A new interpretation of P300 responses upon analysis of coherences

DSE-Mixer: A pure multilayer perceptron network for emotion recognition from EEG feature maps

BACKGROUND

Decoding emotions from brain maps is a challenging task. Convolutional Neural Network (CNN) is commonly used for EEG feature map. However, due to its local bias, CNN is unable to efficiently utilize the global spatial information of EEG signals which limits the accuracy of emotion recognition.

NEW METHODS

We design the Dual-scal EEG-Mixer(DSE-Mixer) model for EEG feature map processing. Its brain region mixer layer and electrode mixer layer are designed to fuse EEG information at different spatial scales. For each mixer layer, the structure of alternating mixing of rows and columns of the input table enables cross-regional and cross-Mchannel communication of EEG information. In addition, a channel attention mechanism is introduced to adaptively learn the importance of each channel.

RESULTS

On the DEAP dataset, the DSE-Mixer model achieved a binary classification accuracy of 95.19% for arousal and 95.22% for valence. For the four-class classification across valence and arousal, the accuracies were HVHA: 92.12%, HVLA: 89.77%, LVLA: 93.35%, and LVHA: 92.63%. On the SEED dataset, the average recognition accuracy for the three emotions (positive, negative, and neutral) is 93.69%.

COMPARISON WITH EXISTING METHODS

In the emotion recognition research based on the DEAP and SEED datasets, DSE-Mixer achieved a high ranking performance. Compared to the two commonly used model in computer vision field, CNN and Vision Transformer(VIT), DSE-Mixer achieved significantly higher classification accuracy while requiring much less computational complexity.

CONCLUSIONS

DSE-Mixer provides a novel brain map processing model with a small size, demonstrating outstanding performance in emotion recognition.

Age-related changes in the interference between cognitive task components and concurrent sensorimotor coordination

Continuous sensorimotor coordinations (CSCs) such as driving, walking, using control interfaces or maintaining the body's balance are often performed alongside concurrent cognitive tasks involving attention and executive function. A range of these task combinations show interference, particularly in older adults, but the timing, direction and reciprocity of interference is not yet understood at the level of the tasks' information-processing operations. This paper compares the chronometry of dual task interference between a visual oddball task and a continuous visuomanual tracking task performed by young and older adults. The oddball task's constituent operations were identified using electrophysiological correlates, and deviations in the tracking task reflected perturbations to state monitoring and adjustment characteristics of CSC tasks. Despite instructions to give equal priority to both tasks, older participants maintained a high level of resourcing of the oddball task when dual tasking whereas young participants reduced resourcing to accommodate the demands of the tracking task. Older participants had a longer period of tracking inaccuracy during the executive function component of the oddball task, and unlike in young participants, this decrement was also observed when the stimulus was not a target and the executive function of updating the target tally was not required. These detailed chronometric results clarify that age-related amplification of CSC-cognitive interference are largely due to greater inflexibility in task prioritization. Prioritization of the cognitive task over the CSC in this type of dual tasking may have safety implications in everyday task settings.

Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

Alzheimer's disease dementia (ADD) is the most diffuse neurodegenerative disorder belonging to mild cognitive impairment (MCI) and dementia in old persons. This disease is provoked by an abnormal accumulation of amyloid-beta and tauopathy proteins in the brain. Very recently, the first disease-modifying drug has been licensed with reserve (i.e., Aducanumab). Therefore, there is a need to identify and use biomarkers probing the neurophysiological underpinnings of human cognitive functions to test the clinical efficacy of that drug. In this regard, event-related electroencephalographic potentials (ERPs) and oscillations (EROs) are promising candidates. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association and Global Brain Consortium reviewed the field literature on the effects of the most used symptomatic drug against ADD (i.e., Acetylcholinesterase inhibitors) on ERPs and EROs in ADD patients with MCI and dementia at the group level. The most convincing results were found in ADD patients. In those patients, Acetylcholinesterase inhibitors partially normalized ERP P300 peak latency and amplitude in oddball paradigms using visual stimuli. In these same paradigms, those drugs partially normalize ERO phase-locking at the theta band (4-7 Hz) and spectral coherence between electrode pairs at the gamma (around 40 Hz) band. These results are of great interest and may motivate multicentric, double-blind, randomized, and placebo-controlled clinical trials in MCI and ADD patients for final cross-validation.

