Frontal midline EEG dynamics during working memory

Sound degradation type differentially affects neural indicators of cognitive workload and speech tracking

Hearing-in-noise (HIN) is a challenging task that is essential to human functioning in social, vocational, and educational contexts. Successful speech perception in noisy settings is thought to rely in part on the brain's ability to enhance neural representations of attended speech. In everyday HIN situations, important features of speech (i.e., pitch, rhythm) may be degraded in addition to being embedded in noise. The impact of these differences in sound quality on experiences of workload and neural representations of speech will be important for informing our knowledge on the cognitive demands imposed by every-day difficult listening situations. We investigated HIN perception in 20 healthy adults using continuous speech that was either clean, spectrally degraded, or temporally degraded. Each sound condition was presented both with and without pink noise. Participants engaged in a selective listening task, in which a short-story was presented with varying sound quality, while EEG data were recorded. Neural correlates of cognitive workload were obtained using power levels of two frequency bands sensitive to task difficulty manipulations: alpha (8 - 12 Hz) and theta (4 - 8 Hz). Acoustic and linguistic features (speech envelope, word onsets, word surprisal) were decoded to reveal the degree to which speech was successfully encoded. Overall, alpha-theta power increased significantly when noise was added across sound conditions, while prediction accuracy of speech tracking decreased, suggesting that more effort was required to listen, and that the speech was not as successfully encoded. The temporal degradation also resulted in greater EEG power, possibly as a function of a compensatory mechanism to restore the important temporal information required for speech comprehension. Our findings suggest that measures related to cognitive workload and successful speech encoding are differentially affected by noise and sound degradations, which may help to inform future interventions that aim to mitigate these every-day challenges.

Neural correlates of emotional working memory predict depression and anxiety

Introduction

Emotional working memory (WM) plays a critical role in cognitive functions such as emotion regulation, decision-making, and learning. Understanding how emotional stimuli, particularly negative ones, affect WM performance is crucial for identifying cognitive markers of mental health issues like anxiety and depression. Our objective is to determine whether trait anxiety and depression levels are associated with specific performance outcomes in emotional WM and whether behavioral and neural indicators demonstrate statistically significant correlations with individual anxiety and depression levels in university students.

Methods

In our research: Experiment 1 (n = 25) tested WM performance with both positive and negative emotional stimuli under different cognitive loads (2 vs. 4 items), while Experiment 2 (n = 34) combined EEG recording to investigate the neural index of anxiety and depression during negative emotional WM.

Results

Results showed that negative emotional stimuli impaired WM performance, especially under higher cognitive loads, with anxiety level being linked to increased theta activity during encoding and depression level associated with decreased alpha activity during retrieval. Additionally, individuals with higher anxiety exhibited reduced sensitivity to cognitive load differences in WM tasks involving negative emotions.

Discussion

These results demonstrated that specific EEG patterns during negative emotional WM were significantly associated with individual anxiety and depression levels, suggesting the potential utility of EEG measures for identifying at-risk individuals of anxiety and depression in university student populations. By linking cognitive and neural indicators, the study contributes to the development of personalized interventions for mental health monitoring and treatment.

Test anxiety shapes theta band activity linked to elevated working memory load during the encoding phase

Test anxiety is a prevalent issue among students, recognized for its disruptive impact on working memory through the depletion of attentional control resources; however, its precise effect on the underlying processes of working memory remains insufficiently understood. This study investigated the impact of test anxiety on neural oscillatory patterns during a Sternberg working memory task with three levels of cognitive load (2, 4 and 8 letters), using EEG. Participants with high test anxiety (HTA) and low test anxiety (LTA) were compared. Results showed that under the 4-letter condition, HTA individuals exhibited reduced involvement of top-down attentional control compared to LTA individuals, characterized by decreased theta activity during the encoding phase. For LTA individuals, theta activity increased with cognitive load from 2 to 4 letters during the encoding phase but plateaued beyond 4 letters, while HTA individuals showed no significant theta modulation across loads. These findings highlighted the nuanced effect of test anxiety on working memory neural dynamics under varying cognitive loads. This study showed that test anxiety reduced theta band activity during the working memory encoding phase under medium load due to insufficient attentional control; and the cognitive load effect on theta band activity during the encoding phase was influenced by test anxiety level.

Novelty modulates proactive and reactive cognitive control modes: Evidence from ERP and EEG data

Novelty refers to the quality of an idea or product that is new or unusual. It has been shown to influence a broad range of cognitive processes, such as increasing arousal and facilitating working memory. However, no studies have directly investigated the effects of novelty on cognitive control, particularly on the trade-off between proactive and reactive cognitive control. The present study employed an adapted AX Continuous Performance Task (AX-CPT) combined with electroencephalography (EEG) to investigate the impact of novelty on proactive and reactive control modes. The behavioral results showed that reaction times in BX trials were longer under novel conditions than common conditions, indicating that participants may rely more on reactive control and/or rely less on proactive control when influenced by novelty. The EEG results showed smaller effects of cue-P3 and cue-locked theta-ERS under novelty, suggesting that novelty might decrease proactive control, including the decreased maintenance and utilization of contextual information. Moreover, in the novel conditions, the effect of probe-locked theta-ERS was greater, while the effect of probe-P3 was smaller. This indicates that novelty may enhance reactive control, including increased conflict monitoring and reduced response inhibition cost. The findings suggest that exposure to novelty can influence how individuals balance proactive and reactive control, potentially causing a bias towards reactive control.

Linking the multiple-demand cognitive control system to human electrophysiological activity

The frontoparietal multiple-demand (MD) network serves as a core system for domain-general cognitive control, with robust activation with increased demand across diverse tasks. While fMRI studies have characterised the MD network's role in cognitive demand, linking these findings to electrophysiological activity remains a critical challenge. This article discusses the potential of oscillatory and aperiodic neural activity to bridge this gap. Although recent meta-analyses highlight mid-frontal theta power as a robust marker of task demand, its localised spatial distribution, limited cross-task generalisability, and potential confounds from aperiodic components limit its ability to fully represent the MD network. In contrast, aperiodic activity, particularly broadband power, has emerged as a strong candidate for indexing task demand due to its robust decoding performance and cross-task generalisability in response to diverse task demands, and spatial overlap with MD regions. Aperiodic activity may reflect fundamental neural properties, such as spiking rates and excitation/inhibition (E/I) balance, and is scale-free and exists across modalities, positioning it as a promising mechanism underpinning domain-general cognitive control that links to the MD network. Meanwhile, multiplexed low-frequency oscillations (e.g., delta and theta) may implement inter-regional synchronisation within the MD network, enabling large-scale coordination between MD subregions that supports cognitive control. Together, this article proposes a hypothetical framework linking the MD network to electrophysiological responses: Aperiodic broadband power, potentially reflecting population-level spiking activity, may support activation within MD regions, while multiplexed low-frequency oscillatory synchronisations may mediate inter-regional connectivity between MD regions.

Neural insights on expert surgeons' mental workload during live robotic surgeries

Despite its adoption and benefits, robotic surgeries can impose additional mental workload on surgeons. Validated questionnaires mostly administered at the end of procedures may not accurately capture the dynamic nature of mental workload over an entire procedure. Hence, we sought to determine if electroencephalogram (EEG) based neural activities in different brain regions can measure variations in expert surgeons' mental workload intraoperatively. EEG data was collected from five different surgeons performing 13 robotic-assisted urological procedures. Data analysis focused on three surgery phases (before, critical, and after). After performing each phase, surgeons provided a rating of their perceived mental workload. A linear mixed effects model was applied to explore the impact of the study phases on the relative spectral band power of EEG signals. The relative theta band power in the frontal brain region was highest during the critical portions of the procedure (p < 0.05). As the subjective ratings increased, the relative frontal theta band power increased (p < 0.001) while the relative parietal alpha band power decreased across all phases. We show that EEG signals can distinguish intraoperative workload in robotic surgeries. This has several applications including predicting risk factors for increased case complexity and surgical education.

Modulation of Interbrain and Intrabrain Connectivity due to Social Presence and Task Difficulty: A Dual EEG/fNIRS Hyperscanning Study

This study employed fNIRS- and EEG-hyperscanning to investigate the effects of task sharing, social presence, and mental workload on intrabrain and interbrain functional connectivity, and neurophysiological responses of dyads during a dual n-back task. The findings indicated a positive correlation between the n-back level and reaction times, heart rate, and PFC oxygenation, whereas task accuracy and heart rate variability decreased with difficulty. The effect of social presence was smaller than the effect of task difficulty, suggesting a lower level of mental workload during the social condition, possibly due to social facilitation. In the social condition, interbrain connectivity tended to decrease as task difficulty increased, indicating that partners could monitor each other's actions to the extent that task demands allowed. The intrabrain connectivity analysis showed a larger difference between individual and social sessions compared with the difference between own and coactor's go trials in the social session. Overall, the EEG- and fNIRS-hyperscanning measures obtained during a dual n-back task in this study provide evidence regarding the differential modulation of interbrain and intrabrain functional connectivity due to the copresence of another actor responding to the same stimulus to pursue a different goal and changes in task difficulty.

Targeting Neural Oscillations for Cognitive Enhancement in Alzheimer's Disease

Alzheimer's disease (AD), the most prevalent form of dementia, is marked by progressive cognitive decline, affecting memory, language, orientation, and behavior. Pathological hallmarks include extracellular amyloid plaques and intracellular tau tangles, which disrupt synaptic function and connectivity. Neural oscillations, the rhythmic synchronization of neuronal activity across frequency bands, are integral to cognitive processes but become dysregulated in AD, contributing to network dysfunction and memory impairments. Targeting these oscillations has emerged as a promising therapeutic strategy. Preclinical studies have demonstrated that specific frequency modulations can restore oscillatory balance, improve synaptic plasticity, and reduce amyloid and tau pathology. In animal models, interventions, such as gamma entrainment using sensory stimulation and transcranial alternating current stimulation (tACS), have shown efficacy in enhancing memory function and modulating neuroinflammatory responses. Clinical trials have reported promising cognitive improvements with repetitive transcranial magnetic stimulation (rTMS) and deep brain stimulation (DBS), particularly when targeting key hubs in memory-related networks, such as the default mode network (DMN) and frontal-parietal network. Moreover, gamma-tACS has been linked to increased cholinergic activity and enhanced network connectivity, which are correlated with improved cognitive outcomes in AD patients. Despite these advancements, challenges remain in optimizing stimulation parameters, individualizing treatment protocols, and understanding long-term effects. Emerging approaches, including transcranial pulse stimulation (TPS) and closed-loop adaptive neuromodulation, hold promise for refining therapeutic strategies. Integrating neuromodulation with pharmacological and lifestyle interventions may maximize cognitive benefits. Continued interdisciplinary efforts are essential to refine these approaches and translate them into clinical practice, advancing the potential for neural oscillation-based therapies in AD.

Phase-lagged tACS between executive and default mode networks modulates working memory

Transcranial alternating current stimulation (tACS) is an efficient neuromodulation technique to enhance cognitive function in a non-invasive manner. Using functional magnetic resonance imaging, we investigated whether a cross-frequency coupled tACS protocol with a phase lag (45 and 180 degrees) between the central executive and the default mode networks modulated working-memory performance. We found tACS-phase-dependent modulation of task performance reflected in hippocampal activation and task-related functional connectivity. Our observations provide a neurophysiological basis for neuromodulation and a feasible non-invasive approach to selectively stimulate a task-relevant deep brain structure. Overall, our study highlights the potential of tACS as a powerful tool for enhancing cognitive function and sheds light on the underlying mechanisms of this technique.

Attentional Refreshing in Working Memory and Its Interplay with Long-term Memory: A Behavioral and Electroencephalographic Study

Despite the growing interest in the study of attentional refreshing, the functioning of this working memory maintenance mechanism, including its cerebral underpinnings, is still debated. In particular, it remains unclear whether refreshing promotes long-term memory and whether it, in return, depends on long-term memory content to operate. Here, we used direct maintenance instructions and measured brain activity to investigate working memory maintenance with two objectives: (1) test if different behavioral and oscillatory patterns could be observed when participants were instructed to use attentional refreshing versus verbal rehearsal, and (2) observe whether and how refreshing is modulated when maintaining novel (pseudowords) versus familiar (words) memoranda. We conducted an EEG experiment using a modified Brown-Peterson task, in which we manipulated the type of maintenance engaged through explicit instructions (verbal rehearsal vs. refreshing), the type of memoranda (words vs. pseudowords), and the memory load (2 vs. 6). Using scalp EEG, we measured both neural oscillations during working memory maintenance and ERPs during the concurrent parity judgment task. For words, we showed that verbal rehearsal benefited more short-term recall whereas refreshing benefited more delayed recall. In keeping with these behavioral differences between maintenance instructions, frontal-midline theta power increased with memory load only when using verbal rehearsal, whereas occipito-parietal alpha desynchronization was larger with refreshing than verbal rehearsal. When maintaining pseudowords, verbal rehearsal also benefitted short-term recall more than refreshing. However, no long-term memory benefit of refreshing was observed for pseudowords, and oscillatory activity was not different under the two maintenance instructions. Our results provide new evidence supporting the independence between attentional refreshing and verbal rehearsal, and bring new insight into refreshing functioning. We discuss the possible interpretations of these results and the implications for the attentional refreshing literature.

The Problem with Time: Application of Partial Least Squares Analysis on Time-Frequency Plots to Account for Varying Time Intervals with Applied EEG Data

Background/Objectives: When attempting to study neurocognitive mechanisms with electroencephalography (EEG) in applied ecologically valid settings, responses to stimuli may differ in time, which presents challenges to traditional EEG averaging methods. In this proof-of-concept paper, we present a method to normalize time over unequal trial lengths while preserving frequency content. Methods: Epochs are converted to time-frequency space where they are resampled to contain an equal number of timepoints representing the proportion of trial complete rather than true time. To validate this method, we used EEG data recorded from 8 novices and 4 experts in veterinary medicine while completing decision-making tasks using two question types: multiple-choice and script concordance questions used in veterinary school exams. Results: The resulting resampled time-frequency data were analyzed with partial least squares (PLS), a multivariate technique that extracts patterns of data that support a contrast between conditions and groups while controlling for Type I error. We found a significant latent variable representing a difference between question types for experts only. Conclusions: Despite within and between subject differences in timing, we found consistent differences between question types in experts in gamma and beta bands that are consistent with changes resulting from increased information load and decision-making. This novel analysis method may be a viable path forward to preserve ecological validity in EEG studies.

Altered brain network stability in OCD following rTMS intervention: Insights from structural balance theory

Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising intervention for Obsessive-Compulsive Disorder (OCD). However, understanding brain network changes following rTMS remains limited, despite its potential to enhance treatment efficacy. In this retrospective study, we investigated brain network reorganization in OCD patients after rTMS, using structural balance theory as a framework. We hypothesized that rTMS-induced functional plasticity would alter brain network topology, particularly affecting triadic associations, and leading to increased balance energy levels, indicative of a less stable network state. Brain functional networks were constructed from resting-state EEGs of OCD patients, with phase lag indexes calculated both before and after rTMS treatment. These networks were analyzed by comparing global parameters, including positive and negative links, triadic interactions (balanced/unbalanced), hub formation tendencies, and balance energy levels. We observed a significant decrease in weak-balanced triads and an increase in strong-unbalanced triads within the Beta І frequency band (12-15 Hz). Additionally, there was a notable reduction in the tendency of negative links to form hubs across certain frequency bands. These changes led to an increase in the network's balanced energy level, pushing it toward a less stable state. We hope these findings will refine rTMS strategies by facilitating brain network reorganization.

Elusive Gains of Cognitive Training: Limited Effects on Neural Activity Across Sessions

BACKGROUND/OBJECTIVES

Cognitive training paradigms rely on the idea that consistent practice can drive neural plasticity, improving not only connectivity within critical brain networks, but also ultimately result in overall enhancement of trained cognitive functions, irrespective of the specific task. Here we opted to investigate the temporal dynamics of neural activity and cognitive performance during a structured cognitive training program.

METHODS

A group of 20 middle-aged participants completed 20 training sessions over 10 weeks. Quantitative EEG (qEEG) parameters, including alpha and theta power, alpha/theta ratio, and fronto-parietal coherence, were analyzed at four time points to assess changes in neural activity.

