Event-related Synchronization Research Articles

Pre-stimulus Activity Mediates Event-Related Theta Synchronization and Alpha Desynchronization During Memory Formation in Healthy Aging

Abstract The capacity to learn is a key determinant for the quality of life but is known to decline to varying degrees with age. However, despite mounting evidence of memory deficits in older age, the neural mechanisms contributing to successful or impeded memory remain unclear. Previous research has primarily focused on memory formation through remembered versus forgotten comparisons, lacking the ability to capture the incremental nature of learning. Moreover, previous EEG studies have primarily examined oscillatory brain activity during the encoding phase, such as event-related synchronization (ERS) of mid-frontal theta and desynchronization (ERD) of parietal alpha, while neglecting the potential influence of pre-stimulus activity. To address these limitations, we employed a sequence learning paradigm, where 113 young and 117 older participants learned a fixed sequence of visual locations through repeated observations (6423 sequence repetitions, 55 '944 stimuli). This paradigm enabled us to investigate mid-frontal theta ERS, parietal alpha ERD, and how they are affected by pre-stimulus activity during the incremental learning process. Behavioral results revealed that young subjects learned significantly faster than older subjects, in line with expected age-related cognitive decline. Successful incremental learning was directly linked to decreases of mid-frontal theta ERS and increases of parietal alpha ERD. Notably, these neurophysiological changes were less pronounced in older individuals, reflecting a slower rate of learning. Importantly, the mediation analysis revealed that in both age groups, mid-frontal pre-stimulus theta partially mediated the relationship between learning and mid-frontal theta ERS. Furthermore, the overall impact of learning on parietal alpha ERD was primarily driven by its positive influence on pre-stimulus alpha activity. Our findings offer new insights into the age-related differences in memory formation and highlight the importance of pre-stimulus activity in explaining post-stimulus responses during learning.

Surfing beta burst waveforms to improve motor imagery-based BCI

Abstract Our understanding of motor-related, macroscale brain processes has been significantly shaped by the description of the event-related desynchronization (ERD) and synchronization (ERS) phenomena in the mu and beta frequency bands prior to, during and following movement. The demonstration of reproducible, spatially- and band-limited signal power changes has, consequently, attracted the interest of non invasive brain-computer interface (BCI) research for a long time. BCIs often rely on motor imagery (MI) experimental paradigms that are expected to generate brain signal modulations analogous to movement-related ERD and ERS. However, a number of recent neuroscience studies has questioned the nature of these phenomena. Beta band activity has been shown to occur, on a single-trial level, in short, transient and heterogeneous events termed bursts rather than sustained oscillations. In a previous study, we established that an analysis of hand MI binary classification tasks based on beta bursts can be superior to beta power in terms of classification score. In this article we elaborate on this idea, proposing a signal processing algorithm that is comparable to- and compatible with state-of-the-art techniques. Our pipeline filters brain recordings by convolving them with kernels extracted from beta bursts and then applies spatial filtering before classification. This data-driven filtering allowed for a simple and efficient analysis of signals from multiple sensors thus being suitable for online applications. By adopting a time-resolved decoding approach we explored MI dynamics and showed the specificity of the new classification features. In accordance with previous results, beta bursts improved classification performance compared to beta band power, while often increasing information transfer rate compared to state-of-the-art approaches.

Attentional network deficits in patients with migraine: behavioral and electrophysiological evidence

