Mu Rhythm Research Articles

Mirroring Communicative Actions: Contextual Modulation of Mu Rhythm Desynchronization in Response to the ‘Back-Of-Hand’ Action in 9-Month-Old Infants

ABSTRACT This study measured mu rhythm desynchronization (MRD), while nine-month-old infants observed an agent extend her arm and hand, palm up (‘back-of-hand action’) either in social (object and recipient present), individual (object present, recipient absent), or social object-absent (recipient present, object absent) situations across two experiments. In addition, infants’ MRD was measured as they reached for objects. Results revealed significant mu desynchronization in the right centro-parietal region selectively for the social group, indicating that infants processed the back-of-hand action as an object-directed request. Findings suggest to extend the action reconstruction account to object-directed communicative actions as well.

Sensorimotor Rhythm-Brain Computer Interface With Audio-Cue, Motor Observation and Multisensory Feedback for Upper-Limb Stroke Rehabilitation: A Controlled Study.

Several studies have shown the positive clinical effect of brain computer interface (BCI) training for stroke rehabilitation. This study investigated the efficacy of the sensorimotor rhythm (SMR)-based BCI with audio-cue, motor observation and multisensory feedback for post-stroke rehabilitation. Furthermore, we discussed the interaction between training intensity and training duration in BCI training. Twenty-four stroke patients with severe upper limb (UL) motor deficits were randomly assigned to two groups: 2-week SMR-BCI training combined with conventional treatment (BCI Group, BG, n = 12) and 2-week conventional treatment without SMR-BCI intervention (Control Group, CG, n = 12). Motor function was measured using clinical measurement scales, including Fugl-Meyer Assessment-Upper Extremities (FMA-UE; primary outcome measure), Wolf Motor Functional Test (WMFT), and Modified Barthel Index (MBI), at baseline (Week 0), post-intervention (Week 2), and follow-up week (Week 4). EEG data from patients allocated to the BG was recorded at Week 0 and Week 2 and quantified by mu suppression means event-related desynchronization (ERD) in mu rhythm (8–12 Hz). All functional assessment scores (FMA-UE, WMFT, and MBI) significantly improved at Week 2 for both groups (p < 0.05). The BG had significantly higher FMA-UE and WMFT improvement at Week 4 compared to the CG. The mu suppression of bilateral hemisphere both had a positive trend with the motor function scores at Week 2. This study proposes a new effective SMR-BCI system and demonstrates that the SMR-BCI training with audio-cue, motor observation and multisensory feedback, together with conventional therapy may promote long-lasting UL motor improvement.Clinical Trial Registration: [http://www.chictr.org.cn], identifier [ChiCTR2000041119].

Age-related Differences in Mu Rhythm During Emotional Destination Memory Task.

Destination memory defined as the ability to remember to whom we addressed a piece of information is found to be impaired in normal aging. Theories of affect development and research findings have shown that emotional charging improves performance on memory tasks, and also that Mu rhythm is desynchronized as an index of mirror neuron activation during such tasks. In this paper, we sought to investigate the differences in Mu rhythm during an emotional destination memory task, between younger and older adults. 16 cognitively normal older adults, recruited from Alzheimer's disease day center and 16 young adults, recruited via advertisements, participated in this experimental study. We investigated destination memory of emotionally charged faces (Emotional Destination Memory, EDM) while applying electroencephalograph (EEG) in real time in young versus older adults. We measured Mu rhythm in frontal, fronto-temporal and central areas. EEG data has been pre-processed, segmented in non-overlapping epochs, and independent component analysis (ICA) has been conducted to reject artifacts. Results showed that young adults performed better than older adults in remembering facts associated with angry faces. Also, different neurophysiological activation was found, with older adults showing Mu suppression in frontal and fronto-temporal regions, specifically in F3, F7 and F8 electrodes, in contrast with young adults who showed Mu enhancement. Regarding within group differences, it was found that in the older adults group, electrodes F8 and central C3 were the most activated, while in the young adults group, C3 was the most activated electrode. The findings suggest better behavioral performance of young adults as a result of better cognitive state and adaptive bias. On a neurophysiological level, it is suggested that older adults employ Mu suppression, thus possible activation of mirror neurons, as a compensatory mechanism while mirroring properties are not spontaneously activated in young adults.

Mu rhythm suppression over sensorimotor regions is associated with greater empathic accuracy.

When people encounter others’ emotions, they engage multiple brain systems, including parts of the sensorimotor cortex associated with motor simulation. Simulation-related brain activity is commonly described as a ‘low-level’ component of empathy and social cognition. It remains unclear whether and how sensorimotor simulation contributes to complex empathic judgments. Here, we combine a naturalistic social paradigm with a reliable index of sensorimotor cortex-based simulation: electroencephalography suppression of oscillatory activity in the mu frequency band. We recruited participants to watch naturalistic video clips of people (‘targets’) describing emotional life events. In two experiments, participants viewed these clips (i) with video and sound, (ii) with only video or (iii) with only sound and provided continuous ratings of how they believed the target felt. We operationalized ‘empathic accuracy’ as the correlation between participants’ inferences and targets’ self-report. In Experiment 1 (US sample), across all conditions, right-lateralized mu suppression tracked empathic accuracy. In Experiment 2 (Israeli sample), this replicated only when using individualized frequency-bands and only for the visual stimuli. Our results provide novel evidence that sensorimotor representations—as measured through mu suppression—play a role not only in low-level motor simulation, but also in higher-level inferences about others’ emotions, especially when visual cues are crucial for accuracy.

EEG–EMG coupling as a hybrid method for steering detection in car driving settings

Understanding mental processes in complex human behavior is a key issue in driving, representing a milestone for developing user-centered assistive driving devices. Here, we propose a hybrid method based on electroencephalographic (EEG) and electromyographic (EMG) signatures to distinguish left and right steering in driving scenarios. Twenty-four participants took part in the experiment consisting of recordings of 128-channel EEG and EMG activity from deltoids and forearm extensors in non-ecological and ecological steering tasks. Specifically, we identified the EEG mu rhythm modulation correlates with motor preparation of self-paced steering actions in the non-ecological task, while the concurrent EMG activity of the left (right) deltoids correlates with right (left) steering. Consequently, we exploited the mu rhythm de-synchronization resulting from the non-ecological task to detect the steering side using cross-correlation analysis with the ecological EMG signals. Results returned significant cross-correlation values showing the coupling between the non-ecological EEG feature and the muscular activity collected in ecological driving conditions. Moreover, such cross-correlation patterns discriminate the steering side earlier relative to the single EMG signal. This hybrid system overcomes the limitation of the EEG signals collected in ecological settings such as low reliability, accuracy, and adaptability, thus adding to the EMG the characteristic predictive power of the cerebral data. These results prove how it is possible to complement different physiological signals to control the level of assistance needed by the driver.

Neural Suppression Elicited During Motor Imagery Following the Observation of Biological Motion From Point-Light Walker Stimuli.

Introduction: Advantageous effects of biological motion (BM) detection, a low-perceptual mechanism that allows the rapid recognition and understanding of spatiotemporal characteristics of movement via salient kinematics information, can be amplified when combined with motor imagery (MI), i.e., the mental simulation of motor acts. According to Jeannerod’s neurostimulation theory, asynchronous firing and reduction of mu and beta rhythm oscillations, referred to as suppression over the sensorimotor area, are sensitive to both MI and action observation (AO) of BM. Yet, not many studies investigated the use of BM stimuli using combined AO-MI tasks. In this study, we assessed the neural response in the form of event-related synchronization and desynchronization (ERD/S) patterns following the observation of point-light-walkers and concordant MI, as compared to MI alone.Methods: Twenty right-handed healthy participants accomplished the experimental task by observing BM stimuli and subsequently performing the same movement using kinesthetic MI (walking, cycling, and jumping conditions). We recorded an electroencephalogram (EEG) with 32 channels and performed time-frequency analysis on alpha (8–13 Hz) and beta (18–24 Hz) frequency bands during the MI task. A two-way repeated-measures ANOVA was performed to test statistical significance among conditions and electrodes of interest.Results: The results revealed significant ERD/S patterns in the alpha frequency band between conditions and electrode positions. Post hoc comparisons showed significant differences between condition 1 (walking) and condition 3 (jumping) over the left primary motor cortex. For the beta band, a significantly less difference in ERD patterns (p < 0.01) was detected only between condition 3 (jumping) and condition 4 (reference).Discussion: Our results confirmed that the observation of BM combined with MI elicits a neural suppression, although just in the case of jumping. This is in line with previous findings of AO and MI (AOMI) eliciting a neural suppression for simulated whole-body movements. In the last years, increasing evidence started to support the integration of AOMI training as an adjuvant neurorehabilitation tool in Parkinson’s disease (PD).Conclusion: We concluded that using BM stimuli in AOMI training could be promising, as it promotes attention to kinematic features and imitative motor learning.

Spotted around the web: Virtual reality, mu rhythm, ‘tortured phrases’

Spotted around the web: Virtual reality, mu rhythm, ‘tortured phrases’

A Transformer-Based Approach Combining Deep Learning Network and Spatial-Temporal Information for Raw EEG Classification.

The attention mechanism of the Transformer has the advantage of extracting feature correlation in the long-sequence data and visualizing the model. As time-series data, the spatial and temporal dependencies of the EEG signals between the time points and the different channels contain important information for accurate classification. So far, Transformer-based approaches have not been widely explored in motor-imagery EEG classification and visualization, especially lacking general models based on cross-individual validation. Taking advantage of the Transformer model and the spatial-temporal characteristics of the EEG signals, we designed Transformer-based models for classifications of motor imagery EEG based on the PhysioNet dataset. With 3s EEG data, our models obtained the best classification accuracy of 83.31%, 74.44%, and 64.22% on two-, three-, and four-class motor-imagery tasks in cross-individual validation, which outperformed other state-of-the-art models by 0.88%, 2.11%, and 1.06%. The inclusion of the positional embedding modules in the Transformer could improve the EEG classification performance. Furthermore, the visualization results of attention weights provided insights into the working mechanism of the Transformer-based networks during motor imagery tasks. The topography of the attention weights revealed a pattern of event-related desynchronization (ERD) which was consistent with the results from the spectral analysis of Mu and beta rhythm over the sensorimotor areas. Together, our deep learning methods not only provide novel and powerful tools for classifying and understanding EEG data but also have broad applications for brain-computer interface (BCI) systems.

Cortical mu rhythms during action and passive music listening.

Brain systems supporting body movement are active during music listening in the absence of overt movement. This covert motor activity is not well understood, but some theories propose a role in auditory timing prediction facilitated by motor simulation. One question is how music-related covert motor activity relates to motor activity during overt movement. We address this question using scalp electroencephalogram by measuring mu rhythms-cortical field phenomena associated with the somatomotor system that appear over sensorimotor cortex. Lateralized mu enhancement over hand sensorimotor cortex during/just before foot movement in foot versus hand movement paradigms is thought to reflect hand movement inhibition during current/prospective movement of another effector. Behavior of mu during music listening with movement suppressed has yet to be determined. We recorded 32-channel EEG (n = 17) during silence without movement, overt movement (foot/hand), and music listening without movement. Using an independent component analysis-based source equivalent dipole clustering technique, we identified three mu-related clusters, localized to left primary motor and right and midline premotor cortices. Right foot tapping was accompanied by mu enhancement in the left lateral source cluster, replicating previous work. Music listening was accompanied by similar mu enhancement in the left, as well as midline, clusters. We are the first, to our knowledge, to report, and also to source-resolve, music-related mu modulation in the absence of overt movements. Covert music-related motor activity has been shown to play a role in beat perception (Ross JM, Iversen JR, Balasubramaniam R. Neurocase 22: 558-565, 2016). Our current results show enhancement in somatotopically organized mu, supporting overt motor inhibition during beat perception.NEW & NOTEWORTHY We are the first to report music-related mu enhancement in the absence of overt movements and the first to source-resolve mu activity during music listening. We suggest that music-related mu modulation reflects overt motor inhibition during passive music listening. This work is relevant for the development of theories relating to the involvement of covert motor system activity for predictive beat perception.

A Toolbox and Crowdsourcing Platform for Automatic Labeling of Independent Components in Electroencephalography.

Independent Component Analysis (ICA) is a conventional approach to exclude non-brain signals such as eye movements and muscle artifacts from electroencephalography (EEG). A rejection of independent components (ICs) is usually performed in semiautomatic mode and requires experts’ involvement. As also revealed by our study, experts’ opinions about the nature of a component often disagree, highlighting the need to develop a robust and sustainable automatic system for EEG ICs classification. The current article presents a toolbox and crowdsourcing platform for Automatic Labeling of Independent Components in Electroencephalography (ALICE) available via link http://alice.adase.org/. The ALICE toolbox aims to build a sustainable algorithm to remove artifacts and find specific patterns in EEG signals using ICA decomposition based on accumulated experts’ knowledge. The difference from previous toolboxes is that the ALICE project will accumulate different benchmarks based on crowdsourced visual labeling of ICs collected from publicly available and in-house EEG recordings. The choice of labeling is based on the estimation of IC time-series, IC amplitude topography, and spectral power distribution. The platform allows supervised machine learning (ML) model training and re-training on available data subsamples for better performance in specific tasks (i.e., movement artifact detection in healthy or autistic children). Also, current research implements the novel strategy for consentient labeling of ICs by several experts. The provided baseline model could detect noisy IC and components related to the functional brain oscillations such as alpha and mu rhythm. The ALICE project implies the creation and constant replenishment of the IC database, which will improve ML algorithms for automatic labeling and extraction of non-brain signals from EEG. The toolbox and current dataset are open-source and freely available to the researcher community.

Graspability Modulates the Stronger Neural Signature of Motor Preparation for Real Objects vs. Pictures.

The cognitive and neural bases of visual perception are typically studied using pictures rather than real-world stimuli. Unlike pictures, real objects are actionable solids that can be manipulated with the hands. Recent evidence from human brain imaging suggests that neural responses to real objects differ from responses to pictures; however, little is known about the neural mechanisms that drive these differences. Here, we tested whether brain responses to real objects versus pictures are differentially modulated by the "in-the-moment" graspability of the stimulus. In human dorsal cortex, electroencephalographic responses show a "real object advantage" in the strength and duration of mu (μ) and low beta (β) rhythm desynchronization-well-known neural signatures of visuomotor action planning. We compared desynchronization for real tools versus closely matched pictures of the same objects, when the stimuli were positioned unoccluded versus behind a large transparent barrier that prevented immediate access to the stimuli. We found that, without the barrier in place, real objects elicited stronger μ and β desynchronization compared to pictures, both during stimulus presentation and after stimulus offset, replicating previous findings. Critically, however, with the barrier in place, this real object advantage was attenuated during the period of stimulus presentation, whereas the amplification in later periods remained. These results suggest that the "real object advantage" is driven initially by immediate actionability, whereas later differences perhaps reflect other, more inherent properties of real objects. The findings showcase how the use of richer multidimensional stimuli can provide a more complete and ecologically valid understanding of object vision.

Mu rhythm dynamics suggest automatic activation of motor and premotor brain regions during speech processing

Results are mixed regarding the question of whether listening to speech activates automatic speech specific neural processes, or whether such activity is due to general cognitive mechanisms such as attention and memory. We suggest that analyzing the dynamics of mu rhythms over the course of a trial using event-related spectral perturbations (ERSPs) is useful for disentangling the competing hypotheses. Our findings suggest that there is automatic activation of motor and premotor areas of the brain that occurs while passively listening to speech, and that this activation is not present while listening to noise. Moreover, this activation is more strongly present in the low alpha frequencies, which are associated with attention, when participants engage in active discrimination of stimuli, and late in the trial prior to a button press.