RESULTS

Results revealed significant overall improvements in the trained task (n-back) performance, without an effect on the untrained task (OSPAN). qEEG analyses showed increased change in posterior (and a less robust in frontal) alpha power, particularly during mid-training, suggesting an improved neural efficiency in regions associated with attentional allocation and task engagement. Theta power remained stable across sessions, indicating a limited influence on neural processes underlying working memory and attentional control. The parietal alpha/theta ratio showed weak increases during mid-training, reflecting subtle shifts in the neural efficacy and cognitive engagement. There were no significant changes in functional connectivity between frontal and parietal locations.

CONCLUSIONS

Our findings suggest that cognitive training primarily influences localized neural activity, rather than network-level connectivity. This lack of a longer-range network-level effect might also explain the failure of cognitive training paradigms to induce performance enhancements on the untrained tasks.

The brain under pressure: Exploring neurophysiological responses to cognitive stress

Stress is an increasingly dominating part of our daily lives and higher performance requirements at work or to ourselves influence the physiological reaction of our body. Elevated stress levels can be reliably identified through electroencephalogram (EEG) and heart rate (HR) measurements. In this study, we examined how an arithmetic stress-inducing task impacted EEG and HR, establishing meaningful correlations between behavioral data and physiological recordings. Thirty-one healthy participants (15 females, 16 males, aged 20 to 37) willingly participated. Under time pressure, participants completed arithmetic calculations and filled out stress questionnaires before and after the task. Linear mixed effects (LME) allowed us to generate topographical association maps showing significant relations between EEG features (delta, theta, alpha, beta, and gamma power) and factors such as task difficulty, error rate, response time, stress scores, and HR. With task difficulty, we observed left centroparietal and parieto-occipital theta power decreases, and alpha power increases. Furthermore, frontal alpha, delta and theta activity increased with error rate and relative response time, while parieto-temporo-occipital alpha power decreased. Practice effects on EEG power included increases in temporal, parietal, and parieto-occipital theta and alpha activity. HR was positively associated with frontal delta, theta and alpha power whereas frontal gamma power decreases. Significant alpha laterality scores were observed for all factors except task difficulty and relative response time, showing overall increases in left parietal regions. Significant frontal alpha asymmetries emerged with increases in error rate, sex, run number, and HR and occipital alpha asymmetries were also found with run number and HR. Additionally we explored practice effects and noted sex-related differences in EEG features, HR, and questionnaire scores. Overall, our study enhances the understanding of EEG/ECG-based mental stress detection, crucial for early interventions, personalized treatment and objective stress assessment towards the development of a neuroadaptive system.

Frontal midline theta power during the cue-target-interval reflects increased cognitive effort in rewarded task-switching

Cognitive performance largely depends on how much effort is invested during task-execution. This also means that we rarely perform as good as we could. Cognitive effort is adjusted to the expected outcome of performance, meaning that it is driven by motivation. The results from recent studies suggest that the expenditure of cognitive control is particularly prone to being affected by modulations of cognitive effort. Although recent EEG studies investigated the neural underpinnings of the interaction of effort and control, reports on how cognitive effort is reflected by oscillatory activity of the EEG are quite sparse. It is the goal of the present study to bridge this gap by performing an exploratory analysis of high-density EEG data from a switching-task using manipulations of monetary incentives. A beamformer approach is used to localize the sensor-level effects in source-space. The results indicate that the manipulation of cognitive effort was successful. The participants reported significantly higher motivation and cognitive effort in high versus low reward trials. Performance was also significantly increased. The analysis of the EEG data revealed that the increase of cognitive effort was reflected by an increased mid-frontal theta activity during the cue-target interval, suggesting an increased use of proactive control. This interpretation is supported by the result from a regression analysis performed on single-trial data, showing higher mid-frontal theta power prior to target-onset being associated with faster responses. Alpha-desynchronization throughout the trial was also more pronounced in high reward trials, signaling a bias of attention towards the processing of external stimuli. Source reconstruction suggests that these effects are located in areas related to cognitive control, and visual processing.

Oscillatory activity in bilateral prefrontal cortices is altered by distractor strength during working memory processing

Working memory (WM) enables the temporary storage of limited information and is a central component of higher order cognitive function. Irrelevant and/or distracting information can have a negative impact on WM processing and suppressing such incoming stimuli is critical to maintaining adequate performance. However, the neural mechanisms and dynamics underlying such distractor inhibition remain poorly understood. In the current study, we enrolled 46 healthy adults (Mage: 27.92, Nfemale: 28) who completed a Sternberg type WM task with high- and low-distractor conditions during magnetoencephalography (MEG). MEG data were transformed into the time-frequency domain and significant task-related oscillatory responses were imaged to identify the underlying anatomical areas. Whole-brain paired t-tests, with cluster-based permutation testing for multiple comparisons correction, were performed to assess differences between the low- and high-distractor conditions for each oscillatory response. Across conditions, we found strong alpha and beta oscillations (i.e., decreases relative to baseline) and increases in theta power throughout the encoding and maintenance periods. Whole-brain contrasts revealed significantly stronger alpha and beta oscillations in bilateral prefrontal regions during maintenance in high- compared to low-distractor trials, with the stronger beta oscillations being centered on the left dorsolateral prefrontal cortex and right inferior frontal gyrus, while those for alpha being within the right anterior prefrontal cortices and the right middle frontal gyrus. These findings suggest that alpha and beta oscillations in the bilateral prefrontal cortices play a major role in the inhibition of distracting information during WM maintenance. Our results also contribute to prior research on cognitive control and functional inhibition, in which prefrontal regions have been widely implicated.

The strength of anticipated distractors shapes EEG alpha and theta oscillations in a Working Memory task

Working Memory (WM) requires maintenance of task-relevant information and suppression of task-irrelevant/distracting information. Alpha and theta oscillations have been extensively investigated in relation to WM. However, studies that examine both theta and alpha bands in relation to distractors, encompassing not only power modulation but also connectivity modulation, remain scarce. Here, we depicted, at the EEG-source level, the increase in power and connectivity in theta and alpha bands induced by strong relative to weak distractors during a visual Sternberg-like WM task involving the encoding of verbal items. During retention, a strong or weak distractor was presented, predictable in time and nature. Analysis focused on the encoding and retention phases before distractor presentation. Theta and alpha power were computed in cortical regions of interest, and connectivity networks estimated via spectral Granger causality and synthetized using in/out degree indices. The following modulations were observed for strong vs. weak distractors. In theta band during encoding, the power in frontal regions increased, together with frontal-to-frontal and bottom-up occipital-to-temporal-to-frontal connectivity; even during retention, bottom-up theta connectivity increased. In alpha band during retention, but not during encoding, the power in temporal-occipital regions increased, together with top-down frontal-to-occipital and temporal-to-occipital connectivity. From our results, we postulate a proactive cooperation between theta and alpha mechanisms: the first would mediate enhancement of target representation both during encoding and retention, and the second would mediate increased inhibition of sensory areas during retention only, to suppress the processing of imminent distractor without interfering with the processing of ongoing target stimulus during encoding.

How is social dominance related to our short-term memory? An EEG/ERP investigation of encoding and retrieval during a working memory task

Social hierarchies exist in all societies and impact cognitive functions, brain mechanisms, social interactions, and behaviors. High status individuals often exhibit enhanced working memory (WM) performance compared to lower status individuals. This study examined whether individual differences in social dominance, as a predictor of future status, relate to WM abilities. Five hundred and twenty-five students completed the Personality Research Form dominance subscale questionnaire. From this sample, students with the highest and lowest scores were invited to participate in the study. Sixty-four participants volunteered to take part and were subsequently categorized into high- and low-dominance groups based on their dominance subscale questionnaire (PRF_d) scores. They performed a Sternberg WM task with set sizes of 1, 4, or 7 letters while their EEG was recorded. Event-related potential (ERP) and power spectral analysis revealed significantly reduced P3b amplitude and higher event-related synchronization (ERS) of theta and beta during encoding and retrieval phases in the high-than low-dominance group. Despite these neural processing differences, behavioral performance was equivalent between groups, potentially reflecting comparable cognitive load demands of the task across dominance levels. Further, there were similar P3b patterns for each set-size within groups. These findings provide initial evidence that individual differences in social dominance trait correlate with WM functioning, as indexed by neural processing efficiency during WM performance.