BackgroundPatients with migraine often experience not only headache pain but also cognitive dysfunction, particularly in attention, which is frequently overlooked in both diagnosis and treatment. The influence of these attentional deficits on the pain-related clinical characteristics of migraine remains poorly understood, and clarifying this relationship could improve care strategies.MethodsThis study included 52 patients with migraine and 34 healthy controls. We employed the Attentional Network Test for Interactions and Vigilance–Executive and Arousal Components paradigm, combined with electroencephalography, to assess attentional deficits in patients with migraine, with an emphasis on phasic alerting, orienting, executive control, executive vigilance, and arousal vigilance. An extreme gradient boosting binary classifier was trained on features showing group differences to distinguish patients with migraine from healthy controls. Moreover, an extreme gradient boosting regression model was developed to predict clinical characteristics of patients with migraine using their attentional deficit features.ResultsFor general performance, patients with migraine presented a larger inverse efficiency score, a higher prestimulus beta-band power spectral density and a lower gamma-band event-related synchronization at Cz electrode, and stronger high alpha-band activity at the primary visual cortex, compared to healthy controls. Although no behavior differences in three basic attentional networks were found, patients showed magnified N1 amplitude and prolonged latency of P2 for phasic alerting-trials as well as an increased orienting evoked-P1 amplitude. For vigilance function, improvements in the hit rate of executive vigilance-trials were exhibited in controls but not in patients. Besides, patients with migraine exhibited longer reaction time as well as larger variability in arousal vigilance-trials than controls. The binary classifier developed by such attentional deficit features achieved an F1 score of 0.762 and an accuracy of 0.779 in distinguishing patients with migraine from healthy controls. Crucially, the predicted value available from the regression model involving attentional deficit features significantly correlated with the real value for the frequency of headache.ConclusionsPatients with migraine demonstrated significant attentional deficits, which can be used to differentiate migraine patients from healthy populations and to predict clinical characteristics. These findings highlight the need to address cognitive dysfunction, particularly attentional deficits, in the clinical management of migraine.

Spatiotemporal correlates of emotional conflict processing in typically developing adolescents using magnetoencephalography

Brain networks involved in emotional conflict processing have been extensively studied using functional magnetic resonance imaging in adults. Yet, the temporal correlates of these brain activations are still largely unknown, particularly in a key phase of emotional development, adolescence. Here, we elucidate the spatiotemporal profile of emotional conflict processing in 24 typically developing adolescents (10–18 years; 22 Caucasian) during an emotional face-word Stroop task. Using magnetoencephalography (MEG), we calculated dynamic statistical parametric maps and compared trials with and without emotional conflict whole-brain cluster-based permutation tests, followed by cluster-based ROI time-frequency analyses. Cluster analysis revealed four significant clusters, including early activation of the cingulate and temporal cortices, which may be related to dorsal and ventral streams of processing, respectively. This was followed by late components in the middle frontal and prefrontal cortices, which are likely related to response execution and post-response monitoring. Time-frequency analysis revealed event-related synchronizations and desynchronizations in beta and gamma bands across the cingulate cortex, which highlight the different roles of the cingulate subdivisions. Our findings provide further evidence of the cingulate's key role in emotional conflict processing across time. Improving our understanding of this key cognitive process will guide future work with neuropsychiatric populations, which may aid diagnosis and treatment outcomes.

EEG-Characteristics of Aesthetic Perception and Evaluation of Artworks During a Museum Visit: А Neuroaesthetic Study

