EEG Acquisition Research Articles

Effects of Repeated Concussions and Sex on Early Processing of Emotional Facial Expressions as Revealed by Electrophysiology.

Concussions affect the processing of emotional stimuli. This study aimed to investigate how sex interacts with concussion effects on early event-related brain potentials (ERP) measures (P1, N1) of emotional facial expressions (EFE) processing in asymptomatic, multi-concussion athletes during an EFE identification task. Forty control athletes (20 females and 20 males) and 43 multi-concussed athletes (22 females and 21 males), recruited more than 3 months after their last concussion, were tested. Participants completed the Beck Depression Inventory II, the Beck Anxiety Inventory, the Post-Concussion Symptom Scale, and an Emotional Facial Expression Identification Task. Pictures of male and female faces expressing neutral, angry, and happy emotions were randomly presented and the emotion depicted had to be identified as fast as possible during EEG acquisition. Relative to controls, concussed athletes of both sex exhibited a significant suppression of P1 amplitude recorded from the dominant right hemisphere while performing the emotional face expression identification task. The present study also highlighted a sex-specific suppression of the N1 component amplitude after concussion which affected male athletes. These findings suggest that repeated concussions alter the typical pattern of right-hemisphere response dominance to EFE in early stages of EFE processing and that the neurophysiological mechanisms underlying the processing of emotional stimuli are distinctively affected across sex. (JINS, 2018, 24, 673-683).

Contact Pressure and Flexibility of Multipin Dry EEG Electrodes.

In state-of-the-art electroencephalography (EEG) Silver/Silver-Chloride electrodes are applied together with electrolyte gels or pastes. Their application requires extensive preparation, trained medical staff and limits measurement time and mobility. We recently proposed a novel multichannel cap system for dry EEG electrodes for mobile and out-of-the-lab EEG acquisition. During the tests with these novel polymer-based multipin dry electrodes, we observed that the quality of the recording depends on the applied normal force and resulting contact pressure. Consequently, in this paper we systematically investigate the influence of electrode-skin contact pressure and electrode substrate flexibility on interfacial impedance and perceived wearing comfort in a study on 12 volunteers. The normal force applied to the electrode was varied between the minimum required force to achieve impedances and a maximum of 4 N, using a new force measurement applicator. We found that for a polymer shore hardness A98, with increasing normal force, the impedance decreases from and to and at frontal hairless and temporal hairy positions, respectively. Similar results were obtained for shore A90, A80, and A70. The best compromise of low and stable impedances as well as a good wearing comfort was determined for applied normal forces between 2 and 3 N using electrodes with shore A98 or A90. Our results provide the basis for improved EEG cap designs with optimal wearing comfort and recording quality for dry multipin electrodes, which will enable new fields of application for EEG.

6. FACT OR ARTIFACT? BENEFITS AND LIMITATIONS OF ADVANCED NEUROIMAGING METHODS FOR PSYCHOSIS

Overall : Neuroimaging tools introduced the ability to non-invasively search for pathological signatures in the brains of subjects suffering from psychosis. In fact, with almost any neuroimaging modality there are studies that report the identification of abnormalities in the brains of schizophrenia subjects. The abundance of findings made it much clearer that brain abnormalities are common and expected in mental disorders. However, the quantity of findings, and especially their inconsistence across studies also raise questions as to the source of these abnormalities. Are they signifying a complicated range of pathologies and interactions? Or do they reflect auxiliary changes that are not directly related to the root, or the etiology of the disorder?In addition, these inconsistencies raise technical questions such as are our tools sufficiently sensitive to reliably identify brain abnormalities in psychosis? And, to what extent are our tools sensitive to misinterpretation and to artifacts, which may explain some of the group differences found when comparing psychotic populations with controls? Emerging imaging modalities attempt to address these concerns by improving the specificity, i.e., the ability to relate identified abnormalities with underlying pathologies. At the same time analysis must carefully pay attention to common physiological sources of artifacts, such as subject motion, blood flow, brain metabolism, partial volume, etc.This symposium will bring together five leading neuroimagers from 4 continents, who will present paradigm-shifting state of the art in their field, while providing critical cautionary remarks regarding the shortcomings of these methods, as well as recommendations for proper use in the context of psychosis studies. Speakers are:1) Prof. Jennifer Caughlin, M.D. Department of Psychiatry and Behavioral Sciences, Johns Hopkins University. She will present state of the art in TSPO-PET acquisition and analysis, and its potential for the evaluation of neuroinflammation in schizophrenia.2) Prof. Ofer Pasternak, Ph.D. Departments of Psychiatry and Radiology, Harvard Medical School. He will present recent advances in diffusion MRI, and how microstructural imaging may inform the study of psychosis.3) Prof. Christoph Mulert, M.D. Department of Psychiatry and Psychotherapy. University medical center Hamburg, Germany. He will present new approaches for EEG acquisitions combined with fMRI that may shed light on neuronal activity.4) Prof. Helen Juan Zhou, Ph.D. Neuroscience & Behavioural Disorders Programme, Duke-Nus Medical School, Singapore. She will present the emerging field of connectomics and its potential application to study functional and structural brain networks in schizophrenia.The discussant will be Prof. Christos Pantelis, M.D. Department of Psychiatry, University of Melbourne, Australia. Dr. Pantelis will complement the panel by bringing in a more clinical point of view, informed of the needs in psychiatric neuroimaging. The panel will also benefit from his vast experience across all imaging modalities.This symposium is designed to provide information and considerations that can be essential for psychosis researchers before considering the application of advanced imaging tools. We will describe the main and unique findings that were provided by each modality, towards a discussion of how far are imaging studies from leading to a breakthrough in the understanding of the pathophysiology of psychosis or its treatment.

Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset

We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for ‘target’ versus ‘non-target’ (dataset A) and symbol ‘O’ versus symbol ‘X’ (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques.

Online Transcranial Magnetic Stimulation Protocol for Measuring Cortical Physiology Associated with Response Inhibition.

We describe the development of a reproducible, child-friendly motor response inhibition task suitable for online Transcranial Magnetic Stimulation (TMS) characterization of primary motor cortex (M1) excitability and inhibition. Motor response inhibition prevents unwanted actions and is abnormal in several neuropsychiatric conditions. TMS is a non-invasive technology that can quantify M1 excitability and inhibition using single- and paired-pulse protocols and can be precisely timed to study cortical physiology with high temporal resolution. We modified the original Slater-Hammel (S-H) stop signal task to create a "racecar" version with TMS pulses time-locked to intra-trial events. This task is self-paced, with each trial initiating after a button push to move the racecar towards the 800 ms target. GO trials require a finger-lift to stop the racecar just before this target. Interspersed randomly are STOP trials (25%) during which the dynamically adjusted stop signal prompts subjects to prevent finger-lift. For GO trials, TMS pulses were delivered at 650 ms after trial onset; whereas, for STOP trials, the TMS pulses occurred 150 ms after the stop signal. The timings of the TMS pulses were decided based on electroencephalography (EEG) studies showing event-related changes in these time ranges during stop signal tasks. This task was studied in 3 blocks at two study sites (n=38) and we recorded behavioral performance and event-related motor-evoked potentials (MEP). Regression modelling was used to analyze MEP amplitudes using age as a covariate with multiple independent variables (sex, study site, block, TMS pulse condition [single- vs. paired-pulse], trial condition [GO, successful STOP, failed STOP]). The analysis showed that TMS pulse condition (p<0.0001) and its interaction with trial condition (p=0.009) were significant. Future applications for this online S-H/TMS paradigm include the addition of simultaneous EEG acquisition to measure TMS-evoked EEG potentials. A potential limitation is that in children, the TMS pulse sound couldaffect behavioral task performance.

Online Transcranial Magnetic Stimulation Protocol for Measuring Cortical Physiology Associated with Response Inhibition