Understanding brain function in vascular cognitive impairment and dementia with EEG and MEG: A systematic review

Vascular Cognitive Impairment (VCI) is the second most prevalent dementia after Alzheimer's Disease (AD), and cerebrovascular disease (CBVD) is a major comorbid contributor to the progression of most neurodegenerative diseases. Early differentiation of cognitive impairment is critical given both the high prevalence of CBVD, and that its risk factors are modifiable. The ability for electroencephalogram (EEG) and magnetoencephalogram (MEG) to detect changes in brain functioning for other dementias suggests that they may also be promising biomarkers for early VCI. The present systematic review aims to summarize the literature regarding electrophysiological patterns of mild and major VCI. Despite considerable heterogeneity in clinical definition and electrophysiological methodology, common patterns exist when comparing patients with VCI to healthy controls (HC) and patients with AD, though there is a low specificity when comparing between VCI subgroups. Similar to other dementias, slowed frequency patterns and disrupted inter- and intra-hemispheric connectivity are repeatedly reported for VCI patients, as well as longer latencies and smaller amplitudes in evoked responses. Further study is needed to fully establish MEG and EEG as clinically useful biomarkers, including a clear definition of VCI and standardized methodology, allowing for comparison across groups and consolidation of multicenter efforts.

Early soft and flexible fusion of electroencephalography and functional magnetic resonance imaging via double coupled matrix tensor factorization for multisubject group analysis

Data fusion refers to the joint analysis of multiple datasets that provide different (e.g., complementary) views of the same task. In general, it can extract more information than separate analyses can. Jointly analyzing electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) measurements has been proved to be highly beneficial to the study of the brain function, mainly because these neuroimaging modalities have complementary spatiotemporal resolution: EEG offers good temporal resolution while fMRI is better in its spatial resolution. The EEG–fMRI fusion methods that have been reported so far ignore the underlying multiway nature of the data in at least one of the modalities and/or rely on very strong assumptions concerning the relation of the respective datasets. For example, in multisubject analysis, it is commonly assumed that the hemodynamic response function is a priori known for all subjects and/or the coupling across corresponding modes is assumed to be exact (hard). In this article, these two limitations are overcome by adopting tensor models for both modalities and by following soft and flexible coupling approaches to implement the multimodal fusion. The obtained results are compared against those of parallel independent component analysis and hard coupling alternatives, with both synthetic and real data (epilepsy and visual oddball paradigm). Our results demonstrate the clear advantage of using soft and flexible coupled tensor decompositions in scenarios that do not conform with the hard coupling assumption.

Modulation of the cognitive event-related potential P3 by transcranial direct current stimulation: Systematic review and meta-analysis

Transcranial direct current stimulation (tDCS) has been widely used to modulate cognition and behavior. However, only a few studies have been probing the brain mechanism underlying the effects of tDCS on cognitive processing, especially throughout electrophysiological markers, such as the P3. This meta-analysis assessed the effects of tDCS in P3 amplitude and latency during an oddball, n-back, and Go/No-Go tasks, as well as during emotional processing. A total of 36 studies were identified, but only 23 were included in the quantitative analysis. The results show that the parietal P3 amplitude increased during oddball and n-back tasks, mostly after anodal stimulation over the left dorsolateral prefrontal cortex (p = 0.018, SMD = 0.4) and right inferior frontal gyrus (p < 0.001, SMD = 0.669) respectively. These findings suggest the potential usefulness of the parietal P3 ERP as a marker of tDCS-induced effects during task performance. Nonetheless, this study had a low number of studies and the presence of considerable risk of bias, highlighting issues to be addressed in the future.

Dynamic relationships between spontaneous and evoked electrophysiological activity

Spontaneous neural activity fluctuations have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioral outcomes. However, the complex electrophysiological mechanisms by which these fluctuations shape stimulus-evoked neural activity remain largely to be explored. Employing a large-scale magnetoencephalographic dataset and an electroencephalographic replication dataset, we investigate the relationship between spontaneous and evoked neural activity across a range of electrophysiological variables. We observe that for high-frequency activity, high pre-stimulus amplitudes lead to greater evoked desynchronization, while for low frequencies, high pre-stimulus amplitudes induce larger degrees of event-related synchronization. We further decompose electrophysiological power into oscillatory and scale-free components, demonstrating different patterns of spontaneous-evoked correlation for each component. Finally, we find correlations between spontaneous and evoked time-domain electrophysiological signals. Overall, we demonstrate that the dynamics of multiple electrophysiological variables exhibit distinct relationships between their spontaneous and evoked activity, a result which carries implications for experimental design and analysis in non-invasive electrophysiology.