Twenty-eight people (30–70 years old, 12 men, 16 women, artists and non-artists) participated in a comparative neuroaesthetic study in the conditions of real-life visit to M. Vrubel mono-exhibition (Russian Museum, St. Petersburg). During the visit to the exhibition (usually lasted for around 60 min), EEG of participants was recorded. The subjects were looking at the paintings for 30 seconds to 3 min and evaluated the subjective aesthetic “attractiveness” of the paintings by a series of button presses (from 1 to 10). Were analyzed EEG spectral power in the α1 (8–10 Hz)-, α2 (10–13 Hz)-, β1 (13–18 Hz)-, β2 (13–30 Hz)-frequency bands during viewing the most famous Vrubel paintings (“Bogatyr”, “Swan Princess”, “Swan”, “Sitting Demon”, “Flying Demon”, “Pan”, etc.) and event-related EEG synchronization/desynchronization in relation to the subjective emotional and aesthetic evaluation of these paintings. Professional artists showed lower spectral power values in α1 (leads F3, C3, T4, Pz) and α2 (F3, Fz, F4, C3, Cz, C4, P3, Pz, P4)-frequency bands in frontal, central, and parietal regions. The artists were also found to have lower power values in β1,2-frequency bands in frontal (F3, F4, C3) regions and higher power values in occipital (O1, O2 – β1, β2) and posterior temporal (β2) cortical regions compared to the group of subjects with no special artistic education. Moreover, artists decision-making about the high emotional-aesthetic attractiveness of paintings was accompanied by an increase in event-related EEG synchronization for 11.5–27 Hz in frontal and central cortical areas over 580–360 ms before giving the response, compared to non-artists, whereas low emotional-aesthetic evaluation was characterized by 9–27 Hz EEG desynchronization, which started 60 ms before the giving the response and lasted up to 440 ms after it, in the posterior temporal and parietal regions. The differences in frontal cortical areas may indicate a higher engagement of the reward system during the perception of aesthetically pleasing paintings, and the differences in parietal and posterior temporal areas may indicate a continuing visual synthesis (more sustained visual attention) during the perception of subjectively less attractive paintings in artists compared to non-artists.

Theta oscillations in observers’ temporal cortex index postural instability of point-light displays

This study investigates whether postural equilibration follows the same principles of motor resonance as goal-oriented actions, namely, whether an individual activates the same neuronal substrates when experiencing postural perturbation as when observing another individual in this condition. To address this question, we examined electroencephalographic dynamics while subjects observed point-light displays featuring an unstable human display, a stable human display, and their respective scrambled counterparts lacking shape information and biological motion. We focused on theta band (4–7 Hz), which is a fundamental frequency for modulating brain activity during challenging balance tasks and reflects postural stability monitoring. Rather than mirroring activity, our findings suggest an inhibitory response to postural instability. Theta event-related synchronization in the left temporal cortex was dampened for the unstable display as compared to its scramble counterpart and to the stable display. This low theta response coincided with an increase in left temporal-prefrontal connectivity, compatible with top-down inhibitory mechanisms. By contrast, the stronger theta response to the stable display as compared to the unstable one could be due to the difficulty of recognizing low-motion biological stimuli, or alternatively, to a facilitation of stimulus processing and strengthening of the mirroring response. The response facilitation for stable posture, coupled with a diminished response to the unstable display, could contribute to a broader mechanism mitigating postural threats and ensuring stable balance. Future investigations should leverage these findings to explore how posture-related responses correlate with perceptual and motor expertise, and to more clearly define these mechanisms during dynamic social interactions.

Increased visual alpha-band activity during self-paced finger tapping does not affect early visual stimulus processing.

Alpha-band activity is thought to be involved in orchestrating neural processing within and across brain regions relevant to various functions such as perception, cognition, and motor activity. Across different studies, attenuated alpha-band activity has been linked to increased neural excitability. Yet, there have been conflicting results concerning the consequences of alpha-band modulations for early sensory processing. We here examined whether movement-related alterations in visual alpha-band activity affected the early sensory processing of visual stimuli. For this purpose, in an EEG experiment, participants were engaged in a voluntary finger-tapping task while passively viewing flickering dots. We found extensive and expected movement-related amplitude modulations of motor alpha- and beta-band activity with event-related-desynchronization (ERD) before and during, and event-related-synchronization (ERS) after single voluntary finger taps. Crucially, while a visual alpha-band ERS accompanied the motor alpha-ERD before and during each finger tap, flicker-evoked Steady-State-Visually-Evoked-Potentials (SSVEPs), as a marker of early visual sensory gain, were not modulated in amplitude. As early sensory stimulus processing was unaffected by amplitude-modulated visual alpha-band activity, this argues against the idea that alpha-band activity represents a mechanism by which early sensory gain modulation is implemented. The distinct neural dynamics of visual alpha-band activity and early sensory processing may point to distinct and multiplexed neural selection processes in visual processing.

