Ratio Indexes Based on Spectral Electroencephalographic Brainwaves for Assessment of Mental Involvement: A Systematic Review.

BACKGROUND: This review systematically examined the scientific literature about electroencephalogram-derived ratio indexes used to assess human mental involvement, in order to deduce what they are, how they are defined and used, and what their best fields of application are. (2) Methods: The review was carried out according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. (3) Results: From the search query, 82 documents resulted. The majority (82%) were classified as related to mental strain, while 12% were classified as related to sensory and emotion aspects, and 6% to movement. The electroencephalographic electrode montage used was low-density in 13%, high-density in 6% and very-low-density in 81% of documents. The most used electrode positions for computation of involvement indexes were in the frontal and prefrontal cortex. Overall, 37 different formulations of involvement indexes were found. None of them could be directly related to a specific field of application. (4) Conclusions: Standardization in the definition of these indexes is missing, both in the considered frequency bands and in the exploited electrodes. Future research may focus on the development of indexes with a unique definition to monitor and characterize mental involvement.

Parental education is associated with differential engagement of neural pathways during inhibitory control.

Response inhibition and socioeconomic status (SES) are critical predictors of many important outcomes, including educational attainment and health. The current study extends our understanding of SES and cognition by examining brain activity associated with response inhibition, during the key developmental period of adolescence. Adolescent males (N = 81), aged 16-17, completed a response inhibition task while undergoing fMRI brain imaging and reported on their parents' education, one component of socioeconomic status. A region of interest analysis showed that parental education was associated with brain activation differences in the classic response inhibition network (right inferior frontal gyrus + subthalamic nucleus + globus pallidus) despite the absence of consistent parental education-performance effects. Further, although activity in our main regions of interest was not associated with performance differences, several regions that were associated with better inhibitory performance (ventromedial prefrontal cortex, middle frontal gyrus, middle temporal gyrus, amygdala/hippocampus) also differed in their levels of activation according to parental education. Taken together, these results suggest that individuals from households with higher versus lower parental education engage key brain regions involved in response inhibition to differing degrees, though these differences may not translate into performance differences.

Assessment of bladder function for stabilizing urinary volume overnight with recording of brain waves (ABSORB study).

OBJECTIVES: The bladder urothelium is not always impermeable. During sleep, the bladder might absorb urine in healthy individuals who sleep through the night. This study aimed to determine whether the bladder absorbs urine by using a method other than ultrasonic scanning and to simultaneously evaluate sleeping conditions. METHODS: Eleven participants (five males, six females) aged 20 to 49 years without lower urinary tract symptoms or urination while sleeping were enrolled. Bladder volume was estimated by studying the relationship between dilution and absorbance of indigo carmine dissolved in urine. A 12F Foley catheter was inserted into the bladder before sleep. Urine samples (5 mL) were extracted at 2, 3, 4, 5, and 6 am sleep stages were monitored with a single-channel portable electroencephalograph device. RESULTS: The estimated bladder volume at 6 am and voided volume immediately after rising were significantly correlated (Spearman's ρ = 0.62, P = .046). Eight participants (three males, five females) showed an absorption pattern of the estimated bladder volume change. In a male participant, the blue dye's strength gradually decreased until 4 am (estimated 859 mL) and increased from 5 am (estimated 455 mL). In another, the blue dye's strength increased at 4 am (estimated 449 mL) vs at 3 am (estimated 757 mL). In all participants, electroencephalograph data demonstrated that sleep was maintained despite having a full bladder. CONCLUSIONS: The bladder absorbs urine and maintains an approximate volume of functional bladder capacity during sleep to avoid incontinence and maintain sleep in adults due to an urge to void urine during the sleep cycle.

Scalp-HFO indexes are biomarkers for the lateralization and localization of the epileptogenic zone in preoperative assessment.

During the noninvasive evaluation phase for refractory epilepsy, the localization of the epileptogenic zone (EZ) is essential for the surgical protocols. Confirmation of laterality is required when the preoperative evaluation limits the EZ to bilateral anterior temporal lobes or bilateral frontal lobes. High-frequency oscillations (HFOs) are considered to be promising biological markers for the EZ. However, a large number of studies on HFOs stem from intracranial research. There were few quantitative measures for scalp HFOs, so we proposed a new method to quantify and analyze scalp HFOs. This method was called the "scalp-HFO index" (HI) and calculated in both the EZ and non-EZ. The calculation was based on the numbers and spectral power of scalp HFOs automatically detected. We labeled the brain lobes involved in the EZ as regions of interest (ROIs). The HIs based on the ripple numbers (n-HI) and spectral power (s-HI) were significantly higher in the ROI than in the contra-ROI (P = 0.012, P = 0.003), indicating that HIs contributed to the lateralization of EZ. The sensitivity and specificity of n-HI for the localization of the EZ were 90% and 79.58%, respectively, suggesting that n-HI was valuable in localizing the EZ. HI may contribute to the implantation strategy of invasive electrodes. However, few scalp HFOs were recorded when the EZ was located in the medial cortex region.NEW & NOTEWORTHY We proposed the scalp-high-frequency oscillation (HFO) index (HI) as a quantitative assessment method for scalp HFOs to locate the epileptogenic zone (EZ). Our results showed that the HI in regions of interest (ROIs) was significantly higher than in contra-ROIs. Sensitivity and specificity of HI based on ripple rates (n-HI) for EZ localization were 90% and 79.58%, respectively. If the n-HI of the brain region was >1.35, it was more likely to be an epileptogenic region. Clinical application of HIs as an indicator may facilitate localization of the EZ.

Differential dopaminergic modulation of spontaneous cortico-subthalamic activity in Parkinson's disease.

Pathological oscillations including elevated beta activity in the subthalamic nucleus (STN) and between STN and cortical areas are a hallmark of neural activity in Parkinson's disease (PD). Oscillations also play an important role in normal physiological processes and serve distinct functional roles at different points in time. We characterised the effect of dopaminergic medication on oscillatory whole-brain networks in PD in a time-resolved manner by employing a hidden Markov model on combined STN local field potentials and magnetoencephalography (MEG) recordings from 17 PD patients. Dopaminergic medication led to coherence within the medial and orbitofrontal cortex in the delta/theta frequency range. This is in line with known side effects of dopamine treatment such as deteriorated executive functions in PD. In addition, dopamine caused the beta band activity to switch from an STN-mediated motor network to a frontoparietal-mediated one. In contrast, dopamine did not modify local STN-STN coherence in PD. STN-STN synchrony emerged both on and off medication. By providing electrophysiological evidence for the differential effects of dopaminergic medication on the discovered networks, our findings open further avenues for electrical and pharmacological interventions in PD.

Effects of Thai Local Ingredient Odorants, Litsea cubeba and Garlic Essential Oils, on Brainwaves and Moods.

The functional food market is growing with a compound annual growth rate of 7.9%. Thai food recipes use several kinds of herbs. Lemongrass, garlic, and turmeric are ingredients used in Thai curry paste. Essential oils released in the preparation step create the flavor and fragrance of the famous tom yum and massaman dishes. While the biological activities of these ingredients have been investigated, including the antioxidant, anti-inflammatory, and antimicrobial activities, there is still a lack of understanding regarding the responses to the essential oils of these plants. To investigate the effects of essential oil inhalation on the brain and mood responses, electroencephalography was carried out during the non-task resting state, and self-assessment of the mood state was performed. The essential oils were prepared in several dilutions in the range of the supra-threshold level. The results show that Litsea cubeba oil inhalation showed a sedative effect, observed from alpha and beta wave power reductions. The frontal and temporal regions of the brain were involved in the wave alterations. Garlic oil increased the alpha wave power at lower concentrations; however, a sedative effect was also observed at higher concentrations. Lower dilution oil induced changes in the fast alpha activity in the frontal region. The alpha and beta wave powers were decreased with higher dilution oils, particularly in the temporal, parietal, and occipital regions. Both Litsea cubeba and turmeric oils resulted in better positive moods than garlic oil. Garlic oil caused more negative moods than the others. The psychophysiological activities and the related brain functions require further investigation. The knowledge obtained from this study may be used to design functional food products.

