Episodic and semantic memory: an analysis in the EEG theta and alpha band

A Review of Childhood Developmental Changes in Attention as Indexed in the Electrical Activity of the Brain

This review aims to present age-related changes in the neuroelectric responses of typically developing children (TDC) who are presumed to meet developmental stages appropriately. The review is based on findings from the frequently used neuropsychological tasks of active attention, where attention is deliberately focused versus passive attention where attention is drawn to a stimulus, facilitatory attention, which enhances the processing of a stimulus versus inhibitory attention, which suppresses the processing of a stimulus. The review discusses the early and late stages of attentional selectivity that correspond to early and late information processing. Age-related changes in early attentional selectivity were quantitatively represented in latencies of the event-related potential (ERP) components. Age-related changes in late attentional selectivity are also qualitatively represented by structural and functional reorganization of attentional processing and the brain areas involved. The purely bottom-up or top-down processing is challenged with age-related findings on difficult tasks that ensure a high cognitive load. TDC findings on brain oscillatory activity are enriched by findings from attention deficit hyperactivity disorder (ADHD). The transition from the low to fast oscillations in TDC and ADHD confirmed the maturational lag hypothesis. The deviant topographical localization of the oscillations confirmed the maturational deviance model. The gamma-based match and utilization model integrates all levels of attentional processing. According to these findings and theoretical formulations, brain oscillations can potentially display the human brain's wholistic-integrative functions.

Two are better than one: Differences in cortical EEG patterns during auditory and visual verbal working memory processing between Unilateral and Bilateral Cochlear Implanted children

Despite the proven effectiveness of cochlear implant (CI) in the hearing restoration of deaf or hard-of-hearing (DHH) children, to date, extreme variability in verbal working memory (VWM) abilities is observed in both unilateral and bilateral CI user children (CIs). Although clinical experience has long observed deficits in this fundamental executive function in CIs, the cause to date is still unknown. Here, we have set out to investigate differences in brain functioning regarding the impact of monaural and binaural listening in CIs compared with normal hearing (NH) peers during a three-level difficulty n-back task undertaken in two sensory modalities (auditory and visual). The objective of this pioneering study was to identify electroencephalographic (EEG) marker pattern differences in visual and auditory VWM performances in CIs compared to NH peers and possible differences between unilateral cochlear implant (UCI) and bilateral cochlear implant (BCI) users. The main results revealed differences in theta and gamma EEG bands. Compared with hearing controls and BCIs, UCIs showed hypoactivation of theta in the frontal area during the most complex condition of the auditory task and a correlation of the same activation with VWM performance. Hypoactivation in theta was also observed, again for UCIs, in the left hemisphere when compared to BCIs and in the gamma band in UCIs compared to both BCIs and NHs. For the latter two, a correlation was found between left hemispheric gamma oscillation and performance in the audio task. These findings, discussed in the light of recent research, suggest that unilateral CI is deficient in supporting auditory VWM in DHH. At the same time, bilateral CI would allow the DHH child to approach the VWM benchmark for NH children. The present study suggests the possible effectiveness of EEG in supporting, through a targeted approach, the diagnosis and rehabilitation of VWM in DHH children.

EEG-based neurophysiological indices for expert psychomotor performance - a review

A primary objective of current human neuropsychological performance research is to define the physiological correlates of adaptive knowledge utilization, in order to support the enhanced execution of both simple and complex tasks. Within the present article, electroencephalography-based neurophysiological indices characterizing expert psychomotor performance, will be explored. As a means of characterizing fundamental processes underlying efficient psychometric performance, the neural efficiency model will be evaluated in terms of alpha-wave-based selective cortical processes. Cognitive and motor domains will initially be explored independently, which will act to encapsulate the task-related neuronal adaptive requirements for enhanced psychomotor performance associating with the neural efficiency model. Moderating variables impacting the practical application of such neuropsychological model, will also be investigated. As a result, the aim of this review is to provide insight into detectable task-related modulation involved in developed neurocognitive strategies which support heightened psychomotor performance, for the implementation within practical settings requiring a high degree of expert performance (such as sports or military operational settings).

Neural correlates tracking different aspects of the emerging representation of novel visual categories

Current studies investigating electroencephalogram correlates associated with categorization of sensory stimuli (P300 event-related potential, alpha event-related desynchronization, theta event-related synchronization) typically use an oddball paradigm with few, familiar, highly distinct stimuli providing limited insight about the aspects of categorization (e.g. difficulty, membership, uncertainty) that the correlates are linked to. Using a more complex task, we investigated whether such more specific links could be established between correlates and learning and how these links change during the emergence of new categories. In our study, participants learned to categorize novel stimuli varying continuously on multiple integral feature dimensions, while electroencephalogram was recorded from the beginning of the learning process. While there was no significant P300 event-related potential modulation, both alpha event-related desynchronization and theta event-related synchronization followed a characteristic trajectory in proportion with the gradual acquisition of the two categories. Moreover, the two correlates were modulated by different aspects of categorization, alpha event-related desynchronization by the difficulty of the task, whereas the magnitude of theta -related synchronization by the identity and possibly the strength of category membership. Thus, neural signals commonly related to categorization are appropriate for tracking both the dynamic emergence of internal representation of categories, and different meaningful aspects of the categorization process.

Combining EEG and 3D-eye-tracking to study the prediction of upcoming speech in naturalistic virtual environments: A proof of principle

EEG and eye-tracking provide complementary information when investigating language comprehension. Evidence that speech processing may be facilitated by speech prediction comes from the observation that a listener's eye gaze moves towards a referent before it is mentioned if the remainder of the spoken sentence is predictable. However, changes to the trajectory of anticipatory fixations could result from a change in prediction or an attention shift. Conversely, N400 amplitudes and concurrent spectral power provide information about the ease of word processing the moment the word is perceived. In a proof-of-principle investigation, we combined EEG and eye-tracking to study linguistic prediction in naturalistic, virtual environments. We observed increased processing, reflected in theta band power, either during verb processing - when the verb was predictive of the noun - or during noun processing - when the verb was not predictive of the noun. Alpha power was higher in response to the predictive verb and unpredictable nouns. We replicated typical effects of noun congruence but not predictability on the N400 in response to the noun. Thus, the rich visual context that accompanied speech in virtual reality influenced language processing compared to previous reports, where the visual context may have facilitated processing of unpredictable nouns. Finally, anticipatory fixations were predictive of spectral power during noun processing and the length of time fixating the target could be predicted by spectral power at verb onset, conditional on the object having been fixated. Overall, we show that combining EEG and eye-tracking provides a promising new method to answer novel research questions about the prediction of upcoming linguistic input, for example, regarding the role of extralinguistic cues in prediction during language comprehension.

Investigating EEG-based cross-session and cross-task vigilance estimation in BCI systems

Objective. The state of vigilance is crucial for effective performance in brain-computer interface (BCI) tasks, and therefore, it is essential to investigate vigilance levels in BCI tasks. Despite this, most studies have focused on vigilance levels in driving tasks rather than on BCI tasks, and the electroencephalogram (EEG) patterns of vigilance states in different BCI tasks remain unclear. This study aimed to identify similarities and differences in EEG patterns and performances of vigilance estimation in different BCI tasks and sessions.Approach.To achieve this, we built a steady-state visual evoked potential-based BCI system and a rapid serial visual presentation-based BCI system and recruited 18 participants to carry out four BCI experimental sessions over four days.Main results. Our findings demonstrate that specific neural patterns for high and low vigilance levels are relatively stable across sessions. Differential entropy features significantly differ between different vigilance levels in all frequency bands and between BCI tasks in the delta and theta frequency bands, with the theta frequency band features playing a critical role in vigilance estimation. Additionally, prefrontal, temporal, and occipital regions are more relevant to the vigilance state in BCI tasks. Our results suggest that cross-session vigilance estimation is more accurate than cross-task estimation.Significance.Our study clarifies the underlying mechanisms of vigilance state in two BCI tasks and provides a foundation for further research in vigilance estimation in BCI applications.

Frontal Alpha Asymmetry in Posttraumatic Stress Disorder: Group Differences Among Individuals With and Without PTSD During an Inhibitory Control Task

The current study examined frontal alpha asymmetry (FAA) as a marker of approach- and avoidance-related prefrontal activity in participants with and without trauma exposure and posttraumatic stress disorder (PTSD). We investigated FAA in an inhibitory control paradigm (threatening vs nonthreatening cues) under 2 levels of cognitive demand (baseline: images constant within a block of trials; vs filtering: images varied randomly within a block) in 3 groups of participants: individuals with PTSD (n = 16), exposed to trauma but without PTSD (n = 14), and a control group without PTSD or trauma exposure (n = 15). Under low demand (baseline), both PTSD and trauma-exposed participants exhibited significantly greater relative left than right frontal brain activity (approach) to threatening than to nonthreatening images. Under high demand (filtering), no FAA differences were found between threatening and nonthreatening images, but PTSD participants revealed more relative left than right FAA, whereas trauma-exposed participants showed reduced left relative right FAA. In all conditions, healthy controls exhibited reduced left relative to right FAA and no differences between threatening and nonthreatening images. Study findings suggest dysfunctional prefrontal mechanisms of emotion regulation in PTSD, but adaptive prefrontal regulation in trauma-exposed individuals without PTSD.

Does the Frontal Brain Electrical Activity Mediate the Effect of Home Executive Function Environment and Screen Time on Children's Executive Function?

Executive functions play an important role in various developmental aspects of children; however, environmental factors influencing individual differences in children's executive function and their neural substructures, particularly in middle childhood, are rarely investigated. Therefore, the current study aimed to investigate the relationship between the home executive function environment (HEFE) and screen time with the executive function of children aged 8-12 years by employing the mediating variables of alpha, beta, and theta waves. The parents of 133 normal children completed Barkley Deficits in Executive Functioning, HEFE, and Screen Time Scales. Alpha, beta, and theta brain waves were also measured. Data were examined using correlational and path analysis. The results suggested a positive and significant relationship between home executive functions and the executive functions of children. Furthermore, the results indicated an inverse and significant relationship between screen time and executive function. The results also proved the mediating role of alpha, beta, and theta brain waves in the relationship between screen time and the children's executive function. Environmental factors (such as home environment and screen time) affect the function of brain waves and, thus, the daily executive function of children.

Using electroencephalography to explore neurocognitive correlates of procedural proficiency: A pilot study to compare experts and novices during simulated endotracheal intubation

The objective of this study was to explore the use of EEG as a measure of neurocognitive engagement during a procedural task. In this observational study, self-reported cognitive load, observed performance, and EEG signatures in experts and novices were compared during simulated endotracheal intubation. Twelve medical students (novices) and eight senior anesthesiology trainees (experts) were included in the study. Experts reported significantly lower cognitive load (P < 0.001) and outperformed novices based on the observational checklist (P < 0.001). EEG signatures differed significantly between the experts and novices. Experts showed a greater increase in delta and theta band amplitudes, especially in temporal and frontal locations and in right occipital areas for delta. A machine learning algorithm showed 83.3 % accuracy for expert-novice skill classification using the selected EEG features. Performance scores were positively correlated (P < 0.05) with event-related amplitudes for delta and theta bands at locations where experts and novices showed significant differences. Increased delta and frontal/midline theta oscillations on EEG suggested that experts had better attentional control than novices. This pilot study provides initial evidence that EEG may be a useful, noninvasive measure of neurocognitive engagement in operational settings and that it has the potential to complement traditional clinical skills assessment.

Temporal profiles of cortical oscillations in novice performers for goal-directed aiming in a shooting task

Goal-directed aiming relies on the ability to control attention and visuomotor movements while preparing for motor execution. Research in precision sports has investigated cortical oscillations for supporting expert performance. However, the results may be influenced by adaptive and strategic behaviors after intensive training. Whether and at what time points distinctive oscillations support goal-directed aiming without such training remains elusive. In this electroencephalographic (EEG) study, we investigated how the theta, alpha and beta oscillations change to support accurate aiming before novices took an action. We first conducted a model-based analysis to examine the correlation of cortical oscillations with accurate shooting on a trial-by-trial basis in a within-individual manner. The results showed that alpha and beta oscillations at different time points during the aiming period were better predictors of aiming accuracy. We then compared the oscillatory power for good versus poor performance. The results showed decreases in the alpha and beta power across distributed cortical areas and an increase in the frontal theta power successively before shot release. Moreover, greater intertrial phase coherence was observed for good performance than for poor performance in posterior alpha activity and anterior beta activity during the aiming period. In conclusion, these results advance our understanding of the temporal dynamics of theta, alpha and beta oscillations in orchestrating goal setting, motor preparation and focused attention to monitoring both external and internal states for accurate aiming. Among the three, alpha and beta oscillations are critical for predicting aiming performance and theta oscillations reflect effortful cognitive control.

Tactile expectancy modulates occipital alpha oscillations in early blindness

Alpha oscillatory activity is thought to contribute to visual expectancy through the engagement of task-relevant occipital regions. In early blindness, occipital alpha oscillations are systematically reduced, suggesting that occipital alpha depends on visual experience. However, it remains possible that alpha activity could serve expectancy in non-visual modalities in blind people, especially considering that previous research has shown the recruitment of the occipital cortex for non-visual processing. To test this idea, we used electroencephalography to examine whether alpha oscillations reflected a differential recruitment of task-relevant regions between expected and unexpected conditions in two haptic tasks (texture and shape discrimination). As expected, sensor-level analyses showed that alpha suppression in parieto-occipital sites was significantly reduced in early blind individuals compared with sighted participants. The source reconstruction analysis revealed that group differences originated in the middle occipital cortex. In that region, expected trials evoked higher alpha desynchronization than unexpected trials in the early blind group only. Our results support the role of alpha rhythms in the recruitment of occipital areas in early blind participants, and for the first time we show that although posterior alpha activity is reduced in blindness, it remains sensitive to expectancy factors. Our findings therefore suggest that occipital alpha activity is involved in tactile expectancy in blind individuals, serving a similar function to visual anticipation in sighted populations but switched to the tactile modality. Altogether, our results indicate that expectancy-dependent modulation of alpha oscillatory activity does not depend on visual experience. SIGNIFICANCE STATEMENT: Are posterior alpha oscillations and their role in expectancy and anticipation dependent on visual experience? Our results show that tactile expectancy can modulate posterior alpha activity in blind (but not sighted) individuals through the engagement of occipital regions, suggesting that in early blindness, alpha oscillations maintain their proposed role in visual anticipation but subserve tactile processing. Our findings bring a new understanding of the role that alpha oscillatory activity plays in blindness, contrasting with the view that alpha activity is task unspecific in blind populations.

Machine Learning Based on Event-Related EEG of Sustained Attention Differentiates Adults with Chronic High-Altitude Exposure from Healthy Controls

(1) Objective: The aim of this study was to examine the effect of high altitude on inhibitory control processes that underlie sustained attention in the neural correlates of EEG data, and explore whether the EEG data reflecting inhibitory control contain valuable information to classify high-altitude chronic hypoxia and plain controls. (2) Methods: 35 chronic high-altitude hypoxic adults and 32 matched controls were recruited. They were required to perform the go/no-go sustained attention task (GSAT) using event-related potentials. Three machine learning algorithms, namely a support vector machine (SVM), logistic regression (LR), and a decision tree (DT), were trained based on the related ERP components and neural oscillations to build a dichotomous classification model. (3) Results: Behaviorally, we found that the high altitude (HA) group had lower omission error rates during all observation periods than the low altitude (LA) group. Meanwhile, the ERP results showed that the HA participants had significantly shorter latency than the LAs for sustained potential (SP), indicating vigilance to response-related conflict. Meanwhile, event-related spectral perturbation (ERSP) analysis suggested that lowlander immigrants exposed to high altitudes may have compensatory activated prefrontal cortexes (PFC), as reflected by slow alpha, beta, and theta frequency-band neural oscillations. Finally, the machine learning results showed that the SVM achieved the optimal classification F1 score in the later stage of sustained attention, with an F1 score of 0.93, accuracy of 92.54%, sensitivity of 91.43%, specificity of 93.75%, and area under ROC curve (AUC) of 0.97. The results proved that SVM classification algorithms could be applied to identify chronic high-altitude hypoxia. (4) Conclusions: Compared with other methods, the SVM leads to a good overall performance that increases with the time spent on task, illustrating that the ERPs and neural oscillations may provide neuroelectrophysiological markers for identifying chronic plateau hypoxia.

Short-term PM2.5 exposure and cognitive function: Association and neurophysiological mechanisms

BACKGROUND

Although converging evidence has demonstrated that exposure to fine particulate matter (PM_2.5) caused adverse effects on brain structure and cognitive function, the association between the short-term exposure to PM_2.5 and cognition dysfunction remained underexplored, especially possible neurophysiological mechanisms.

METHODS

We conducted a longitudinal observational study with four repeated measurement sessions among 90 young adults from September 2020 to June 2021. During each measurement session, we measured participants' personal-level air pollution exposure for one week with portable monitors, followed by executive function assessment and electrophysiological signal recording at an assessment center. Standard Stroop color-word test was used accompanied with electroencephalogram (EEG) recording to assess performance on executive function. We used linear mixed-effect model with lagged values of PM_2.5 levels to analyze the association between PM_2.5 exposure and changes in executive function, and mediation analysis to investigate mediation effect by EEG signal.

RESULTS

Adjusted mixed-effect models demonstrated that elevated PM_2.5 exposure three days prior to cognitive assessment (lag-3) was associated with (1) declined performance in both congruent and incongruent tasks in Stroop test, (2) reduced lower and upper alpha event-related desynchronization (ERD) during 500-1000 ms after stimuli, both indicating impaired executive control. Lower and upper alpha ERD also mediated observed associations between short-term PM_2.5 exposure and executive function. No significant associations were found between short-term PM_2.5 exposure or aperiodic exponents in tonic and phasic states, or periodic alpha oscillations in tonic state.

CONCLUSION

Our results provided evidence that short-term PM_2.5 exposure was associated with executive dysfunction. Reduced alpha ERD was likely to be the underlying pathway through which PM_2.5 induced adverse effects on neuron activities during cognitive tasks.

Effects of Atomoxetine on Motor and Cognitive Behaviors and Brain Electrophysiological Activity of Dopamine Transporter Knockout Rats

Changes in dopaminergic and noradrenergic transmission are considered to be the underlying cause of attention deficit and hyperactivity disorder (ADHD). Atomoxetine (ATX) is a selective norepinephrine transporter (NET) inhibitor that is currently used for ADHD treatment. In this study, we aimed to evaluate the effect of atomoxetine on the behavior and brain activity of dopamine transporter knockout (DAT-KO) rats, which are characterized by an ADHD-like behavioral phenotype. Prepulse inhibition (PPI) was assessed in DAT-KO and wild type rats after saline and ATX injections, as well as behavioral parameters in the Hebb-Williams maze and power spectra and coherence of electrophysiological activity. DAT-KO rats demonstrated a pronounced behavioral and electrophysiological phenotype, characterized by hyperactivity, increased number of errors in the maze, repetitive behaviors and disrupted PPI, changes in cortical and striatal power spectra and interareal coherence. Atomoxetine significantly improved PPI and decreased repetitive behaviors in DAT-KO rats and influenced behavior of wild-type rats. ATX also led to significant changes in power spectra and coherence of DAT-KO and wild type rats. Assessment of noradrenergic modulation effects in DAT-KO provides insight into the intricate interplay of monoaminergic systems, although further research is still required to fully understand the complexity of this interaction.

Cortical functionality during reversal learning on a decision-making task in young men

The evaluation of external and internal stimuli permits the ongoing actualization of choice-related information and, thus, the association between stimuli and outcomes. This process is essential to decision-making as it allows constant adaptation to environmental changes in order to maximize gains and minimize losses. Reversal learning paradigms are used to study this process, which has been associated with prefrontal cortex activity (frontopolar, dorsolateral) in conjunction with posterior areas (parietal, temporal), due to their participation in integrating and processing the stimuli-reward relation. The aim of this study was to assess the cortical functionality associated with reversal learning during the decision-making process. The EEG activity of 22 young men was recorded while performing a decision-making task in a reversal learning condition compared to an initial learning condition. EEG data were analyzed during evaluation of the stimuli, before motor execution (formation of preferences), and during task feedback (outcome evaluation). The formation of preferences stage was characterized by a higher correlation of the alpha2 band between the parietal cortices. In the feedback stage of the reversal learning condition, a higher absolute power of the theta band in the left dorsolateral (F3), and a lower correlation of the alpha1 band between the right frontopolar and dorsolateral (Fp2-F4), as well as between the right frontopolar and temporal (Fp2-T4), were observed. The data obtained show that the EEG activity of the areas recorded changed in the evaluation of the stimuli information in the reversal learning condition during a decision-making task.

Language as the Working Model of Human Mind

The Human Mind, functional aspect of Human Brain, has been envisaged to be working on the tenets of Chaos, a seeming order within a disorder, the premise of Universe. The armamentarium of Human Mind makes use of distributed neuronal networks sub-serving Sensorial Mechanisms, Mirror Neurone System (MNS) and Motor Mechanisms etching a stochastic trajectory on the virtual phase-space of Human Mind, obeying the ethos of Chaos. The informational sensorial mechanisms recruit attentional mechanisms channelising through the window of chaotic neural dynamics onto MNS that providing algorithmic image information flow along virtual phase- space coordinates concluding onto motor mechanisms that generates and mirrors a stimulus- specific and stimulus-adequate response. The singularity of self-iterating fractal architectonics of Event-Related Synchrony (ERS), a Power Spectral Density (PSD) precept of electroencephalographic (EEG) time-series denotes preferential and categorical inhibition gateway and an Event-Related Desynchrony (ERD) represents event related and locked gateway to stimulatory/excitatory neuronal architectonics leading to stimulus-locked and adequate neural response. The contextual inference in relation to stochastic phase-space trajectory of self- iterating fractal of Off-Center α ERS (Central)-On-Surround α ERD-On Surround θ ERS document efficient neural dynamics of working memory., across patterned modulation and flow of the neurally coded information.

Alpha oscillations in left perisylvian cortices support semantic processing and predict performance

Semantic processing is the ability to discern and maintain conceptual relationships among words and objects. While the neural circuits serving semantic representation and controlled retrieval are well established, the neuronal dynamics underlying these processes are poorly understood. Herein, we examined 25 healthy young adults who completed a semantic relation word-matching task during magnetoencephalography (MEG). MEG data were examined in the time-frequency domain and significant oscillatory responses were imaged using a beamformer. Whole-brain statistical analyses were conducted to compare semantic-related to length-related neural oscillatory responses. Time series were extracted to visualize the dynamics and were linked to task performance using structural equation modeling. The results indicated that participants had significantly longer reaction times in semantic compared to length trials. Robust MEG responses in the theta (3-6 Hz), alpha (10-16 Hz), and gamma (64-76 Hz and 64-94 Hz) bands were observed in parieto-occipital and frontal cortices. Whole-brain analyses revealed stronger alpha oscillations in a left-lateralized network during semantically related relative to length trials. Importantly, stronger alpha oscillations in the left superior temporal gyrus during semantic trials predicted faster responses. These data reinforce existing literature and add novel temporal evidence supporting the executive role of the semantic control network in behavior.

Alpha suppression indexes a spotlight of visual-spatial attention that can shine on both perceptual and memory representations

Although researchers have been recording the human electroencephalogram (EEG) for almost a century, we still do not completely understand what cognitive processes are measured by the activity of different frequency bands. The 8- to 12-Hz activity in the alpha band has long been a focus of this research, but our understanding of its links to cognitive mechanisms has been rapidly evolving recently. Here, we review and discuss the existing evidence for two competing perspectives about alpha activity. One view proposes that the suppression of alpha-band power following the onset of a stimulus array measures attentional selection. The competing view is that this same activity measures the buffering of the task-relevant representations in working memory. We conclude that alpha-band activity following the presentation of stimuli appears to be due to the operation of an attentional selection mechanism, with characteristics that mirror the classic views of attention as selecting both perceptual inputs and representations already stored in memory.

Neurofeedback training improves episodic and semantic long-term memory performance

Understanding and improving memory are vital to enhance human life. Theta rhythm is associated with memory consolidation and coding, but the trainability and effects on long-term memory of theta rhythm are unknown. This study investigated the ability to improve long-term memory using a neurofeedback (NFB) technique reflecting the theta/low-beta power ratio on an electroencephalogram (EEG). Our study consisted of three stages. First, the long-term memory of participants was measured. In the second stage, the participants in the NFB group received 3 days of theta/low-beta NFB training. In the third stage, the long-term memory was measured again. The NFB group had better episodic and semantic long-term memory than the control group and significant differences in brain activity between episodic and semantic memory during the recall tests were revealed. These findings suggest that it is possible to improve episodic and semantic long-term memory abilities through theta/low-beta NFB training.

Brain Fingerprinting and Lie Detection: A Study of Dynamic Functional Connectivity Patterns of Deception Using EEG Phase Synchrony Analysis

This study investigated the brain functional connectivity (FC) patterns related to lie detection (LD) tasks with the purpose of analyzing the underlying cognitive processes and mechanisms in deception. Using the guilty knowledge test protocol, 30 subjects were divided randomly into guilty and innocent groups, and their electroencephalogram (EEG) signals were recorded on 32 electrodes. Phase synchrony of EEG was analyzed between different brain regions. A few-trials-based relative phase synchrony (FTRPS) measure was proposed to avoid the false synchronization that occurs due to volume conduction. FTRPS values with a significantly statistical difference between two groups were employed to construct FC patterns of deception, and the FTRPS values from the FC networks were extracted as the features for the training and testing of the support vector machine. Finally, four more intuitive brain fingerprinting graphs (BFG) on delta, theta, alpha and beta bands were respectively proposed. The experimental results reveal that deceptive responses elicited greater oscillatory synchronization than truthful responses between different brain regions, which plays an important role in executing lying tasks. The functional connectivity in the BFG are mainly implicated in the visuo-spatial imagery, bottom-top attention and memory systems, work memory and episodic encoding, and top-down attention and inhibition processing. These may, in part, underlie the mechanism of communication between different brain cortices during lying. High classification accuracy demonstrates the validation of BFG to identify deception behavior, and suggests that the proposed FTRPS could be a sensitive measure for LD in the real application.

Sensitive period for the plasticity of alpha activity in humans

Visual experience is crucial for the development of neural processing. For example, alpha activity development is a vision-dependent mechanism. Indeed, studies report no alpha activity is present in blind adults. Nevertheless, studies have not investigated the developmental trajectory of this activity in infants and children with blindness. Here, we hypothesize that the difference in neural activity of blind compared to sighted subjects is: absent at birth, progressive with age, specifically occipital and linked to a gradual motor impairment. Therefore, we consider spectral power of resting-state EEG and its association with motor impairment indices, in blind subjects and in sighted controls between 0 and 11 years of age. Blind subjects show posterior alpha activity during the first three years of life, although weaker and slower maturing compared to sighted subjects. The first great differentiation between blind and sighted subjects occurs between 3 and 6 years of age. Starting in this period, reduced alpha activity increases the probability of motor impairment in blind subjects, likely because of impaired perception/interaction. These results show that visual experience mediates the neural mechanisms generating alpha oscillations during the first years of life, suggesting that it is a sensitive period for the plasticity of this process.

Examination and Comparison of Theta Band Connectivity in Left- and Right-Hand Dominant Individuals throughout a Motor Skill Acquisition

The majority of the population identifies as right-hand dominant, with a minority 10.6% identifying as left-hand dominant. Social factors may partially skew the distribution, but it remains that left-hand dominant individuals make up approximately 40 million people in the United States alone and yet, remain underrepresented in the motor control literature. Recent research has revealed behavioral and neurological differences between populations, therein overturning assumptions of a simple hemispheric flip in motor-related activations. The present work showed differentially adaptable motor programs between populations and found fundamental differences in methods of skill acquisition highlighting underlying neural strategies unique to each population. Difference maps and descriptive metrics of coherent activation patterns showed differences in how theta oscillations were utilized. The right-hand group relied on occipital parietal lobe connectivity for visual information integration necessary to inform the motor task, while the left-hand group relied on a more frontal lobe localized cognitive based approach. The findings provide insight into potential alternative methods of information integration and emphasize the importance for inclusion of the left-hand dominant population in the growing conceptualization of the brain promoting the generation of a more complete, stable, and accurate understanding of our complex biology.

The effect of zolpidem on memory consolidation over a night of sleep

STUDY OBJECTIVES

Nonrapid eye movement sleep boosts hippocampus-dependent, long-term memory formation more so than wake. Studies have pointed to several electrophysiological events that likely play a role in this process, including thalamocortical sleep spindles (12-15 Hz). However, interventional studies that directly probe the causal role of spindles in consolidation are scarce. Previous studies have used zolpidem, a GABA-A agonist, to increase sleep spindles during a daytime nap and promote hippocampal-dependent episodic memory. The current study investigated the effect of zolpidem on nighttime sleep and overnight improvement of episodic memories.

METHODS

We used a double-blind, placebo-controlled within-subject design to test the a priori hypothesis that zolpidem would lead to increased memory performance on a word-paired associates task by boosting spindle activity. We also explored the impact of zolpidem across a range of other spectral sleep features, including slow oscillations (0-1 Hz), delta (1-4 Hz), theta (4-8 Hz), sigma (12-15 Hz), as well as spindle-SO coupling.

RESULTS

We showed greater memory improvement after a night of sleep with zolpidem, compared to placebo, replicating a prior nap study. Additionally, zolpidem increased sigma power, decreased theta and delta power, and altered the phase angle of spindle-SO coupling, compared to placebo. Spindle density, theta power, and spindle-SO coupling were associated with next-day memory performance.

CONCLUSIONS

These results are consistent with the hypothesis that sleep, specifically the timing and amount of sleep spindles, plays a causal role in the long-term formation of episodic memories. Furthermore, our results emphasize the role of nonrapid eye movement theta activity in human memory consolidation.

Risk Variants in Three Alzheimer's Disease Genes Show Association with EEG Endophenotypes

Background:

Dementia due to Alzheimer’s disease (AD) is a complex neurodegenerative disorder, which much of heritability remains unexplained. At the clinical level, one of the most common physiological alterations is the slowing of oscillatory brain activity, measurable by electroencephalography (EEG). Relative power (RP) at the conventional frequency bands (i.e., delta, theta, alpha, beta-1, and beta-2) can be considered as AD endophenotypes.

Objective:

The aim of this work is to analyze the association between sixteen genes previously related with AD: APOE, PICALM, CLU, BCHE, CETP, CR1, SLC6A3, GRIN2 β, SORL1, TOMM40, GSK3 β, UNC5C, OPRD1, NAV2, HOMER2, and IL1RAP, and the slowing of the brain activity, assessed by means of RP at the aforementioned frequency bands.

Methods:

An Iberian cohort of 45 elderly controls, 45 individuals with mild cognitive impairment, and 109 AD patients in the three stages of the disease was considered. Genomic information and brain activity of each subject were analyzed.

Results:

The slowing of brain activity was observed in carriers of risk alleles in IL1RAP (rs10212109, rs9823517, rs4687150), UNC5C (rs17024131), and NAV2 (rs1425227, rs862785) genes, regardless of the disease status and situation towards the strongest risk factors: age, sex, and APOE ɛ4 presence.

Conclusion:

Endophenotypes reduce the complexity of the general phenotype and genetic variants with a major effect on those specific traits may be then identified. The found associations in this work are novel and may contribute to the comprehension of AD pathogenesis, each with a different biological role, and influencing multiple factors involved in brain physiology.

The Locus Coeruleus- Norepinephrine System in Stress and Arousal: Unraveling Historical, Current, and Future Perspectives

Arousal may be understood on a spectrum, with excessive sleepiness, cognitive dysfunction, and inattention on one side, a wakeful state in the middle, and hypervigilance, panic, and psychosis on the other side. However, historically, the concepts of arousal and stress have been challenging to define as measurable experimental variables. Divergent efforts to study these subjects have given rise to several disciplines, including neurobiology, neuroendocrinology, and cognitive neuroscience. We discuss technological advancements that chronologically led to our current understanding of the arousal system, focusing on the multifaceted nucleus locus coeruleus. We share our contemporary perspective and the hypotheses of others in the context of our current technological capabilities and future developments that will be required to move forward in this area of research.

Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks

In the main control room (MCR) of a nuclear power plant (NPP), the quality of an operator's performance can depend on their level of attention to the task. Insufficient operator attention accounted for more than 26% of the total causes of human errors and is the highest category for errors. It is therefore necessary to check whether operators are sufficiently attentive either as supervisors or peers during reactor operation. Recently, digital control technologies have been introduced to the operating environment of an NPP MCR. These upgrades are expected to enhance plant and operator performance. At the same time, because personal computers are used in the advanced MCR, the operators perform more cognitive works than physical work. However, operators may not consciously check fellow operators' attention in this environment indicating potentially higher importance of the role of operator attention. Therefore, remote measurement of an operator's attention in real time would be a useful tool, providing feedback to supervisors. The objective of this study is to investigate the development of quantitative indicators that can identify an operator's attention, to diagnose or detect a lack of operator attention thus preventing potential human errors in advanced MCRs. To establish a robust baseline of operator attention, this study used two of the widely used biosignals: electroencephalography (EEG) and eye movement. We designed an experiment to collect EEG and eye movements of the subjects who were monitoring and diagnosing nuclear operator safety-relevant tasks. There was a statistically significant difference between biosignals with and without appropriate attention. Furthermore, an average classification accuracy of about 90% was obtained by the k-nearest neighbors and support vector machine classifiers with a few EEG and eye movements features. Potential applications of EEG and eye movement measures in monitoring and diagnosis tasks in an NPP MCR are also discussed.

Neural Oscillations: Understanding a Neural Code of Pain

Neural oscillations play an important role in the integration and segregation of brain regions that are important for brain functions, including pain. Disturbances in oscillatory activity are associated with several disease states, including chronic pain. Studies of neural oscillations related to pain have identified several functional bands, especially alpha, beta, and gamma bands, implicated in nociceptive processing. In this review, we introduce several properties of neural oscillations that are important to understand the role of brain oscillations in nociceptive processing. We also discuss the role of neural oscillations in the maintenance of efficient communication in the brain. Finally, we discuss the role of neural oscillations in healthy and chronic pain nociceptive processing. These data and concepts illustrate the key role of regional and interregional neural oscillations in nociceptive processing underlying acute and chronic pains.

Virtual reality experiences promote autobiographical retrieval mechanisms: Electrophysiological correlates of laboratory and virtual experiences

Recent advancements in memory research indicate that virtual reality (VR) experiences are more vividly memorized as compared to conventional laboratory events. In contrast to the latter, VR experiences are highly immersive, simulating the multimodality, vividness and inclusiveness of real-life experiences. Therefore, VR might enable researchers to identify memory processes underlying events which participants have actually experienced, in contrast to conventional on-screen experiences. To differentiate the electrophysiological correlates of memory processes underlying VR experiences as compared to conventional laboratory experiences, participants watched videos either in a PC condition or in a VR condition, followed by an unannounced recognition memory test. As hypothesized, we replicated the well-established theta old/new effect for the PC condition, but remarkably, this effect was absent in the VR condition. Additionally, the latter was accompanied by significantly lower alpha activity as compared to the PC condition. As increases in theta-band responses are related to top-down control on, and memory load during retrieval, the observed theta responses might rather relate to retrieval effort than to retrieval success per se. Congruently, higher alpha activity measured over occipital sensor areas in the PC condition reflect visually guided search processes within episodic memory. The VR condition comes in with lower alpha activity, reflecting immediate and effortless memory access. Hence, our findings indicate that the retrieval of VR experiences promotes autobiographical  retrieval mechanisms, whereas recalling conventional laboratory events comes in with higher effort, which might not reflect the mechanisms of everyday memory.

A Critical Analysis on Characterizing the Meditation Experience Through the Electroencephalogram

Meditation practices, originated from ancient traditions, have increasingly received attention due to their potential benefits to mental and physical health. The scientific community invests efforts into scrutinizing and quantifying the effects of these practices, especially on the brain. There are methodological challenges in describing the neural correlates of the subjective experience of meditation. We noticed, however, that technical considerations on signal processing also don't follow standardized approaches, which may hinder generalizations. Therefore, in this article, we discuss the usage of the electroencephalogram (EEG) as a tool to study meditation experiences in healthy individuals. We describe the main EEG signal processing techniques and how they have been translated to the meditation field until April 2020. Moreover, we examine in detail the limitations/assumptions of these techniques and highlight some good practices, further discussing how technical specifications may impact the interpretation of the outcomes. By shedding light on technical features, this article contributes to more rigorous approaches to evaluate the construct of meditation.

The Importance of Cursive Handwriting Over Typewriting for Learning in the Classroom: A High-Density EEG Study of 12-Year-Old Children and Young Adults

To write by hand, to type, or to draw – which of these strategies is the most efficient for optimal learning in the classroom? As digital devices are increasingly replacing traditional writing by hand, it is crucial to examine the long-term implications of this practice. High-density electroencephalogram (HD EEG) was used in 12 young adults and 12, 12-year-old children to study brain electrical activity as they were writing in cursive by hand, typewriting, or drawing visually presented words that were varying in difficulty. Analyses of temporal spectral evolution (TSE, i.e., time-dependent amplitude changes) were performed on EEG data recorded with a 256-channel sensor array. For young adults, we found that when writing by hand using a digital pen on a touchscreen, brain areas in the parietal and central regions showed event-related synchronized activity in the theta range. Existing literature suggests that such oscillatory neuronal activity in these particular brain areas is important for memory and for the encoding of new information and, therefore, provides the brain with optimal conditions for learning. When drawing, we found similar activation patterns in the parietal areas, in addition to event-related desynchronization in the alpha/beta range, suggesting both similarities but also slight differences in activation patterns when drawing and writing by hand. When typewriting on a keyboard, we found event-related desynchronized activity in the theta range and, to a lesser extent, in the alpha range in parietal and central brain regions. However, as this activity was desynchronized and differed from when writing by hand and drawing, its relation to learning remains unclear. For 12-year-old children, the same activation patterns were found, but to a lesser extent. We suggest that children, from an early age, must be exposed to handwriting and drawing activities in school to establish the neuronal oscillation patterns that are beneficial for learning. We conclude that because of the benefits of sensory-motor integration due to the larger involvement of the senses as well as fine and precisely controlled hand movements when writing by hand and when drawing, it is vital to maintain both activities in a learning environment to facilitate and optimize learning.

Brain NMDA Receptors in Schizophrenia and Depression

N-methyl-D-aspartate (NMDA) receptor antagonists such as phencyclidine (PCP), dizocilpine (MK-801) and ketamine have long been considered a model of schizophrenia, both in animals and humans. However, ketamine has been recently approved for treatment-resistant depression, although with severe restrictions. Interestingly, the dosage in both conditions is similar, and positive symptoms of schizophrenia appear before antidepressant effects emerge. Here, we describe the temporal mechanisms implicated in schizophrenia-like and antidepressant-like effects of NMDA blockade in rats, and postulate that such effects may indicate that NMDA receptor antagonists induce similar mechanistic effects, and only the basal pre-drug state of the organism delimitates the overall outcome. Hence, blockade of NMDA receptors in depressive-like status can lead to amelioration or remission of symptoms, whereas healthy individuals develop psychotic symptoms and schizophrenia patients show an exacerbation of these symptoms after the administration of NMDA receptor antagonists.

Type-1 diabetes shapes working memory processing strategies

BACKGROUND

Type 1 diabetes (T1D) is a metabolic disorder characterized by recurrent hypo- and hyperglycemic episodes, whose clinical development has been associated with cognitive and working memory (WM) deficits.

OBJECTIVE

To contrast quantitative electroencephalography (qEEG) measures between young patients with T1D and healthy controls while performing a visuospatial WM task with two memory load levels and facial emotional stimuli.

METHODS

Four or five neutral or happy faces were sequentially and pseudo-randomly presented in different spatial locations, followed by subsequent sequences displaying the reversed spatial order or any other. Participants were instructed to discriminate between these two alternatives during EEG recording.

RESULTS

A significant increase in the absolute power of the delta and theta bands, distributed mainly over the frontal region was found during task execution, with a slight decrease of alpha band power in both groups but mainly in control individuals. However, these changes were more pronounced in the T1D patients, and reached their maximum level during the WM encoding phase, even on trials with the lower memory load. In contrast, changes seemed to occur more gradually in controls and results differed significantly only on the trials with the higher WM load.

CONCLUSIONS

These results reflect adaptive WM-processing mechanisms in which cognitive strategies have evolved in T1D patients in order to meet task demands.

Potential Clinical Applications and Future Prospect of Wireless and Mobile Electroencephalography on the Assessment of Cognitive Impairment

Electroencephalography (EEG) systems have been used for assessing cognitive function in dementia for several decades. Studies have demonstrated that EEG in Alzheimer's disease (AD) patients is generally characterized by significant and specific increases in delta and theta power, a decrease in alpha power, and a decrease in the coherence of the fast bands between different brain areas linked by long corticocortical fibers. Posterior EEG characteristics in dementia with Lewy bodies (DLB) allowed discrimination of DLB from AD and controls with high accuracy. Traditional EEG systems require a long application time and discomfort, which limited its use in dementia patients. Alternative tools for assessing cognition may be simple, low-cost, and mobile medical devices such as wireless and mobile EEG (wmEEG) sensor platforms with flexible electronics and stretchable electrode sheets that could be compatible with long-term EEG monitoring even in dementia patients. In this study, we review the utility of EEG in reflecting cognitive function and the prospects for clinical application of wmEEG monitoring for detecting early dementia and discriminating subtypes of dementia effectively and objectively assessing longitudinal cognitive changes. Repeated and longitudinal documentation of EEG using wmEEG will contribute to detection of specific sleep/wake EEG patterns for patients with sleep and wake-related problems related to dementia.

Reduced Theta Power During Memory Retrieval in Depressed Adults

BACKGROUND

Major depressive disorder (MDD) is associated with poor recollection, but the neural mechanisms responsible for this deficit are unclear. Recollection is supported by interactions between the hippocampus and cortex that appear to be mediated by oscillatory activity in the theta band (4-7 Hz) and that are elicited during source memory retrieval. Therefore, we tested the hypothesis that evoked theta power during source memory retrieval would be reduced in MDD, as this would provide a physiological basis for deficient recollection in adults with depression.

METHODS

Morlet wavelets were applied to event-related potentials collected from 24 unmedicated adults with MDD and 24 healthy control adults during the retrieval of source and semantic memories. Whole-scalp analyses focused on group differences in evoked theta power.

RESULTS

There were no group differences in behavior. Nevertheless, from 400 to 799 ms, theta power was broadly reduced in adults with depression versus healthy adults. This reduction was observed during source and semantic retrieval. Parietal midline electrodes showed significantly reduced theta power during source-but not semantic-retrieval in adults with depression versus healthy adults in this interval. Furthermore, theta power over parietal midline sites from 400 to 799 ms was more strongly related to source memory accuracy in healthy adults versus adults with depression.

CONCLUSIONS

Relative to healthy control adults, adults with depression showed reduced theta power during memory retrieval and a weaker relationship between parietal midline theta power and source memory accuracy. These findings indicate that abnormal theta signals may contribute to memory deficits in adults with MDD.

Theta/delta coupling across cortical laminae contributes to semantic cognition

Rhythmic activity in populations of neurons is associated with cognitive and motor function. Our understanding of the neuronal mechanisms underlying these core brain functions has benefitted from demonstrations of cellular, synaptic, and network phenomena, leading to the generation of discrete rhythms at the local network level. However, discrete frequencies of rhythmic activity rarely occur alone. Despite this, little is known about why multiple rhythms are generated together or what mechanisms underlie their interaction to promote brain function. One overarching theory is that different temporal scales of rhythmic activity correspond to communication between brain regions separated by different spatial scales. To test this, we quantified the cross-frequency interactions between two dominant rhythms-theta and delta activity-manifested during magnetoencephalography recordings of subjects performing a word-pair semantic decision task. Semantic processing has been suggested to involve the formation of functional links between anatomically disparate neuronal populations over a range of spatial scales, and a distributed network was manifest in the profile of theta-delta coupling seen. Furthermore, differences in the pattern of theta-delta coupling significantly correlated with semantic outcome. Using an established experimental model of concurrent delta and theta rhythms in neocortex, we show that these outcome-dependent dynamics could be reproduced in a manner determined by the strength of cholinergic neuromodulation. Theta-delta coupling correlated with discrete neuronal activity motifs segregated by the cortical layer, neuronal intrinsic properties, and long-range axonal targets. Thus, the model suggested that local, interlaminar neocortical theta-delta coupling may serve to coordinate both cortico-cortical and cortico-subcortical computations during distributed network activity. NEW & NOTEWORTHY Here, we show, for the first time, that a network of spatially distributed brain regions can be revealed by cross-frequency coupling between delta and theta frequencies in subjects using magnetoencephalography recording during a semantic decision task. A biological model of this cross-frequency coupling suggested an interlaminar, cell-specific division of labor within the neocortex may serve to route the flow of cortico-cortical and cortico-subcortical information to promote such spatially distributed, functional networks.

SMR Neurofeedback Training Facilitates Working Memory Performance in Healthy Older Adults: A Behavioral and EEG Study

Cognitive aging has become a major concern because life expectancy has increased and elderly populations are socially and economically active. Neurofeedback is a technique of neuromodulation through operant conditioning paradigm that uses a computer interface to provide real-time information about brain activity to increase individual self-perception and assist in modulation. The sensorimotor rhythm (SMR) training protocol is known to enhance attention and has been applied to improve cognitive performance, primarily for attention and memory gains. The aim of this study is to test if the SMR protocol can improve working memory performance in an aging population and consequently favor cognitive reserve. Seventeen older adults (12 females) took part in a randomized placebo-controlled study. They completed a visual working memory test, Delayed Matching to Sample Task (DMTS), before and after the SMR neurofeedback protocol in order to compare their visual working memory performance. Moreover, a 19-channels EEG was collected while they perform the DMTS pre- and post-training. The experimental group showed an improvement in their working memory performance after the training with similar activation power, mainly in theta and beta frequency band at frontal and alpha at temporal regions. The sham group showed some variations in the score of working memory after the training, but were not statistically significant and their power spectrum demonstrate enhancement in alpha and beta band frontal and temporal. The group that did not receive neurofeedback training did not show a change in their working memory performance, neither in their EEG spectrum. The results suggest that neurofeedback can benefit brain reserve in an aging population because individuals enhanced their working memory performance after training and have their EEG activation changed according to expected in working memory tasks.

Early diagnosis of mild cognitive impairment and Alzheimer's with event-related potentials and event-related desynchronization in N-back working memory tasks

BACKGROUND AND OBJECTIVE

In this study we investigate whether or not event-related potentials (ERP) and/or event-related (de)synchronization (ERD/ERS) can be used to differentiate between 27 healthy elderly (HE), 21 subjects diagnosed with mild cognitive impairment (MCI) and 15 mild Alzheimer's disease (AD) patients.

METHODS

Using 32-channel EEG recordings, we measured ERP responses to a three-level (N-back, N = 0,1,2) visual working memory task. We also performed ERD analysis over the same EEG data, dividing the full-band signal into the well-known delta, theta, alpha, beta and gamma bands. Both ERP and ERD analyses were followed by cluster analysis with correction for multicomparisons whenever significant differences were found between groups.

RESULTS

Regarding ERP (full-band analysis), our findings have shown both patient groups (MCI and AD) with reduced P450 amplitude (compared to HE controls) in the execution of the non-match 1-back task at many scalp electrodes, chiefly at parietal and centro-parietal areas. However, no significant differences were found between MCI and AD in ERP analysis whatever was the task. As for sub-band analyses, ERD/ERS measures revealed that HE subjects elicited consistently greater alpha ERD responses than MCI and AD patients during the 1-back task in the match condition, with all differences located at frontal, central and occipital regions. Moreover, in the non-match condition, it was possible to distinguish between MCI and AD patients when they were performing the 0-back task, with MCI presenting more desynchronization than AD on the theta band at temporal and fronto-temporal areas. In summary, ERD analyses have revealed themselves more valuable than ERP, since they showed significant differences in all three group comparisons: HE vs. MCI, HE vs. AD, and MCI vs. AD.

CONCLUSIONS

Based on these findings, we conclude that ERD responses to working memory (N-back) tasks could be useful not only for early MCI diagnosis or for improved AD diagnosis, but probably also for assessing the likelihood of MCI progression to AD, after further validated by a longitudinal study.

The frequency architecture of brain and brain body oscillations: an analysis

Research on brain oscillations has brought up a picture of coupled oscillators. Some of the most important questions that will be analyzed are, how many frequencies are there, what are the coupling principles, what their functional meaning is, and whether body oscillations follow similar coupling principles. It is argued that physiologically, two basic coupling principles govern brain as well as body oscillations: (i) amplitude (envelope) modulation between any frequencies m and n, where the phase of the slower frequency m modulates the envelope of the faster frequency n, and (ii) phase coupling between m and n, where the frequency of n is a harmonic multiple of m. An analysis of the center frequency of traditional frequency bands and their coupling principles suggest a binary hierarchy of frequencies. This principle leads to the foundation of the binary hierarchy brain body oscillation theory. Its central hypotheses are that the frequencies of body oscillations can be predicted from brain oscillations and that brain and body oscillations are aligned to each other. The empirical evaluation of the predicted frequencies for body oscillations is discussed on the basis of findings for heart rate, heart rate variability, breathing frequencies, fluctuations in the BOLD signal, and other body oscillations. The conclusion is that brain and many body oscillations can be described by a single system, where the cross talk - reflecting communication - within and between brain and body oscillations is governed by m : n phase to envelope and phase to phase coupling.

Recognition memory advantage for negative emotional words has an early expiry date: Evidence from brain oscillations and ERPs

Evidence from prior studies has shown an advantage in recognition memory for emotional compared to neutral words. Whether this advantage is short-lived or rather extends over longer periods, as well as whether the effect depends on words' valence (i.e., positive or negative), remains unknown. In the present ERP/EEG study, we investigated this issue by manipulating the lag distance (LAG-2, LAG-8 and LAG-16) between the presentation of old and new words in an online recognition memory task. LAG differences were observed at behavior, ERPs and in the theta frequency band. In line with previous studies, negative words were associated with faster reaction times, higher hit rates and increased amplitude in a positive ERP component between 386 and 564 ms compared to positive and neutral words. Remarkably, the interaction of LAG by EMOTION revealed that negative words were associated with better performance and larger ERPs amplitudes only at LAG-2. Also in the LAG-2 condition, emotional words (i.e., positive and negative words) induced a stronger desynchronization in the beta band between 386 and 542 ms compared to neutral words. These early enhanced memory effects for emotional words are discussed in terms of the Negative Emotional Valence Enhances Recapitulation (NEVER) model and the mobilization-minimization hypothesis.

Characterization of electroencephalography signals for estimating saliency features in videos

Understanding the functions of the visual system has been one of the major targets in neuroscience for many years. However, the relation between spontaneous brain activities and visual saliency in natural stimuli has yet to be elucidated. In this study, we developed an optimized machine learning-based decoding model to explore the possible relationships between the electroencephalography (EEG) characteristics and visual saliency. The optimal features were extracted from the EEG signals and saliency map which was computed according to an unsupervised saliency model (Tavakoli and Laaksonen, 2017). Subsequently, various unsupervised feature selection/extraction techniques were examined using different supervised regression models. The robustness of the presented model was fully verified by means of ten-fold or nested cross validation procedure, and promising results were achieved in the reconstruction of saliency features based on the selected EEG characteristics. Through the successful demonstration of using EEG characteristics to predict the real-time saliency distribution in natural videos, we suggest the feasibility of quantifying visual content through measuring brain activities (EEG signals) in real environments, which would facilitate the understanding of cortical involvement in the processing of natural visual stimuli and application developments motivated by human visual processing.

An embedded implementation based on adaptive filter bank for brain-computer interface systems

BACKGROUND

Brain-computer interface (BCI) is a new communication pathway for users with neurological deficiencies. The implementation of a BCI system requires complex electroencephalography (EEG) signal processing including filtering, feature extraction and classification algorithms. Most of current BCI systems are implemented on personal computers. Therefore, there is a great interest in implementing BCI on embedded platforms to meet system specifications in terms of time response, cost effectiveness, power consumption, and accuracy.

NEW-METHOD

This article presents an embedded-BCI (EBCI) system based on a Stratix-IV field programmable gate array. The proposed system relays on the weighted overlap-add (WOLA) algorithm to perform dynamic filtering of EEG-signals by analyzing the event-related desynchronization/synchronization (ERD/ERS). The EEG-signals are classified, using the linear discriminant analysis algorithm, based on their spatial features.

RESULTS

The proposed system performs fast classification within a time delay of 0.430 s/trial, achieving an average accuracy of 76.80% according to an offline approach and 80.25% using our own recording. The estimated power consumption of the prototype is approximately 0.7 W.

COMPARISON-WITH-EXISTING-METHOD

Results show that the proposed EBCI system reduces the overall classification error rate for the three datasets of the BCI-competition by 5% compared to other similar implementations. Moreover, experiment shows that the proposed system maintains a high accuracy rate with a short processing time, a low power consumption, and a low cost.

CONCLUSIONS

Performing dynamic filtering of EEG-signals using WOLA increases the recognition rate of ERD/ERS patterns of motor imagery brain activity. This approach allows to develop a complete prototype of a EBCI system that achieves excellent accuracy rates.

Changes in brain connectivity following exposure to bilateral eye movements

The present research assessed how engaging in bilateral eye movements influences brain activity. Participants had their resting-state brain activity recorded with electroencephalography (EEG) before and after they performed 30 s of bilateral eye movements or a center-control manipulation. We assessed differences in change scores for absolute power and coherence between the eye-movement and center-control conditions. A main effect for handedness was present for EEG power in the theta and beta frequency bands, with inconsistent-handed participants displaying a greater increase than consistent-handed participants in both frequency bands. For theta, the increase in power for inconsistent handers was specific to participants in the bilateral eye-movement condition, whose increase in theta power exceeded the increase in theta power for consistent-handed participants regardless of condition. In contrast, for coherence, a main effect for condition was present for the delta frequency band, with participants in the control condition exhibiting a significant drop in posterior delta coherence pre to post. We suggest that the maintenance of posterior delta coherence over time may be an important factor in sustaining attention. Further, the malleability of EEG power for inconsistent-handed participants reveals the importance of individual-differences variables in the potential for behavioral manipulations to change brain activity.

Exploration of neural correlates of movement intention based on characterisation of temporal dependencies in electroencephalography

Brain computer interfaces (BCIs) provide a direct communication channel by using brain signals, enabling patients with motor impairments to interact with external devices. Motion intention detection is useful for intuitive movement-based BCI as movement is the fundamental mode of interaction with the environment. The aim of this paper is to investigate the temporal dynamics of brain processes using electroencephalography (EEG) to explore novel neural correlates of motion intention. We investigate the changes in temporal dependencies of the EEG by characterising the decay of autocorrelation during asynchronous voluntary finger tapping movement. The evolution of the autocorrelation function is characterised by its relaxation time, which is used as a robust marker for motion intention. We observed that there was reorganisation of temporal dependencies in EEG during motion intention. The autocorrelation decayed slower during movement intention and faster during the resting state. There was an increase in temporal dependence during movement intention. The relaxation time of the autocorrelation function showed significant (p < 0.05) discrimination between movement and resting state with the mean sensitivity of 78.37 ± 8.83%. The relaxation time provides movement related information that is complementary to the well-known event-related desynchronisation (ERD) by characterising the broad band EEG dynamics which is frequency independent in contrast to ERD. It can also detect motion intention on average 0.51s before the actual movement onset. We have thoroughly compared autocorrelation relaxation time features with ERD in four frequency bands. The relaxation time may therefore, complement the well-known features used in motion-based BCI leading to more robust and intuitive BCI solutions. The results obtained suggest that changes in autocorrelation decay may involve reorganisation of temporal dependencies of brain activity over longer duration during motion intention. This opens the possibilities of investigating further the temporal dynamics of fundamental neural processes underpinning motion intention.