We describe the development of a reproducible, child-friendly motor response inhibition task suitable for online Transcranial Magnetic Stimulation (TMS) characterization of primary motor cortex (M1) excitability and inhibition. Motor response inhibition prevents unwanted actions and is abnormal in several neuropsychiatric conditions. TMS is a non-invasive technology that can quantify M1 excitability and inhibition using single- and paired-pulse protocols and can be precisely timed to study cortical physiology with high temporal resolution. We modified the original Slater-Hammel (S-H) stop signal task to create a "racecar" version with TMS pulses time-locked to intra-trial events. This task is self-paced, with each trial initiating after a button push to move the racecar towards the 800 ms target. GO trials require a finger-lift to stop the racecar just before this target. Interspersed randomly are STOP trials (25%) during which the dynamically adjusted stop signal prompts subjects to prevent finger-lift. For GO trials, TMS pulses were delivered at 650 ms after trial onset; whereas, for STOP trials, the TMS pulses occurred 150 ms after the stop signal. The timings of the TMS pulses were decided based on electroencephalography (EEG) studies showing event-related changes in these time ranges during stop signal tasks. This task was studied in 3 blocks at two study sites (n=38) and we recorded behavioral performance and event-related motor-evoked potentials (MEP). Regression modelling was used to analyze MEP amplitudes using age as a covariate with multiple independent variables (sex, study site, block, TMS pulse condition [single- vs. paired-pulse], trial condition [GO, successful STOP, failed STOP]). The analysis showed that TMS pulse condition (p<0.0001) and its interaction with trial condition (p=0.009) were significant. Future applications for this online S-H/TMS paradigm include the addition of simultaneous EEG acquisition to measure TMS-evoked EEG potentials. A potential limitation is that in children, the TMS pulse sound could affect behavioral task performance.

Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI.

Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2–20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.

Validation and Benchmarking of a Wearable EEG Acquisition Platform for Real-World Applications.

This paper presents the experimental validation of a readout circuit for the acquisition, amplification, and transmission of extremely weak biopotentials with a focus on electroencephalography (EEG) signals. The device, dubbed CochlEEG, benefits from a low-power design for long-term power autonomy and provides configurable gain and sampling rates to suit the needs of various EEG applications. CochlEEG features high sampling rates, up to 4kHz, low-noise signal acquisitions, support for active electrodes, and a potential for Wi-Fi data transmission. Moreover, it is lightweight, pocket size, and affordable, which makes CochlEEG suitable for wearable and real-world applications. The efficiency of CochlEEG in EEG data acquisition is also investigated in this paper. Auditory steady-state responses acquisition results validate CochlEEG's capability in recording EEG with a signal quality comparable to commercial mobile or research EEG acquisition devices. Moreover, the results of an oddball paradigm experiment prove the capability of CochlEEG in recording event-related potentials and demonstrate its potential for brain-computer interface applications and electrophysiological research applications requiring higher temporal resolution.

Identifying the neural signature of thermic comfort sensation: neuroergonomic evaluation of a new ventilating system integrated in car seat

Identifying the neural signature of thermic comfort sensation: neuroergonomic evaluation of a new ventilating system integrated in car seat

A Pervasive Approach to EEG‐Based Depression Detection

Nowadays, depression is the world’s major health concern and economic burden worldwide. However, due to the limitations of current methods for depression diagnosis, a pervasive and objective approach is essential. In the present study, a psychophysiological database, containing 213 (92 depressed patients and 121 normal controls) subjects, was constructed. The electroencephalogram (EEG) signals of all participants under resting state and sound stimulation were collected using a pervasive prefrontal‐lobe three‐electrode EEG system at Fp1, Fp2, and Fpz electrode sites. After denoising using the Finite Impulse Response filter combining the Kalman derivation formula, Discrete Wavelet Transformation, and an Adaptive Predictor Filter, a total of 270 linear and nonlinear features were extracted. Then, the minimal‐redundancy‐maximal‐relevance feature selection technique reduced the dimensionality of the feature space. Four classification methods (Support Vector Machine, K‐Nearest Neighbor, Classification Trees, and Artificial Neural Network) distinguished the depressed participants from normal controls. The classifiers’ performances were evaluated using 10‐fold cross‐validation. The results showed that K‐Nearest Neighbor (KNN) had the highest accuracy of 79.27%. The result also suggested that the absolute power of the theta wave might be a valid characteristic for discriminating depression. This study proves the feasibility of a pervasive three‐electrode EEG acquisition system for depression diagnosis.

Assessing a novel micro-seepage electrode with flexible and elastic tips for wearable EEG acquisition