Assessment of Visual and Brainstem Auditory Evoked Potentials in Patients with Hashimoto's Thyroiditis.

BACKGROUND: The present study was aimed to evaluate parameters of visual and brainstem auditory evoked potentials (VEP, BAEP) in euthyreotic Hashimoto's thyroiditis (HT) patients without central nervous system involvement. METHODS: 100 HT patients (92 women, 8 men), mean age 46.9 years, and 50 healthy controls. They underwent a neurological examination, thyroid hormone levels, thyroid autoantibody titers, and brain imaging. Latencies and amplitudes of the N75, P100, and N145 component of VEP and the I-V components of BAEP were analyzed. RESULTS: The neurological examination revealed in 31 patients signs of increased neurovegetative excitability. Brain resonance imaging showed no abnormalities in HT patients. The mean P100, relative P100, and N145 VEP latencies were significantly longer, and P100 amplitude significantly higher in HT patients than the controls. HT patients also had a longer mean wave BAEP V latency and mean wave III-V and I-V interpeak latencies, and significantly lower mean wave I and V amplitudes. Abnormal VEP and BAEP were recorded in 34% of the patients. There were no statistically significant correlations between the mean VEP parameters and thyroid profile and the applied dose of L-thyroxine. There was a relationship between the level of TSH and the wave BAEP III-V interpeak latency. CONCLUSIONS: There were changes in the brain's bioelectrical activity in one-third of the patients with HT without nervous system involvement. The increased amplitude of the VEP may indicate increased cerebral cortex activity. Disorders of the brain's bioelectrical activity in the course of HT may be associated with an autoimmune process.

Changes in electrophysiological static and dynamic human brain functional architecture from childhood to late adulthood.

This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6-9 years), young adults (18-34 years) and healthy elders (53-78 years). The effects of age on static resting-state functional brain integration were assessed using band-limited power envelope correlation, whereas those on transient functional brain dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (1) a strengthening of functional integration within and between resting-state networks and (2) an increased temporal stability of transient (100-300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamic stability within the primary visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging. These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.

Brain oscillatory activity associated with switch and mixing costs during reactive control.

Task-switching paradigms, which involve task repetitions and between-task switches, have long been used as a benchmark of cognitive control processes. When mixed and single-task blocks are presented, two types of costs usually occur: the switch cost, measured by contrasting performance on switch and repeat trials during the mixed-task blocks, and the mixing cost, calculated as the performance difference between the all-repeat trials from the single-task blocks and the repeat trials from the mixed-task blocks. Both costs can be mitigated by informational cues that signal the upcoming task switch beforehand. Recent electroencephalographic studies have started unveiling the brain oscillatory activity underlying the switch cost during the preparatory cue-target interval, thus, targeting proactive control processes. Less attention has instead been paid to the mixing cost and, importantly, to the oscillatory dynamics involved in switch and mixing costs during reactive control. To fill this gap, here, we analyzed the time-frequency data obtained during a task-switching paradigm wherein the simultaneous presentation of task cues and targets increased the need for reactive control. Results showed that while alpha and beta bands were modulated by switch and mixing costs in a similar gradual fashion, with greater suppression going from switch to repeat and all-repeat trials, theta power was sensitive to the switch cost with increased power for switch than repeat trials. Together, our findings join previous studies underlining the importance of theta, alpha and beta oscillations in task-switching and extend them by depicting the oscillations involved in switch and mixing costs during reactive control processes.