Ipsilesional Mu Rhythm Desynchronization Correlates With Improvements in Affected Hand Grip Strength and Functional Connectivity in Sensorimotor Cortices Following BCI-FES Intervention for Upper Extremity in Stroke Survivors.

Stroke is a leading cause of acquired long-term upper extremity motor disability. Current standard of care trajectories fail to deliver sufficient motor rehabilitation to stroke survivors. Recent research suggests that use of brain-computer interface (BCI) devices improves motor function in stroke survivors, regardless of stroke severity and chronicity, and may induce and/or facilitate neuroplastic changes associated with motor rehabilitation. The present sub analyses of ongoing crossover-controlled trial NCT02098265 examine first whether, during movements of the affected hand compared to rest, ipsilesional Mu rhythm desynchronization of cerebral cortical sensorimotor areas [Brodmann’s areas (BA) 1-7] is localized and tracks with changes in grip force strength. Secondly, we test the hypothesis that BCI intervention results in changes in frequency-specific directional flow of information transmission (direct path functional connectivity) in BA 1-7 by measuring changes in isolated effective coherence (iCoh) between cerebral cortical sensorimotor areas thought to relate to electrophysiological signatures of motor actions and motor learning. A sample of 16 stroke survivors with right hemisphere lesions (left hand motor impairment), received a maximum of 18–30 h of BCI intervention. Electroencephalograms were recorded during intervention sessions while outcome measures of motor function and capacity were assessed at baseline and completion of intervention. Greater desynchronization of Mu rhythm, during movements of the impaired hand compared to rest, were primarily localized to ipsilesional sensorimotor cortices (BA 1-7). In addition, increased Mu desynchronization in the ipsilesional primary motor cortex, Post vs. Pre BCI intervention, correlated significantly with improvements in hand function as assessed by grip force measurements. Moreover, the results show a significant change in the direction of causal information flow, as measured by iCoh, toward the ipsilesional motor (BA 4) and ipsilesional premotor cortices (BA 6) during BCI intervention. Significant iCoh increases from ipsilesional BA 4 to ipsilesional BA 6 were observed in both Mu [8–12 Hz] and Beta [18–26 Hz] frequency ranges. In summary, the present results are indicative of improvements in motor capacity and behavior, and they are consistent with the view that BCI-FES intervention improves functional motor capacity of the ipsilesional hemisphere and the impaired hand.

Altering Facial Movements Abolishes Neural Mirroring of Facial Expressions

People tend to automatically imitate others’ facial expressions of emotion. That reaction, termed “facial mimicry” has been linked to sensorimotor simulation—a process in which the observer’s brain recreates and mirrors the emotional experience of the other person, potentially enabling empathy and deep, motivated processing of social signals. However, the neural mechanisms that underlie sensorimotor simulation remain unclear. This study tests how interfering with facial mimicry by asking participants to hold a pen in their mouth influences the activity of the human mirror neuron system, indexed by the desynchronization of the EEG mu rhythm. This response arises from sensorimotor brain areas during observed and executed movements and has been linked with empathy. We recorded EEG during passive viewing of dynamic facial expressions of anger, fear, and happiness, as well as nonbiological moving objects. We examine mu desynchronization under conditions of free versus altered facial mimicry and show that desynchronization is present when adult participants can freely move but not when their facial movements are inhibited. Our findings highlight the importance of motor activity and facial expression in emotion communication. They also have important implications for behaviors that involve occupying or hiding the lower part of the face.

Exploring developmental changes in infant anticipation and perceptual processing: EEG responses to tactile stimulation.