ObjectElectroencephalogram (EEG) electrodes play an important role in the applications of wearable brain-computer interfaces (BCI). Although traditional wet gel-based electrodes can obtain low contact impedance and high signal-to-noise ratio (SNR), cumbersome procedures including skin preparation, gelling, and hair cleaning make them inconvenient to use. Dry electrodes can avoid these shortcomings; however, they can hardly achieve impedance and SNR as good as wet electrodes. This study aims to develop a novel micro-seepage electrode, which possesses both high convenience of dry electrode and low contact impedance of wet electrode, and assess contact impedance, comfort level, and EEG signal quality of the proposed electrode. MethodThe proposed micro-seepage electrode can continuously provide a small amount of electrolyte from flexible brush-pen like tips to scalp, which keeps the scalp-electrode interface moist like that of wet electrodes. The electrode can be put on and taken off easily like dry electrode, and there is also no need to wash hair after use. This study investigated the contact impedance of the electrode with regard to electrolyte type, recording duration, and contact pressure on the occipital area. In addition, this study compared SNR and classification accuracy of steady-state visual evoked potentials (SSVEPs) between the proposed electrode and the wet electrode. ResultThe proposed electrode can be set up very quickly. The flexible and elastic tips make it comfortable to wear. Using the contact lens cleaning solution as electrolyte, the average impedance of the electrode was 12.1 kΩ@10 Hz. The impedance kept below 20 kΩ for more than 8 h on volunteers’ scalp. The SNR and classification accuracy of SSVEPs obtained by the proposed electrodes were comparable to those of wet electrodes. SignificanceThe proposed micro-seepage electrode can provide a comfortable and convenient solution for high-quality EEG acquisition.

Neurophysiological correlates of depressive symptoms in young adults: A quantitative EEG study

BackgroundThere is an unmet need for practical and reliable biomarkers for mood disorders in young adults. Identifying the brain activity associated with the early signs of depressive disorders could have important diagnostic and therapeutic implications. In this study we sought to investigate the EEG characteristics in young adults with newly identified depressive symptoms. MethodsBased on the initial screening, a total of 100 participants (n = 50 euthymic, n = 50 depressive) underwent 32-channel EEG acquisition. Simple logistic regression and C-statistic were used to explore if EEG power could be used to discriminate between the groups. The strongest EEG predictors of mood using multivariate logistic regression models. ResultsSimple logistic regression analysis with subsequent C-statistics revealed that only high-alpha and beta power originating from the left central cortex (C3) have a reliable discriminative value (ROC curve >0.7 (70%)) for differentiating the depressive group from the euthymic group. Multivariate regression analysis showed that the single most significant predictor of group (depressive vs. euthymic) is the high-alpha power over C3 (p = 0.03). ConclusionThe present findings suggest that EEG is a useful tool in the identification of neurophysiological correlates of depressive symptoms in young adults with no previous psychiatric history. SignificanceOur results could guide future studies investigating the early neurophysiological changes and surrogate outcomes in depression.

Features Selection and Pattern Classification of Electroencephalography Motor Imagery Tasks of Right Hand

This study presentsa Brain Computer Interface (BCI) approach to detect the motor intents of the disabled people with right hand amputation. Electroencephalography (EEG) Motor Imagery (MI)-based Brain Computer Interface (BCI) systems have been recently used to improve the quality of life of disabled people. However, to naturally trigger particular applications (i.e., upper limb prostheses), independent BCIs appeal further paradigms to involve realistic motor imagery tasks. This study proposes an approach to classifying imagined hand gesture tasks, including the water glass gesture and the index pointer gesture of the right hand using OPENBCI as a consumer-grade EEG acquisition device. For three subjects, the data recorded by OPENBCI were sampled with a sampling rate of 250 Hz. The Minimum Redundancy Maximum Relevance (MRMR) technique was implemented as a feature selection method along with the Support Vector Machine (SVM) algorithm for classification. By obtaining a maximum classification accuracy of 91.7%, the results showed the feasibility of such Brain Computer Interface systems to detect different motor imagery tasks for the right hand. Consequently, upper limb prostheses could be manipulated using the intended motor imagery tasks.