Using Muse: Rapid Mobile Assessment of Brain Performance

The advent of mobile electroencephalography (mEEG) has created a means for large scale collection of neural data thus affording a deeper insight into cognitive phenomena such as cognitive fatigue. Cognitive fatigue - a neural state that is associated with an increased incidence of errorful performance - is responsible for accidents on a daily basis which at times can cost human lives. To gain better insight into the neural signature of cognitive fatigue in the present study we used mEEG to examine the relationship between perceived cognitive fatigue and human-event related brain potentials (ERPs) and electroencephalographic (EEG) oscillations in a sample of 1,000 people. As a secondary goal, we wanted to further demonstrate the capability of mEEG to accurately measure ERP and EEG data. To accomplish these goals, participants performed a standard visual oddball task on an Apple iPad while EEG data were recorded from a Muse EEG headband. Counter to traditional EEG studies, experimental setup and data collection was completed in less than seven minutes on average. An analysis of our EEG data revealed robust N200 and P300 ERP components and neural oscillations in the delta, theta, alpha, and beta bands. In line with previous findings we observed correlations between ERP components and EEG power and perceived cognitive fatigue. Further, we demonstrate here that a linear combination of ERP and EEG features is a significantly better predictor of perceived cognitive fatigue than any ERP or EEG feature on its own. In sum, our results provide validation of mEEG as a viable tool for research and provide further insight into the impact of cognitive fatigue on the human brain.

Riemann-Based Algorithms Assessment for Single- and Multiple-Trial P300 Classification in Non-Optimal Environments

The P300 wave is commonly used in Brain-Computer Interface technology due to its higher bit rates when compared to other BCI paradigms. P300 classification pipelines based on Riemannian Geometry provide accuracies on par with state-of-the-art pipelines, without having the need for spatial filters, and also possess the ability to be calibrated with little data. In this study, five different P300 detection pipelines are compared, with three of them using Riemannian Geometry as either feature extraction or classification algorithms. The goal of this study is to assess the viability of Riemannian Geometry-based methods in non-optimal environments with sudden background noise changes, rather than maximizing classification accuracy values. For fifteen subjects, the average single-trial accuracy obtained for each pipeline was: 56.06% for Linear Discriminant Analysis (LDA), 72.13% for Bayesian Linear Discriminant Analysis (BLDA), 63.56% for Riemannian Minimum Distance to Mean (MDM), 69.22% for Riemannian Tangent Space with Logistic Regression (TS-LogR), and 63.30% for Riemannian Tangent Space with Support Vector Machine (TS-SVM). The results are higher for the pipelines based on BLDA and TS-LogR, suggesting that they could be viable methods for the detection of the P300 component when maximizing the bit rate is needed. For multiple-trial classification, the BLDA pipeline converged faster towards higher average values, closely followed by the TS-LogR pipeline. The two remaining Riemannian methods' accuracy also increases with the number of trials, but towards a lower value compared to the aforementioned ones. Single-stimulus detection metrics revealed that the TS-LogR pipeline can be a viable classification method, as its results are only slightly lower than those obtained with BLDA. P300 waveforms were also analyzed to check for evidence of the component being elicited. Finally, a questionnaire was used to retrieve the most intuitive focusing methods employed by the subjects.

Fast fronto-parietal cortical dynamics of conflict detection and context updating in a flanker task

Recent research has found that the traditional target P3 consists of a family of P3-like positivities that can be functionally and topographically dissociated from one another. The current study examined target N2 and P3-like subcomponents indexing conflict detection and context updating at low- and high-order levels in the neural hierarchy during cognitive control. Electroencephalographic signals were recorded from 45 young adults while they completed a hybrid go/nogo flanker task, and Residue Iteration Decomposition (RIDE) was applied to functionally dissociate these peaks. Analyses showed a stimulus-locked frontal N2 revealing early detection and fast perceptual categorization of nogo, congruent and incongruent trials, resulting in frontal P3-like activity elicited by nogo trials in the latency-variable RIDE cluster, and by incongruent trials in the response-locked cluster. The congruent trials did not elicit frontal P3-like activity. These findings suggest that behavioral incongruency effects are related to intermediate and later stages of motor response re-programming.

Non-stationary Group-Level Connectivity Analysis for Enhanced Interpretability of Oddball Tasks

Neural responses of oddball tasks can be used as a physiological biomarker to evaluate the brain potential of information processing under the assumption that the differential contribution of deviant stimuli can be assessed accurately. Nevertheless, the non-stationarity of neural activity causes the brain networks to fluctuate hugely in time, deteriorating the estimation of pairwise synergies. To deal with the time variability of neural responses, we have developed a piecewise multi-subject analysis that is applied over a set of time intervals within the stationary assumption holds. To segment the whole stimulus-locked epoch into multiple temporal windows, we experimented with two approaches for piecewise segmentation of EEG recordings: a fixed time-window, at which the estimates of FC measures fulfill a given confidence level, and variable time-window, which is segmented at the change points of the time-varying classifier performance. Employing the weighted Phase Lock Index as a functional connectivity metric, we have presented the validation in a real-world EEG data, proving the effectiveness of variable time segmentation for connectivity extraction when combined with a supervised thresholding approach. Consequently, we performed a piecewise group-level analysis of electroencephalographic data that deals with non-stationary functional connectivity measures, evaluating more carefully the contribution of a link node-set in discriminating between the labeled oddball responses.

