Cortical dynamics of human scalp EEG origins in a visually guided motor execution

Neural activity related to productive vocabulary knowledge effects during second language comprehension

Second language learners and educators often believe that improving one's listening ability hinges on acquiring an extensive vocabulary and engaging in thorough listening practice. Our previous study suggested that listening comprehension is also impacted by the ability to produce vocabulary. Nevertheless, it remained uncertain whether quick comprehension could be attributed to a simple acceleration of processing or to changes in neural activity. To identify neural activity changes during sentence listening comprehension according to different levels of lexical knowledge (productive, only comprehensive, uncomprehensive), we measured participants' electrical activity in the brain via electroencephalography (EEG) and conducted a time-frequency-based EEG power analysis. Additionally, we employed a decoding model to verify the predictability of vocabulary knowledge levels based on neural activity. The decoding results showed that EEG activity could discriminate between listening to sentences containing phrases that include productive knowledge and ones without. The positive impact of productive vocabulary knowledge on sentence comprehension, driven by distinctive neural processing during sentence comprehension, was unequivocally evident. Our study emphasizes the importance of productive vocabulary knowledge acquisition to enhance the process of second language listening comprehension.

Relationship between electroencephalographic data and comfort perception captured in a Virtual Reality design environment of an aircraft cabin

Successful aircraft cabin design depends on how the different stakeholders are involved since the first phases of product development. To predict passenger satisfaction prior to the manufacturing phase, human response was investigated in a Virtual Reality (VR) environment simulating a cabin aircraft. Subjective assessments of virtual designs have been collected via questionnaires, while the underlying neural mechanisms have been captured through electroencephalographic (EEG) data. In particular, we focused on the modulation of EEG alpha rhythm as a valuable marker of the brain’s internal state and investigated which changes in alpha power and connectivity can be related to a different visual comfort perception by comparing groups with higher and lower comfort rates. Results show that alpha-band power decreased in occipital regions during subjects’ immersion in the virtual cabin compared with the relaxation state, reflecting attention to the environment. Moreover, alpha-band power was modulated by comfort perception: lower comfort was associated with a lower alpha power compared to higher comfort. Further, alpha-band Granger connectivity shows top-down mechanisms in higher comfort participants, modulating attention and restoring partial relaxation. Present results contribute to understanding the role of alpha rhythm in visual comfort perception and demonstrate that VR and EEG represent promising tools to quantify human–environment interactions.

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

BACKGROUND

For 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.

METHODS

One 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.

RESULTS

In 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.

CONCLUSION

Perinatal 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.

Atypical neural processing during the execution of complex sensorimotor behavior in autism

Stereotyped behavior is rhythmic, repetitive movement that is essentially invariant in form. Stereotypy is common in several clinical disorders, such as autism spectrum disorders (ASD), where it is considered maladaptive. However, it also occurs early in typical development (TD) where it is hypothesized to serve as the foundation on which complex, adaptive motor behavior develops. This transition from stereotyped to complex movement in TD is thought to be supported by sensorimotor integration. Stereotypy in clinical disorders may persist due to deficits in sensorimotor integration. The present study assessed whether differences in sensorimotor processing may limit the expression of complex motor behavior in individuals with ASD and contribute to the clinical stereotypy observed in this population. Adult participants with ASD and TD performed a computer-based stimulus-tracking task in the presence and absence of visual feedback. Electroencephalography was recorded during the task. Groups were compared on motor performance (root mean square error), motor complexity (sample entropy), and neural complexity (multiscale sample entropy of the electroencephalography signal) in the presence and absence of visual feedback. No group differences were found for motor performance or motor complexity. The ASD group demonstrated greater neural complexity and greater differences between feedback conditions than TD individuals, specifically in signals relevant to sensorimotor processing. Motor performance and motor complexity correlated with clinical stereotypy in the ASD group. These findings support the hypothesis that individuals with ASD have differences in sensorimotor processing when executing complex motor behavior and that stereotypy is associated with low motor complexity.

Recognizing humanity: dehumanization predicts neural mirroring and empathic accuracy in face-to-face interactions

Dehumanization is the failure to recognize the cognitive and emotional complexities of the people around us. While its presence has been well documented in horrific acts of violence, it is also theorized to play a role in everyday life. We measured its presence and effects in face-to-face dyadic interactions between strangers and found that not only was there variance in the extent to which they perceived one another as human, but this variance predicted neural processing and behavior. Specifically, participants showed stronger neural mirroring, indexed by electroencephalography (EEG) mu-suppression, in response to partners they evaluated as more human, suggesting their brains neurally simulated those targets' actions more. Participants were also marginally more empathically accurate about the emotions of partners deemed more human and performed better with them on a cooperative task. These results suggest that there are indeed differences in our recognition of the humanity of people we meet-demonstrated for the first time in a real, face-to-face interaction-and that this mundane variation affects our ability to neurally simulate, cooperate and empathize.