FV 14 Dynamic modulation of vigilance states during affective stimulation

Background To investigate the interplay between affective information processing and functional brain states, differences in arousal regulation after stimulation with affective narratives were investigated. Based on EEG acquisitions at resting state, it is possible to differentiate stages of wakefulness regulation. The temporal evolution of these vigilance stages sheds light on individual variations in arousal level in reaction to preceding affective stimulation ( Olbrich et al., 2009 ). Methods Resting state EEG was recorded from eighteen healthy subjects for 10 min each with eyes closed: first at baseline and then after passive listening to three emotional narratives about experiences in early childhood of strangers (securely attached, insecure-dismissing, insecure-preoccupied) ( Borchardt et al., 2015 ). Using the VIGALL 2.0 algorithm, vigilance stages (high: A1, A2, A3, low: B2/3) in consecutive EEG segments (duration: 2.4 s) were classified and their dynamic profile was analyszed ( Sander et al., 2015 ). Additionally, the Temperament and Character Inventory (TCI) was assessed ( Cloninger et al., 1993 ). Results At baseline, the percentage of subjects in low vigilance stages was continuously high and stable over time, while in conditions after emotional stimulation the percentage of subjects was first highest in high vigilance stages but quickly decreased over time. A difference between narrative conditions was revealed in the insecure-dismissing condition, in which the decrease of the percentage of subjects in high vigilance stages was highest compared to the other two conditions. Analyzing dynamics of vigilance stages, only in the insecure-dismissing condition, the number of EEG segments in high vigilance stages in the first 160 s (interval 1) was significantly higher compared to the last 160 s (interval 4) after normalization to the subject-specific baseline level (p = 0.008). In a subgroup of the participants (N = 14), we found a significant, strong negative correlation (r = −0.82, p = 0.0003) between individual dynamic of slope in high vigilance stages at baseline and harm avoidance, a temperament trait of personality, whose characteristics are elevated tiredness, weakness, and a prolonged recovery after emotional stress. Discussion At resting state, a continuous decrease of vigilance is a physiological finding ( Olbrich et al., 2009 ). So far, an effect of preceding auditory stimulation with affective content on regulation of wakefulness has not been investigated and provides evidence for dynamic influences of emotions and mood on brain states ( Borchardt et al., 2015 , Bola and Borchardt, 2016 ).

P 100 A 64-channel dry multipin-electrode cap for EEG

Multichannel Electroencephalography (EEG) is widely used in clinical neurology and neuroscientific research. EEG caps with 64 wet Silver/Silver-Chloride (Ag/AgCl) electrodes represent an often-used standard in the field. Reproducible electrode-skin contact for these electrodes is ensured by electrolyte gel or paste. Thus, these electrodes require specific mechanisms to apply and hold the gel at the electrode positions in the caps and require skilled personnel to apply the EEG cap. Dry electrodes allow more degrees of freedom in the design and fabrication of EEG caps and can be self-applied without preparation. We present a novel 64-channel EEG cap with dry electrodes. The base material of the EEG cap is a light-weight and flexible fabric, which contains small holes (perforation) making it breathable. Polyurethane (PU) based multipin electrodes serve as dry contact electrodes. A coating provides electrical conductivity of these polymer based electrodes. The use of silver coating opens the way for dry AgCl electrodes and thus, signal quality similar to wet Ag/AgCl electrodes. Thin coaxial wires are soldered to the bottom of the electrodes enabling active shielding. A second layer of fabrics protects the electrodes and the wires. Our results demonstrate that resting state EEG, eye movements, alpha activity, and pattern reversal VEP can be recorded with the novel dry 64-channel EEG cap with short preparation time and without significant differences between the novel EEG cap and a conventional cap based on wet Ag/AgCl electrodes. In conclusion, the proposed novel 64-channel EEG cap with dry electrodes can potentially replace conventional wet 64-channel EEG caps and thus enable new fields of application like brain-computer-interfaces and mobile EEG acquisition.

Composing only by thought: Novel application of the P300 brain-computer interface.

The P300 event-related potential is a well-known pattern in the electroencephalogram (EEG). This kind of brain signal is used for many different brain-computer interface (BCI) applications, e.g., spellers, environmental controllers, web browsers, or for painting. In recent times, BCI systems are mature enough to leave the laboratories to be used by the end-users, namely severely disabled people. Therefore, new challenges arise and the systems should be implemented and evaluated according to user-centered design (USD) guidelines. We developed and implemented a new system that utilizes the P300 pattern to compose music. Our Brain Composing system consists of three parts: the EEG acquisition device, the P300-based BCI, and the music composing software. Seventeen musical participants and one professional composer performed a copy-spelling, a copy-composing, and a free-composing task with the system. According to the USD guidelines, we investigated the efficiency, the effectiveness and subjective criteria in terms of satisfaction, enjoyment, frustration, and attractiveness. The musical participants group achieved high average accuracies: 88.24% (copy-spelling), 88.58% (copy-composing), and 76.51% (free-composing). The professional composer achieved also high accuracies: 100% (copy-spelling), 93.62% (copy-composing), and 98.20% (free-composing). General results regarding the subjective criteria evaluation were that the participants enjoyed the usage of the Brain Composing system and were highly satisfied with the system. Showing very positive results with healthy people in this study, this was the first step towards a music composing system for severely disabled people.