Effect of brightness of visual stimuli on EEG signals

The aim of this study was to examine brightness effect, which is the perceptual property of visual stimuli, on brain responses obtained during visual processing of these stimuli. For this purpose, brain responses of the brain to changes in brightness were explored comparatively using different emotional images (pleasant, unpleasant and neutral) with different luminance levels. In the study, electroencephalography recordings from 12 different electrode sites of 31 healthy participants were used. The power spectra obtained from the analysis of the recordings using short time Fourier transform were analyzed, and a statistical analysis was performed on features extracted from these power spectra. Statistical findings were compared with those obtained from behavioral data. The results showed that the brightness of visual stimuli affected the power of brain responses depending on frequency, time and location. According to the statistically verified findings, the increase in the brightness of pleasant and neutral images increased the average power of responses in the parietal and occipital regions whereas the increase in the brightness of unpleasant images decreased the average power of responses in these regions. Moreover, the statistical results obtained for unpleasant images were found to be in accordance with the behavioral data. The results revealed that the brightness of visual stimuli could be represented by changing the activity power of the brain cortex. The findings emphasized that the brightness of visual stimuli should be viewed as an important parameter in studies using emotional image techniques such as image classification, emotion evaluation and neuro-marketing.

Search asymmetry in a serial auditory task: Neural source analyses of EEG implicate attention strategies

Here we report a detailed analysis of the fast network dynamics underlying P3a and P3b event-related potential (ERP) subcomponents generated during an unconventional serial auditory search paradigm. We dissect the electroencephalographic (EEG) data from an earlier study of ours, using a variety of advanced signal processing techniques, in order to discover how the brain is processing auditory targets differently when they possess a rare, salient, unpredictable feature not shared with distractors than when targets lack this feature but distractors have it. We find that brain regions associated with the Ventral Attention Network (VAN) are the primary neural generators of the P3a subcomponent in response to feature-present targets, whereas regions associated with the Dorsal Attention Network (DAN), as well as regions associated with detecting auditory oddball stimuli (ODD), may be the primary neural generators of the P3b, in the context of our study, and perhaps in search paradigms in general. Moreover, measurements of the time courses of oscillatory power changes and inter-regional synchronization in theta and low-gamma frequency bands were consistent with the early activation and synchronization within the VAN associated with the P3a subcomponent, and with the later activation and synchronization within the DAN and ODD networks associated with the P3b subcomponent. Implications of these finding for the mechanisms underlying search asymmetry phenomena are discussed.

Asymmetric interference between cognitive task components and concurrent sensorimotor coordination

Everyday cognitive tasks are frequently performed under dual-task conditions alongside continuous sensorimotor coordinations (CSCs) such as driving, walking, or balancing. Observed interference in these dual-task settings is commonly attributed to demands on executive function or attentional resources, but the time course and reciprocity of interference are not well understood at the level of information-processing components. Here we used electrophysiology to study the detailed chronometry of dual-task interference between a visual oddball task and a continuous visuomanual tracking task. The oddball task's electrophysiological components were linked to underlying cognitive processes, and the tracking task served as a proxy for the continuous cycle of state monitoring and adjustment inherent to CSCs. Dual-tasking interfered with the oddball task's accuracy and attentional processes (attenuated P2 and P3b magnitude and parietal alpha-band event-related desynchronization), but errors in tracking due to dual-tasking accrued at a later timescale and only in trials in which the target stimulus appeared and its tally had to be incremented. Interference between cognitive tasks and CSCs can be asymmetric in terms of timing as well as affected information-processing components. NEW & NOTEWORTHY Interference between cognitive tasks and continuous sensorimotor coordination (CSC) has been widely reported, but this is the first demonstration that the cognitive operation that is impaired by concurrent CSC may not be the one that impairs the CSC. Also demonstrated is that interference between such tasks can be temporally asymmetric. The asynchronicity of this interference has significant implications for understanding and mitigating loss of mobility in old age, and for rehabilitation for neurological impairments.

Usage of drip drops as stimuli in an auditory P300 BCI paradigm

Recently, many auditory BCIs are using beeps as auditory stimuli, while beeps sound unnatural and unpleasant for some people. It is proved that natural sounds make people feel comfortable, decrease fatigue, and improve the performance of auditory BCI systems. Drip drop is a kind of natural sounds that makes humans feel relaxed and comfortable. In this work, three kinds of drip drops were used as stimuli in an auditory-based BCI system to improve the user-friendness of the system. This study explored whether drip drops could be used as stimuli in the auditory BCI system. The auditory BCI paradigm with drip-drop stimuli, which was called the drip-drop paradigm (DP), was compared with the auditory paradigm with beep stimuli, also known as the beep paradigm (BP), in items of event-related potential amplitudes, online accuracies and scores on the likability and difficulty to demonstrate the advantages of DP. DP obtained significantly higher online accuracy and information transfer rate than the BP (p < 0.05, Wilcoxon signed test; p < 0.05, Wilcoxon signed test). Besides, DP obtained higher scores on the likability with no significant difference on the difficulty (p < 0.05, Wilcoxon signed test). The results showed that the drip drops were reliable acoustic materials as stimuli in an auditory BCI system.

Theta- and delta-band EEG network dynamics during a novelty oddball task

While the P3 component during target detection and novelty processing has been widely studied, less is known about its underlying network dynamics. A recent cognitive model suggests that frontal-parietal and frontal-temporal interregional connectivity are related to attention/action selection and target-related memory updating during the P3, respectively, but empirical work testing this model is lacking. Other work suggests the importance of theta- and delta-band connectivity between the medial frontal cortex and distributed cortical regions during attention, stimulus detection, and response selection processes, and similar dynamics may underlie P3-related network connectivity. The present study evaluated the functional connectivity elicited during a visual task, which combined oddball target and novelty stimuli, in a sample of 231 same-sex twins. It was hypothesized that both target and novel conditions would involve theta frontoparietal connectivity and medial frontal theta power, but that target stimuli would elicit the strongest frontotemporal connectivity. EEG time-frequency analysis revealed greater theta-band frontoparietal connectivity and medial frontal power during both target and novel conditions compared to standards, which may index conflict/uncertainty resolution processes. Theta-band frontotemporal connectivity was maximal during the target condition, potentially reflecting context updating or stimulus-response activation. Delta-band frontocentral-parietal connectivity was also strongest following targets, which may be sensitive to response-related demands. These results suggest the existence of functional networks related to P3 that are differentially engaged by target oddballs and novel distractors. Compared to simple P3 amplitude, network measures may provide a more nuanced view of the neural dynamics during target detection/novelty processing in normative and pathological populations.

Affective pictures processing is reflected by an increased long-distance EEG connectivity

Analysis of affective picture processing by means of EEG has invaded the literature. The methodology of event-related EEG coherence is one of the essential methods used to analyze functional connectivity. The aims of the present study are to find out the long range EEG connectivity changes in perception of different affective pictures and analyze gender differences in these long range connected networks. EEGs of 28 healthy subjects (14 female) were recorded at 32 locations. The participants passively viewed emotional pictures (IAPS, unpleasant, pleasant, neutral). The long-distance intra-hemispheric event-related coherence was analyzed for delta (1-3.5 Hz), theta (4-7.5 Hz), and alpha (8-13 Hz) frequency ranges for F₃-T₇, F₄-T₈, F₃-TP₇, F₄-TP₈, F₃-P₃, F₄-P₄, F₃-O₁, F₄-O₂, C₃-O₁, C₄-O₂ electrode pairs. Unpleasant pictures elicited significantly higher delta coherence values than neutral pictures (p < 0.05), over fronto-parietal, fronto-occipital, and centro-occipital electrode pairs. Furthermore, unpleasant pictures elicited higher theta coherence values than pleasant (p < 0.05) and neutral pictures (p < 0.05). The present study showed that female subjects had higher delta (p < 0.05) and theta (p < 0.05) coherence values than male subjects. This difference was observed more for emotional pictures than for neutral pictures. This study showed that the brain connectivity was higher during emotional pictures than neutral pictures. Females had higher connectivity between different parts of the brain than males during emotional processes. According to these results, we may comment that increased valence and arousal caused increased brain activity. It seems that not just single sources but functional networks were also activated during perception of emotional pictures.

Frontotemporal function]al connectivity and executive functions contribute to episodic memory performance

The contributions of hemispheric-specific electrophysiology (electroencephalogram or EEG) and independent executive functions (inhibitory control, working memory, cognitive flexibility) to episodic memory performance were examined using abstract paintings. Right hemisphere frontotemporal functional connectivity during encoding and retrieval, measured via EEG alpha coherence, statistically predicted performance on recency but not recognition judgments for the abstract paintings. Theta coherence, however, did not predict performance. Likewise, cognitive flexibility statistically predicted performance on recency judgments, but not recognition. These findings suggest that recognition and recency operate via separate electrophysiological and executive mechanisms.

A 15-day course of donepezil modulates spectral EEG dynamics related to target auditory stimuli in young, healthy adult volunteers

OBJECTIVE

To identify possible electroencephalographic (EEG) markers of donepezil's effect on cortical activity in young, healthy adult volunteers at the group level.

METHODS

Thirty subjects were administered a daily dose of either 5mg donepezil or placebo for 15days in a double-blind, randomized, cross-over trial. The electroencephalogram during an auditory oddball paradigm was recorded from 58 scalp electrodes. Current source density (CSD) transformations were applied to EEG epochs. The event-related potential (ERP), inter-trial coherence (ITC: the phase consistency of the EEG spectrum) and event-related spectral perturbation (ERSP: the EEG power spectrum relative to the baseline) were calculated for the target (oddball) stimuli.

RESULTS

The donepezil and placebo conditions differed in terms of the changes in delta/theta/alpha/beta ITC and ERSP in various regions of the scalp (especially the frontal electrodes) but not in terms of latency and amplitude of the P300-ERP component.

CONCLUSION

Our results suggest that ITC and ERSP analyses can provide EEG markers of donepezil's effects in young, healthy, adult volunteers at a group level.

SIGNIFICANCE

Novel EEG markers could be useful to assess the therapeutic potential of drug candidates in Alzheimer's disease in healthy volunteers prior to the initiation of Phase II/III clinical studies in patients.

Review of evoked and event-related delta responses in the human brain

In the last decade, the brain's oscillatory responses have invaded the literature. The studies on delta (0.5-3.5Hz) oscillatory responses in humans upon application of cognitive paradigms showed that delta oscillations are related to cognitive processes, mainly in decision making and attentional processes. The present manuscript comprehensively reviews the studies on delta oscillatory responses upon cognitive stimulation in healthy subjects and in different pathologies, namely Alzheimer's disease, Mild Cognitive Impairment (MCI), bipolar disorder, schizophrenia and alcoholism. Further delta oscillatory response upon presentation of faces, facial expressions, and affective pictures are reviewed. The relationship between pre-stimulus delta activity and post-stimulus evoked and event-related responses and/or oscillations is discussed. Cross-frequency couplings of delta oscillations with higher frequency windows are also included in the review. The conclusion of this review includes several important remarks, including that delta oscillatory responses are involved in cognitive and emotional processes. A decrease of delta oscillatory responses could be a general electrophysiological marker for cognitive dysfunction (Alzheimer's disease, MCI, bipolar disorder, schizophrenia and alcoholism). The pre-stimulus activity (phase or amplitude changes in delta activity) has an effect on post-stimulus EEG responses.

Improving N1 classification by grouping EEG trials with phases of pre-stimulus EEG oscillations

A reactive brain-computer interface using electroencephalography (EEG) relies on the classification of evoked ERP responses. As the trial-to-trial variation is evitable in EEG signals, it is a challenge to capture the consistent classification features distribution. Clustering EEG trials with similar features and utilizing a specific classifier adjusted to each cluster can improve EEG classification. In this paper, instead of measuring the similarity of ERP features, the brain states during image stimuli presentation that evoked N1 responses were used to group EEG trials. The correlation between momentary phases of pre-stimulus EEG oscillations and N1 amplitudes was analyzed. The results demonstrated that the phases of time-frequency points about 5.3 Hz and 0.3 s before the stimulus onset have significant effect on the ERP classification accuracy. Our findings revealed that N1 components in ERP fluctuated with momentary phases of EEG. We also further studied the influence of pre-stimulus momentary phases on classification of N1 features. Results showed that linear classifiers demonstrated outstanding classification performance when training and testing trials have close momentary phases. Therefore, this gave us a new direction to improve EEG classification by grouping EEG trials with similar pre-stimulus phases and using each to train unit classifiers respectively.

Changes in cerebellar activity and inter-hemispheric coherence accompany improved reading performance following Quadrato Motor Training

Dyslexia is a multifactorial reading deficit that involves multiple brain systems. Among other theories, it has been suggested that cerebellar dysfunction may be involved in dyslexia. This theory has been supported by findings from anatomical and functional imaging. A possible rationale for cerebellar involvement in dyslexia could lie in the cerebellum’s role as an oscillator, producing synchronized activity within neuronal networks including sensorimotor networks critical for reading. If these findings are causally related to dyslexia, a training regimen that enhances cerebellar oscillatory activity should improve reading performance. We examined the cognitive and neural effects of Quadrato Motor Training (QMT), a structured sensorimotor training program that involves sequencing of motor responses based on verbal commands. Twenty-two adult Hebrew readers (12 dyslexics and 10 controls) were recruited for the study. Using Magnetoencephalography (MEG), we measured changes in alpha power and coherence following QMT in a within-subject design. Reading performance was assessed pre- and post-training using a comprehensive battery of behavioral tests. Our results demonstrate improved performance on a speeded reading task following one month of intensive QMT in both the dyslexic and control groups. Dyslexic participants, but not controls, showed significant increase in cerebellar oscillatory alpha power following training. In addition, across both time points, inter-hemispheric alpha coherence was higher in the dyslexic group compared to the control group. In conclusion, the current findings suggest that the combination of motor and language training embedded in QMT increases cerebellar oscillatory activity in dyslexics and improves reading performance. These results support the hypothesis that the cerebellum plays a role in skilled reading, and begin to unravel the underlying mechanisms that mediate cerebellar contribution in cognitive and neuronal augmentation.

Prestimulus frontal-parietal coherence predicts auditory detection performance in rats

Electrophysiology in primates has implicated long-range neural coherence as a potential mechanism for enhancing sensory detection. To test whether local synchronization and long-range neural coherence support detection performance in rats, we recorded local field potentials (LFPs) in frontal and parietal cortex while rats performed an auditory detection task. We observed significantly elevated power at multiple low frequencies (<15 Hz) preceding the target beep when the animal failed to respond to the signal (misses), in both frontal and parietal cortex. In terms of long-range coherence, we observed significantly more frontal-parietal coherence in the beta band (15-30 Hz) before the signal on misses compared with hits. This effect persisted after regressing away linear trends in the coherence values during a session, showing that the excess frontal-parietal beta coherence prior to misses cannot be explained by slow motivational changes during a session. In addition, a trend toward higher low-frequency (<15 Hz) coherence prior to miss trials compared with hits became highly significant when we rereferenced the LFPs to the mean voltage on each recording array, suggesting that the results are specific to our frontal and parietal areas. These results do not support a role for long-range frontal-parietal coherence or local synchronization in facilitating the detection of external stimuli. Rather, they extend to long-range frontal-parietal coherence previous findings that correlate local synchronization of low-frequency (<15 Hz) oscillations with inattention to external stimuli and synchronization of beta rhythms (15-30 Hz) with voluntary or involuntary prolongation of the current cognitive or motor state.

A review of EEG and MEG for brainnetome research

The majority of brain activities are performed by functionally integrating separate regions of the brain. Therefore, the synchronous operation of the brain's multiple regions or neuronal assemblies can be represented as a network with nodes that are interconnected by links. Because of the complexity of brain interactions and their varying effects at different levels of complexity, one of the corresponding authors of this paper recently proposed the brainnetome as a new -ome to explore and integrate the brain network at different scales. Because electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive and have outstanding temporal resolution and because they are the primary clinical techniques used to capture the dynamics of neuronal connections, they lend themselves to the analysis of the neural networks comprising the brainnetome. Because of EEG/MEG's applicability to brainnetome analyses, the aim of this review is to identify the procedures that can be used to form a network using EEG/MEG data in sensor or source space and to promote EEG/MEG network analysis for either neuroscience or clinical applications. To accomplish this aim, we show the relationship of the brainnetome to brain networks at the macroscale and provide a systematic review of network construction using EEG and MEG. Some potential applications of the EEG/MEG brainnetome are to use newly developed methods to associate the properties of a brainnetome with indices of cognition or disease conditions. Associations based on EEG/MEG brainnetome analysis may improve the comprehension of the functioning of the brain in neuroscience research or the recognition of abnormal patterns in neurological disease.

A review of gamma oscillations in healthy subjects and in cognitive impairment

This review describes a wide range of functional correlates of gamma oscillations in whole-brain work, in neuroethology, sensory-cognitive dynamics, emotion, and cognitive impairment. This survey opens a new window towards understanding the brain's gamma activity. Gamma responses are selectively distributed in the whole brain, and do not reflect only a unique, specific function of the nervous system. Sensory responses from cortex, thalamus, hippocampus, and reticular formations in animal and human brains, and also cognitive responses, were described by several authors. According to reviewed results, it becomes obvious that cognitive disorders, and medication-which influence the transmitter release-change entirely the understanding of the big picture in cognitive processes. Gamma activity is evoked or induced by different sensory stimuli or cognitive tasks. Thus, it is argued that gamma-band synchronization is an elementary and fundamental process in whole-brain operation. In conclusion, reasoning and suggestions for understanding gamma activity are highlighted.