Echoes from Sensory Entrainment in Auditory Working Memory for Pitch

Ongoing neural oscillations reflect cycles of excitation and inhibition in local neural populations, with individual neurons being more or less likely to fire depending upon the oscillatory phase. As a result, the oscillations could determine whether or not a sound is perceived and/or whether its neural representation enters into later processing stages. While empirical support for this idea has come from sound detection studies, large gaps in knowledge still exist regarding memory for sound events. In the current study, it was investigated how sensory entrainment impacts the fidelity of working memory representations for pitch. In two separate experiments, an 8 Hz amplitude modulated (AM) entraining stimulus was presented prior to a multitone complex having an f0 between 270 and 715 Hz. This "target" sound could be presented at phases from 0 to 2π radians in relation to the previous AM. After a retention interval of 4 s (Experiment 1; n = 26) or 2 s (Experiment 2; n = 28), listeners were tasked to reproduce the target sound's pitch by moving their finger along the horizontal axis of a response pad. It was hypothesized that if entrainment modulates auditory working memory fidelity, reproductions of a target's pitch would be more accurate and precise when targets were presented in phase with the entrainment. Cosine fits of the average data for both experiments showed a significant entrainment "echo" in the accuracy of pitch matches. There was no apparent echo in the matching precision. Fitting of the individual data accuracy showed that the optimal phase was consistent across individuals, aligning near the next AM peak had the AM continued. The results show that sensory entrainment modulates auditory working memory in addition to stimulus detection, consistent with the proposal that ongoing neural oscillatory activity modulates higher-order auditory processes.

Scalp Electroencephalogram-Derived Involvement Indexes during a Working Memory Task Performed by Patients with Epilepsy

Electroencephalography (EEG) wearable devices are particularly suitable for monitoring a subject's engagement while performing daily cognitive tasks. EEG information provided by wearable devices varies with the location of the electrodes, the suitable location of which can be obtained using standard multi-channel EEG recorders. Cognitive engagement can be assessed during working memory (WM) tasks, testing the mental ability to process information over a short period of time. WM could be impaired in patients with epilepsy. This study aims to evaluate the cognitive engagement of nine patients with epilepsy, coming from a public dataset by Boran et al., during a verbal WM task and to identify the most suitable location of the electrodes for this purpose. Cognitive engagement was evaluated by computing 37 engagement indexes based on the ratio of two or more EEG rhythms assessed by their spectral power. Results show that involvement index trends follow changes in cognitive engagement elicited by the WM task, and, overall, most changes appear most pronounced in the frontal regions, as observed in healthy subjects. Therefore, involvement indexes can reflect cognitive status changes, and frontal regions seem to be the ones to focus on when designing a wearable mental involvement monitoring EEG system, both in physiological and epileptic conditions.

Clinical and neuropsychological correlates of theta-band functional excitation-inhibition ratio in autism: An EEG study

OBJECTIVE

How abnormal brain signaling impacts cognition in autism spectrum disorder (ASD) remained elusive. This study aimed to investigate the local and global brain signaling in ASD indicated by theta-band functional excitation-inhibition (fE/I) ratio and explored psychophysiological relationships between fE/I, cognitive deficits, and ASD symptomatology.

METHODS

A total of 83 ASD and typically developing (TD) individuals participated in this study. Participants' interference control and set-shifting abilities were assessed. Resting-state electroencephalography (EEG) was used for estimating theta-band fE/I ratio.

RESULTS

ASD individuals (n = 31 without visual EEG abnormality; n = 22 with visual EEG abnormality) generally performed slower in a cognitive task tapping interference control and set-maintenance abilities, but only ASD individuals with visually abnormal EEG performed significantly slower than their TD counterparts (Bonferroni-corrected ps < .001). Heightened theta-band fE/I ratios at the whole-head level, left and right hemispheres were observed in the ASD subgroup without visual EEG abnormality only (Bonferroni-corrected ps < .001), which remained highly significant when only data from medication-naïve participants were analyzed. In addition, higher left hemispheric fE/I ratios in ASD individuals without visual EEG abnormality were significantly correlated with faster interference control task performance, in turn faster reaction time was significantly associated with less severe restricted, repetitive behavior (Bonferroni-corrected ps ≤ .0017).

CONCLUSIONS

Differential theta-band fE/I within the ASD population. Heightened theta-band fE/I in ASD without visual EEG abnormality may be associated with more efficient filtering of distractors and a less severe ASD symptom manifestation.

SIGNIFICANCE

Brain signaling, indicated by theta-band fE/I, was different in ASD subgroups. Only ASD with visually-normal EEG showed heightened theta-band fE/I, which was associated with faster processing of visual distractors during a cognitive task. More efficient distractor filtering was associated with less restricted, repetitive behaviors.

Assessing the effects of an 8-week mindfulness training program on neural oscillations and self-reports during meditation practice

Previous literature suggests that mindfulness meditation can have positive effects on mental health, however, its mechanisms of action are still unclear. In this pre-registered study, we investigate the effects of mindfulness training on lapses of attention (and their associated neural correlates) during meditation practice. For this purpose, we recorded Electroencephalogram (EEG) during meditation practice before and after 8 weeks of mindfulness training (or waitlist) in 41 participants (21 treatment and 20 controls). In order to detect lapses of attention and characterize their EEG correlates, we interrupted participants during meditation to report their level of focus and drowsiness. First, we show that self-reported lapses of attention during meditation practice were associated to an increased occurrence of theta oscillations (3-6 Hz), which were slower in frequency and more spatially widespread than theta oscillations occurring during focused attention states. Then, we show that mindfulness training did not reduce the occurrence of lapses of attention nor their associated EEG correlate (i.e. theta oscillations) during meditation. Instead, we find that mindfulness training was associated with a significant slowing of alpha oscillations in frontal electrodes during meditation. Crucially, frontal alpha slowing during meditation practice has been reported in experienced meditators and is thought to reflect relative decreases in arousal levels. Together, our findings provide insights into the EEG correlates of mindfulness meditation, which could have important implications for the identification of its mechanisms of action and/or the development of neuromodulation protocols aimed at facilitating meditation practice.

EEG alpha and theta time-frequency structure during a written mathematical task

Since the first electroencephalogram (EEG) was obtained, there have been many possibilities to use it as a tool to access brain cognitive dynamics. Mathematical (Math) problem solving is one of the most important cortical processes, but it is still far from being well understood. EEG is an inexpensive and simple indirect measure of brain operation, but only recently has low-cost equipment (mobile EEG) allowed sophisticated analyses in non-clinical settings. The main purpose of this work is to study EEG activation during a Math task in a realistic environment, using mobile EEG. A matching pursuit (MP)-based signal analysis technique was employed, since MP properties render it a priori suitable to study induced EEG activity over long time sequences, when it is not tightly locked to a given stimulus. The study sample comprised sixty healthy volunteers. Unlike the majority of previous studies, subjects were studied in a sitting position with their eyes open. They completed a written Math task outside the EEG lab, wearing a mobile EEG device (EPOC+). Theta [4 Hz-7.5 Hz], alpha (7.5 Hz-13 Hz] and 0.5 Hz micro-bands in the [0.5 Hz-20 Hz] range were studied with a low-density stochastic MP dictionary. Over 1-min windows, ongoing EEG alpha and theta activity was decomposed into numerous MP atoms with median duration around 3 s, similar to the duration of induced, time-locked activity obtained with event-related (des)synchronization (ERS/ERD) studies. Relative to Rest, there was lower right-side and posterior MP alpha atom/min during Math, whereas MP theta atom/min was significantly higher on anteriorly located electrodes, especially on the left side. MP alpha findings were particularly significant on a narrow range around 10 Hz-10.5 Hz, consistent with FFT alpha peak findings from ERS/ERD studies. With a streamlined protocol, these results replicate previous findings of EEG alpha and theta activation obtained during Math tasks with different signal analysis techniques and in different time frames. The efficient application to real-world, noisy EEG data with a low-resolution stochastic MP dictionary shows that this technique is very encouraging. These results provide support for studies of mathematical cognition with mobile EEG and matching pursuit.

Same, Same but Different? A Multi-Method Review of the Processes Underlying Executive Control

Attention, working memory, and executive control are commonly considered distinct cognitive functions with important reciprocal interactions. Yet, longstanding evidence from lesion studies has demonstrated both overlap and dissociation in their behavioural expression and anatomical underpinnings, suggesting that a lower dimensional framework could be employed to further identify processes supporting goal-directed behaviour. Here, we describe the anatomical and functional correspondence between attention, working memory, and executive control by providing an overview of cognitive models, as well as recent data from lesion studies, invasive and non-invasive multimodal neuroimaging and brain stimulation. We emphasize the benefits of considering converging evidence from multiple methodologies centred on the identification of brain mechanisms supporting goal-driven behaviour. We propose that expanding on this approach should enable the construction of a comprehensive anatomo-functional framework with testable new hypotheses, and aid clinical neuroscience to intervene on impairments of executive functions.

Modulation of EEG Signals by Visual and Auditory Distractors in Virtual Reality-Based Continuous Performance Tests

Compared to traditional continuous performance tasks, virtual reality-based continuous performance tests (VR-CPT) offer higher ecological validity. While previous studies have primarily focused on behavioral outcomes in VR-CPT and incorporated various distractors to enhance ecological realism, little attention has been paid to the effects of distractors on EEG. Therefore, our study aimed to investigate the influence of distractors on EEG during VR-CPT. We studied visual distractors and auditory distractors separately, recruiting 68 subjects (M =20.82, SD =1.72) and asking each to complete four tasks. These tasks were categorized into four groups according to the presence or absence of visual and auditory distractors. We conducted paired t-tests on the mean relative power of the five electrodes in the ROI region across different frequency bands. Significant differences were found in theta waves between Group 3 (M =2.49, SD =2.02) and Group 4 (M =2.68, SD =2.39) (p < 0.05); in alpha waves between Group 3 (M =2.08, SD =3.73) and Group 4 (M =3.03, SD =4.60) (p < 0.001); and in beta waves between Group 1 (M = -4.44 , SD =2.29) and Group 2 (M = -5.03 , SD =2.48) (p < 0.001), as well as between Group 3 (M = -4.48 , SD =2.03) and Group 4 (M = -4.67 , SD =2.23) (p < 0.05). The incorporation of distractors in VR-CPT modulates EEG signals across different frequency bands, with visual distractors attenuating theta band activity, auditory distractors enhancing alpha band activity, and both types of distractors reducing beta oscillations following target stimuli. This insight holds significant promise for the rehabilitation of children and adolescents with attention deficits.

Brain oscillations during emotion regulation and the two-dimensional model of adult attachment

Emotion Regulation (ER) refers to the processes by which individuals influence their own emotions. It is a crucial aspect of human behavior, affecting everything from interpersonal relationships to mental health. The relationship between ER and Attachment Theory (AT) is pivotal. AT suggests that early bonds with primary caregivers influence future relationship expectations and behaviors. These initial experiences shape internal models of self and others, affecting how individuals regulate their emotions. Understanding the interplay between ER and AT is essential for comprehending the human affective system. In this study, we explored the neural underpinnings of ER, focusing on two distinct strategies: cognitive reappraisal and expressive suppression. Using electroencephalography (EEG), we examined changes in neural oscillations from 52 adults during an ER task. Specifically, we observed increased frontal theta activity (3-6 Hz) during reappraisal compared to suppression strategies. This frontal theta activity suggests enhanced cognitive control engagement. Conversely, during suppression, we noted a decrease in beta frequency (15-30 Hz) activity from central electrodes, indicative of differing neural processes. Further integrating psychological theories, we explored the relationship between these neural markers and dimensions of human attachment. Employing the Experiences in Close Relationships-12 scale (ECR-12), we identified a negative correlation between attachment anxiety and frontal theta activity. Lower levels of attachment anxiety were associated with increased theta activity, reflecting potentially more effective emotion regulation. Additionally, we found that higher theta activity corresponded with fewer difficulties in emotional control measured by the Difficulties in Emotion Regulation Scale (DERS). Regarding central beta activity, our findings revealed an interesting correlation with Emotional Inattention, a concept tied to Attachment Avoidance. This suggests that central beta activity may serve as a neural marker for specific attachment-related ER processing. These results highlight the distinct neural pathways involved in different ER strategies and their relationship with the AT and neural responses during emotional processing.

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.

Multi-scale analysis of acupuncture mechanisms for motor and sensory cortex activity based on SEEG data

Acupuncture, a traditional Chinese therapy, is gaining attention for its impact on the brain. While existing electroencephalogram and functional magnetic resonance image research has made significant contributions, this paper utilizes stereo-electroencephalography data for a comprehensive exploration of neurophysiological effects. Employing a multi-scale approach, channel-level analysis reveals notable $\delta $-band activity changes during acupuncture. At the brain region level, acupuncture modulated connectivity between the paracentral lobule and the precentral gyrus. Whole-brain analysis indicates acupuncture's influence on network organization, and enhancing $E_{glob}$ and increased interaction between the motor and sensory cortex. Brain functional reorganization is an important basis for functional recovery or compensation after central nervous system injury. The use of acupuncture to stimulate peripheral nerve trunks, muscle motor points, acupoints, etc., in clinical practice may contribute to the reorganization of brain function. This multi-scale perspective provides diverse insights into acupuncture's effects. Remarkably, this paper pioneers the introduction of stereo-electroencephalography data, advancing our understanding of acupuncture's mechanisms and potential therapeutic benefits in clinical settings.

The cerebellum monitors errors and entrains executive networks

Frontal midline θ (Fmθ) activity occurs in medial prefrontal cortices (mPFC), when expected and actual outcomes conflict. Cerebellar forward models could inform the mPFC about this mismatch. To verify this hypothesis we correlated the mPFC activation during a visuomotor tracking task (VM) with performance accuracy, in control and cerebellum-lesioned participants. Additionally, purely visual (V), motor (M) and a motor plus visual tasks (V + M) were performed. An Independent Component, with a mid-frontal topography scalp map and equivalent dipole location in the dorsal anterior cingulate cortex accounted for Fmθ. In control participants Fmθ power increased during VM, when the error level crossed a threshold, but not during V + M, M and V. This increase scaled with tracking error. Fmθ power failed to increase during VM in cerebellar participants, even at highest tracking errors. Thus, in control participants, activation of mPFC is induced when a continuous monitoring effort for online error detection is required. The presence of a threshold error for enhancing Fmθ, suggests the switch from an automatic to an executive tracking control, which recruits the mPFC. Given that the cerebellum stores forward models, the absence of Fmθ increases during tracking errors in cerebellar participants indicates that cerebellum is necessary for supplying the mPFC with prediction error-related information. This occurs when automatic control falters, and a deliberate correction mechanism needs to be triggered. Further studies are needed to verify if this alerting function also occurs in the context of the other cognitive and non-cognitive functions in which the cerebellum is involved.

Wearable functional near-infrared spectroscopy for measuring dissociable activation dynamics of prefrontal cortex subregions during working memory

The prefrontal cortex (PFC) has been extensively studied in relation to various cognitive abilities, including executive function, attention, and memory. Nevertheless, there is a gap in our scientific knowledge regarding the functionally dissociable neural dynamics across the PFC during a cognitive task and their individual differences in performance. Here, we explored this possibility using a delayed match-to-sample (DMTS) working memory (WM) task using NIRSIT, a high-density, wireless, wearable functional near-infrared spectroscopy (fNIRS) system. First, upon presentation of the sample stimulus, we observed an immediate signal increase in the ventral (orbitofrontal) region of the anterior PFC, followed by activity in the dorsolateral PFC. After the DMTS test stimulus appeared, the orbitofrontal cortex activated once again, while the rest of the PFC showed overall disengagement. Individuals with higher accuracy showed earlier and sustained activation of the PFC across the trial. Furthermore, higher network efficiency and functional connectivity in the PFC were correlated with individual WM performance. Our study sheds new light on the dynamics of PFC subregional activity during a cognitive task and its potential applicability in explaining individual differences in experimental, educational, or clinical populations. PRACTITIONER POINTS: Wearable functional near-infrared spectroscopy (fNIRS) captured dissociable temporal dynamics across prefrontal subregions during a delayed match-to-sample task. Anterior regions of the orbitofrontal cortex (OFC) activated first during the delay period, followed by the dorsolateral prefrontal cortex (PFC). PFC disengaged overall after the delay, but the OFC reactivated to the test stimulus. Earlier and sustained activation of PFC was associated with better accuracy. Functional connectivity and network efficiency also varied with task performance.