Methylphenidate decreases the EEG mu power in the right primary motor cortex in healthy adults during motor imagery and execution

This study investigated the effects of dopaminergic drugs on the EEG mu power during motor imagery, action observation, and execution. This is a double-blind, crossover study with a sample of 15 healthy adults under placebo vs. methylphenidate vs. risperidone conditions during motor imagery, action observation, and execution tasks. The participants had drug dosage adjustment based on body weight/dose (mg/kg). We also analyzed the mu band power by electroencephalography during the study steps. The main result is the interaction between the condition and task factors for the C3 and C4 electrodes, with decreasing EEG mu power in the methylphenidate when compared to risperidone (p ≤ 0.0083). Our results can indicate that the methylphenidate decreases the neurophysiological activity in the central cortical regions during the perceptual experience of tasks with or without body movement.

Preserved action recognition in children with autism spectrum disorders: Evidence from an EEG and eye-tracking study

Individuals with Autism Spectrum Disorder (ASD) have difficulties recognizing and understanding others' actions. The goal of the present study was to determine whether children with and without ASD show differences in the way they process stimuli depicting Biological Motion (BM). Thirty-two children aged 7-16 (16 ASD and 16 typically developing (TD) controls) participated in two experiments. In the first experiment, electroencephalography (EEG) was used to record low (8-10 Hz) and high (10-13 Hz) mu and beta (15-25 Hz) bands during the observation three different Point Light Displays (PLD) of action. In the second experiment, participants answered to action-recognition tests and their accuracy and response time were recorded, together with their eye-movements. There were no group differences in EEG data (first experiment), indicating that children with and without ASD do not differ in their mu suppression (8-13 Hz) and beta activity (15-25 Hz). However, behavioral data from second experiment revealed that children with ASD were less accurate and slower than TD children in their responses to an action recognition task. In addition, eye-tracking data indicated that children with ASD paid less attention to the body compared to the background when watching PLD stimuli. Our results indicate that the more the participants focused on the PLDs, the more they displayed mu suppressions. These results could challenge the results of previous studies that had not controlled for visual attention and found a possible deficit in MNS functions of individuals with ASD. We discuss possible mechanisms and interpretations.

Visual feedback during motor performance is associated with increased complexity and adaptability of motor and neural output

Complex motor behavior is believed to be dependent on sensorimotor integration - the neural process of using sensory input to plan, guide, and correct movements. Previous studies have shown that the complexity of motor output is low when sensory feedback is withheld during precision motor tasks. However, much of this research has focused on motor behavior rather than neural processing, and therefore, has not specifically assessed the role of sensorimotor neural functioning in the execution of complex motor behavior. The present study uses a stimulus-tracking task with simultaneous electroencephalography (EEG) recording to assess the effect of visual feedback on motor performance, motor complexity, and sensorimotor neural processing in healthy adults. The complexity of the EEG signal was analyzed to capture the information content in frequency bands (alpha and beta) and scalp regions (central, parietal, and occipital) that are associated with sensorimotor processing. Consistent with previous literature, motor performance and its complexity were higher when visual feedback was provided relative to when it was withheld. The complexity of the neural signal was also higher when visual feedback was provided. This was most robust at frequency bands (alpha and beta) and scalp regions (parietal and occipital) associated with sensorimotor processing. The findings show that visual feedback increases the information available to the brain when generating complex, adaptive motor output.

Tonic Resting State Hubness Supports High Gamma Activity Defined Verbal Memory Encoding Network in Epilepsy

High gamma activity (HGA) of verbal-memory encoding using invasive-electroencephalogram has laid the foundation for numerous studies testing the integrity of memory in diseased populations. Yet, the functional connectivity characteristics of networks subserving these memory linkages remains uncertain. By integrating this electrophysiological biomarker of memory encoding from IEEG with resting-state BOLD fluctuations, we estimated the segregation and hubness of HGA-memory regions in drug-resistant epilepsy patients and matched healthy controls. HGA-memory regions express distinctly different hubness compared to neighboring regions in health and in epilepsy, and this hubness was more relevant than segregation in predicting verbal memory encoding. The HGA-memory network comprised regions from both the cognitive control and primary processing networks, validating that effective verbal-memory encoding requires integrating brain functions, and is not dominated by a central cognitive core. Our results demonstrate a tonic intrinsic set of functional connectivity, which provides the necessary conditions for effective, phasic, task-dependent memory encoding.