Task-switching costs have distinct phase-locked and nonphase-locked EEG power effects.

Event-related potentials (ERPs) and total time-frequency power analyses have shown that performance costs during task switching are related to differential preparation to switch tasks (switch cost) and repeat the same task (mixing cost) during both proactive control (cue-to-target interval; CTI) and reactive control (post-target). The time-frequency EEG signal is comprised of both phase-locked activity (associated with stimulus-specific processes) and nonphase-locked activity (represents processes thought to persist over longer timeframes and do not contribute to the average ERP). In the present study, we used a cued task-switching paradigm to examine whether phase-locked and nonphase-locked power are differentially modulated by switch and mixing effects in intervals associated with the need for proactive control (CTI) and reactive control (post-target interval). Phase-locked activity was observed in the theta and alpha bands, closely resembled that seen for total power, and was consistent with switch and mixing ERP positivities. Nonphase-locked analyses showed theta and alpha power effects for both switch and mixing effects early in the CTI and as well as more sustained alpha and beta activity around cue onset, and extending from mid-CTI into the post-target interval. Nonphase-locked activity in pretarget alpha and posttarget theta power were both correlated with response time mixing cost. These findings provide novel insight into phase-locked and nonphase-locked activity associated with switch and mixing costs that are not evident with ERP or total time-frequency analyses.

Correlation and Similarity between Cerebral and Non-Cerebral Electrical Activity for User's States Assessment.

Human tissues own conductive properties, and the electrical activity produced by human organs can propagate throughout the body due to neuro transmitters and electrolytes. Therefore, it might be reasonable to hypothesize correlations and similarities between electrical activities among different parts of the body. Since no works have been found in this direction, the proposed study aimed at overcoming this lack of evidence and seeking analogies between the brain activity and the electrical activity of non-cerebral locations, such as the neck and wrists, to determine if i) cerebral parameters can be estimated from non-cerebral sites, and if ii) non-cerebral sensors can replace cerebral sensors for the evaluation of the users under specific experimental conditions, such as eyes open or closed. In fact, the use of cerebral sensors requires high-qualified personnel, and reliable recording systems, which are still expensive. Therefore, the possibility to use cheaper and easy-to-use equipment to estimate cerebral parameters will allow making some brain-based applications less invasive and expensive, and easier to employ. The results demonstrated the occurrence of significant correlations and analogies between cerebral and non-cerebral electrical activity. Furthermore, the same discrimination and classification accuracy were found in using the cerebral or non-cerebral sites for the user's status assessment.

Bayesian multi-dipole modelling in the frequency domain.

BACKGROUND: Magneto- and Electro-encephalography record the electromagnetic field generated by neural currents with high temporal frequency and good spatial resolution, and are therefore well suited for source localization in the time and in the frequency domain. In particular, localization of the generators of neural oscillations is very important in the study of cognitive processes in the healthy and in the pathological brain. NEW METHOD: We introduce the use of a Bayesian multi-dipole localization method in the frequency domain. Given the Fourier Transform of the data at one or multiple frequencies and/or trials, the algorithm approximates numerically the posterior distribution with Monte Carlo techniques. RESULTS: We use synthetic data to show that the proposed method behaves well under a wide range of experimental conditions, including low signal-to-noise ratios and correlated sources. We use dipole clusters to mimic the effect of extended sources. In addition, we test the algorithm on real MEG data to confirm its feasibility. COMPARISON WITH EXISTING METHOD(S): Throughout the whole study, DICS (Dynamic Imaging of Coherent Sources) is used systematically as a benchmark. The two methods provide similar general pictures; the posterior distributions of the Bayesian approach contain much richer information at the price of a higher computational cost. CONCLUSIONS: The Bayesian method described in this paper represents a reliable approach for localization of multiple dipoles in the frequency domain.

A novel supportive assessment for comprehensive aggression using EEG and ECG.

Aggression is a complex, ubiquitous phenomenon that impacts behavioral traits and psychological health. Assessing aggression is challenging because aggression constitutes multiple subtraits, such as anger, reactive aggression, and overt aggression. Conventional methods of assessing aggression are susceptible to bias because they mainly rely upon self-reports. Thus, more objective methods that provide a multifaceted understanding of aggression in individuals are required. Here, we propose a supportive method of assessing specific aggression subtraits in Koreans using electroencephalography (EEG) and electrocardiography (ECG). Our evaluations and statistical analyses revealed that EEG and ECG signals in subjects responding to video cues that induced aggression are associated with aggression subtraits. In particular, we identified spectral differences in EEG signals in response to stimuli with situation-dependent aggression. The α and ß signals of the Fp2 site (the right ventromedial prefrontal region) are highly associated with anger, reactive aggression, and overt aggression. Moreover, ECG signals are associated with anger and overt aggression. These results link neurobiological findings to psychological explanations of aggression and multiple aspects of human behavior. Our findings can potentially be applied to supportive assessment methods for psychological counseling or psychiatric diagnoses.

Effects of an Integrated Neurofeedback System with Dry Electrodes: EEG Acquisition and Cognition Assessment.

Electroencephalogram (EEG) neurofeedback improves cognitive capacity and behaviors by regulating brain activity, which can lead to cognitive enhancement in healthy people and better rehabilitation in patients. The increased use of EEG neurofeedback highlights the urgent need to reduce the discomfort and preparation time and increase the stability and simplicity of the system's operation. Based on brain-computer interface technology and a multithreading design, we describe a neurofeedback system with an integrated design that incorporates wearable, multichannel, dry electrode EEG acquisition equipment and cognitive function assessment. Then, we evaluated the effectiveness of the system in a single-blind control experiment in healthy people, who increased the alpha frequency band power in a neurofeedback protocol. We found that upregulation of the alpha power density improved working memory following short-term training (only five training sessions in a week), while the attention network regulation may be related to other frequency band activities, such as theta and beta. Our integrated system will be an effective neurofeedback training and cognitive function assessment system for personal and clinical use.

Guidelines for Feature Matching Assessment of Brain-Computer Interfaces for Augmentative and Alternative Communication.

Purpose: Brain-computer interfaces (BCIs) can provide access to augmentative and alternative communication (AAC) devices using neurological activity alone without voluntary movements. As with traditional AAC access methods, BCI performance may be influenced by the cognitive-sensory-motor and motor imagery profiles of those who use these devices. Therefore, we propose a person-centered, feature matching framework consistent with clinical AAC best practices to ensure selection of the most appropriate BCI technology to meet individuals' communication needs. Method: The proposed feature matching procedure is based on the current state of the art in BCI technology and published reports on cognitive, sensory, motor, and motor imagery factors important for successful operation of BCI devices. Results: Considerations for successful selection of BCI for accessing AAC are summarized based on interpretation from a multidisciplinary team with experience in AAC, BCI, neuromotor disorders, and cognitive assessment. The set of features that support each BCI option are discussed in a hypothetical case format to model possible transition of BCI research from the laboratory into clinical AAC applications. Conclusions: This procedure is an initial step toward consideration of feature matching assessment for the full range of BCI devices. Future investigations are needed to fully examine how person-centered factors influence BCI performance across devices.

Bilateral Transcranial Direct Current Stimulation Reshapes Resting-State Brain Networks: A Magnetoencephalography Assessment.

Transcranial direct current stimulation (tDCS) can noninvasively induce brain plasticity, and it is potentially useful to treat patients affected by neurological conditions. However, little is known about tDCS effects on resting-state brain networks, which are largely involved in brain physiological functions and in diseases. In this randomized, sham-controlled, double-blind study on healthy subjects, we have assessed the effect of bilateral tDCS applied over the sensorimotor cortices on brain and network activity using a whole-head magnetoencephalography system. Bilateral tDCS, with the cathode (-) centered over C4 and the anode (+) centered over C3, reshapes brain networks in a nonfocal fashion. Compared to sham stimulation, tDCS reduces left frontal alpha, beta, and gamma power and increases global connectivity, especially in delta, alpha, beta, and gamma frequencies. The increase of connectivity is consistent across bands and widespread. These results shed new light on the effects of tDCS and may be of help in personalizing treatments in neurological disorders.