Finding tau rhythms in EEG: An independent component analysis approach

Tau rhythms are largely defined by sound responsive alpha band (~8-13 Hz) oscillations generated largely within auditory areas of the superior temporal gyri. Studies of tau have mostly employed magnetoencephalography or intracranial recording because of tau's elusiveness in the electroencephalogram. Here, we demonstrate that independent component analysis (ICA) decomposition can be an effective way to identify tau sources and study tau source activities in EEG recordings. Subjects (N = 18) were passively exposed to complex acoustic stimuli while the EEG was recorded from 68 electrodes across the scalp. Subjects' data were split into 60 parallel processing pipelines entailing use of five levels of high-pass filtering (passbands of 0.1, 0.5, 1, 2, and 4 Hz), three levels of low-pass filtering (25, 50, and 100 Hz), and four different ICA algorithms (fastICA, infomax, adaptive mixture ICA [AMICA], and multi-model AMICA [mAMICA]). Tau-related independent component (IC) processes were identified from this data as being localized near the superior temporal gyri with a spectral peak in the 8-13 Hz alpha band. These "tau ICs" showed alpha suppression during sound presentations that was not seen for other commonly observed IC clusters with spectral peaks in the alpha range (e.g., those associated with somatomotor mu, and parietal or occipital alpha). The choice of analysis parameters impacted the likelihood of obtaining tau ICs from an ICA decomposition. Lower cutoff frequencies for high-pass filtering resulted in significantly fewer subjects showing a tau IC than more aggressive high-pass filtering. Decomposition using the fastICA algorithm performed the poorest in this regard, while mAMICA performed best. The best combination of filters and ICA model choice was able to identify at least one tau IC in the data of ~94% of the sample. Altogether, the data reveal close similarities between tau EEG IC dynamics and tau dynamics observed in MEG and intracranial data. Use of relatively aggressive high-pass filters and mAMICA decomposition should allow researchers to identify and characterize tau rhythms in a majority of their subjects. We believe adopting the ICA decomposition approach to EEG analysis can increase the rate and range of discoveries related to auditory responsive tau rhythms.

Transcutaneous auricular vagus nerve stimulation improves working memory in temporal lobe epilepsy: A randomized double-blind study

AIMS

This study investigated the impact of transcutaneous auricular vagus nerve stimulation (taVNS) on working memory (WM) in refractory temporal lobe epilepsy (rTLE) and the underlying mechanisms.

METHODS

In this randomized double-blind study, 28 rTLE patients were subjected to an active or sham taVNS (a/s-taVNS) protocol for 20 weeks (a-taVNS group, n = 19; s-ta VNS group, n = 9). Patients performed visual WM tasks during stimulation and neural oscillations were simultaneously recorded by 19-channel electroencephalography.

RESULTS

Compared with the baseline state, reaction time was significantly shorter after 20 weeks of taVNS in the a-taVNS group (p = 0.010), whereas no difference was observed in the s-taVNS group (p > 0.05). The power spectral density (PSD) of the theta frequency band in the Fz channel decreased significantly after a-taVNS during WM-encoding (p = 0.020), maintenance (p = 0.038), and retrieval (p = 0.039) phases, but not in the s-taVNS group (all p > 0.05).

CONCLUSION

Neural oscillations during WM were altered by taVNS and WM performance was improved. Alterations in frontal midline theta oscillations may be a marker for the effect of taVNS on cognitive regulation.

Executive Functions Assessment Based on Wireless EEG and 3D Gait Analysis During Dual-Task: A Feasibility Study

Executive functions (EFs) are neurocognitive processes planning and regulating daily life actions. Performance of two simultaneous tasks, requiring the same cognitive resources, lead to a cognitive fatigue. Several studies investigated cognitive-motor task and the interference during walking, highlighting an increasing risk of falls especially in elderly and people with neurological diseases. A few studies instrumentally explored relationship between activation-no-activation of two EFs (working memory and inhibition) and spatial-temporal gait parameters. Aim of our study was to detect activation of inhibition and working memory during progressive difficulty levels of cognitive tasks and spontaneous walking using, respectively, wireless electroencephalography (EEG) and 3D-gait analysis. Thirteen healthy subjects were recruited. Two cognitive tasks were performed, activating inhibition (Go-NoGo) and working memory (N-back). EEG features (absolute and relative power in different bands) and kinematic parameters (7 spatial-temporal ones and Gait Variable Score for 9 range of motion of lower limbs) were analyzed. A significant decrease of stride length and an increase of external-rotation of foot progression were found during dual task with Go-NoGo. Moreover, a significant correlation was found between the relative power in the delta band at channels Fz, C4 and progressive difficulty levels of Go-NoGo (activating inhibition) during walking, whereas working memory showed no correlation. This study reinforces the hypothesis of the prevalent involvement of inhibition with respect to working memory during dual task walking and reveals specific kinematic adaptations. The foundations for EEG-based monitoring of cognitive processes involved in gait are laid. Clinical and Translational Impact Statement: Clinical and instrumental evaluation and training of executive functions (as inhibition), during cognitive-motor task, could be useful for rehabilitation treatment of gait disorder in elderly and people with neurological disease.

Age-related alterations in the oscillatory dynamics serving verbal working memory processing

Working memory (WM) is a foundational cognitive function involving the temporary storage of information. Unfortunately, WM is also one of the most sensitive cognitive functions to the detrimental effects of aging. Expanding the field's understanding of age-related WM changes is critical to advancing the development of strategies to mitigate age-related WM declines. In the current study, we investigated the neural mechanisms serving WM function in seventy-eight healthy aging adults (range: 20.2-65.2 years) using magnetoencephalography (MEG) and a Sternberg WM task with letter stimuli. Neural activity during the different phases of the WM task (i.e., encoding, maintenance, and retrieval) were imaged using a time-frequency resolved beamformer and whole-brain statistics were performed. We found stronger increases in theta activity and stronger decreases in alpha and beta activity (i.e., more negative relative to baseline) as a function of healthy aging. Specifically, age-related increases in theta activity were detected during the encoding period in the primary visual and left prefrontal cortices. Additionally, alpha and beta oscillations were stronger (i.e., more negative) during both encoding and maintenance in the left prefrontal cortex in older individuals. Finally, alpha and beta oscillations during the retrieval phase were stronger (i.e., more negative) in older participants within the prefrontal, parietal, and temporal cortices. Together, these results indicate that healthy aging strongly modulates the neural oscillatory dynamics serving WM function.

Brain-computer interface for robot control with eye artifacts for assistive applications

Human-robot interaction is a rapidly developing field and robots have been taking more active roles in our daily lives. Patient care is one of the fields in which robots are becoming more present, especially for people with disabilities. People with neurodegenerative disorders might not consciously or voluntarily produce movements other than those involving the eyes or eyelids. In this context, Brain-Computer Interface (BCI) systems present an alternative way to communicate or interact with the external world. In order to improve the lives of people with disabilities, this paper presents a novel BCI to control an assistive robot with user's eye artifacts. In this study, eye artifacts that contaminate the electroencephalogram (EEG) signals are considered a valuable source of information thanks to their high signal-to-noise ratio and intentional generation. The proposed methodology detects eye artifacts from EEG signals through characteristic shapes that occur during the events. The lateral movements are distinguished by their ordered peak and valley formation and the opposite phase of the signals measured at F7 and F8 channels. This work, as far as the authors' knowledge, is the first method that used this behavior to detect lateral eye movements. For the blinks detection, a double-thresholding method is proposed by the authors to catch both weak blinks as well as regular ones, differentiating itself from the other algorithms in the literature that normally use only one threshold. Real-time detected events with their virtual time stamps are fed into a second algorithm, to further distinguish between double and quadruple blinks from single blinks occurrence frequency. After testing the algorithm offline and in realtime, the algorithm is implemented on the device. The created BCI was used to control an assistive robot through a graphical user interface. The validation experiments including 5 participants prove that the developed BCI is able to control the robot.

A wireless and battery-less implant for multimodal closed-loop neuromodulation in small animals

Fully implantable wireless systems for the recording and modulation of neural circuits that do not require physical tethers or batteries allow for studies that demand the use of unconstrained and freely behaving animals in isolation or in social groups. Moreover, feedback-control algorithms that can be executed within such devices without the need for remote computing eliminate virtual tethers and any associated latencies. Here we report a wireless and battery-less technology of this type, implanted subdermally along the back of freely moving small animals, for the autonomous recording of electroencephalograms, electromyograms and body temperature, and for closed-loop neuromodulation via optogenetics and pharmacology. The device incorporates a system-on-a-chip with Bluetooth Low Energy for data transmission and a compressed deep-learning module for autonomous operation, that offers neurorecording capabilities matching those of gold-standard wired systems. We also show the use of the implant in studies of sleep-wake regulation and for the programmable closed-loop pharmacological suppression of epileptic seizures via feedback from electroencephalography. The technology can support a broader range of applications in neuroscience and in biomedical research with small animals.

Electroencephalogram-Based Subject Matching Learning (ESML): A Deep Learning Framework on Electroencephalogram-Based Biometrics and Task Identification

An EEG signal (Electroencephalogram) is a bioelectric phenomenon reflecting human brain activities. In this paper, we propose a novel deep learning framework ESML (EEG-based Subject Matching Learning) using raw EEG signals to learn latent representations for EEG-based user identification and tack classification. ESML consists of two parts: one is the ESML1 model via an LSTM-based method for EEG-user linking, and one is the ESML2 model via a CNN-based method for EEG-task linking. The new model ESML is simple, but effective and efficient. It does not require any restrictions for EEG data collection on motions and thinking for users, and it does not need any EEG preprocessing operations, such as EEG denoising and feature extraction. The experiments were conducted on three public datasets and the results show that ESML performs the best and achieves significant performance improvement when compared to baseline methods (i.e., SVM, LDA, NN, DTS, Bayesian, AdaBoost and MLP). The ESML1 model provided the best precision at 96% with 109 users and the ESML2 model achieved 99% precision at 3-Class task classification. These experimental results provide direct evidence that EEG signals can be used for user identification and task classification.

Effect of stress on spatial working memory and EEG signal dynamics in the follicular and luteal phases of the menstrual cycle in young single girls

AIM

Women undergo behavioral changes during the menstrual cycle. This study aimed to investigate the effect of estradiol (Es) on stress and effect of stress on spatial working memory (WM) and also to investigate electroencephalogram (EEG) signal's dynamics in the early and late follicular (EF and LF) and luteal (LU) phases of unmarried girls' menstrual cycle.

METHODS

Stress was induced by presentation of a short (3 min) movie clip. Simultaneous with a memory test and stress induction, EEG, serum Es levels, and galvanic skin response (GSR) were assessed.

RESULTS

Serum Es concentrations were decreased in LF, LU, and EF phases. The mean GSR score decreased after stress induction in all three phases, but it increased in the LF and LU phases versus the EF phase. Spatial WM diminished after stress induction in all three phases, but it increased in the LF phase versus the two phases before and after stress induction. Average power spectrum density in all frequency bands increased after stress induction in the frontal and prefrontal channels in the spatial WM test.

CONCLUSION

The results showed that stress led to spatial WM dysfunction; however, Es improved spatial WM performance in the LF phase versus the other two phases.

Mnemonic-trained brain tuning to a regular odd-even pattern subserves digit memory in children

It is said that our species use mnemonics - that "magic of memorization" - to engrave an enormous amount of information in the brain. Yet, it is unclear how mnemonics affect memory and what the neural underpinnings are. In this electroencephalography study, we examined the hypotheses whether mnemonic training improved processing-efficiency and/or altered encoding-pattern to support memory enhancement. By 22-day training of a digit-image mnemonic (a custom memory technique used by world-class mnemonists), a group of children showed increased short-term memory after training, but with limited gain generalization. This training resulted in regular odd-even neural patterns (i.e., enhanced P200 and theta power during the encoding of digits at even- versus odd- positions in a sequence). Critically, the P200 and theta power effects predicted the training-induced memory improvement. These findings provide evidence of how mnemonics alter encoding pattern, as reflected in functional brain organization, to support memory enhancement.

Cognitive aging at work and in daily life-a narrative review on challenges due to age-related changes in central cognitive functions

Demographic change is leading to an increasing proportion of older employees in the labor market. At the same time, work activities are becoming more and more complex and require a high degree of flexibility, adaptability, and cognitive performance. Cognitive control mechanism, which is subject to age-related changes and is important in numerous everyday and work activities, plays a special role. Executive functions with its core functions updating, shifting, and inhibition comprises cognitive control mechanisms that serve to plan, coordinate, and achieve higher-level goals especially in inexperienced and conflicting actions. In this review, influences of age-related changes in cognitive control are demonstrated with reference to work and real-life activities, in which the selection of an information or response in the presence of competing but task-irrelevant stimuli or responses is particularly required. These activities comprise the understanding of spoken language under difficult listening conditions, dual-task walking, car driving in critical traffic situations, and coping with work interruptions. Mechanisms for compensating age-related limitations in cognitive control and their neurophysiological correlates are discussed with a focus on EEG measures. The examples illustrate how to access influences of age and cognitive control on and in everyday and work activities, focusing on its functional role for the work ability and well-being of older people.

Physiological Measurements of Situation Awareness: A Systematic Review

OBJECTIVE

The goal of this systematic literature review is to investigate the relationship between indirect physiological measurements and direct measures of situation awareness (SA).

BACKGROUND

Across different environments and tasks, assessments of SA are often performed using techniques designed specifically to directly measure SA, such as SAGAT, SPAM, and/or SART. However, research suggests that indirect physiological sensing methods may also be capable of predicting SA. Currently, it is unclear which particular physiological approaches are sensitive to changes in SA.

METHOD

Seven databases were searched using the PRISMA reporting guidelines. Eligibility criteria included human-subject experiments that used at least one direct SA assessment technique, as well as at least one physiological measurement. Information extracted from each article was the physiological metric(s), the direct SA measurement(s), the correlation between these two metrics, and the experimental task(s). All studies underwent a quality assessment.

RESULTS

Twenty-five articles were included in this review. Eye tracking techniques were the most commonly used physiological measures, and correlations between conscious aspects of eye movement measures and direct SA scores were observed. Evidence for cardiovascular predictors of SA were mixed. EEG studies were too few to form strong conclusions, but were consistently positive.

CONCLUSION

Further investigation is needed to methodically collect more relevant data and comprehensively model the relationships between a wider range of physiological measurements and direct assessments of SA.

APPLICATION

This review will guide researchers and practitioners in methods to indirectly assess SA with sensors and highlight opportunities for future research on wearables and SA.

Measuring the attention networks and quantitative-electroencephalography correlates of attention in depression

Given the association between major depressive disorder (MDD) and cortical inefficiency related to executive control, specifically in the sense that individuals with MDD may recruit more cognitive resources to complete tasks at the same capacity as those without MDD, the current study was interested in examining the attention networks and executive functioning of those with MDD. Past research has used the Attention Network Test (ANT) to measure changes of attention in clinical vs. healthy populations; however, theoretical concerns have been raised regarding the task. The Combined Attention Systems Task (CAST) was developed to address these concerns and was used in our study in combination with quantitative-electroencephalography (QEEG) to assess both behavioural and neurophysiological changes in participants with MDD (n = 18) compared to healthy controls (HCs; n = 22). We found no behavioural differences between MDD and HC groups suggesting individuals with MDD in our sample were not experiencing the executive functioning deficits previously reported in the literature. Neurophysiological measures of attention revealed that MDD participants had greater theta and alpha₁ activity relative to HCs, suggesting that although individuals with MDD do not show deficits in behavioural attention, they exhibit altered neural processing which underlies cognitive function.

Comparative analysis of multifaceted neural effects associated with varying endogenous cognitive load

Contemporary neuroscience has firmly established that mental state variation concurs with changes in neural dynamic activity in a complex way that a one-to-one mapping cannot describe. To explore the scenario of the multifaceted changes in neural dynamics associated with simple mental state variation, we took cognitive load - a common cognitive manipulation in psychology - as a venue to characterize how multiple neural dynamic features are simultaneously altered by the manipulation and how their sensitivity differs. Electroencephalogram was collected from 152 participants performing stimulus-free tasks with different demands. The results show that task demand alters wide-ranging neural dynamic features, including band-specific oscillations across broad frequency bands, scale-free dynamics, and cross-frequency phase-amplitude coupling. The scale-free dynamics outperformed others in indexing cognitive load variation. This study demonstrates a complex relationship between cognitive dynamics and neural dynamics, which points to a necessity to integrate multifaceted neural dynamic features when studying mind-brain relationship in the future.

Effect of Lower Limb Exoskeleton on the Modulation of Neural Activity and Gait Classification

Neurorehabilitation with robotic devices requires a paradigm shift to enhance human-robot interaction. The coupling of robot assisted gait training (RAGT) with a brain-machine interface (BMI) represents an important step in this direction but requires better elucidation of the effect of RAGT on the user's neural modulation. Here, we investigated how different exoskeleton walking modes modify brain and muscular activity during exoskeleton assisted gait. We recorded electroencephalographic (EEG) and electromyographic (EMG) activity from ten healthy volunteers walking with an exoskeleton with three modes of user assistance (i.e., transparent, adaptive and full assistance) and during free overground gait. Results identified that exoskeleton walking (irrespective of the exoskeleton mode) induces a stronger modulation of central mid-line mu (8-13 Hz) and low-beta (14-20 Hz) rhythms compared to free overground walking. These modifications are accompanied by a significant re-organization of the EMG patterns in exoskeleton walking. On the other hand, we observed no significant differences in neural activity during exoskeleton walking with the different assistance levels. We subsequently implemented four gait classifiers based on deep neural networks trained on the EEG data during the different walking conditions. Our hypothesis was that exoskeleton modes could impact the creation of a BMI-driven RAGT. We demonstrated that all classifiers achieved an average accuracy of 84.13±3.49% in classifying swing and stance phases on their respective datasets. In addition, we demonstrated that the classifier trained on the transparent mode exoskeleton data can classify gait phases during adaptive and full modes with an accuracy of 78.3±4.8% , while the classifier trained on free overground walking data fails to classify the gait during exoskeleton walking (accuracy of 59.4±11.8% ). These findings provide important insights into the effect of robotic training on neural activity and contribute to the advancement of BMI technology for improving robotic gait rehabilitation therapy.

Effortful listening produces both enhancement and suppression of alpha in the EEG

Introduction

Adverse listening conditions can drive increased mental effort during listening. Neuromagnetic alpha oscillations (8-13 Hz) may index this listening effort, but inconsistencies regarding the direction of the relationship are abundant. We performed source analyses on high-density EEG data collected during a speech-on-speech listening task to address the possibility that opposing alpha power relationships among alpha producing brain sources drive this inconsistency.

Methods

Listeners (N=20) heard two simultaneously presented sentences of the form: Ready go to now. They either reported the color/number pair of a "Baron" call sign sentence (active: high effort), or ignored the stimuli (passive: low effort). Independent component analysis (ICA) was used to segregate temporally distinct sources in the EEG.

Results

Analysis of independent components (ICs) revealed simultaneous alpha enhancements (e.g., for somatomotor mu ICs) and suppressions (e.g., for left temporal ICs) for different brain sources. The active condition exhibited stronger enhancement for left somatomotor mu rhythm ICs, but stronger suppression for central occipital ICs.

Discussion

This study shows both alpha enhancement and suppression to be associated with increases in listening effort. Literature inconsistencies could partially relate to some source activities overwhelming others in scalp recordings.

Neuropsychological Characterization of Autosomal Recessive Intellectual Developmental Disorder 59 Associated with IMPA1 (MRT59)

Biallelic loss of function of IMPA1 causes autosomal recessive intellectual developmental disorder 59 (MRT59, OMIM #617323). MRT59 has been reported to present with significant intellectual disability and disruptive behavior, but little is known about the neurocognitive pattern of those patients. Thus, the aims of this study were: (1) to assess the cognitive profile of these patients, and (2) to evaluate their functional dependence levels. Eighteen adults, aged 37 to 89 years, participated in this study: nine MRT59 patients, five heterozygous carriers and four non-carrier family members. All of them were from a consanguineous family living in Northeast Brazil. All IMPA1 patients had the (c.489_493dupGGGCT) pathogenic variant in homozygosis. For cognitive assessment, the WASI battery was applied in nine MRT59 patients and compared to heterozygous carriers and non-carrier family members. Functional dependence was evaluated using the functional independence measure (FIM). Patients showed moderate to severe intellectual disability and severe functional disabilities. Heterozygous carriers did not differ from non-carriers. MRT59 patients should be followed up by health professionals in an interdisciplinary way to understand their cognitive disabilities and functional needs properly.

Tracking drivers' minds: Continuous evaluation of mental load and cognitive processing in a realistic driving simulator scenario by means of the EEG

Driving safety strongly depends on the driver's mental states and attention to the driving situation. Previous studies demonstrate a clear relationship between EEG measures and mental states, such as alertness and drowsiness, but often only map their mental state for a longer period of time. In this driving simulation study, we exploit the high temporal resolution of the EEG to capture fine-grained modulations in cognitive processes occurring before and after eye activity in the form of saccades, fixations, and eye blinks. A total of 15 subjects drove through an approximately 50-km course consisting of highway, country road, and urban passages. Based on the ratio of brain oscillatory alpha and theta activity, the total distance was classified into 10-m-long sections with low, medium, and high task loads. Blink-evoked and fixation-evoked event-related potentials, spectral perturbations, and lateralizations were analyzed as neuro-cognitive correlates of cognition and attention. Depending on EEG-based estimation of task load, these measures showed distinct patterns associated with driving behavior parameters such as speed and steering acceleration and represent a temporally highly resolved image of specific cognitive processes during driving. In future applications, combinations of these EEG measures could form the basis for driver warning systems which increase overall driving safety by considering rapid fluctuations in driver's attention and mental states.

Is Hypnotic Induction Necessary to Experience Hypnosis and Responsible for Changes in Brain Activity?

The relevance of formal hypnotic induction to the experience of trance and its neural correlates is not clear, in that hypnotizability, beliefs and expectation of hypnosis may play a major role. The aim of the study was assessing the EEG brain activity of participants with high (highs) or low hypnotizability scores (lows), aware of their hypnotizability level and informed that the session will include simple relaxation, formal hypnotic induction and neutral hypnosis. A total of 16 highs and 15 lows (according to the Stanford Hypnotic Susceptibility Scale, form A) were enrolled. Their EEGs were recorded during consecutive conditions of open/closed-eyes relaxation, hypnotic induction, neutral hypnosis and post hypnosis not interrupted by interviews. The studied variables were theta, alpha and gamma power spectral density (PSD), and the Determinism (DET) and Entropy (ENT) of the EEG signal Multidimensional Recurrence Plot (mRP). Highs reported significantly greater changes in their state of consciousness than lows across the session. The theta, alpha and gamma PSD did not exhibit condition-related changes in both groups. The Alpha PSD was larger in highs than in lows on midline sites, and the different sides/regions' theta and gamma PSD were observed in the two groups independently from conditions. ENT showed no correlation with hypnotizability, while DET positively correlated with hypnotizability during hypnosis. In conclusion, the relevance of formal hypnotic induction to the experience of trance may be scarce in highs, as they are aware of their hypnotizability scores and expecting hypnosis. Cognitive processing varies throughout the session depending on the hypnotizability level.

Genuine beta bursts in human working memory: controlling for the influence of lower-frequency rhythms

Human working memory is associated with significant modulations in oscillatory brain activity. However, the functional role of brain rhythms at different frequencies is still debated. Modulations in the beta frequency range (15-40 Hz) are especially difficult to interpret because they could be artifactually produced by (more prominent) oscillations in lower frequencies that show non-sinusoidal properties. In this study, we investigate beta oscillations during working memory while controlling for the possible influence of lower frequency rhythms. We collected electroencephalography (EEG) data in 31 participants who performed a spatial working-memory task with two levels of cognitive load. In order to rule out the possibility that observed beta activity was affected by non-sinusoidalities of lower frequency rhythms, we developed an algorithm that detects transient beta oscillations that do not coincide with more prominent lower frequency rhythms in time and space. Using this algorithm, we show that the amplitude and duration of beta bursts decrease with memory load and during memory manipulation, while their peak frequency and rate increase. In addition, interindividual differences in performance were significantly associated with beta burst rates. Together, our results show that beta rhythms are functionally modulated during working memory and that these changes cannot be attributed to lower frequency rhythms with non-sinusoidal properties.