Motor imagery with cues in virtual reality, audio and screen

Training plays a significant role in motor imagery (MI), particularly in applications such as Motor Imagery-based Brain-Computer Interface (MIBCI) systems and rehabilitation systems. Previous studies have investigated the intricate relationship between cues and MI signals. However, the medium of presentation still remains an emerging area to be explored, as possible factors to enhance Motor Imagery signals..
Approach: We hypothesise that the medium used for cue presentation can significantly influence both performance and training outcomes in MI tasks. To test this hypothesis, we designed and executed an experiment implementing no- feedback MI. Our investigation focused on three distinct cue presentation mediums -audio, screen, and virtual reality(VR) headsets-all of which have potential implications for BCI use in the Activities of Daily Lives.
Main Results: The results of our study uncovered notable variations in MI signals depending on the medium of cue presentation, where the analysis is based on 3 EEG channels. To substantiate our findings, we employed a comprehensive approach, utilizing various evaluation metrics including Event- Related Synchronisation(ERS)/Desynchronisation(ERD), Feature Extraction (using Recursive Feature Elimination (RFE)), Machine Learning methodologies (using Ensemble Learning), and participant Questionnaires. All the approaches signify that Motor Imagery signals are enhanced when presented in VR, followed by audio, and lastly screen. Applying a Machine Learning approach across all subjects, the mean cross-validation accuracy (Mean ± Std. Error) was 69.24 ± 3.12, 68.69 ± 3.3 and 66.1±2.59 when for the VR, audio-based, and screen-based instructions respectively.
Significance: This multi-faceted exploration provides evidence to inform MI- based BCI design and advocates the incorporation of different mediums into the design of MIBCI systems, experimental setups, and user studies. The influence of the medium used for cue presentation may be applied to develop more effective and inclusive MI applications in the realm of human-computer interaction and rehabilitation.

Negative emotions reduce sensorimotor cortex activity during proprioceptive modulation of rolandic ∼20HZ beta rhythm in typically developing children and those with neurodevelopmental conditions

BackgroundThe Rolandic ∼20-Hz beta rhythm of the sensorimotor cortex is associated with motor function and perception. However, the modulation of this rhythm by different emotional stimuli is an innovative area of research. AimsThis study aims at investigating the impact of affective pictures (positive, negative, and neutral) on the proprioceptive modulation of the Rolandic ∼20 Hz beta rhythm in typically developing children and children with neurodevelopmental disorders (i.e. cerebral palsy and autism). Methods and proceduresEEG was recorded while participants experienced passive wrist movements during the simultaneous viewing of affective pictures. Time-frequency analysis of the sensorimotor oscillatory activity was performed. Outcomes and resultsOur findings revealed that pictures with negative emotional valence notably diminish event-related synchronization (ERS) amplitude during the perception of hand movement in all groups of children. Conclusions and implicationsThese findings suggest that emotional stimuli, particularly the negative ones, could significantly influence brain's processing of proprioception, adding knowledge to the interaction of common comorbidities, such as sensorimotor disorders and emotional dysregulation, in children with neurodevelopmental disabilities.

Evaluation of perceived urgency from single-trial EEG data elicited by upper-body vibration feedback using deep learning

Notification systems that convey urgency without adding cognitive burden are crucial in human–computer interaction. Haptic feedback systems, particularly those utilizing vibration feedback, have emerged as a compelling solution, capable of providing desirable levels of urgency depending on the application. High-risk applications require an evaluation of the urgency level elicited during critical notifications. Traditional evaluations of perceived urgency rely on subjective self-reporting and performance metrics, which, while useful, are not real-time and can be distracting from the task at hand. In contrast, EEG technology offers a direct, non-intrusive method of assessing the user’s cognitive state. Leveraging deep learning, this study introduces a novel approach to evaluate perceived urgency from single-trial EEG data, induced by vibration stimuli on the upper body, utilizing our newly collected urgency-via-vibration dataset. The proposed model combines a 2D convolutional neural network with a temporal convolutional network to capture spatial and temporal EEG features, outperforming several established EEG models. The proposed model achieves an average classification accuracy of 83% through leave-one-subject-out cross-validation across three urgency classes (not urgent, urgent, and very urgent) from a single trial of EEG data. Furthermore, explainability analysis showed that the prefrontal brain region, followed by the central brain region, are the most influential in predicting the urgency level. A follow-up neural statistical analysis revealed an increase in event-related synchronization (ERS) in the theta frequency band (4–7 Hz) with the increased level of urgency, which is associated with high arousal and attention in the neuroscience literature. A limitation of this study is that the proposed model’s performance was tested only the urgency-via-vibration dataset, which may affect the generalizability of the findings.

The association between insomnia symptoms and cognitive flexibility among undergraduates: An event-related potential study

ObjectiveTo explore the association between insomnia symptoms and cognitive flexibility among undergraduates, along with its potential neural mechanisms. MethodA total of 102 participants were divided into insomnia (n = 55) and control (n = 47) groups based on sleep status. Cognitive flexibility was assessed using the Cognitive Flexibility Inventory (CFI) and the Number-Letter Task (N-L task). EEG data were recorded during the N-L task. ResultsThe insomnia group exhibited lower CFI scores and higher switch costs in reaction time and accuracy compared to the control group. ERP analysis showed differences in P2, N2, and P3 component amplitudes between the two groups, with reduced N2 amplitude in the insomnia group under repeat trials. Time-frequency analysis revealed larger theta band event related synchronization in the frontal region and smaller theta band ERS in the parietal region under switch trials in the control group; the alpha band event-related desynchronization in the parietal region under repeat trials was significantly smaller in the control group compared to switch trials. ConclusionCompared to undergraduates with normal sleep, those with insomnia symptoms exhibited reduced cognitive flexibility, which may be associated with some alterations in brain electrophysiological activities.

Neural basis of lower-limb visual feedback therapy: an EEG study in healthy subjects

BackgroundVideo-feedback observational therapy (VOT) is an intensive rehabilitation technique based on movement repetition and visualization that has shown benefits for motor rehabilitation of the upper and lower limbs. Despite an increase in recent literature on the neurophysiological effects of VOT in the upper limb, there is little knowledge about the cortical effects of visual feedback therapies when applied to the lower limbs. The aim of our study was to better understand the neurophysiological effects of VOT. Thus, we identified and compared the EEG biomarkers of healthy subjects undergoing lower limb VOT during three tasks: passive observation, observation and motor imagery, observation and motor execution.MethodsWe recruited 38 healthy volunteers and monitored their EEG activity while they performed a right ankle dorsiflexion task in the VOT. Three graded motor tasks associated with action observation were tested: action observation alone (O), motor imagery with action observation (OI), and motor execution synchronized with action observation (OM). The alpha and beta event-related desynchronization (ERD) and event-related synchronization (or beta rebound, ERS) rhythms were used as biomarkers of cortical activation and compared between conditions with a permutation test. Changes in connectivity during the task were computed with phase locking value (PLV).ResultsDuring the task, in the alpha band, the ERD was comparable between O and OI activities across the precentral, central and parietal electrodes. OM involved the same regions but had greater ERD over the central electrodes. In the beta band, there was a gradation of ERD intensity in O, OI and OM over central electrodes. After the task, the ERS changes were weak during the O task but were strong during the OI and OM (Cz) tasks, with no differences between OI and OM.ConclusionAlpha band ERD results demonstrated the recruitment of mirror neurons during lower limb VOT due to visual feedback. Beta band ERD reflects strong recruitment of the sensorimotor cortex evoked by motor imagery and action execution. These results also emphasize the need for an active motor task, either motor imagery or motor execution task during VOT, to elicit a post-task ERS, which is absent during passive observation.Trial Registration NCT05743647

Adaptive and Compensatory Neural Signatures in Fibromyalgia: An Analysis of Resting-State and Stimulus-Evoked EEG Oscillations.

This study aimed to investigate clinical and physiological predictors of brain oscillatory activity in patients with fibromyalgia (FM), assessing resting-state power, event-related desynchronization (ERD), and event-related synchronization (ERS) during tasks. We performed a cross-sectional analysis, including clinical and neurophysiological data from 78 subjects with FM. Multivariate regression models were built to explore predictors of electroencephalography bands. Our findings show a negative correlation between beta oscillations and pain intensity; fibromyalgia duration is positively associated with increased oscillatory power at low frequencies and in the beta band; ERS oscillations in the theta and alpha bands seem to be correlated with better symptoms of FM; fatigue has a signature in the alpha band-a positive relationship in resting-state and a negative relationship in ERS oscillations. Specific neural signatures lead to potential clusters of neural adaptation, in which beta oscillatory activity in the resting state represents a more adaptive activity when pain levels are low and stimulus-evoked oscillations at lower frequencies are likely brain compensatory mechanisms. These neurophysiological changes may help to understand the impact of long-term chronic pain in the central nervous system and the descending inhibitory system in fibromyalgia subjects.

Contingent magnetic variation and beta-band oscillations in sensorimotor temporal decision-making

The ability to accurately encode the temporal information of sensory events and hence to make prompt action is fundamental to humans’ prompt behavioral decision-making. Here we examined the ability of ensemble coding (averaging multiple inter-intervals in a sound sequence) and subsequent immediate reproduction of target duration at half, equal, or double that of the perceived mean interval in a sensorimotor loop. With magnetoencephalography (MEG), we found that the contingent magnetic variation (CMV) in the central scalp varied as a function of the averaging tasks, with a faster rate for buildup amplitudes and shorter peak latencies in the “half” condition as compared to the “double” condition. ERD (event-related desynchronization) -to-ERS (event-related synchronization) latency was shorter in the ”half” condition. A robust beta band (15–23 Hz) power suppression and recovery between the final tone and the action of key pressing was found for time reproduction. The beta modulation depth (i.e., the ERD-to-ERS power difference) was larger in motor areas than in primary auditory areas. Moreover, results of phase slope index (PSI) indicated that beta oscillations in the left supplementary motor area (SMA) led those in the right superior temporal gyrus (STG), showing SMA to STG directionality for the processing of sequential (temporal) auditory interval information. Our findings provide the first evidence to show that CMV and beta oscillations predict the coupling between perception and action in time averaging.

Effects of Single-Session Practice Structure on Motor Skill Acquisition and Alpha and Beta EEG Oscillations

Background: Although it is known that practicing a motor skill updates the associated internal model, it is still unclear as to how cortical oscillations linked with the motor skill change under differing practice schedules. The current study investigated α- and β-power changes associated with motor skill acquisition. Objectives: Firstly, we investigated the behavioral effects of practice on motor learning and retention during repetitive (RP) and variable (VP) practice schedules on an anticipation timing task. Secondly, we investigated changes in cortical α (10 - 13 Hz) and β (15 - 30 Hz) event-related synchronization and desynchronization (ERS/ERD) under RP and VP during early (EP) and late (LP) stages of practice. Methods: To investigate the behavioral effects of practice on learning and retention, participants were pretested, post-tested at 5 min (retention), and tested twice at 30 min (one for longer retention, one for transfer to a novel velocity). To investigate electroencephalography (EEG) α and β power changes, data were collected from electrode sites T7, T8, C3, C4, CP3, CP4, FCz, AFz, and Pz. Results: Based on a 2 × 4 (practice group × test block) ANOVA, results indicated a significant learning effect for both group participants, with VP participants performing better on the 30-min transfer test. To investigate EEG α and β power changes, data were analyzed using separate, 2 × 2 repeated measures ANOVA (group [RP and VP] × practice trial blocks [EP and LP]). Power analyses revealed (1) attenuated α ERD at T7 (cognitive/verbal rehearsal), C3 (motor cortex), CP3, CP4, and FCz (pooled data representing premotor cortices), and AFz (frontal cortex and attentional processes) during LP, with greater changes observed in premotor activity (PMA), T7, and AFz electrode sites in RP participants. β frequency analysis, using beta modulation depth (BMD), revealed that participants in both groups had increased BMD at premotor, motor, and frontal electrode sites at LP, with RP participants exhibiting greater changes. Conclusions: Results are in accordance with previous research indicating that practicing under a VP schedule leads to superior motor skill transfer than practicing under an RP schedule. Moreover, lesser changes in α ERD along and lower BMD observed in VP participants might be responsible for a more adaptable and flexible motor program, allowing for greater skill retention and transfer in individuals practicing under VP conditions.