Simultaneous EEG-NIRS Measurement of the Inferior Parietal Lobule During a Reaching Task With Delayed Visual Feedback

We investigated whether the inferior parietal lobule (IPL) responds in real-time to multisensory inconsistency during movement. The IPL is thought to be involved in both the detection of inconsistencies in multisensory information obtained during movement and that obtained during self-other discrimination. However, because of the limited temporal resolution of conventional neuroimaging techniques, it is difficult to distinguish IPL activity during movement from that during self-other discrimination. We simultaneously conducted electroencephalography (EEG) and near-infrared spectroscopy (NIRS) with the goal of examining IPL activity with a high spatiotemporal resolution during single reaching movements. Under a visual feedback-delay condition, gamma event-related synchronization (γ-ERS), i.e., an increase in gamma (31–47 Hz) EEG power occurred during reaching movements. This γ-ERS is considered to reflect processing of information about prediction errors. To integrate this temporal information with spatial information from the NIRS signals, we developed a new analysis technique that enabled estimation of the regions that show a hemodynamic response characterized by EEG fluctuation present in the visual feedback-delay condition. As a result, IPL activity was explained by γ-ERS specific to visual feedback delay during movements. Thus, we succeeded in demonstrating real-time activation of the IPL in response to multisensory inconsistency. However, we did not find any correlation between either IPL activity or γ-ERS with the sense of agency. Therefore, our results suggest that while the IPL is influenced by prediction error signals, it does not engage in direct processing underlying the conscious experience of making a movement, which is the foundation of self-other discrimination.

Abnormal alpha modulation in response to human eye gaze predicts inattention severity in children with ADHD

•

In response to the human eye gaze, compared with TD children, ADHD children showed a decreased alpha lateralization.

•

The attenuation of alpha modulation in ADHD children was mainly manifested in the left hemisphere.

•

The left hemisphere alpha modulation predicted higher inattentive severity and lower behavioural accuracy in ADHD children.

•

Classification analysis showed the left alpha modulation has a high capability to recognize ADHD from TD children.

Attention-deficit/hyperactivity disorder (ADHD) is characterized by problems in directing and sustaining attention. Recent behavioral studies indicated that children with ADHD are more likely to fail to show the orienting effect in response to human eye gaze. The present study aimed to identify the neurophysiological bases of attention deficits directed by social human eye gaze in children with ADHD, focusing on the relationship between alpha modulations and ADHD symptoms. The electroencephalography data were recorded from 8–13-year-old children (typically developing (TD): n = 24; ADHD: n = 21) while they performed a cued visuospatial covert attention task. The cues were designed as human eyes that might gaze to the left or right visual field. The results revealed that TD children showed a significant alpha lateralization in response to the gaze of human eyes, whereas children with ADHD showed an inverse pattern of alpha modulation in the left parieto-occipital area. Importantly, the abnormal alpha modulation in the left hemisphere predicted inattentive symptom severity and behavioral accuracy in children with ADHD. These results suggest that the dysfunction of alpha modulation in the left hemisphere in response to social cues might be a potential neurophysiologic marker of attention deficit in children with ADHD.

From Neurons to Social Beings: Short Review of the Mirror Neuron System Research and Its Socio-Psychological and Psychiatric Implications

The mirror neuron system (MNS) is a brain network activated when we move our body parts and when we observe the actions of other agent. Since the mirror neuron’s discovery in research on monkeys, several studies have examined its network and properties in both animals and humans. This review discusses MNS studies of animals and human MNS studies related to high-order social cognitions such as emotion and empathy, as well as relations between MNS dysfunction and mental disorders. Finally, these evidences are understood from an evolutionary perspective.

On the Efficiency of Individualized Theta/Beta Ratio Neurofeedback Combined with Forehead EMG Training in ADHD Children

Background: Neurofeedback training (NFT) to decrease the theta/beta ratio (TBR) has been used for treating hyperactivity and impulsivity in attention deficit hyperactivity disorder (ADHD); however, often with low efficiency. Individual variance in EEG profile can confound NFT, because it may lead to influencing non-relevant activity, if ignored. More importantly, it may lead to influencing ADHD-related activities adversely, which may even result in worsening ADHD symptoms. Electromyogenic (EMG) signal resulted from forehead muscles can also explain the low efficiency of the NFT in ADHD from both practical and psychological point-of-view. The first aim of this study was to determine EEG and EMG biomarkers most related to the main ADHD characteristics, such as impulsivity and hyperactivity. The second aim was to confirm our hypothesis that the efficiency of the TBR NFT can be increased by individual adjustment of the frequency bands and simultaneous training on forehead muscle tension. Methods: We recruited 94 children diagnosed with ADHD (ADHD) and 23 healthy controls (HC). All participants were male and aged between six and nine. Impulsivity and attention were assessed with Go/no-Go task and delayed gratification task, respectively; and 19-channel EEG and forehead EMG were recorded. Then, the ADHD group was randomly subdivided into (1) standard, (2) individualized, (3) individualized+EMG, and (4) sham NFT (control) groups. The groups were compared based on TBR and EEG alpha activity, as well as hyperactivity and impulsivity three times: pre-NFT, post-NFT and 6 months after the NFT (follow-up). Results: ADHD children were characterized with decreased individual alpha peak frequency, alpha bandwidth and alpha amplitude suppression magnitude, as well as with increased alpha1/alpha2 (a1/a2) ratio and scalp muscle tension when c (η2 ≥ 0.212). All contingent TBR NFT groups exhibited significant NFT-related decrease in TBR not evident in the control group. Moreover, we detected a higher overall alpha activity in the individualized but not in the standard NFT group. Mixed MANOVA considering between-subject factor GROUP and within-subject factor TIME showed that the individualized+EMG group exhibited the highest level of clinical improvement, which was associated with increase in the individual alpha activity at the 6 months follow-up when comparing with the other approaches (post hoc t = 3.456, p = 0.011). Conclusions: This study identified various (adjusted) alpha activity metrics as biomarkers with close relationship with ADHD symptoms, and demonstrated that TBR NFT individually adjusted for variances in alpha activity is more successful and clinically more efficient than standard, non-individualized NFT. Moreover, these training effects of the individualized TBR NFT lasted longer when combined with EMG.

Ongoing slow oscillatory phase modulates speech intelligibility in cooperation with motor cortical activity

Neural oscillation is attracting attention as an underlying mechanism for speech recognition. Speech intelligibility is enhanced by the synchronization of speech rhythms and slow neural oscillation, which is typically observed as human scalp electroencephalography (EEG). In addition to the effect of neural oscillation, it has been proposed that speech recognition is enhanced by the identification of a speaker’s motor signals, which are used for speech production. To verify the relationship between the effect of neural oscillation and motor cortical activity, we measured scalp EEG, and simultaneous EEG and functional magnetic resonance imaging (fMRI) during a speech recognition task in which participants were required to recognize spoken words embedded in noise sound. We proposed an index to quantitatively evaluate the EEG phase effect on behavioral performance. The results showed that the delta and theta EEG phase before speech inputs modulated the participant’s response time when conducting speech recognition tasks. The simultaneous EEG-fMRI experiment showed that slow EEG activity was correlated with motor cortical activity. These results suggested that the effect of the slow oscillatory phase was associated with the activity of the motor cortex during speech recognition.

The interpretation of mu suppression as an index of mirror neuron activity: past, present and future

Mu suppression studies have been widely used to infer the activity of the human mirror neuron system (MNS) in a number of processes, ranging from action understanding, language, empathy and the development of autism spectrum disorders (ASDs). Although mu suppression is enjoying a resurgence of interest, it has a long history. This review aimed to revisit mu's past, and examine its recent use to investigate MNS involvement in language, social processes and ASDs. Mu suppression studies have largely failed to produce robust evidence for the role of the MNS in these domains. Several key potential shortcomings with the use and interpretation of mu suppression, documented in the older literature and highlighted by more recent reports, are explored here.

Amplitude of Sensorimotor Mu Rhythm Is Correlated with BOLD from Multiple Brain Regions: A Simultaneous EEG-fMRI Study

The mu rhythm is a field oscillation in the ∼10Hz range over the sensorimotor cortex. For decades, the suppression of mu (event-related desynchronization) has been used to index movement planning, execution, and imagery. Recent work reports that non-motor processes, such as spatial attention and movement observation, also desynchronize mu, raising the possibility that the mu rhythm is associated with the activity of multiple brain regions and systems. In this study, we tested this hypothesis by recording simultaneous resting-state EEG-fMRI from healthy subjects. Independent component analysis (ICA) was applied to extract the mu components. The amplitude (power) fluctuations of mu were estimated as a time series using a moving-window approach, which, after convolving with a canonical hemodynamic response function (HRF), was correlated with blood-oxygen-level-dependent (BOLD) signals from the entire brain. Two main results were found. First, mu power was negatively correlated with BOLD from areas of the sensorimotor network, the attention control network, the putative mirror neuron system, and the network thought to support theory of mind. Second, mu power was positively correlated with BOLD from areas of the salience network, including anterior cingulate cortex and anterior insula. These results are consistent with the hypothesis that sensorimotor mu rhythm is associated with multiple brain regions and systems. They also suggest that caution should be exercised when attempting to interpret mu modulation in terms of a single brain network.

Mu suppression - A good measure of the human mirror neuron system?

Mu suppression has been proposed as a signature of the activity of the human mirror neuron system (MNS). However the mu frequency band (8–13 Hz) overlaps with the alpha frequency band, which is sensitive to attentional fluctuation, and thus mu suppression could potentially be confounded by changes in attentional engagement. The specific baseline against which mu suppression is assessed may be crucial, yet there is little consistency in how this is defined. We examined mu suppression in 61 typical adults, the largest mu suppression study so far conducted. We compared different methods of baselining, and examined activity at central and occipital electrodes, to both biological (hands) and non-biological (kaleidoscope) moving stimuli, to investigate the involvement of attention and alpha activity in mu suppression. We also examined changes in beta power, another candidate index of MNS engagement. We observed strong mu suppression restricted to central electrodes when participants performed hand movements, demonstrating that mu is indeed responsive to the activity of the motor cortex. However, when we looked for a similar signature of mu suppression to passively observed stimuli, the baselining method proved to be crucial. Selective suppression for biological versus non-biological stimuli was seen at central electrodes only when we used a within-trial baseline based on a static stimulus: this method greatly reduced trial-by-trial variation in the suppression measure compared with baselines based on blank trials presented in separate blocks. Even in this optimal condition, 16–21% of participants showed no mu suppression. Changes in beta power also did not match our predicted pattern for MNS engagement, and did not seem to offer a better measure than mu. Our conclusions are in contrast to those of a recent meta-analysis, which concluded that mu suppression is a valid means to examine mirror neuron activity. We argue that mu suppression can be used to index the human MNS, but the effect is weak and unreliable and easily confounded with alpha suppression.

Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources

BACKGROUND

Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized.

METHODS

EEG data were generated by simulating multiple cortical sources (2-4) with the same strength or two sources with relative strength ratios of 1:1 to 4:1, and adding noise. These data were used to reconstruct the cortical sources using current source density (CSD) algorithms: sLORETA, MNLS, and LORETA using a p-norm with p equal to 1, 1.5 and 2. Precision (percentage of the reconstructed activity corresponding to simulated activity) and Recall (percentage of the simulated sources reconstructed) of each of the CSD algorithms were calculated.

RESULTS

While sLORETA has the best performance when only one source is present, when two or more sources are present LORETA with p equal to 1.5 performs better. When the relative strength of one of the sources is decreased, all algorithms have more difficulty reconstructing that source. However, LORETA 1.5 continues to outperform other algorithms. If only the strongest source is of interest sLORETA is recommended, while LORETA with p equal to 1.5 is recommended if two or more of the cortical sources are of interest. These results provide guidance for choosing a CSD algorithm to locate multiple cortical sources of EEG and for interpreting the results of these algorithms.

EEG imaging of toddlers during dyadic turn-taking: Mu-rhythm modulation while producing or observing social actions

Contemporary active-EEG and EEG-imaging methods show particular promise for studying the development of action planning and social-action representation in infancy and early childhood. Action-related mu suppression was measured in eleven 3-year-old children and their mothers during a 'live,' largely unscripted social interaction. High-density EEG was recorded from children and synchronized with motion-captured records of children's and mothers' hand actions, and with video recordings. Independent Component Analysis (ICA) was used to separate brain and non-brain source signals in toddlers' EEG records. EEG source dynamics were compared across three kinds of epochs: toddlers' own actions (execution), mothers' actions (observation), and between-turn intervals (no action). Mu (6-9Hz) power was suppressed in left and right somatomotor cortex during both action execution and observation, as reflected by independent components of individual children's EEG data. These mu rhythm components were accompanied by beta-harmonic (~16Hz) suppression, similar to findings from adults. The toddlers' power spectrum and scalp density projections provide converging evidence of adult-like mu-suppression features. Mu-suppression components' source locations were modeled using an age-specific 4-layer forward head model. Putative sources clustered around somatosensory cortex, near the hand/arm region. The results demonstrate that action-locked, event-related EEG dynamics can be measured, and source-resolved, from toddlers during social interactions with relatively unrestricted social behaviors.

Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts in simultaneous EEG-fMRI data

Electroencephalography (EEG) data simultaneously acquired with functional magnetic resonance imaging (fMRI) data are preprocessed to remove gradient artifacts (GAs) and ballistocardiographic artifacts (BCAs). Nonetheless, these data, especially in the gamma frequency range, can be contaminated by residual artifacts produced by mechanical vibrations in the MRI system, in particular the cryogenic pump that compresses and transports the helium that chills the magnet (the helium-pump). However, few options are available for the removal of helium-pump artifacts. In this study, we propose a recursive approach of EEG-segment-based principal component analysis (rsPCA) that enables the removal of these helium-pump artifacts. Using the rsPCA method, feature vectors representing helium-pump artifacts were successfully extracted as eigenvectors, and the reconstructed signals of the feature vectors were subsequently removed. A test using simultaneous EEG-fMRI data acquired from left-hand (LH) and right-hand (RH) clenching tasks performed by volunteers found that the proposed rsPCA method substantially reduced helium-pump artifacts in the EEG data and significantly enhanced task-related gamma band activity levels (p=0.0038 and 0.0363 for LH and RH tasks, respectively) in EEG data that have had GAs and BCAs removed. The spatial patterns of the fMRI data were estimated using a hemodynamic response function (HRF) modeled from the estimated gamma band activity in a general linear model (GLM) framework. Active voxel clusters were identified in the post-/pre-central gyri of motor area, only from the rsPCA method (uncorrected p<0.001 for both LH/RH tasks). In addition, the superior temporal pole areas were consistently observed (uncorrected p<0.001 for the LH task and uncorrected p<0.05 for the RH task) in the spatial patterns of the HRF model for gamma band activity when the task paradigm and movement were also included in the GLM.

Event-related alpha suppression in response to facial motion

While biological motion refers to both face and body movements, little is known about the visual perception of facial motion. We therefore examined alpha wave suppression as a reduction in power is thought to reflect visual activity, in addition to attentional reorienting and memory processes. Nineteen neurologically healthy adults were tested on their ability to discriminate between successive facial motion captures. These animations exhibited both rigid and non-rigid facial motion, as well as speech expressions. The structural and surface appearance of these facial animations did not differ, thus participants decisions were based solely on differences in facial movements. Upright, orientation-inverted and luminance-inverted facial stimuli were compared. At occipital and parieto-occipital regions, upright facial motion evoked a transient increase in alpha which was then followed by a significant reduction. This finding is discussed in terms of neural efficiency, gating mechanisms and neural synchronization. Moreover, there was no difference in the amount of alpha suppression evoked by each facial stimulus at occipital regions, suggesting early visual processing remains unaffected by manipulation paradigms. However, upright facial motion evoked greater suppression at parieto-occipital sites, and did so in the shortest latency. Increased activity within this region may reflect higher attentional reorienting to natural facial motion but also involvement of areas associated with the visual control of body effectors.

Abstract art and cortical motor activation: an EEG study

The role of the motor system in the perception of visual art remains to be better understood. Earlier studies on the visual perception of abstract art (from Gestalt theory, as in Arnheim, 1954 and 1988, to balance preference studies as in Locher and Stappers, 2002, and more recent work by Locher et al., 2007; Redies, 2007, and Taylor et al., 2011), neglected the question, while the field of neuroesthetics (Ramachandran and Hirstein, 1999; Zeki, 1999) mostly concentrated on figurative works. Much recent work has demonstrated the multimodality of vision, encompassing the activation of motor, somatosensory, and viscero-motor brain regions. The present study investigated whether the observation of high-resolution digitized static images of abstract paintings by Lucio Fontana is associated with specific cortical motor activation in the beholder's brain. Mu rhythm suppression was evoked by the observation of original art works but not by control stimuli (as in the case of graphically modified versions of these works). Most interestingly, previous visual exposure to the stimuli did not affect the mu rhythm suppression induced by their observation. The present results clearly show the involvement of the cortical motor system in the viewing of static abstract art works.