There is an increasing interest in alpha-range rhythms in the electroencephalogram (EEG) in relation to perceptual and attentional processes. The infant mu rhythm has been extensively studied in the context of linkages between action observation and action production in infancy, but less is known about the mu rhythm in relation to cross-modal processes involving somatosensation. We investigated differences in mu responses to cued vibrotactile stimulation of the hand in two age groups of infants: From 6 to 7months and 13 to 14months. We were also interested in anticipatory neural responses in the alpha frequency range prior to tactile stimulation. Tactile stimulation of infants' left or right hand was preceded by an audiovisual cue signaling which hand would be stimulated. In response to the tactile stimulus, infants demonstrated significant mu desynchronization over the central areas contralateral to the hand stimulated, with higher mu peak frequency and greater contralateral mu desynchronization for older infants. Prior to the tactile stimulus, both age groups showed significant bilateral alpha desynchronization over frontocentral sites, which may be indicative of generalized anticipation of an upcoming stimulus. The findings highlight the potential of examining the sensorimotor mu rhythm in the context of infant attentional development.

Audiovisual incongruence differentially impacts left and right hemisphere sensorimotor oscillations: Potential applications to production.

Speech production gives rise to distinct auditory and somatosensory feedback signals which are dynamically integrated to enable online monitoring and error correction, though it remains unclear how the sensorimotor system supports the integration of these multimodal signals. Capitalizing on the parity of sensorimotor processes supporting perception and production, the current study employed the McGurk paradigm to induce multimodal sensory congruence/incongruence. EEG data from a cohort of 39 typical speakers were decomposed with independent component analysis to identify bilateral mu rhythms; indices of sensorimotor activity. Subsequent time-frequency analyses revealed bilateral patterns of event related desynchronization (ERD) across alpha and beta frequency ranges over the time course of perceptual events. Right mu activity was characterized by reduced ERD during all cases of audiovisual incongruence, while left mu activity was attenuated and protracted in McGurk trials eliciting sensory fusion. Results were interpreted to suggest distinct hemispheric contributions, with right hemisphere mu activity supporting a coarse incongruence detection process and left hemisphere mu activity reflecting a more granular level of analysis including phonological identification and incongruence resolution. Findings are also considered in regard to incongruence detection and resolution processes during production.

EEG-Based Evidence of Mirror Neuron Activity from App-Mediated Stroke Patient Observation.

Background and Objectives: The mirror neuron system in the sensorimotor region of the cerebral cortex is equally activated during both action observation and execution. Action observation training mimics the functioning of the mirror neuron system, requiring patients to watch and imitate the actions necessary to perform activities of daily living. StrokeCare is a user-friendly application based on the principles of action observation training, designed to assist people recovering from stroke. Therefore, when observing the daily life behavior provided in the StrokeCare app, whether the MNS is activated and mu inhibition appears. Materials and Methods: We performed electroencephalography (EEG) on 24 patients with chronic stroke (infarction: 11, hemorrhage: 13) during tasks closely related to daily activities, such as dressing, undressing, and walking. The StrokeCare app provided action videos for patients to watch. Landscape imagery observation facilitated comparison among tasks. We analyzed the mu rhythm from the C3, CZ, and C4 regions and calculated the mean log ratios for comparison of mu suppression values. Results: The EEG mu power log ratios were significantly suppressed during action observation in dressing, undressing, walking, and landscape conditions, in decreasing order. However, there were no significant activity differences in the C3, C4 and CZ regions. The dressing task showed maximum suppression after a color spectrum was used to map the relative power values of the mu rhythm for each task. Conclusions: These findings reveal that the human mirror neuron system was more strongly activated during observation of actions closely related to daily life activities than landscape images.

Effects of perinatal dioxin exposure on mirror neuron activity in 9-year-old children living in a hot spot of dioxin contamination in Vietnam

BackgroundFor 8 years, we have followed up a birth cohort comprising 241 mother-and-infant pairs living around the Da Nang airbase, a hot spot of dioxin contamination in Vietnam, and have reported the impacts of perinatal dioxin exposure on the neurodevelopment of children at various ages. In the present study, 9 years after birth, we investigated the effects of perinatal dioxin exposure on mu and theta rhythms by analyzing EEG power during the execution and observation of hand movements, which indicate mirror neuron system activity. MethodsOne hundred fifty-five 9-year-old children (86 boys and 69 girls) from the Da Nang birth cohort participated in the EEG examination with free viewing of hand movements. The dioxin levels in their mothers’ breast milk, measured 1 month after birth, were used as perinatal dioxin exposure markers. A log transform of the ratio of EEG power during execution or observation of the hand movements relative to the power during observation of a bouncing ball for theta and mu rhythms was used to evaluate mirror neuron activity. ResultsIn both brain hemispheres, the log power ratio in the theta band was significantly higher (i.e., less reduction of power) during observation of hand movements in girls exposed to high levels of TCDD. In boys, however, dioxin congeners other than TCDD, including HxCDDs and several PCDF congeners, contributed to increased log power ratios in the theta band. Particularly for PCDF congeners, the log power ratios in the lowest group among 4 exposure groups were lowest and significantly increased (i.e., decreasing reduction of power) with increasing dose. ConclusionPerinatal TCDD exposure may influence the mirror neuron system of the brain, which plays an important role for social-emotional behavior in children, particularly in girls living in a hot spot of dioxin contamination in Vietnam.

The Early Start Denver Model Intervention and Mu Rhythm Attenuation in Autism Spectrum Disorders.

We examined the relationship between the Early start Denver model (ESDM) intervention and mu rhythm attenuation, an EEG paradigm reflecting neural processes associated with action perception and social information processing. Children were assigned to either receive comprehensive ESDM intervention for two years, or were encouraged to pursue resources in the community. Two years after intervention, EEG was collected during the execution and observation of grasping actions performed by familiar and unfamiliar agents. The ESDM group showed significantly greater attenuation when viewing a parent or caregiver executing a grasping action, compared with an unfamiliar individual executing the same action. Our findings suggest that the ESDM may have a unique impact on neural circuitry underlying social cognition and familiarity.

WS1.3. Normal EEG: Drowsiness and Sleep, and Normal Variants

The EEG in the normal awake child and adult is well known and needs to be known for proper reading and reporting and identifying an abnormal transient or pattern. The following are points of emphasis: Alpha rhythm seen after age of 5 years, Significant theta activity (4–7 Hz) is present in the EEG of children and adolescents. Delta activity in the awake tracing is rarely seen after the age of 5 years. Beta rhythm is seen anteriorly. All these will be discussed in details with traces. In the evaluation of abnormalities in the EEG, one needs to be constantly aware that there are many EEG transients that morphologically resemble epileptiform discharges and that need to be distinguished from diagnostically crucial epileptiform abnormalities to avoid overdiagnosis or misdiagnosis. These include: Artifacts: for example, electrode pop, muscle potentials, eye movements, electrocardiogram (EKG), chewing, electrical, etc. Normal components of ongoing background activity: for example, vertex sharp transients of sleep, f waves, slow wave sleep, POSTs, mu rhythm, lambda waves, drowsy activity during sleep in children that may often be associated with sharp components, etc. Epileptiform variants of dubious clinical significance: there are a large number of benign epileptiform variants that must be recognized, lest they be misinterpreted. Although morphologically similar, they are nonepileptogenic as they have no established relationship with the process responsible for generating epileptic seizures. Such sharp transients include 14 to 6 per second positive spikes, small sharp spikes or benign epileptiform transients of sleep, 6 Hz spike wave or phantom spike wave, wicket spikes, psychomotor variant pattern or rhythmic midtemporal discharges, breach rhythm, etc. Sleep not only activates diagnostically useful epileptiform EEG patterns, but also unmasks several types of nonepileptogenic sharp transients. It is necessary that anyone dedicating a career in epilepsy be well aware of these. Often reading EEG requires eyeballing and identifying patterns. The more the number of EEGs reviewed the more the possibility of not missing out normal patterns and rhythms. These will be demonstrated in various EEG epochs in the workshop.