Characterizing synchrony patterns across cognitive task stages of associative recognition memory.

Numerous studies seek to understand the role of oscillatory synchronization in cognition. This problem is particularly challenging in the context of complex cognitive behavior, which consists of a sequence of processing steps with uncertain duration. In this study, we analyzed oscillatory connectivity measures in time windows that previous computational models had associated with a specific sequence of processing steps in an associative memory recognition task (visual encoding, familiarity, memory retrieval, decision making, and motor response). The timing of these processing steps was estimated on a single-trial basis with a novel hidden semi-Markov model multivariate pattern analysis (HSMM-MVPA) method. We show that different processing stages are associated with specific patterns of oscillatory connectivity. Visual encoding is characterized by a dense network connecting frontal, posterior, and temporal areas as well as frontal and occipital phase locking in the 4-9 Hz theta band. Familiarity is associated with frontal phase locking in the 9-14 Hz alpha band. Decision making is associated with frontal and temporo-central interhemispheric connections in the alpha band. During decision making, a second network in the theta band that connects left-temporal, central, and occipital areas bears similarity to the neural signature for preparing a motor response. A similar theta band network is also present during the motor response, with additionally alpha band connectivity between right-temporal and posterior areas. This demonstrates that the processing stages discovered with the HSMM-MVPA method are indeed linked to distinct synchronization patterns, leading to a closer understanding of the functional role of oscillations in cognition.

Extraction of features from sleep EEG for Bayesian assessment of brain development.

Brain development can be evaluated by experts analysing age-related patterns in sleep electroencephalograms (EEG). Natural variations in the patterns, noise, and artefacts affect the evaluation accuracy as well as experts' agreement. The knowledge of predictive posterior distribution allows experts to estimate confidence intervals within which decisions are distributed. Bayesian approach to probabilistic inference has provided accurate estimates of intervals of interest. In this paper we propose a new feature extraction technique for Bayesian assessment and estimation of predictive distribution in a case of newborn brain development assessment. The new EEG features are verified within the Bayesian framework on a large EEG data set including 1,100 recordings made from newborns in 10 age groups. The proposed features are highly correlated with brain maturation and their use increases the assessment accuracy.

Predictive modeling of EEG time series for evaluating surgery targets in epilepsy patients.

During the last 20 years, predictive modeling in epilepsy research has largely been concerned with the prediction of seizure events, whereas the inference of effective brain targets for resective surgery has received surprisingly little attention. In this exploratory pilot study, we describe a distributional clustering framework for the modeling of multivariate time series and use it to predict the effects of brain surgery in epilepsy patients. By analyzing the intracranial EEG, we demonstrate how patients who became seizure free after surgery are clearly distinguished from those who did not. More specifically, for 5 out of 7 patients who obtained seizure freedom (= Engel class I) our method predicts the specific collection of brain areas that got actually resected during surgery to yield a markedly lower posterior probability for the seizure related clusters, when compared to the resection of random or empty collections. Conversely, for 4 out of 5 Engel class III/IV patients who still suffer from postsurgical seizures, performance of the actually resected collection is not significantly better than performances displayed by random or empty collections. As the number of possible collections ranges into billions and more, this is a substantial contribution to a problem that today is still solved by visual EEG inspection. Apart from epilepsy research, our clustering methodology is also of general interest for the analysis of multivariate time series and as a generative model for temporally evolving functional networks in the neurosciences and beyond. Hum Brain Mapp 38:2509-2531, 2017. © 2017 Wiley Periodicals, Inc.