P313 Changes in EEG complexity of brain dynamics associated with bold fluctuations during resting state

Objectives Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data how the EEG complexity of brain dynamic, such as instability or entropy of EEG rhythmic structure, may reflect variations in the BOLD signal. Methods We aimed to find the relationships between EEG dynamics and brain activation obtained by simultaneous EEG-fMRI during resting state condition in 25 healthy right-handed adult voluntaries. We applied nonlinear analysis in order to obtain chaotic features of EEG, which we used as regressors in GLM relating to changes in the BOLD signal. Results Fluctuations in beta rhythm were associated with the BOLD signal increase in basal ganglia and thalamic structures ( p 0.05 , FDR-corrected). Moreover, our data showed that Higuchi fractal dimension correlated with activation of cortical areas and limbic system regions. Offset of alpha-peak frequency and envelope frequency coincided with activation of thalamus, insula, hippocampus and temporal cortex predominantly in the right hemisphere. Conclusions Previously, nonlinear EEG analysis in clinical neurophysiology pointed that decreased complexity of brain dynamics might implicate increased neuronal interaction. Our results indicate that dynamic properties of spontaneous EEG have a significant association with resting state BOLD fluctuations reflecting possible sources of rhythmic neuronal activity. In particular, the observed increase in the BOLD signal significantly correlated with deviation of beta rhythm power that supports the hypothesis of basal-thalamic origin of beta rhythm. The study was supported by a grant of the Russian Science Foundation 116-15-00300.

Familiarity affects electrocortical power spectra during dance imagery, listening to different music genres: independent component analysis of Alpha and Beta rhythms

Changes in electrocortical activity during motor imagery are among the most interesting findings in the recent neuroscientific studies; existing studies, however, do not focus specifically on Alpha and Beta rhythms, in relationship with the motor experience and verifying if the style of music can influence the cortical activity during motor imagery task. Power spectra analysis was used to compare the EEG activity during dance imagery tasks in a group of dancers and in a control group. Twenty-one volunteers performed a dance imagery task listening to three kinds of music. For EEG acquisition an 8-channel headset with wireless amplifier was used. This study used independent component analysis (ICA) to assess EEG frequency spectrum associated with the musical genre. High Alpha (10.0–11.5 Hz) and Low Beta (12.0–15.5 Hz) EEG frequency spectra were analyzed. Considering EEG power spectra analysis, no statistically significant differences were found between groups at baseline. Statistically significant difference (p < 0.01) emerged comparingthe two groups, during dance imagery task, listening to Classical, Rock and Waltz music, in High Alpha band; whereas listening to Classical music in Low Beta band. Expert group showed a greater power level with respect to control group for both bands. No statistically significant difference emerged in EEG power spectrum, comparing the three kinds of music, for both groups (intra-group analysis). Findings are comparable with previous studies obtained by other neuroimaging modalities, highlighting how high-resolution EEG may prove to be a promising tool for measuring cortex electrical activity during motor imagery. This study successfully applied ICA to decompose the EEG segments recorded during the tasks, finding consistent independent brain processes across multiple subjects. The statistically significant differences between expert dancers and controls, could indicate a difference in the attentional effort during the dance imagery task. The remarks partially confirm existing findings on the relationship among EEG activity, Alpha rhythm and motor imagery and also extend the knowledge on the EEG response to auditory stimuli during motor imagery in particular for Beta rhythm components, emphasizing specific characteristics in function of the level of familiarity to the dance imagery task.

Design and implementation of sixteen channel EEG acquisition system

ABSTRACTIn this paper, a portable and cost-effective 16-channel EEG acquisition system with multiple analog front ends cascaded was designed. Channels required were selected according to chip selecting signal to configure each in a dynamic and personalized manner. In order to test system performance, EEG signals of five subjects from spontaneous state were sent to the host computer through the high-speed wireless module. Related steady-state visual evoked experiment was collected and analyzed. It was observed that obvious alpha rhythm appears during eyes-closed in spontaneous EEG signals; and peak values appears at the corresponding stimulating frequency and harmonics in steady-state visual evoked experiment. The results show that the acquisition system can accurately collect spontaneous EEG signals and evoked EEG signals. Therefore, it is suggested this system can be used in applications of brain computer interface and have certain theoretical and practical values.

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies.

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed.