Frontal midline EEG dynamics during working memory

Dual-Task Performance in Hearing-Impaired Older Adults-Study Protocol for a Cross-Sectional Mobile Brain/Body Imaging Study

Background: Hearing impairments are associated with reduced walking performance under Dual-task (DT) conditions. Little is known about the neural representation of DT performance while walking in this target group compared to healthy controls or younger adults. Therefore, utilizing the Mobile Brain/Body Imaging approach (MoBI), we aim at gaining deeper insights into the brain dynamics underlying the interaction of cognitive and motor processes during different DT conditions (visual and auditory) controlling for age and the potential performance decrements of older adults with hearing impairments.

Methods: The cross-sectional study integrates a multifactorial mixed-measure design. Between-subject factors grouping the sample will be age (younger vs. older adults) and hearing impairment (mild vs. not hearing impaired). The within-subject factors will be the task complexity (single- vs. DT) and cognitive task modality (visual vs. auditory). Stimuli of the cognitive task will vary according to the stimulus modality (visual vs. auditory), presentation side (left vs. right), and presentation-response compatibility (ipsilateral vs. contralateral). Analyses of DT costs and underlying neuronal correlates focus either on gait or cognitive performance. Based on an a priori sample size calculation 96 (48 healthy and 48 mildly hearing impaired) community-dwelling older adults (50–70 years) and 48 younger adults (20–30 years) will be recruited. Gait parameters of speed and rhythm will be captured. EEG activity will be recorded using 64 active electrodes.

Discussion: The study evaluates cognitive-motor interference (CMI) in groups of young and older adults as well as older adults with hearing impairment. The underlying processes of the interaction between motor and cognitive tasks will be identified at a behavioral and neurophysiological level comparing an auditory or a visual secondary task. We assume that performance differences are linked to different cognitive-motor processes, i.e., stimulus input, resource allocation, and movement execution. Moreover, for the different DT conditions (auditory vs. visual) we assume performance decrements within the auditory condition, especially for older, hearing-impaired adults. Findings will provide evidence of general mechanisms of CMI (ST vs. DT walking) as well as task-specific effects in dual-task performance while over ground walking.

The Influence of Mental Imagery Expertise of Pen and Paper Players versus Computer Gamers upon Performance and Electrocortical Correlates in a Difficult Mental Rotation Task

We investigated the influence of mental imagery expertise in 15 pen and paper role-players as an expert group compared to the gender-matched control group of computer role-players in the difficult Vandenberg and Kuse mental rotation task. In this task, the participants have to decide which two of four rotated figures match the target figure. The dependent measures were performance speed and accuracy. In our exploratory investigation, we further examined midline frontal theta band activation, parietal alpha band activation, and parietal alpha band asymmetry in EEG as indicator for the chosen rotation strategy. Additionally, we explored the gender influence on performance and EEG activation, although a very small female sample section was given. The expected gender difference concerning performance accuracy was negated by expertise in pen and paper role-playing women, while the gender-specific difference in performance speed was preserved. Moreover, gender differences concerning electro-cortical measures revealed differences in rotation strategy, with women using top-down strategies compared to men, who were using top-down strategies and active inhibition of associative cortical areas. These strategy uses were further moderated by expertise, with higher expertise leading to more pronounced activation patters, especially during successful performance. However, due to the very limited sample size, the findings of this explorative study have to be interpreted cautiously.

Distinguishing Multiple Coding Levels in Theta Band Activity During Working Memory Gating Processes

Cognitive control and working memory (WM) processes are essential for goal-directed behaviour. Cognitive control and WM are probably based on overlapping neurophysiological mechanisms. For example, theta-band activity (TBA) plays an important role in both functions. For cognitive control processes, it is known that different aspects of information about stimulus content, motor processes and stimulus-response relationships are encoded simultaneously in the TBA. All this information is probably processed during WM gating processes and must be controlled during them. However, direct data for this are lacking. This question is investigated in this study by combining methods of EEG temporal signal decomposition, time-frequency decomposition and beamforming. We show that portions of stimulus-related information, motor response-related information and information related to the interaction between the stimulus and motor responses in the TBA are influenced in parallel and to a similar extent by WM gate opening and gate closing processes. Nevertheless, it is stimulus-related information in the theta signal in particular that modulates behavioural performance in WM-gating. The data suggest that the identified processes are implemented in specific neuroanatomical structures. In particular, the medial frontal cortex, temporal cortical regions and insular cortex are involved in these dynamics. The study shows that principles of information coding relevant to cognitive control processes are also crucial for understanding WM gating.

Comparison of Quantitative Electroencephalography between Tic Disorder and Attention-Deficit/Hyperactivity Disorder in Children

Objective

Attention-deficit/hyperactivity disorder (ADHD) and tic disorder (TD) are among the most common comorbid psychopathologies and have a shared genetic basis. The psychopathological and neurophysiological aspects of the mechanism underlying the comorbidity of both disorders have been investigated, but the pathophysiological aspects remain unclear. Therefore, this study aimed to compare the neurophysiological characteristics of ADHD with those of TD using resting-state electroencephalography and exact low-resolution brain electromagnetic tomography (eLORETA) analysis.

Methods

We performed eLORETA analysis based on the resting-state scalp-recorded electrical potential distribution in 34 children with ADHD and 21 age-matched children with TD. Between-group differences in electroencephalography (EEG) current source density in delta, theta, alpha, beta, and gamma bands were investigated in each cortical region.

Results

Compared with the TD group, the ADHD group showed significantly increased theta activity in the frontal region (superior frontal gyrus, t = 3.37, p < 0.05; medial frontal gyrus, t = 3.35, p < 0.05). In contrast, children with TD showed decreased posterior alpha activity than those with ADHD (precuneus, t = −3.40, p < 0.05; posterior cingulate gyrus, t = −3.38, p < 0.05). These findings were only significant when the eyes were closed.

Conclusion

Increased theta activity in the frontal region is a neurophysiological marker that can distinguish ADHD from TD. Also, reduced posterior alpha activity might represent aberrant inhibitory control. Further research needs to confirm these characteristics by simultaneously measuring EEG-functional magnetic resonance imaging.

The Modulation of Working-Memory Performance Using Gamma-Electroacupuncture and Theta-Electroacupuncture in Healthy Adults

Working memory (WM), a central component of general cognition, plays an essential role in human beings' daily lives. WM impairments often occur in psychiatric, neurodegenerative, and neurodevelopmental disorders, mainly presenting as loss of high-load WM. In previous research, electroacupuncture (EA) has been shown to be an effective treatment for cognitive impairments. Frequency parameters are an important factor in therapeutic results, but the optimal frequency parameters of EA have not yet been identified. In this study, we chose theta-EA (θ-EA; 6 Hz) and gamma-EA (γ-EA; 40 Hz), corresponding to the transcranial alternating-current stimulation (tACS) frequency parameters at the Baihui (DU20) and Shenting (DU24) acupoints, in order to compare the effects of different EA frequencies on WM. We evaluated WM performance using visual 1-back, 2-back, and 3-back WM tasks involving digits. Each participant (N = 30) attended three different sessions in accordance with a within-subject crossover design. We performed θ-EA, γ-EA, and sham-EA in a counterbalanced order, conducting the WM task both before and after intervention. The results showed that d-prime (d′) under all three stimulation conditions had no significance in the 1-back and 2-back tasks. However, in the 3-back task, there was a significant improvement in d′ after intervention compared to d′ before intervention under θ-EA (F [1, 29] = 22.64; P < 0.001), while we saw no significant difference in the γ-EA and sham-EA groups. Reaction times for hits (RT-hit) under all three stimulation conditions showed decreasing trends in 1-, 2-, and 3-back tasks but without statistically significant differences. These findings suggest that the application of θ-EA might facilitate high-load WM performance.

Theta and Alpha Oscillatory Activity During Working Memory Maintenance in Long-Term Cannabis Users: The Importance of the Polydrug Use Context

Background: Impairments in various subdomains of memory have been associated with chronic cannabis use, but less is known about their neural underpinnings, especially in the domain of the brain's oscillatory activity. Aims: To investigate neural oscillatory activity supporting working memory (WM) in regular cannabis users and non-using controls. We focused our analyses on frontal midline theta and posterior alpha asymmetry as oscillatory fingerprints for the WM's maintenance process. Methods: 30 non-using controls (CG) and 57 regular cannabis users-27 exclusive cannabis users (CU) and 30 polydrug cannabis users (PU) completed a Sternberg modified WM task with a concurrent electroencephalography recording. Theta, alpha and beta frequency bands were examined during WM maintenance. Results: When compared to non-using controls, the PU group displayed increased frontal midline theta (FMT) power during WM maintenance, which was positively correlated with RT. The posterior alpha asymmetry during the maintenance phase, on the other hand, was negatively correlated with RT in the CU group. WM performance did not differ between groups. Conclusions: Both groups of cannabis users (CU and PU), when compared to the control group, displayed differences in oscillatory activity during WM maintenance, unique for each group (in CU posterior alpha and in PU FMT correlated with performance). We interpret those differences as a reflection of compensatory strategies, as there were no differences between groups in task performance. Understanding the psychophysiological processes in regular cannabis users may provide insight on how chronic use may affect neural networks underlying cognitive processes, however, a polydrug use context (i.e., combining cannabis with other illegal substances) seems to be an important factor.

The Temporal Dynamics of EEG Microstate Reveals the Neuromodulation Effect of Acupuncture With Deqi

The electroencephalography (EEG) microstate has recently emerged as a new whole-brain mapping tool for studying the temporal dynamics of the human brain. Meanwhile, the neuromodulation effect of external stimulation on the human brain is of increasing interest to neuroscientists. Acupuncture, which originated in ancient China, is recognized as an external neuromodulation method with therapeutic effects. Effective acupuncture could elicit the deqi effect, which is a combination of multiple sensations. However, whether the EEG microstate could be used to reveal the neuromodulation effect of acupuncture with deqi remains largely unclear. In this study, multichannel EEG data were recorded from 16 healthy subjects during acupuncture manipulation, as well as during pre- and post-manipulation tactile controls and pre- and post-acupuncture rest controls. As the basic acupuncture unit for regulating the central nervous system, the Hegu acupoint was used in this study, and each subject’s acupuncture deqi behavior scores were collected. To reveal the neuroimaging evidence of acupuncture with deqi, EEG microstate analysis was conducted to obtain the microstate maps and microstate parameters for different conditions. Furthermore, Pearson’s correlation was analyzed to investigate the correlation relationship between microstate parameters and deqi behavioral scores. Results showed that: (1) compared with tactile controls, acupuncture manipulation caused significantly increased deqi behavioral scores. (2) Acupuncture manipulation significantly increased the duration, occurrence, and contribution parameters of microstate C, whereas it decreased those parameters of microstate D. (3) Microstate C’s duration parameter showed a significantly positive correlation with acupuncture deqi behavior scores. (4) Acupuncture manipulation significantly increased the transition probabilities with microstate C as node, whereas it reduced the transition probabilities with microstate D as node. (5) Microstate B→C’s transition probability also showed a significantly positive correlation with acupuncture deqi behavior scores. Taken together, the temporal dynamic feature of EEG microstate could be used as objective neuroimaging evidence to reveal the neuromodulation effect of acupuncture with deqi.

Effects of Ketamine and Midazolam on Simultaneous EEG/fMRI Data During Working Memory Processes

Reliable measures of cognitive brain activity from functional neuroimaging techniques may provide early indications of efficacy in clinical trials. Functional magnetic resonance imaging and electroencephalography provide complementary spatiotemporal information and simultaneous recording of these two modalities can remove inter-session drug response and environment variability. We sought to assess the effects of ketamine and midazolam on simultaneous electrophysiological and hemodynamic recordings during working memory (WM) processes. Thirty participants were included in a placebo-controlled, three-way crossover design with ketamine and midazolam. Compared to placebo, ketamine administration attenuated theta power increases and alpha power decreases and midazolam attenuated low beta band decreases to increasing WM load. Additionally, ketamine caused larger blood-oxygen-dependent (BOLD) signal increases in the supplementary motor area and angular gyrus, and weaker deactivations of the default mode network (DMN), whereas no difference was found between midazolam and placebo. Ketamine administration caused positive temporal correlations between frontal-midline theta (fm-theta) power and the BOLD signal to disappear and attenuated negative correlations. However, the relationship between fm-theta and the BOLD signal from DMN areas was maintained in some participants during ketamine administration, as increasing theta strength was associated with stronger BOLD signal reductions in these areas. The presence of, and ability to manipulate, both positive and negative associations between the BOLD signal and fm-theta suggest the presence of multiple fm-theta components involved in WM processes, with ketamine administration disrupting one or more of these theta-linked WM strategies.

EEG Alpha and Beta Band Functional Connectivity and Network Structure Mark Hub Overload in Mild Cognitive Impairment During Memory Maintenance

Background: While decreased alpha and beta-band functional connectivity (FC) and changes in network topology have been reported in Alzheimer's disease, it is not yet entirely known whether these differences can mark cognitive decline in the early stages of the disease. Our study aimed to analyze electroencephalography (EEG) FC and network differences in the alpha and beta frequency band during visuospatial memory maintenance between Mild Cognitive Impairment (MCI) patients and healthy elderly with subjective memory complaints. Methods: Functional connectivity and network structure of 17 MCI patients and 20 control participants were studied with 128-channel EEG during a visuospatial memory task with varying memory load. FC between EEG channels was measured by amplitude envelope correlation with leakage correction (AEC-c), while network analysis was performed by applying the Minimum Spanning Tree (MST) approach, which reconstructs the critical backbone of the original network. Results: Memory load (increasing number of to-be-learned items) enhanced the mean AEC-c in the control group in both frequency bands. In contrast to that, after an initial increase, the MCI group showed significantly (p < 0.05) diminished FC in the alpha band in the highest memory load condition, while in the beta band this modulation was absent. Moreover, mean alpha and beta AEC-c correlated significantly with the size of medial temporal lobe structures in the entire sample. The network analysis revealed increased maximum degree, betweenness centrality, and degree divergence, and decreased diameter and eccentricity in the MCI group compared to the control group in both frequency bands independently of the memory load. This suggests a rerouted network in the MCI group with a more centralized topology and a more unequal traffic load distribution. Conclusion: Alpha- and beta-band FC measured by AEC-c correlates with cognitive load-related modulation, with subtle medial temporal lobe atrophy, and with the disruption of hippocampal fiber integrity in the earliest stages of cognitive decline. The more integrated network topology of the MCI group is in line with the "hub overload and failure" framework and might be part of a compensatory mechanism or a consequence of neural disinhibition.

Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults

Cardiorespiratory fitness was found to influence age-related changes of resting state brain network organization. However, the influence on dedifferentiated involvement of wider and more unspecialized brain regions during task completion is barely understood. We analyzed EEG data recorded during rest and different tasks (sensory, motor, cognitive) with dynamic mode decomposition, which accounts for topological characteristics as well as temporal dynamics of brain networks. As a main feature the dominant spatio-temporal EEG pattern was extracted in multiple frequency bands per participant. To deduce a pattern’s stability, we calculated its proportion of total variance among all activation patterns over time for each task. By comparing fit (N = 15) and less fit older adults (N = 16) characterized by their performance on a 6-min walking test, we found signs of a lower task specificity of the obtained network features for the less fit compared to the fit group. This was indicated by fewer significant differences between tasks in the theta and high beta frequency band in the less fit group. Repeated measures ANOVA revealed that a significantly lower proportion of total variance can be explained by the main pattern in high beta frequency range for the less fit compared to the fit group [F(1,29) = 12.572, p = .001, partial η² = .300]. Our results indicate that the dedifferentiation in task-related brain activation is lower in fit compared to less fit older adults. Thus, our study supports the idea that cardiorespiratory fitness influences task-related brain network organization in different task domains.

Measuring Correlates of Mental Workload During Simulated Driving Using cEEGrid Electrodes: A Test-Retest Reliability Analysis

The EEG reflects mental processes, especially modulations in the alpha and theta frequency bands are associated with attention and the allocation of mental resources. EEG has also been used to study mental processes while driving, both in real environments and in virtual reality. However, conventional EEG methods are of limited use outside of controlled laboratory settings. While modern EEG technologies offer hardly any restrictions for the user, they often still have limitations in measurement reliability. We recently showed that low-density EEG methods using film-based round the ear electrodes (cEEGrids) are well-suited to map mental processes while driving a car in a driving simulator. In the present follow-up study, we explored aspects of ecological and internal validity of the cEEGrid measurements. We analyzed longitudinal data of 127 adults, who drove the same driving course in a virtual environment twice at intervals of 12-15 months while the EEG was recorded. Modulations in the alpha and theta frequency bands as well as within behavioral parameters (driving speed and steering wheel angular velocity) which were highly consistent over the two measurement time points were found to reflect the complexity of the driving task. At the intraindividual level, small to moderate (albeit significant) correlations were observed in about 2/3 of the participants, while other participants showed significant deviations between the two measurements. Thus, the test-retest reliability at the intra-individual level was rather low and challenges the value of the application for diagnostic purposes. However, across all participants the reliability and ecological validity of cEEGrid electrodes were satisfactory in the context of driving-related parameters.

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.

Investigating the effect of losses and gains on effortful engagement during an incentivized Go/NoGo task through anticipatory cortical oscillatory changes

Losses usually have greater subjective value (SV) than gains of equal nominal value but often cause a relative deterioration in effortful performance. Since losses and gains induce differing approach/avoidance behavioral tendencies, we explored whether incentive type interacted with approach/avoidance motor-sets. Alpha- and beta-band event-related desynchronization (ERD) was hypothesized to be weakest when participants expected a loss and prepared an inhibitory motor-set, and strongest when participants expected a gain and prepared an active motor-set. It was also hypothesized that effort would modulate reward and motor-set-related cortical activation patterns. Participants completed a cued Go/NoGo task while expecting a reward (+10p), avoiding a loss (-10p), or receiving no incentive (0p); and while expecting a NoGo cue with a probability of either .75 or .25. Pre-movement alpha- and beta-band EEG power was analyzed using the ERD method, and the SV of effort was evaluated using a cognitive effort discounting task. Gains incentivized faster RTs and stronger preparatory alpha band ERD compared to loss and no incentive conditions, while inhibitory motor-sets resulted in significantly weaker alpha-band ERD. However, there was no interaction between incentive and motor-sets. Participants were more willing to expend effort in losses compared to gain trials, although the SV of effort was not associated with ERD patterns or RTs. Results suggest that incentive and approach/avoidance motor tendencies modulate cortical activations prior to a speeded RT movement independently, and are not associated with the economic value of effort. The present results favor attentional explanations of the effect of incentive modality on effort.

Improving cognitive control: Is theta neurofeedback training associated with proactive rather than reactive control enhancement?

Frontal-midline (FM) theta activity (4-8 Hz) is proposed to reflect a mechanism for cognitive control that is needed for working memory retention, manipulation, and interference resolution. Modulation of FM theta activity via neurofeedback training (NFT) demonstrated transfer to some but not all types of cognitive control. Therefore, the present study investigated whether FM theta NFT enhances performance and modulates underlying EEG characteristics in a delayed match to sample (DMTS) task requiring mainly proactive control and a color Stroop task requiring mainly reactive control. Moreover, temporal characteristics of transfer were explored over two posttests. Across seven 30-min NFT sessions, an FM theta training group exhibited a larger FM theta increase compared to an active control group who upregulated randomly chosen frequency bands. In a posttest performed 13 days after the last training session, the training group showed better retention performance in the DMTS task. Furthermore, manipulation performance was associated with NFT theta increase for the training but not the control group. Contrarily, behavioral group differences and their relation to FM theta change were not significant in the Stroop task, suggesting that NFT is associated with proactive but not reactive control enhancement. Transfer to both tasks at a posttest one day after training was not significant. Behavioral improvements were not accompanied by changes in FM theta activity, indicating no training-induced modulation of EEG characteristics. Together, these findings suggest that NFT supports transfer to cognitive control that manifests late after training but that other training-unspecific factors may also contribute to performance enhancement.

Trail Making Test Performance Using a Touch-Sensitive Tablet: Behavioral Kinematics and Electroencephalography

The Trail Making Test (TMT) is widely used to probe brain function and is performed with pen and paper, involving Parts A (linking numbers) and B (alternating between linking numbers and letters). The relationship between TMT performance and the underlying brain activity remains to be characterized in detail. Accordingly, sixteen healthy young adults performed the TMT using a touch-sensitive tablet to capture enhanced performance metrics, such as the speed of linking movements, during simultaneous electroencephalography (EEG). Linking and non-linking periods were derived as estimates of the time spent executing and preparing movements, respectively. The seconds per link (SPL) was also used to quantify TMT performance. A strong effect of TMT Part A and B was observed on the SPL value as expected (Part B showing increased SPL value); whereas the EEG results indicated robust effects of linking and non-linking periods in multiple frequency bands, and effects consistent with the underlying cognitive demands of the test.

EEG power spectral dynamics associated with listening in adverse conditions

Adverse listening conditions increase the demand on cognitive resources needed for speech comprehension. In an exploratory study, we aimed to identify independent power spectral features in the EEG useful for studying the cognitive processes involved in this effortful listening. Listeners performed the coordinate response measure task with a single-talker masker at a 0-dB signal-to-noise ratio. Sounds were left unfiltered or degraded with low-pass filtering. Independent component analysis (ICA) was used to identify independent components (ICs) in the EEG data, the power spectral dynamics of which were then analyzed. Frontal midline theta, left frontal, right frontal, left mu, right mu, left temporal, parietal, left occipital, central occipital, and right occipital clusters of ICs were identified. All IC clusters showed some significant listening-related changes in their power spectrum. This included sustained theta enhancements, gamma enhancements, alpha enhancements, alpha suppression, beta enhancements, and mu rhythm suppression. Several of these effects were absent or negligible using traditional channel analyses. Comparison of filtered to unfiltered speech revealed a stronger alpha suppression in the parietal and central occipital clusters of ICs for the filtered speech condition. This not only replicates recent findings showing greater alpha suppression as listening difficulty increases but also suggests that such alpha-band effects can stem from multiple cortical sources. We lay out the advantages of the ICA approach over the restrictive analyses that have been used as of late in the study of listening effort. We also make suggestions for moving into hypothesis-driven studies regarding the power spectral features that were revealed.

Neurocognitive subprocesses of working memory performance

Working memory (WM) has been defined as the active maintenance and flexible updating of goal-relevant information in a form that has limited capacity and resists interference. Complex measures of WM recruit multiple subprocesses, making it difficult to isolate specific contributions of putatively independent subsystems. The present study was designed to determine whether neurophysiological indicators of proposed subprocesses of WM predict WM performance. We recruited 200 individuals defined by care-seeking status and measured neural responses using electroencephalography (EEG), while participants performed four WM tasks. We extracted spectral and time-domain EEG features from each task to quantify each of the hypothesized WM subprocesses: maintenance (storage of content), goal maintenance, and updating. We then used EEG measures of each subprocess as predictors of task performance to evaluate their contribution to WM. Significant predictors of WM capacity included contralateral delay activity and frontal theta, features typically associated with maintenance (storage of content) processes. In contrast, significant predictors of reaction time and its variability included contingent negative variation and the P3b, features typically associated with goal maintenance and updating. Broadly, these results suggest two principal dimensions that contribute to WM performance, tonic processes during maintenance contributing to capacity, and phasic processes during stimulus processing that contribute to response speed and variability. The analyses additionally highlight that reliability of features across tasks was greater (and comparable to that of WM performance) for features associated with stimulus processing (P3b and alpha), than with maintenance (gamma, theta and cross-frequency coupling).

Prefrontal Theta-Phase Synchronized Brain Stimulation With Real-Time EEG-Triggered TMS

Background

Theta-band neuronal oscillations in the prefrontal cortex are associated with several cognitive functions. Oscillatory phase is an important correlate of excitability and phase synchrony mediates information transfer between neuronal populations oscillating at that frequency. The ability to extract and exploit the prefrontal theta rhythm in real time in humans would facilitate insight into neurophysiological mechanisms of cognitive processes involving the prefrontal cortex, and development of brain-state-dependent stimulation for therapeutic applications.

Objectives

We investigate individual source-space beamforming-based estimation of the prefrontal theta oscillation as a method to target specific phases of the ongoing theta oscillations in the human dorsomedial prefrontal cortex (DMPFC) with real-time EEG-triggered transcranial magnetic stimulation (TMS). Different spatial filters for extracting the prefrontal theta oscillation from EEG signals are compared and additional signal quality criteria are assessed to take into account the dynamics of this cortical oscillation.

Methods

Twenty two healthy participants were recruited for anatomical MRI scans and EEG recordings with 18 composing the final analysis. We calculated individual spatial filters based on EEG beamforming in source space. The extracted EEG signal was then used to simulate real-time phase-detection and quantify the accuracy as compared to post-hoc phase estimates. Different spatial filters and triggering parameters were compared. Finally, we validated the feasibility of this approach by actual real-time triggering of TMS pulses at different phases of the prefrontal theta oscillation.

Results

Higher phase-detection accuracy was achieved using individualized source-based spatial filters, as compared to an average or standard Laplacian filter, and also by detecting and avoiding periods of low theta amplitude and periods containing a phase reset. Using optimized parameters, prefrontal theta-phase synchronized TMS of DMPFC was achieved with an accuracy of ±55°.

Conclusion

This study demonstrates the feasibility of triggering TMS pulses during different phases of the ongoing prefrontal theta oscillation in real time. This method is relevant for brain state-dependent stimulation in human studies of cognition. It will also enable new personalized therapeutic repetitive TMS protocols for more effective treatment of neuropsychiatric disorders.

Cognitive Workload in an Auditory Digit Span Task When Memory Span Is in the Neighborhood of Seven Items

Abstract. Task performance of digit span has been widely used in the research on human short-term memory. The present study was conducted to show that the dynamic change of underlying mental effort can be further estimated by measuring the strength of theta oscillations at a forehead site on the scalp. Fourteen healthy adults ( Mage = 26.1 years) performed a passive listening (PL) task and an auditory digit span (DS) task, and electroencephalography (EEG) data were recorded simultaneously during the two tasks. Considering that the digit span paradigm has often been conducted in a non-laboratory location, the EEG data were collected with a wireless single-channel headset system. The headset system was validated in this study by replicating the EEG (an enhancement of frontal theta power) as well as event-related potential (N200 and P300) responses to the deviant tone stimuli in the PL task. The outcomes of the DS task showed that the memory span of the participants was at least eight items. Moreover, frontal theta power in response to a list of six to eight digits increased significantly. This pattern of results supports a hypothesis that additional mental effort is required for short-term retention of verbal items when the number of stimulus items exceeds the newly proposed limit of short-term memory capacity. Some strengths and limitations of the current EEG headset system are also discussed.

Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy

Schizophrenia is among the most debilitating neuropsychiatric disorders. However, clear neurophysiological markers that would identify at-risk individuals represent still an unknown. The aim of this study was to investigate possible alterations in the resting alpha oscillatory activity in normal population high on schizotypy trait, a physiological condition known to be severely altered in patients with schizophrenia. Direct comparison of resting-state EEG oscillatory activity between Low and High Schizotypy Group (LSG and HSG) has revealed a clear right hemisphere alteration in alpha activity of the HSG. Specifically, HSG shows a significant slowing down of right hemisphere posterior alpha frequency and an altered distribution of its amplitude, with a tendency towards a reduction in the right hemisphere in comparison to LSG. Furthermore, altered and reduced connectivity in the right fronto-parietal network within the alpha range was found in the HSG. Crucially, a trained pattern classifier based on these indices of alpha activity was able to successfully differentiate HSG from LSG on tested participants further confirming the specific importance of right hemispheric alpha activity and intrahemispheric functional connectivity. By combining alpha activity and connectivity measures with a machine learning predictive model optimized in a nested stratified cross-validation loop, current research offers a promising clinical tool able to identify individuals at-risk of developing psychosis (i.e., high schizotypy individuals).

Functional brain plasticity during L1 training on complex sentences: Changes in gamma-band oscillatory activity

The adult human brain remains plastic even after puberty. However, whether first language (L1) training in adults can alter the language network is yet largely unknown. Thus, we conducted a longitudinal training experiment on syntactically complex German sentence comprehension. Sentence complexity was varied by the depth of the center embedded relative clauses (i.e., single or double embedded). Comprehension was tested after each sentence with a question on the thematic role assignment. Thirty adult, native German speakers were recruited for 4 days of training. Magnetoencephalography (MEG) data were recorded and subjected to spectral power analysis covering the classical frequency bands (i.e., theta, alpha, beta, low gamma, and gamma). Normalized spectral power, time‐locked to the final closure of the relative clause, was subjected to a two‐factor analysis (“sentence complexity” and “training days”). Results showed that for the more complex sentences, the interaction of sentence complexity and training days was observed in Brodmann area 44 (BA 44) as a decrease of gamma power with training. Moreover, in the gamma band (55–95 Hz) functional connectivity between BA 44 and other brain regions such as the inferior frontal sulcus and the inferior parietal cortex were correlated with behavioral performance increase due to training. These results show that even for native speakers, complex L1 sentence training improves language performance and alters neural activities of the left hemispheric language network. Training strengthens the use of the dorsal processing stream with working‐memory‐related brain regions for syntactically complex sentences, thereby demonstrating the brain's functional plasticity for L1 training.

Common neural processes during action-stopping and infrequent stimulus detection: The frontocentral P3 as an index of generic motor inhibition

The stop-signal task (SST) is used to study action-stopping in the laboratory. In SSTs, the P3 event-related potential following stop-signals is considered to be a neural index of motor inhibition. However, a similar P3 deflection is often observed following infrequent events in non-inhibition tasks. Moreover, within SSTs, stop-signals are indeed infrequent events, presenting a systematic confound that hampers the interpretation of the stop-signal P3 (and other candidate neural indices of motor inhibition). Therefore, we performed two studies to test whether the stop-signal P3 is uniquely related to motor inhibition or reflects infrequency detection. In Study 1, participants completed the SST and a visually identical change-detection task requiring the detection of a task-relevant, frequent signal (but not motor inhibition). We observed a P3 associated with motor inhibition in the SST, but no such positivity in the change-detection task. In Study 2, we modified the change-detection task. Some task-relevant events were now infrequent, matching the frequency of stop-signals in the SST. These events indeed evoked a P3, though of smaller amplitude than the P3 in the SST. Independent component analysis suggested that stop-signal P3 and infrequency-P3 ERPs were non-independent and shared a common neural generator. Further analyses suggested that this common neural process likely reflects motor inhibition in both tasks: infrequent events in the change-detection task lead to a non-instructed, incidental slowing of motor responding, the degree of which was strongly correlated with P3 amplitude. These results have wide-reaching implications for the interpretation of neural signals in both stop-signal and infrequency/oddball-tasks.

A Simple and Effective Way to Study Executive Functions by Using 360° Videos

Executive dysfunctions constitute a significant public health problem due to their high impact on everyday life and personal independence. Therefore, the identification of early strategies to assess and rehabilitate these impairments appears to be a priority. The ecological limitations of traditional neuropsychological tests and the numerous difficulties in administering tests in real-life scenarios have led to the increasing use of virtual reality (VR) and 360° environment-based tools for assessing executive functions (EFs) in real life. This perspective aims at proposing the development and implementation of Executive-functions Innovative Tool 360° (EXIT 360°), an innovative, enjoyable, and ecologically valid tool for a multidimensional and multicomponent evaluation of executive dysfunctions. EXIT 360° allows a complete and integrated executive functioning assessment through an original task for EFs delivered via a mobile-powered VR headset combined with eye tracker (ET) and electroencephalograms (EEG). Our tool is born as a 360°-based instrument, easily accessible and clinically usable, that will radically transform clinicians’ and patient’s assessment experience. In EXIT 360°, patients are engaged in a “game for health,” where they must perform everyday subtasks in 360° daily life environments. In this way, the clinicians can obtain quickly more ecologically valid information about several aspects of EFs (e.g., planning, problem-solving). Moreover, the multimodal approach allows completing the assessment of EFs by integrating verbal responses, reaction times, and physiological data (eye movements and brain activation). Overall, EXIT 360° will allow obtaining simultaneously and in real time more information about executive dysfunction and its impact in real life, allowing clinicians to tailor the rehabilitation to the subject’s needs.

Midfrontal theta as moderator between beta oscillations and precision control

Control of movements using visual information is crucial for many daily activities, and such visuomotor control has been revealed to be supported by alpha and beta cortical oscillations. However, it has been remained to be unclear how midfrontal theta and occipital gamma oscillations, which are associated with high-level cognitive functions, would be involved in this process to facilitate performance. Here we addressed this fundamental open question in healthy young adults by measuring high-density cortical activity during a precision force-matching task. We manipulated the amount of error by changing visual feedback gain (low, medium, and high visual gains) and analyzed event-related spectral perturbations. Increasing the visual feedback gain resulted in a decrease in force error and variability. There was an increase in theta synchronization in the midfrontal area and also in beta desynchronization in the sensorimotor and posterior parietal areas with higher visual feedback gains. Gamma de/synchronization was not evident during the task. In addition, we found a moderation effect of midfrontal theta on the positive relationship between the beta oscillations and force error. Subsequent simple slope analysis indicated that the effect of beta oscillations on force error was weaker when midfrontal theta was high. Our findings suggest that the midfrontal area signals the increased need of cognitive control to refine behavior by modulating the visuomotor processing at theta frequencies.

#EEGManyLabs: Investigating the replicability of influential EEG experiments

There is growing awareness across the neuroscience community that the replicability of findings about the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardised analysis pipelines. Inspired by recent efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalography (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound influence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and selection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection. Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, high-powered multi-laboratory collaborations.

Data-Driven Classification of Spectral Profiles Reveals Brain Region-Specific Plasticity in Blindness

Congenital blindness has been shown to result in behavioral adaptation and neuronal reorganization, but the underlying neuronal mechanisms are largely unknown. Brain rhythms are characteristic for anatomically defined brain regions and provide a putative mechanistic link to cognitive processes. In a novel approach, using magnetoencephalography resting state data of congenitally blind and sighted humans, deprivation-related changes in spectral profiles were mapped to the cortex using clustering and classification procedures. Altered spectral profiles in visual areas suggest changes in visual alpha-gamma band inhibitory-excitatory circuits. Remarkably, spectral profiles were also altered in auditory and right frontal areas showing increased power in theta-to-beta frequency bands in blind compared with sighted individuals, possibly related to adaptive auditory and higher cognitive processing. Moreover, occipital alpha correlated with microstructural white matter properties extending bilaterally across posterior parts of the brain. We provide evidence that visual deprivation selectively modulates spectral profiles, possibly reflecting structural and functional adaptation.

A multi-modal modified feedback self-paced BCI to control the gait of an avatar

Brain-computer interfaces (BCI) have been used to control the gait of a virtual self-avatar with a proposed application in the field of gait rehabilitation.

OBJECTIVE

to develop a high performance multi-modal BCI to control single steps and forward walking of an immersive virtual reality avatar. This system will overcome the limitation of existing systems.

APPROACH

This system used MI of these actions, in cue-paced and self-paced modes. Twenty healthy participants participated in this 4 sessions study across 4 different days. They were cued to imagine a single step forward with their right or left foot, or to imagine walking forward. They were instructed to reach a target by using the MI of multiple steps (self-paced switch-control mode) or by maintaining MI of forward walking (continuous-control mode). The movement of the avatar was controlled by two calibrated RLDA classifiers that used the µ power spectral density (PSD) over the foot area of the motor cortex as a feature. The classifiers were retrained after every session. For a subset of the trials, positive modified feedback was presented to half of the participants.

MAIN RESULTS

All participants were able to operate the BCI. Their average offline performance, after retraining the classifiers was 86.0 ± 6.1%, showing that the recalibration of the classifiers enhanced the offline performance of the BCI (p < 0.01). The average online performance was 85.9 ± 8.4% showing that modified feedback enhanced BCI performance (p =0.001). The average performance was 83% at self-paced switch control and 92% at continuous control mode.

SIGNIFICANCE

This study reports on the first novel integration of different design approaches, different control modes and different performance enhancement techniques, all in parallel in one single high performance and multi-modal BCI system, to control single steps and forward walking of an immersive virtual reality avatar.

Inverse effects of time-on-task in task-related and task-unrelated theta activity

The phenomenon of mental fatigue has recently been investigated extensively by means of the EEG. Studies deploying spectral analysis consistently reported an increase of spectral power in the lower frequencies with increasing time-on-task, whereas event-related studies observed decreases in various measures related to task engagement and attentional resources. The results from these two lines of research cannot be aligned easily. (Frontal) theta power has been linked to cognitive control and was found to increase with time-on-task. In contrast, theoretical frameworks on mental fatigue suggest a decline in task-engagement as causal for the performance decline observed in mental fatigue. The goal of the present study was to investigate mental fatigue in time-frequency space using linear regression on single-trial data in order to obtain a better understanding about how time-on-task affects theta oscillatory activity. A data-driven analysis approach indicated an increase of alpha and theta power during the intertrial interval. In contrast, task-related theta activity declined. This reduction of stimulus-locked theta power may be interpreted as a reduction of task engagement with increasing mental fatigue. The increase of theta spectral power in the intertrial interval, moreover, could possibly be explained by an increased idling of cognitive control networks. Alternatively, it might be the case that the increase of theta power with time-on-task is a by-product an alpha power increase. As alpha peak frequency systematically decreases with time-on-task, the theta band might be affected as well.

Theta Oscillations and Source Connectivity During Complex Audiovisual Object Encoding in Working Memory

Working memory is a limited capacity memory system that involves the short-term storage and processing of information. Neuroscientific studies of working memory have mostly focused on the essential roles of neural oscillations during item encoding from single sensory modalities (e.g., visual and auditory). However, the characteristics of neural oscillations during multisensory encoding in working memory are rarely studied. Our study investigated the oscillation characteristics of neural signals in scalp electrodes and mapped functional brain connectivity while participants encoded complex audiovisual objects in a working memory task. Experimental results showed that theta oscillations (4–8 Hz) were prominent and topographically distributed across multiple cortical regions, including prefrontal (e.g., superior frontal gyrus), parietal (e.g., precuneus), temporal (e.g., inferior temporal gyrus), and occipital (e.g., cuneus) cortices. Furthermore, neural connectivity at the theta oscillation frequency was significant in these cortical regions during audiovisual object encoding compared with single modality object encoding. These results suggest that local oscillations and interregional connectivity via theta activity play an important role during audiovisual object encoding and may contribute to the formation of working memory traces from multisensory items.

An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States

Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4-7 Hz, alpha: 8-13 Hz, low beta: 14-20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments.

EEG in motion: Using an oddball task to explore motor interference in active skateboarding

Recent advancements in portable computer devices have opened new avenues in the study of human cognition outside research laboratories. This flexibility in methodology has led to the publication of several electroencephalography studies recording brain responses in real-world scenarios such as cycling and walking outside. In the present study, we tested the classic auditory oddball task while participants moved around an indoor running track using an electric skateboard. This novel approach allows for the study of attention in motion while virtually removing body movement. Using the skateboard auditory oddball paradigm, we found reliable and expected standard-target differences in the P3 and MMN/N2b event-related potentials. We also recorded baseline electroencephalography activity and found that, compared to this baseline, alpha power is attenuated in frontal and parietal regions during skateboarding. In order to explore the influence of motor interference in cognitive resources during skateboarding, we compared participants' preferred riding stance (baseline level of riding difficulty) versus their non-preferred stance (increased level of riding difficulty). We found that an increase in riding difficulty did not modulate the P3 and tonic alpha amplitude during skateboard motion. These results suggest that increases in motor demands might not lead to reductions in cognitive resources as shown in previous literature.

Neural oscillations track the maintenance and proceduralization of novel instructions

Humans are capable of flexibly converting symbolic instructions into novel behaviors. Previous evidence and theoretical models suggest that the implementation of a novel instruction requires the reformatting of its declarative content into an action-oriented code optimized for the execution of the instructed behavior. While neuroimaging research focused on identifying the brain areas involved in such a process, the temporal and electrophysiological mechanisms remain poorly understood. These mechanisms, however, can provide information about the specific cognitive processes that characterize the proceduralization of information. In the present study, we recorded EEG activity while we asked participants to either simply maintain declaratively the content of novel S-R mappings or to proactively prepare for their implementation. By means of time-frequency analyses, we isolated the oscillatory features specific to the proceduralization of instructions. Implementation of the instructed mappings elicited stronger theta activity over frontal electrodes and suppression in mu and beta activity over central electrodes. On the contrary, activity in the alpha band, which has been shown to track the attentional deployment to task-relevant items, showed no differences between tasks. Together, these results support the idea that proceduralization of information is characterized by specific component processes such as orchestrating complex task settings and configuring the motor system that are not observed when instructions are held in a declarative format.

Frontoparietal Beta Amplitude Modulation and its Interareal Cross-frequency Coupling in Visual Working Memory

Visual working memory (VWM) relies on sustained neural activities that code information via various oscillatory frequencies. Previous studies, however, have emphasized time-frequency power changes, while overlooking the possibility that rhythmic amplitude variations can also code frequency-specific VWM information in a completely different dimension. Here, we employed the recently-developed Holo-Hilbert spectral analysis to characterize such nonlinear amplitude modulation(s) (AM) underlying VWM in the frontoparietal systems. We found that the strength of AM in mid-frontal beta and gamma oscillations during late VWM maintenance and VWM retrieval correlated with people's VWM performance. When behavioral performance was altered with transcranial electric stimulation, AM power changes during late VWM maintenance in beta, but not gamma, tracked participants' VWM variations. This beta AM likely codes information by varying its amplitude in theta period for long-range propagation, as our connectivity analysis revealed that interareal theta-beta couplings-bidirectional between mid-frontal and right-parietal during VWM maintenance and unidirectional from right-parietal to left-middle-occipital during late VWM maintenance and retrieval-underpins VWM performance and individual differences.

Allergic rhinitis impairs working memory in association with drop of hippocampal - Prefrontal coupling

Allergic rhinitis (AR) is a chronic inflammatory disease frequently associated with a deficit in learning and memory. Working memory is an important system for decision making and guidance, which depends on interactions between the ventral hippocampus (vHipp) and the prelimbic prefrontal cortex (plPFC). It is still unclear whether AR influences the activity and coupling of these brain areas, which consequently may impair working memory. The current study aimed to examine alterations of the vHipp-plPFC circuit in a rat model of AR. Our results show decreased working memory performance in AR animals, accompanied by a reduction of theta and gamma oscillations in plPFC. Also, AR reduces coherence between vHipp and plPFC in both theta and gamma frequency bands. Cross-frequency coupling analyses confirmed a reduced interaction between hippocampal theta and plPFC gamma oscillations. Granger causality analysis revealed a reduction in the causal effects of vHipp activity on plPFC oscillations and vice versa. A significant correlation was found between working memory performance with disruption of functional connectivity in AR animals. In summary, our data show that in AR, there is a deficit of functional coupling between hippocampal and prefrontal network, and suggest that this mechanism might contribute to working memory impairment in individuals with AR.

Retrosplenial Segregation Reflects the Navigation Load During Ambulatory Movement

Spatial navigation is a complex cognitive process based on vestibular, proprioceptive, and visualcues that are integrated and processed by an extensive network of brain areas. The retrosplenial complex (RSC) is an integral part of coordination and translation between spatial reference frames. Previous studies have demonstrated that the RSC is active during a spatial navigation tasks. The specifics of RSC activity under various navigation loads, however, are still not characterized. This study investigated the local information processed by the RSC under various navigation load conditions manipulated by the number of turns in the physical navigation setup. The results showed that the local information processed via the RSC, which was reflected by the segregation network, was higher when the number of turns increased, suggesting that RSC activity is associated with the navigation task load. The present findings shed light on how the brain processes spatial information in a physical navigation task.

Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques

Brain age prediction studies aim at reliably estimating the difference between the chronological age of an individual and their predicted age based on neuroimaging data, which has been proposed as an informative measure of disease and cognitive decline. As most previous studies relied exclusively on magnetic resonance imaging (MRI) data, we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves age prediction using a large cohort of healthy subjects (N = 613, age 18-88 years) from the Cam-CAN repository. To this end, we examined the performance of dimensionality reduction and multivariate associative techniques, namely Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), to tackle the high dimensionality of neuroimaging data. Using MEG features (mean absolute error (MAE) of 9.60 years) yielded worse performance when compared to using MRI features (MAE of 5.33 years), but a stacking model combining both feature sets improved age prediction performance (MAE of 4.88 years). Furthermore, we found that PCA resulted in inferior performance, whereas CCA in conjunction with Gaussian process regression models yielded the best prediction performance. Notably, CCA allowed us to visualize the features that significantly contributed to brain age prediction. We found that MRI features from subcortical structures were more reliable age predictors than cortical features, and that spectral MEG measures were more reliable than connectivity metrics. Our results provide an insight into the underlying processes that are reflective of brain aging, yielding promise for the identification of reliable biomarkers of neurodegenerative diseases that emerge later during the lifespan.

Inter-brain synchronization during a cooperative task reflects the sense of joint agency

People feel the sense of 'joint agency', which is the sense that 'we' did it, during a mutually cooperative action. Previous studies have reported that the inter-brain synchronization occurs during a mutually cooperative action, nevertheless the neural correlates of the sense of joint agency remains unclear. Here, we investigated whether the sense of joint agency reflects the inter-brain synchronization during a joint action. The pairs of participants engaged in constant rhythm tapping tasks with alternative (turn-taking) or sequential (non-turn-taking) coordination. Electroencephalograms (EEGs) of the participant pair during the tasks were simultaneously measured (hyperscanned), and the participants were subsequently asked to rate the sense of joint agency. The results showed that the participants felt strong sense of joint agency in the turn-taking cooperative actions, but not in the non-turn-taking actions. Moreover, EEG theta (4-7 Hz) oscillations were more synchronized between the frontal region in the leader, who tapped the first, and the right temporo-parietal region in the follower, who tapped following the leader, during the turn-taking cooperative actions than during the non-turn-taking cooperative actions. Furthermore, the degree of inter-brain synchronization was significantly correlated with the sense of joint agency, as well as the temporal accuracy of the tapping actions of the pair. These results indicate that the sense of joint agency strongly reflects the inter-brain synchronization, which depends on the quality of mutual cooperation during a joint action.

Virtual reality alters cortical oscillations related to visuo-tactile integration during rubber hand illusion

Virtual reality (VR) enables the fast, free, and highly controllable setting of experimental body images. Illusions pertaining to a body, such as the rubber hand illusion (RHI), can be easily conducted in VR settings, and some phenomena, such as full-body illusions, are only realized in virtual environments. However, the multisensory-integration process in VR is not yet fully understood. Thus, it remains to be clarified if specific phenomena that occur under VR settings manifest in real life as well. One useful investigative approach is measuring brain activities during a psychological experiment. Electroencephalography (EEG) oscillatory activities provide insight into the human multisensory integration process. Nevertheless, EEG data can be vulnerable to VR noise, which causes measurement and analytical difficulties for EEG data recorded in VR environments. Here, we achieve an experimental RHI setting using a head-mounted display that provides a VR visual space and VR dummy hand along with EEG measurements. We compared EEG data collected in both real and VR environments and observed the gamma and theta band oscillatory activities. Ultimately, we observed statistically significant differences between congruent (RHI) and incongruent (not RHI) conditions in the real environment, which is consistent with previous studies. Differences in the VR condition were observed only on the late theta band oscillation, suggesting that the VR setting itself altered the perceptual and sensory integration mechanisms. Thus, we must model this difference between real and VR settings whenever we use VR to investigate our bodily self-perception.

The open EEGLAB portal Interface: High-Performance computing with EEGLAB

EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety of neuroscience-related software on high-performance computing (HPC) resources in the U.S. XSEDE network. We have reported recently (Delorme et al., 2019) on the Open EEGLAB Portal expansion of the free NSG services to allow the neuroscience community to build and run MATLAB pipelines using the EEGLAB tool environment. We are now releasing an EEGLAB plug-in, nsgportal, that interfaces EEGLAB with NSG directly from within EEGLAB running on MATLAB on any personal lab computer. The plug-in features a flexible MATLAB graphical user interface (GUI) that allows users to easily submit, interact with, and manage NSG jobs, and to retrieve and examine their results. Command line nsgportal tools supporting these GUI functionalities allow EEGLAB users and plug-in tool developers to build largely automated functions and workflows that include optional NSG job submission and processing. Here we present details on nsgportal implementation and documentation, provide user tutorials on example applications, and show sample test results comparing computation times using HPC versus laptop processing.

Narrowband multivariate source separation for semi-blind discovery of experiment contrasts

BACKGROUND

Electrophysiological recordings contain mixtures of signals from distinct neural sources, impeding a straightforward interpretation of the sensor-level data. This mixing is particularly detrimental when distinct sources resonate in overlapping frequencies. Fortunately, the mixing is linear and instantaneous. Multivariate source separation methods may therefore successfully separate statistical sources, even with overlapping spatial distributions.

NEW METHOD

We demonstrate a feature-guided multivariate source separation method that is tuned to narrowband frequency content as well as binary condition differences. This method - comparison scanning generalized eigendecomposition, csGED - harnesses the covariance structure of multichannel data to find directions (i.e., eigenvectors) that maximally separate two subsets of data. To drive condition specificity and frequency specificity, our data subsets were taken from different task conditions and narrowband-filtered prior to applying GED.

RESULTS

To validate the method, we simulated MEG data in two conditions with shared noise characteristics and unique signal. csGED outperformed the best sensor at reconstructing the ground truth signals, even in the presence of large amounts of noise. We next applied csGED to a published empirical MEG dataset on visual perception vs. imagery. csGED identified sources in alpha, beta, and gamma bands, and successfully separated distinct networks in the same frequency band.

COMPARISON WITH EXISTING METHOD(S)

GED is a flexible feature-guided decomposition method that has previously successfully been applied. Our combined frequency- and condition-tuning is a novel adaptation that extends the power of GED in cognitive electrophysiology.

CONCLUSIONS

We demonstrate successful condition-specific source separation by applying csGED to simulated and empirical data.

What Can Neuromarketing Tell Us about Food Packaging?

Packaging is a powerful tool for brands, which can not only catch consumers' attention but also influence their purchase decisions. The application of neuromarketing techniques to the study of food packaging has recently gained considerable popularity both in academia and practice, but there are still some concerns about the methods and metrics commercially offered and the interpretation of their findings. This represents the motivation of this investigation, whose objective is twofold: (1) to analyze the methodologies and measurements commonly used in neuromarketing commercial research on packaging, and (2) to examine the extent to which the results of food packaging studies applying neuromarketing techniques can be reproduced under similar methodologies. Obtained results shed light on the application of neuromarketing techniques in the evaluation of food packaging and reveal that neuromarketing and declarative methodologies are complementary, and its combination may strengthen the studies' results. Additionally, this study highlights the importance of having a framework that improves the validity and reliability of neuromarketing studies to eradicate mistrust toward the discipline and provide brands with valuable insights into food packing design.

Working Memory Decline in Alzheimer's Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS

Alzheimer's disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey-Osterrieth complex figure and Raven's progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.

Oscillatory brain activity and maintenance of verbal and visual working memory: A systematic review

Brain oscillations likely play a significant role in the storage of information in working memory (WM). Despite the wide popularity of the topic, current attempts to summarize the research in the field are narrative reviews. We address this gap by providing a descriptive systematic review, in which we investigated oscillatory correlates of maintenance of verbal and visual information in WM. The systematic approach enabled us to challenge some common views popularized by previous research. The identified literature (100 EEG/MEG studies) highlighted the importance of theta oscillations in verbal WM: frontal midline theta enhanced with load in most verbal studies, while more equivocal results have been obtained in visual studies. Increasing WM load affected alpha activity in most studies, but the direction of the effect was inconsistent: the ratio of studies that found alpha increase versus decrease with increasing load was 80/20% in the verbal WM domain and close to 60/40% in the visual domain. Alpha asymmetry (left < right) was a common finding in both verbal and visual WM studies. Beta and gamma activity studies yielded the least convincing data: a diversity in the spatial and frequency distribution of beta activity prevented us from making a coherent conclusion; gamma rhythm was virtually neglected in verbal WM studies with no systematic support for sustained gamma changes during the delay in EEG studies in general.

Boosting working memory with accelerated clocks

Our perception of time varies with the degree of cognitive engagement in tasks. The perceived passage of time accelerates while working on demanding tasks, whereas time appears to drag during boring situations. Our experiment aimed at investigating whether this relationship is mutual: Can manipulated announcements of elapsed time systematically affect the attentional resources applied to a cognitive task? We measured behavioral performance and the EEG in a whole report working memory paradigm with six items of different colors that each had to be reported after a short delay period. The 32 participants were informed about the current time after each 20 trials, while the clock was running at either 100% (normal), 120% (fast), or 80% (slow) of normal clock speed depending on the experimental block. The mean number of correctly reported colors per trial was significantly increased in the fast as compared to the slow and normal clock conditions. In the EEG, we focused on neural oscillations during working memory encoding and storage. As an electrophysiological correlate of task engagement, frontal theta power during the storage interval was increased in the fast clock condition. Also, the power of frontal theta oscillations predicted the number of correctly reported colors on a single-trial basis. This shows that a covert manipulation of clock speed can lead to an improvement in cognitive performance, presumably mediated by a higher allocation of attentional resources resulting from an adaptation of the subjective passage of time during an experiment.

Cerebral Cortical Activity Following Non-invasive Cerebellar Stimulation-a Systematic Review of Combined TMS and EEG Studies

The cerebellum sends dense projections to both motor and non-motor regions of the cerebral cortex via the cerebellarthalamocortical tract. The integrity of this tract is crucial for healthy motor and cognitive function. This systematic review examines research using transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) to the cerebellum with combined cortical electroencephalography (EEG) to explore the temporal features of cerebellar-cortical connectivity. A detailed discussion of the outcomes and limitations of the studies meeting review criteria is presented. Databases were searched between 1 December 2017 and 6 December 2017, with Scopus alerts current as of 23 July 2019. Of the 407 studies initially identified, 10 met review criteria. Findings suggested that cerebellar-cortical assessment is suited to combined TMS and EEG, although work is required to ensure experimental procedures are optimal for eliciting a reliable cerebellar response from stimulation. A distinct variation in methodologies and outcome measures employed across studies, and small sample sizes limited the conclusions that could be drawn regarding the electrophysiological signatures of cerebellar-cortical communication. This review highlights the need for stringent protocols and methodologies for cerebellar-cortical assessments via combined TMS and EEG. With these in place, combined TMS and EEG will provide a valuable means for exploring cerebellar connectivity with a wide range of cortical sites. Assessments have the potential to aid in the understanding of motor and cognitive function in both healthy and clinical groups, and provide insights into long-range neural communication generally.

Buildup and release from proactive interference - Cognitive and neural mechanisms

Interference from related memories is generally considered one of the major causes of forgetting in human memory. The most prevalent form of interference may be proactive interference (PI), which refers to the finding that memory of more recently studied information can be impaired by the previous study of other information. PI is a fairly persistent effect, but numerous studies have shown that there can also be release from PI. PI buildup and release have primarily been studied using paired-associate learning, the Brown-Peterson task, or multiple-list learning. The review first introduces the three experimental tasks and, for each task, summarizes critical findings on PI buildup and release, from both behavioral and imaging work. Then, an overview is provided of suggested cognitive mechanisms operating on the encoding and retrieval stages as well as of neural correlates of these mechanisms. The results indicate that, in general, both encoding and retrieval processes contribute to PI buildup and release. Finally, empirical gaps in the current work are emphasized and suggestions for future studies are provided.

Theta activity from frontopolar cortex, mid-cingulate cortex and anterior cingulate cortex shows different roles in cognitive planning performance

Cognitive planning, the ability to develop a sequenced plan to achieve a goal, plays a crucial role in human goal-directed behavior. However, the specific role of frontal structures in planning is unclear. We used a novel and ecological task, that allowed us to separate the planning period from the execution period. The spatio-temporal dynamics of EEG recordings showed that planning induced a progressive and sustained increase of frontal-midline theta activity (FMθ) over time. Source analyses indicated that this activity was generated within the prefrontal cortex. Theta activity from the right mid-Cingulate Cortex (MCC) and the left Anterior Cingulate Cortex (ACC) were correlated with an increase in the time needed for elaborating plans. On the other hand, left Frontopolar cortex (FP) theta activity exhibited a negative correlation with the time required for executing a plan. Since reaction times of planning execution correlated with correct responses, left FP theta activity might be associated with efficiency and accuracy in making a plan. Associations between theta activity from the right MCC and the left ACC with reaction times of the planning period may reflect high cognitive demand of the task, due to the engagement of attentional control and conflict monitoring implementation. In turn, the specific association between left FP theta activity and planning performance may reflect the participation of this brain region in successfully self-generated plans.

Resting EEG theta connectivity and alpha power to predict repetitive transcranial magnetic stimulation response in depression: A non-replication from the ICON-DB consortium

OBJECTIVE

Our previous research showed high predictive accuracy at differentiating responders from non-responders to repetitive transcranial magnetic stimulation (rTMS) for depression using resting electroencephalography (EEG) and clinical data from baseline and one-week following treatment onset using a machine learning algorithm. In particular, theta (4-8 Hz) connectivity and alpha power (8-13 Hz) significantly differed between responders and non-responders. Independent replication is a necessary step before the application of potential predictors in clinical practice. This study attempted to replicate the results in an independent dataset.

METHODS

We submitted baseline resting EEG data from an independent sample of participants who underwent rTMS treatment for depression (N = 193, 128 responders) (Krepel et al., 2018) to the same between group comparisons as our previous research (Bailey et al., 2019).

RESULTS

Our previous results were not replicated, with no difference between responders and non-responders in theta connectivity (p = 0.250, Cohen's d = 0.1786) nor alpha power (p = 0.357, η_p² = 0.005).

CONCLUSIONS

These results suggest that baseline resting EEG theta connectivity or alpha power are unlikely to be generalisable predictors of response to rTMS treatment for depression.

SIGNIFICANCE

These results highlight the importance of independent replication, data sharing and using large datasets in the prediction of response research.