal functioning (hypoarousal of the cortex and/or an immaturity) of brain areas not specialized in auditory information processing.

The Effects of Fluency Enhancing Conditions on Sensorimotor Control of Speech in Typically Fluent Speakers: An EEG Mu Rhythm Study

Objective: To determine whether changes in sensorimotor control resulting from speaking conditions that induce fluency in people who stutter (PWS) can be measured using electroencephalographic (EEG) mu rhythms in neurotypical speakers.

Methods: Non-stuttering (NS) adults spoke in one control condition (solo speaking) and four experimental conditions (choral speech, delayed auditory feedback (DAF), prolonged speech and pseudostuttering). Independent component analysis (ICA) was used to identify sensorimotor μ components from EEG recordings. Time-frequency analyses measured μ-alpha (8–13 Hz) and μ-beta (15–25 Hz) event-related synchronization (ERS) and desynchronization (ERD) during each speech condition.

Results: 19/24 participants contributed μ components. Relative to the control condition, the choral and DAF conditions elicited increases in μ-alpha ERD in the right hemisphere. In the pseudostuttering condition, increases in μ-beta ERD were observed in the left hemisphere. No differences were present between the prolonged speech and control conditions.

Conclusions: Differences observed in the experimental conditions are thought to reflect sensorimotor control changes. Increases in right hemisphere μ-alpha ERD likely reflect increased reliance on auditory information, including auditory feedback, during the choral and DAF conditions. In the left hemisphere, increases in μ-beta ERD during pseudostuttering may have resulted from the different movement characteristics of this task compared with the solo speaking task. Relationships to findings in stuttering are discussed.

Significance: Changes in sensorimotor control related feedforward and feedback control in fluency-enhancing speech manipulations can be measured using time-frequency decompositions of EEG μ rhythms in neurotypical speakers. This quiet, non-invasive, and temporally sensitive technique may be applied to learn more about normal sensorimotor control and fluency enhancement in PWS.

EEG oscillations during word processing predict MCI conversion to Alzheimer's disease

Only a subset of mild cognitive impairment (MCI) patients progress to develop a form of dementia. A prominent feature of Alzheimer's disease (AD) is a progressive decline in language. We investigated if subtle anomalies in EEG activity of MCI patients during a word comprehension task could provide insight into the likelihood of conversion to AD. We studied 25 amnestic MCI patients, a subset of whom developed AD within 3-years, and 11 elderly controls. In the task, auditory category descriptions (e.g., 'a type of wood') were followed by a single visual target word either semantically congruent (i.e., oak) or incongruent with the preceding category. We found that the MCI convertors group (i.e. patients that would go on to convert to AD in 3-years) had a diminished early posterior-parietal theta (3-5 Hz) activity induced by first presentation of the target word (i.e., access to lexico-syntactic properties of the word), compared to MCI non-convertors and controls. Moreover, MCI convertors exhibited oscillatory signatures for processing the semantically congruent words that were different from non-convertors and controls. MCI convertors thus showed basic anomalies for lexical and meaning processing. In addition, both MCI groups showed anomalous oscillatory signatures for the verbal learning/memory of repeated words: later alpha suppression (9-11 Hz), which followed first presentation of the target word, was attenuated for the second and third repetition in controls, but not in either MCI group. Our findings suggest that a subtle breakdown in the brain network subserving language comprehension can be foretelling of conversion to AD.

Independent Causal Contributions of Alpha- and Beta-Band Oscillations during Movement Selection

To select a movement, specific neuronal populations controlling particular features of that movement need to be activated, whereas other populations are downregulated. The selective (dis)inhibition of cortical sensorimotor populations is governed by rhythmic neural activity in the alpha (8-12 Hz) and beta (15-25 Hz) frequency range. However, it is unclear whether and how these rhythms contribute independently to motor behavior. Building on a recent dissociation of the sensorimotor alpha- and beta-band rhythms, we test the hypothesis that the beta-band rhythm governs the disinhibition of task-relevant neuronal populations, whereas the alpha-band rhythm suppresses neurons that may interfere with task performance. Cortical alpha- and beta-band rhythms were manipulated with transcranial alternating current stimulation (tACS) while human participants selected how to grasp an object. Stimulation was applied at either 10 or 20 Hz and was imposed on the sensorimotor cortex contralaterally or ipsilaterally to the grasping hand. In line with task-induced changes in endogenous spectral power, the effect of the tACS intervention depended on the frequency and site of stimulation. Whereas tACS stimulation generally increased movement selection times, 10 Hz stimulation led to relatively faster selection times when applied to the hemisphere ipsilateral to the grasping hand, compared with other stimulation conditions. These effects occurred selectively when multiple movements were considered. These observations functionally differentiate the causal contribution of alpha- and beta-band oscillations to movement selection. The findings suggest that sensorimotor beta-band rhythms disinhibit task-relevant populations, whereas alpha-band rhythms inhibit neuronal populations that could interfere with movement selection.

SIGNIFICANCE STATEMENT

This study shows dissociable effects of 10 Hz and 20 Hz tACS on the duration of movement selection. These observations have two elements of general relevance. First, the finding that alpha- and beta-band oscillations contribute independently to movement selection provides insight in how oscillations orchestrate motor behavior, which is key to understand movement selection deficits in neurodegenerative disorders. Second, the findings highlight the potential of 10 Hz stimulation as a neurophysiologically grounded intervention to enhance human performance. In particular, this intervention can potentially be exploited to boost rehabilitation after neural damage by targeting the unaffected hemisphere.

The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial

BACKGROUND

Many studies have demonstrated the usefulness of repetitive task practice by using robotic-assisted gait training (RAGT) devices, including Lokomat, for the treatment of lower limb paresis. Virtual reality (VR) has proved to be a valuable tool to improve neurorehabilitation training. The aim of our pilot randomized clinical trial was to understand the neurophysiological basis of motor function recovery induced by the association between RAGT (by using Lokomat device) and VR (an animated avatar in a 2D VR) by studying electroencephalographic (EEG) oscillations.

METHODS

Twenty-four patients suffering from a first unilateral ischemic stroke in the chronic phase were randomized into two groups. One group performed 40 sessions of Lokomat with VR (RAGT + VR), whereas the other group underwent Lokomat without VR (RAGT-VR). The outcomes (clinical, kinematic, and EEG) were measured before and after the robotic intervention.

RESULTS

As compared to the RAGT-VR group, all the patients of the RAGT + VR group improved in the Rivermead Mobility Index and Tinetti Performance Oriented Mobility Assessment. Moreover, they showed stronger event-related spectral perturbations in the high-γ and β bands and larger fronto-central cortical activations in the affected hemisphere.

CONCLUSIONS

The robotic-based rehabilitation combined with VR in patients with chronic hemiparesis induced an improvement in gait and balance. EEG data suggest that the use of VR may entrain several brain areas (probably encompassing the mirror neuron system) involved in motor planning and learning, thus leading to an enhanced motor performance.

TRIAL REGISTRATION

Retrospectively registered in Clinical Trials on 21-11-2016, n. NCT02971371 .

EEG Mu (µ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults

Stuttering is linked to sensorimotor deficits related to internal modeling mechanisms. This study compared spectral power and oscillatory activity of EEG mu (μ) rhythms between persons who stutter (PWS) and controls in listening and auditory discrimination tasks. EEG data were analyzed from passive listening in noise and accurate (same/different) discrimination of tones or syllables in quiet and noisy backgrounds. Independent component analysis identified left and/or right μ rhythms with characteristic alpha (α) and beta (β) peaks localized to premotor/motor regions in 23 of 27 people who stutter (PWS) and 24 of 27 controls. PWS produced μ spectra with reduced β amplitudes across conditions, suggesting reduced forward modeling capacity. Group time-frequency differences were associated with noisy conditions only. PWS showed increased μ-β desynchronization when listening to noise and early in discrimination events, suggesting evidence of heightened motor activity that might be related to forward modeling deficits. PWS also showed reduced μ-α synchronization in discrimination conditions, indicating reduced sensory gating. Together these findings indicate spectral and oscillatory analyses of μ rhythms are sensitive to stuttering. More specifically, they can reveal stuttering-related sensorimotor processing differences in listening and auditory discrimination that also may be influenced by basal ganglia deficits.

Beta Band Corticomuscular Drive Reflects Muscle Coordination Strategies

During force production, hand muscle activity is known to be coherent with activity in primary motor cortex, specifically in the beta-band (15–30 Hz) frequency range. It is not clear, however, if this coherence reflects the control strategy selected by the nervous system for a given task, or if it instead reflects an intrinsic property of cortico-spinal communication. Here, we measured corticomuscular and intermuscular coherence between muscles of index finger and thumb while a two-finger pinch grip of identical net force was applied to objects which were either stable (allowing synergistic activation of finger muscles) or unstable (requiring individuated finger control). We found that beta-band corticomuscular coherence with the first dorsal interosseous (FDI) and abductor pollicis brevis (APB) muscles, as well as their beta-band coherence with each other, was significantly reduced when individuated control of the thumb and index finger was required. We interpret these findings to show that beta-band coherence is reflective of a synergistic control strategy in which the cortex binds task-related motor neurons into functional units.

Auditory cortical delta-entrainment interacts with oscillatory power in multiple fronto-parietal networks

The timing of slow auditory cortical activity aligns to the rhythmic fluctuations in speech. This entrainment is considered to be a marker of the prosodic and syllabic encoding of speech, and has been shown to correlate with intelligibility. Yet, whether and how auditory cortical entrainment is influenced by the activity in other speech–relevant areas remains unknown. Using source-localized MEG data, we quantified the dependency of auditory entrainment on the state of oscillatory activity in fronto-parietal regions. We found that delta band entrainment interacted with the oscillatory activity in three distinct networks. First, entrainment in the left anterior superior temporal gyrus (STG) was modulated by beta power in orbitofrontal areas, possibly reflecting predictive top-down modulations of auditory encoding. Second, entrainment in the left Heschl's Gyrus and anterior STG was dependent on alpha power in central areas, in line with the importance of motor structures for phonological analysis. And third, entrainment in the right posterior STG modulated theta power in parietal areas, consistent with the engagement of semantic memory. These results illustrate the topographical network interactions of auditory delta entrainment and reveal distinct cross-frequency mechanisms by which entrainment can interact with different cognitive processes underlying speech perception.

•

We study auditory cortical speech entrainment from a network perspective.

•

Found three distinct networks interacting with delta-entrainment in auditory cortex.

•

Entrainment is modulated by frontal beta power, possibly indexing predictions.

•

Central alpha power interacts with entrainment, suggesting motor involvement.

•

Parietal theta is modulated by entrainment, suggesting working memory compensation.

Why Are Children With Epileptic Encephalopathies Encephalopathic?

The epileptic encephalopathies are devastating conditions characterized by frequent seizures, severely abnormal electroencephalograms (EEGs), and cognitive slowing or regression. The cognitive impairment in the epileptic encephalopathies may be more concerning to the patient and parents than the epilepsy itself. There is increasing recognition that the cognitive comorbidity can be both chronic, primarily due to the underlying etiology of the epilepsy, and dynamic or evolving because of recurrent seizures, interictal spikes, and antiepileptic drugs. Much of scholars' understanding of the neurophysiological underpinnings of cognitive dysfunction in the epileptic encephalopathies comes from rodent studies. Frequent seizures and interictal EEG discharges in rats lead to considerable spatial and social-cognitive deficits. Paralleling these cognitive deficits are dyscoordination of dynamic neural activity within and between the neural networks that subserve normal cognitive processes.

A neural mass model of phase-amplitude coupling

Brain activity shows phase-amplitude coupling between its slow and fast oscillatory components. We study phase-amplitude coupling as recorded at individual sites, using a modified version of the well-known Wendling neural mass model. To the population of fast inhibitory interneurons of this model, we added external modulatory input and dynamic self-feedback. These two modifications together are sufficient to let the inhibitory population serve as a limit-cycle oscillator, with frequency characteristics comparable to the beta and gamma bands. The frequency and power of these oscillations can be tuned through the time constant of the dynamic and modulatory input. Alpha band activity is generated, as is usual in such models, as a result of interactions of pyramidal neurons and a population of slow inhibitory interneurons. The slow inhibitory population activity directly influences the fast oscillations via the synaptic gain between slow and fast inhibitory populations. As a result, the amplitude envelope of the fast oscillation is coupled to the phase of the slow activity; this result is consistent with the notion that phase-amplitude coupling is effectuated by interactions between inhibitory interneurons.

Temporal Coordination of Hippocampal Neurons Reflects Cognitive Outcome Post-febrile Status Epilepticus

The coordination of dynamic neural activity within and between neural networks is believed to underlie normal cognitive processes. Conversely, cognitive deficits that occur following neurological insults may result from network discoordination. We hypothesized that cognitive outcome following febrile status epilepticus (FSE) depends on network efficacy within and between fields CA1 and CA3 to dynamically organize cell activity by theta phase. Control and FSE rats were trained to forage or perform an active avoidance spatial task. FSE rats were sorted by those that were able to reach task criterion (FSE-L) and those that could not (FSE-NL). FSE-NL CA1 place cells did not exhibit phase preference in either context and exhibited poor cross-theta interaction between CA1 and CA3. FSE-L and control CA1 place cells exhibited phase preference at peak theta that shifted during active avoidance to the same static phase preference observed in CA3. Temporal coordination of neuronal activity by theta phase may therefore explain variability in cognitive outcome following neurological insults in early development.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

Long-Lasting Cortical Reorganization as the Result of Motor Imagery of Throwing a Ball in a Virtual Tennis Court

In order to characterize the neural signature of a motor imagery (MI) task, the present study investigates for the first time the oscillation characteristics including both of the time-frequency measurements, event related spectral perturbation and intertrial coherence (ITC) underlying the variations in the temporal measurements (event related potentials, ERP) directly related to a MI task. We hypothesize that significant variations in both of the time-frequency measurements underlie the specific changes in the ERP directly related to MI. For the MI task, we chose a simple everyday task (throwing a tennis ball), that does not require any particular motor expertise, set within the controlled virtual reality scenario of a tennis court. When compared to the rest condition a consistent, long-lasting negative fronto-central ERP wave was accompanied by significant changes in both time frequency measurements suggesting long-lasting cortical activity reorganization. The ERP wave was characterized by two peaks at about 300 ms (N300) and 1000 ms (N1000). The N300 component was centrally localized on the scalp and was accompanied by significant phase consistency in the delta brain rhythms in the contralateral central scalp areas. The N1000 component spread wider centrally and was accompanied by a significant power decrease (or event related desynchronization) in low beta brain rhythms localized in fronto-precentral and parieto-occipital scalp areas and also by a significant power increase (or event related synchronization) in theta brain rhythms spreading fronto-centrally. During the transition from N300 to N1000, a contralateral alpha (mu) as well as post-central and parieto-theta rhythms occurred. The visual representation of movement formed in the minds of participants might underlie a top-down process from the fronto-central areas which is reflected by the amplitude changes observed in the fronto-central ERPs and by the significant phase synchrony in contralateral fronto-central delta and contralateral central mu to parietal theta presented here.

Task-related activity in sensorimotor cortex in Parkinson's disease and essential tremor: changes in beta and gamma bands

In Parkinson's disease patients in the OFF medication state, basal ganglia local field potentials exhibit changes in beta and gamma oscillations that correlate with reduced voluntary movement, manifested as rigidity and akinesia. However, magnetoencephalography and low-resolution electrocorticography (ECoG) studies in Parkinson's patients suggest that changes in sensorimotor cortical oscillations differ from those of the basal ganglia. To more clearly define the role of sensorimotor cortex oscillatory activity in Parkinson's, we performed intraoperative, high-resolution (4 mm spacing) ECoG recordings in 10 Parkinson's patients (2 females, ages 47–72) undergoing deep brain stimulation (DBS) lead placement in the awake, OFF medication state. We analyzed ECoG potentials during a computer-controlled reaching task designed to separate movement preparation from movement execution and compared findings to similar invasive recordings in eight patients with essential tremor (3 females, ages 59–78), a condition not associated with rigidity or akinesia. We show that (1) cortical beta spectral power at rest does not differ between Parkinson's and essential tremor patients (p = 0.85), (2) early motor preparation in Parkinson's patients in the OFF medication state is associated with a larger beta desynchronization compared to patients with essential tremor (p = 0.0061), and (3) cortical broadband gamma power is elevated in Parkinson's patients compared to essential tremor patients during both rest and task recordings (p = 0.004). Our findings suggest an oscillatory profile in sensorimotor cortex of Parkinson's patients that, in contrast to the basal ganglia, may act to promote movement to oppose the anti-kinetic bias of the dopamine-depleted state.

Lateralized modulation of beta-band power in sensorimotor areas during action observation

The cortical network for action observation includes areas of the visual cortex and non-visual areas, including areas of the motoric system. Parts of this network are known for their contralateral organization during motion execution, i.e., they predominantly control and respond to movements of the contralateral body side. We were interested whether this lateralized organization was also present during action observation. Human participants viewed point-light displays of human actors, where the actor was facing and moving either to the right or to the left, while participants' neuromagnetic activity was recorded using magnetoencephalography (MEG). We found that right and left facing movements elicited different activity in left and right motoric areas. This lateralization effect was found in two distinct spatio-temporal-spectral clusters: An early lateralization effect in medial sensors at 12-16 Hz and ~276-675 ms after stimulus onset, and a second cluster in more lateral sensors at 22-28 Hz and ~1275-1775 ms. Our results demonstrate that in addition to the known somatotopic organization of parts of the human motoric system, these areas also show a lateralization effect during action observation. Thus, our results indicate that the hemispheric organization of one's own body map known for motion execution extends to the visual observation of others' bodily actions and movements.

Alterations in sociability and functional brain connectivity caused by early-life seizures are prevented by bumetanide

There is a well-described association between infantile epilepsy and pervasive cognitive and behavioral deficits, including a high incidence of autism spectrum disorders. Despite the robustness of the relationship between early-life seizures and the development of autism, the pathophysiological mechanism by which this occurs has not been explored. As a result of increasing evidence that autism is a disorder of brain connectivity we hypothesized that early-life seizures would interrupt normal brain connectivity during brain maturation and result in an autistic phenotype. Normal rat pups underwent recurrent flurothyl-induced seizures from postnatal (P)days 5-14 and then tested, along with controls, for developmental alterations of development brain oscillatory activity from P18-P25. Specifically we wished to understand how normal changes in rhythmicity in and between brain regions change as a function of age and if this rhythmicity is altered or interrupted by early life seizures. In rat pups with early-life seizures, field recordings from dorsal and ventral hippocampus and prefrontal cortex demonstrated marked increase in coherence as well as a decrease in voltage correlation at all bandwidths compared to controls while there were minimal differences in total power and relative power spectral densities. Rats with early-life seizures had resulting impairment in the sociability and social novelty tests but demonstrated no evidence of increased activity or generalized anxiety as measured in the open field. In addition, rats with early-life seizures had lower seizure thresholds than controls, indicating long-standing alterations in the excitatory/inhibition balance. Bumetanide, a pharmacological agent that blocks the activity of NKCC1 and induces a significant shift of ECl toward more hyperpolarized values, administration at the time of the seizures precluded the subsequent abnormalities in coherence and voltage correlation and resulted in normal sociability and seizure threshold. Taken together these findings indicate that early-life seizures alter the development of oscillations and result in autistic-like behaviors. The altered communication between these brain regions could reflect the physiological underpinnings underlying social cognitive deficits seen in autism spectrum disorders.

Dynamic recruitment of resting state sub-networks

Resting state networks (RSNs) are of fundamental importance in human systems neuroscience with evidence suggesting that they are integral to healthy brain function and perturbed in pathology. Despite rapid progress in this area, the temporal dynamics governing the functional connectivities that underlie RSN structure remain poorly understood. Here, we present a framework to help further our understanding of RSN dynamics. We describe a methodology which exploits the direct nature and high temporal resolution of magnetoencephalography (MEG). This technique, which builds on previous work, extends from solving fundamental confounds in MEG (source leakage) to multivariate modelling of transient connectivity. The resulting processing pipeline facilitates direct (electrophysiological) measurement of dynamic functional networks. Our results show that, when functional connectivity is assessed in small time windows, the canonical sensorimotor network can be decomposed into a number of transiently synchronising sub-networks, recruitment of which depends on current mental state. These rapidly changing sub-networks are spatially focal with, for example, bilateral primary sensory and motor areas resolved into two separate sub-networks. The likely interpretation is that the larger canonical sensorimotor network most often seen in neuroimaging studies reflects only a temporal aggregate of these transient sub-networks. Our approach opens new frontiers to study RSN dynamics, showing that MEG is capable of revealing the spatial, temporal and spectral signature of the human connectome in health and disease.

•

The sensorimotor network consists of a series of transiently synchronising subnetworks.

•

These subnetworks are robust across multiple tasks.

•

The occurrence of these subnetworks is modulated by the current mental state.

Cross-frequency transfer in a stochastically driven mesoscopic neuronal model

The brain is known to operate in multiple coexisting frequency bands. Increasing experimental evidence suggests that interactions between those distinct bands play a crucial role in brain processes, but the dynamical mechanisms underlying this cross-frequency coupling are still under investigation. Two approaches have been proposed to address this issue. In the first one distinct nonlinear oscillators representing the brain rhythms involved are coupled actively (bidirectionally), whereas in the second one the oscillators are coupled unidirectionally and thus the driving between them is passive. Here we elaborate the latter approach by implementing a stochastically driven network of coupled neural mass models that operate in the alpha range. This model exhibits a broadband power spectrum with 1/f^b form, similar to those observed experimentally. Our results show that such a model is able to reproduce recent experimental observations on the effect of slow rocking on the alpha activity associated with sleep. This suggests that passive driving can account for cross-frequency transfer in the brain, as a result of the complex nonlinear dynamics of its underlying oscillators.

Estimating cognitive load during self-regulation of brain activity and neurofeedback with therapeutic brain-computer interfaces

Neurofeedback (NFB) training with brain-computer interfaces (BCIs) is currently being studied in a variety of neurological and neuropsychiatric conditions in an aim to reduce disorder-specific symptoms. For this purpose, a range of classification algorithms has been explored to identify different brain states. These neural states, e.g., self-regulated brain activity vs. rest, are separated by setting a threshold parameter. Measures such as the maximum classification accuracy (CA) have been introduced to evaluate the performance of these algorithms. Interestingly enough, precisely these measures are often used to estimate the subject's ability to perform brain self-regulation. This is surprising, given that the goal of improving the tool that differentiates between brain states is different from the aim of optimizing NFB for the subject performing brain self-regulation. For the latter, knowledge about mental resources and work load is essential in order to adapt the difficulty of the intervention accordingly. In this context, we apply an analytical method and provide empirical data to determine the zone of proximal development (ZPD) as a measure of a subject's cognitive resources and the instructional efficacy of NFB. This approach is based on a reconsideration of item-response theory (IRT) and cognitive load theory for instructional design, and combines them with the CA curve to provide a measure of BCI performance.

Parametric estimation of cross-frequency coupling

•

We revisit the general linear model (GLM) approach to cross-frequency coupling.

•

Continuous time series were split into epochs for parametric statistical tests.

•

The GLM and permutation tests produced similar results in experimental data.

•

The GLM offers a good trade-off between computation time and statistical power.

•

Other predictors such as amplitude-amplitude coupling can be easily included.

Background

Growing experimental evidence suggests an important role for cross-frequency coupling in neural processing, in particular for phase-amplitude coupling (PAC). Although the details of methods to detect PAC may vary, a common procedure to estimate the significance level is the comparison of observed values to those of at least 100 surrogate time series. When scanning large parts of the frequency spectrum and multiple recording sites, this could amount to very large computation times.

New method

We demonstrate that the general linear model (GLM) allows for a parametric estimation of significant PAC. Continuous recordings are split into epochs, of a few seconds duration, on which an F-test can be performed. We compared its performance against traditional non-parametric permutation tests in both simulated and experimental data.

Results

Our method was able to reproduce findings of phase-amplitude coupling in local field potential recordings obtained from the subthalamic nucleus in patients with Parkinson's disease. We also show that PAC may be detected between the subthalamic nucleus and cortical motor areas.

Comparison with existing method(s)

Although the GLM slightly underestimated significance compared to permutation tests in the simulations, for experimental data the two methods produced highly similar results. Computation times were drastically lower for the GLM. Furthermore, we demonstrate that the GLM can be easily extended by including additional predictors such as low-frequency amplitude to test for amplitude-amplitude coupling.

Conclusions

The GLM forms an adequate and computationally efficient approach for detecting cross-frequency coupling with the flexibility to add other explanatory variables of interest.

Distinct roles for alpha- and beta-band oscillations during mental simulation of goal-directed actions

Rhythmic neural activity within the alpha (8-12 Hz) and beta (15-25 Hz) frequency bands is modulated during actual and imagined movements. Changes in these rhythms provide a mechanism to select relevant neuronal populations, although the relative contributions of these rhythms remain unclear. Here we use MEG to investigate changes in oscillatory power while healthy human participants imagined grasping a cylinder oriented at different angles. This paradigm allowed us to study the neural signals involved in the simulation of a movement in the absence of signals related to motor execution and sensory reafference. Movement selection demands were manipulated by exploiting the fact that some object orientations evoke consistent grasping movements, whereas others are compatible with both overhand and underhand grasping. By modulating task demands, we show a functional dissociation of the alpha- and beta-band rhythms. As movement selection demands increased, alpha-band oscillatory power increased in the sensorimotor cortex ipsilateral to the arm used for imagery, whereas beta-band power concurrently decreased in the contralateral sensorimotor cortex. The same pattern emerged when motor imagery trials were compared with a control condition, providing converging evidence for the functional dissociation of the two rhythms. These observations call for a re-evaluation of the role of sensorimotor rhythms. We propose that neural oscillations in the alpha-band mediate the allocation of computational resources by disengaging task-irrelevant cortical regions. In contrast, the reduction of neural oscillations in the beta-band is directly related to the disinhibition of neuronal populations involved in the computations of movement parameters.

Non-invasive detection of high gamma band activity during motor imagery

High gamma oscillations (70-150 Hz; HG) are rapidly evolving, spatially localized neurophysiological signals that are believed to be the best representative signature of engaged neural populations. The HG band has been best characterized from invasive electrophysiological approaches such as electrocorticography because of the increased signal-to-noise ratio that results when by-passing the scalp and skull. Despite the recent observation that HG activity can be detected non-invasively by electroencephalography (EEG), it is unclear to what extent EEG can accurately resolve the spatial distribution of HG signals during active task engagement. We have overcome some of the limitations inherent to acquiring HG signals across the scalp by utilizing individual head anatomy in combination with an inverse modeling method. We applied a linearly constrained minimum variance (LCMV) beamformer method on EEG data during a motor imagery paradigm to extract a time-frequency spectrogram at every voxel location on the cortex. To confirm spatially distributed patterns of HG responses, we contrasted overlapping maps of the EEG HG signal with blood oxygen level dependence (BOLD) functional magnetic resonance imaging (fMRI) data acquired from the same set of neurologically normal subjects during a separate session. We show that scalp-based HG band activity detected by EEG during motor imagery spatially co-localizes with BOLD fMRI data. Taken together, these results suggest that EEG can accurately resolve spatially specific estimates of local cortical high frequency signals, potentially opening an avenue for non-invasive measurement of HG potentials from diverse sets of neurologically impaired populations for diagnostic and therapeutic purposes.

Grasping hand verbs: oscillatory beta and alpha correlates of action-word processing

The grounded cognition framework proposes that sensorimotor brain areas, which are typically involved in perception and action, also play a role in linguistic processing. We assessed oscillatory modulation during visual presentation of single verbs and localized cortical motor regions by means of isometric contraction of hand and foot muscles. Analogously to oscillatory activation patterns accompanying voluntary movements, we expected a somatotopically distributed suppression of beta and alpha frequencies in the motor cortex during processing of body-related action verbs. Magnetoencephalographic data were collected during presentation of verbs that express actions performed using the hands (H) or feet (F). Verbs denoting no bodily movement (N) were used as a control. Between 150 and 500 msec after visual word onset, beta rhythms were suppressed in H and F in comparison with N in the left hemisphere. Similarly, alpha oscillations showed left-lateralized power suppression in the H-N contrast, although at a later stage. The cortical oscillatory activity that typically occurs during voluntary movements is therefore found to somatotopically accompany the processing of body-related verbs. The combination of a localizer task with the oscillatory investigation applied to verb reading as in the present study provides further methodological possibilities of tracking language processing in the brain.

Differential oscillatory electroencephalogram between attention-deficit/hyperactivity disorder subtypes and typically developing adolescents

BACKGROUND

A neurobiological-based classification of attention-deficit/hyperactivity disorder (ADHD) subtypes has thus far remained elusive. The aim of this study was to use oscillatory changes in the electroencephalogram (EEG) related to informative cue processing, motor preparation, and top-down control to investigate neurophysiological differences between typically developing (TD) adolescents, and those diagnosed with predominantly inattentive (IA) or combined (CB) (associated with symptoms of inattention as well as impulsivity/hyperactivity) subtypes of ADHD.

METHODS

The EEG was recorded from 57 rigorously screened adolescents (12 to 17 years of age; 23 TD, 17 IA, and 17 CB), while they performed a cued flanker task. We examined the oscillatory changes in theta (3-5 Hz), alpha (8-12 Hz), and beta (22-25 Hz) EEG bands after cues that informed participants with which hand they would subsequently be required to respond.

RESULTS

Relative to TD adolescents, the IA group showed significantly less postcue alpha suppression, suggesting diminished processing of the cue in the visual cortex, whereas the CB group showed significantly less beta suppression at the electrode contralateral to the cued response hand, suggesting poor motor planning. Finally, both ADHD subtypes showed weak functional connectivity between frontal theta and posterior alpha, suggesting common top-down control impairment.

CONCLUSIONS

We found both distinct and common task-related neurophysiological impairments in ADHD subtypes. Our results suggest that task-induced changes in EEG oscillations provide an objective measure, which in conjunction with other sources of information might help distinguish between ADHD subtypes and therefore aid in diagnoses and evaluation of treatment.

EEG source connectivity analysis: from dense array recordings to brain networks

The recent past years have seen a noticeable increase of interest for electroencephalography (EEG) to analyze functional connectivity through brain sources reconstructed from scalp signals. Although considerable advances have been done both on the recording and analysis of EEG signals, a number of methodological questions are still open regarding the optimal way to process the data in order to identify brain networks. In this paper, we analyze the impact of three factors that intervene in this processing: i) the number of scalp electrodes, ii) the combination between the algorithm used to solve the EEG inverse problem and the algorithm used to measure the functional connectivity and iii) the frequency bands retained to estimate the functional connectivity among neocortical sources. Using High-Resolution (hr) EEG recordings in healthy volunteers, we evaluated these factors on evoked responses during picture recognition and naming task. The main reason for selection this task is that a solid literature background is available about involved brain networks (ground truth). From this a priori information, we propose a performance criterion based on the number of connections identified in the regions of interest (ROI) that belong to potentially activated networks. Our results show that the three studied factors have a dramatic impact on the final result (the identified network in the source space) as strong discrepancies were evidenced depending on the methods used. They also suggest that the combination of weighted Minimum Norm Estimator (wMNE) and the Phase Synchronization (PS) methods applied on High-Resolution EEG in beta/gamma bands provides the best performance in term of topological distance between the identified network and the expected network in the above-mentioned cognitive task.

Different roles of alpha and beta band oscillations in anticipatory sensorimotor gating

Alpha (8–12 Hz) and beta band (18–30 Hz) oscillations have been implicated in sensory anticipation and motor preparation. Here, using magneto-encephalography, we tested whether they have distinct functional roles in a saccade task that induces a remapping between sensory and motor reference frames. With a crossed hands posture, subjects had to saccade as fast and accurate as possible toward a tactile stimulus delivered to one of two non-visible index fingers, located to the left or right of gaze. Previous studies have shown that this task, in which the somatotopic stimulus must be remapped to activate oculomotor system in the opposing hemisphere, is occasionally preceded by intrahemispheric remapping, driving a premature saccade into the wrong direction. To test whether the brain could anticipate the remapping, we provided auditory predictive cues (80% validity), which indicated which finger is most likely to be stimulated. Both frequency bands showed different lateralization profiles at central vs. posterior sensors, indicating anticipation of somatosensory and oculomotor processing. Furthermore, beta band power in somatosensory cortex correlated positively with saccade reaction time (SRT), with correlation values that were significantly higher with contralateral vs. ipsilateral activation. In contrast, alpha band power in parietal cortex correlated negatively with SRT, with correlation values that were significantly more negative with ipsilateral than contralateral activation. These results suggest distinct functional roles of beta and alpha band activity: (1) somatosensory gating by beta oscillations, increasing excitability in contralateral somatosensory cortex (positive correlation); and (2) oculomotor gating by posterior alpha oscillations, inhibiting gaze-centered oculomotor regions involved in generating the saccade to the wrong direction (negative correlation). Our results show that low frequency rhythms gate upcoming sensorimotor transformations.