Age-related changes in brain oscillatory patterns during an n-back task in children and adolescents

The development of brain oscillatory responses and their possible role in the working memory (WM) performance of children, adolescents and young adults was investigated. A set of 0- and 1-back tasks with letter stimuli were administered to a final sample of 131 subjects (between 6 and 20 years of age). A decrease in response times (RTs) and an increase of the sensitivity index d-prime (d′) were seen with increased age. RTs increased and d′ decreased with load, indicating higher difficulty for higher loads. Event-related synchronization (ERS) and event-related desynchronization (ERD) were obtained by the convolution of Morlet wavelets on the recorded EEG. Statistical analyses were performed of the absolute and relative power of brain oscillations defined by topography, frequency and latency. Posterior alpha and beta ERD, and frontocentral theta ERS, were induced by the stimuli presented during the n-back task. While relative theta ERS increased with age, absolute theta ERS, absolute and relative alpha and, absolute beta ERD, decreased with age. Age-related improvement in behavioral performance was mediated by relative theta. Alpha and beta ERD were more pronounced for the most difficult task (1-back) and for the target condition. Globally, there was high consistency of the effects of target type and task load across development. Theta ERS maturation is a crucial step for improving WM performance during development, while alpha and beta ERD maturation seem to be less critical for behavioral performance improvement with age, possibly due to a sufficient level of alpha-beta ERD for good performance in young children.

Applications of Brain Wave Classification for Controlling an Intelligent Wheelchair

The independence and autonomy of both elderly and disabled people have been a growing concern in today’s society. Therefore, wheelchairs have proven to be fundamental for the movement of these people with physical disabilities in the lower limbs, paralysis, or other type of restrictive diseases. Various adapted sensors can be employed in order to facilitate the wheelchair’s driving experience. This work develops the proof concept of a brain–computer interface (BCI), whose ultimate final goal will be to control an intelligent wheelchair. An event-related (de)synchronization neuro-mechanism will be used, since it corresponds to a synchronization, or desynchronization, in the mu and beta brain rhythms, during the execution, preparation, or imagination of motor actions. Two datasets were used for algorithm development: one from the IV competition of BCIs (A), acquired through twenty-two Ag/AgCl electrodes and encompassing motor imagery of the right and left hands, and feet; and the other (B) was obtained in the laboratory using an Emotiv EPOC headset, also with the same motor imaginary. Regarding feature extraction, several approaches were tested: namely, two versions of the signal’s power spectral density, followed by a filter bank version; the use of respective frequency coefficients; and, finally, two versions of the known method filter bank common spatial pattern (FBCSP). Concerning the results from the second version of FBCSP, dataset A presented an F1-score of 0.797 and a rather low false positive rate of 0.150. Moreover, the correspondent average kappa score reached the value of 0.693, which is in the same order of magnitude as 0.57, obtained by the competition. Regarding dataset B, the average value of the F1-score was 0.651, followed by a kappa score of 0.447, and a false positive rate of 0.471. However, it should be noted that some subjects from this dataset presented F1-scores of 0.747 and 0.911, suggesting that the movement imagery (MI) aptness of different users may influence their performance. In conclusion, it is possible to obtain promising results, using an architecture for a real-time application.

An optimized EEGNet decoder for decoding motor image of four class fingers flexion

As a cutting-edge technology of connecting biological brain and external devices, brain-computer interface (BCI) exhibits promising applications on extensive fields such as medical and military. As for the disable individuals with four limbs losing the motor functions, it is a potential treatment way to drive mechanical equipments by the means of non-invasive BCI, which is badly depended on the accuracy of the decoded electroencephalogram (EEG) singles. In this study, an explanatory convolutional neural network namely EEGNet based on SimAM attention module was proposed to enhance the accuracy of decoding the EEG singles of index and thumb fingers for both left and right hand using sensory motor rhythm (SMR). An average classification accuracy of 72.91% the data of eight healthy subjects was obtained, which were captured from the one second before finger movement to two seconds after action. Furthermore, the character of event-related desynchronization (ERD) and event related synchronization (ERS) of index and thumb fingers was also studied in this study. These findings have significant importance for controlling external devices or other rehabilitation equipment using BCI in a fine way.

Adults with cerebral palsy exhibit uncharacteristic cortical oscillations during an adaptive sensorimotor control task

Prior research has shown that the sensorimotor cortical oscillations are uncharacteristic in persons with cerebral palsy (CP); however, it is unknown if these altered cortical oscillations have an impact on adaptive sensorimotor control. This investigation evaluated the cortical dynamics when the motor action needs to be changed “on-the-fly”. Adults with CP and neurotypical controls completed a sensorimotor task that required either proactive or reactive control while undergoing magnetoencephalography (MEG). When compared with the controls, the adults with CP had a weaker beta (18–24 Hz) event-related desynchronization (ERD), post-movement beta rebound (PMBR, 16–20 Hz) and theta (4–6 Hz) event-related synchronization (ERS) in the sensorimotor cortices. In agreement with normative work, the controls exhibited differences in the strength of the sensorimotor gamma (66–84 Hz) ERS during proactive compared to reactive trials, but similar condition-wise changes were not seen in adults with CP. Lastly, the adults with CP who had a stronger theta ERS tended to have better hand dexterity, as indicated by the Box and Blocks Test and Purdue Pegboard Test. These results may suggest that alterations in the theta and gamma cortical oscillations play a role in the altered hand dexterity and uncharacteristic adaptive sensorimotor control noted in adults with CP.

Brain Networks Modulation during Simple and Complex Gait: A "Mobile Brain/Body Imaging" Study.

Walking encompasses a complex interplay of neuromuscular coordination and cognitive processes. Disruptions in gait can impact personal independence and quality of life, especially among the elderly and neurodegenerative patients. While traditional biomechanical analyses and neuroimaging techniques have contributed to understanding gait control, they often lack the temporal resolution needed for rapid neural dynamics. This study employs a mobile brain/body imaging (MoBI) platform with high-density electroencephalography (hd-EEG) to explore event-related desynchronization and synchronization (ERD/ERS) during overground walking. Simultaneous to hdEEG, we recorded gait spatiotemporal parameters. Participants were asked to walk under usual walking and dual-task walking conditions. For data analysis, we extracted ERD/ERS in α, β, and γ bands from 17 selected regions of interest encompassing not only the sensorimotor cerebral network but also the cognitive and affective networks. A correlation analysis was performed between gait parameters and ERD/ERS intensities in different networks in the different phases of gait. Results showed that ERD/ERS modulations across gait phases in the α and β bands extended beyond the sensorimotor network, over the cognitive and limbic networks, and were more prominent in all networks during dual tasks with respect to usual walking. Correlation analyses showed that a stronger α ERS in the initial double-support phases correlates with shorter step length, emphasizing the role of attention in motor control. Additionally, β ERD/ERS in affective and cognitive networks during dual-task walking correlated with dual-task gait performance, suggesting compensatory mechanisms in complex tasks. This study advances our understanding of neural dynamics during overground walking, emphasizing the multidimensional nature of gait control involving cognitive and affective networks.