Beta oscillatory responses in healthy subjects and subjects with mild cognitive impairment

The aim of the present study was to investigate the role of beta oscillatory responses upon cognitive load in healthy subjects and in subjects with mild cognitive impairment (MCI). The role of beta oscillations upon cognitive stimulation is least studied in comparison to other frequency bands. The study included 17 consecutive patients with MCI (mean age = 70.8 ± 5.6 years) according to Petersen's criteria, and 17 age- and education-matched normal elderly controls (mean age = 68.5 ± 5.5 years). The experiments used a visual oddball paradigm. EEG was recorded at 30 cortical locations. EEG-evoked power, inter-trial phase synchronization, and event-related beta responses filtered in 15-20 Hz were obtained in response to target and non-target stimuli for both groups of subjects. In healthy subjects, EEG-evoked beta power, inter-trial phase synchronization of beta responses and event-related filtered beta responses were significantly higher in responses to target than non-target stimuli (p < 0.05). In MCI patients, there were no differences in evoked beta power between target and non-target stimuli. Furthermore, upon presentation of visual oddball paradigm, occipital electrodes depict higher beta response in comparison to other electrode sites. The increased beta response upon presentation of target stimuli in healthy subjects implies that beta oscillations could shift the system to an attention state, and had important function in cognitive activity. This may, in future, open the way to consider beta activity as an important operator in brain cognitive processes.

A comparison study of two P300 speller paradigms for brain-computer interface

In this paper, a comparison of two existing P300 spellers is conducted. In the first speller, the visual stimuli of characters are presented in a single character (SC) paradigm and each button corresponding to a character flashes individually in a random order. The second speller is based on a region-based (RB) paradigm. In the first level, all characters are grouped and each button corresponding to a group flashes individually in a random order. Once a group is selected, the characters in it will appear on the flashing buttons of the second level for the selection of desired character. In a spelling experiment involving 12 subjects, higher online accuracy was obtained on the RB paradigm-based P300 speller than the SC paradigm-based P300 speller. Furthermore, we analyzed P300 detection performance, the P300 waveforms and Fisher ratios using the data collected by the two spellers. It was found that the stimuli display paradigm of the RB speller enhances P300 potential and is more suitable for P300 detection.

A hybrid model for the neural representation of complex mental processing in the human brain

In the present conceptual review several theoretical and empirical sources of information were integrated, and a hybrid model of the neural representation of complex mental processing in the human brain was proposed. Based on empirical evidence for strategy-related and inter-individually different task-related brain activation networks, and further based on empirical evidence for a remarkable overlap of fronto-parietal activation networks across different complex mental processes, it was concluded by the author that there might be innate and modular organized neuro-developmental starting regions, for example, in intra-parietal, and both medial and middle frontal brain regions, from which the neural organization of different kinds of complex mental processes emerge differently during individually shaped learning histories. Thus, the here proposed model provides a hybrid of both massive modular and holistic concepts of idiosyncratic brain physiological elaboration of complex mental processing. It is further concluded that 3-D information, obtained by respective methodological approaches, are not appropriate to identify the non-linear spatio-temporal dynamics of complex mental process-related brain activity in a sufficient way. How different participating network parts communicate with each other seems to be an indispensable aspect, which has to be considered in particular to improve our understanding of the neural organization of complex cognition.

Brain fingerprinting: a comprehensive tutorial review of detection of concealed information with event-related brain potentials

Brain fingerprinting (BF) detects concealed information stored in the brain by measuring brainwaves. A specific EEG event-related potential, a P300-MERMER, is elicited by stimuli that are significant in the present context. BF detects P300-MERMER responses to words/pictures relevant to a crime scene, terrorist training, bomb-making knowledge, etc. BF detects information by measuring cognitive information processing. BF does not detect lies, stress, or emotion. BF computes a determination of "information present" or "information absent" and a statistical confidence for each individual determination. Laboratory and field tests at the FBI, CIA, US Navy and elsewhere have resulted in 0% errors: no false positives and no false negatives. 100% of determinations made were correct. 3% of results have been "indeterminate." BF has been applied in criminal cases and ruled admissible in court. Scientific standards for BF tests are discussed. Meeting the BF scientific standards is necessary for accuracy and validity. Alternative techniques that failed to meet the BF scientific standards produced low accuracy and susceptibility to countermeasures. BF is highly resistant to countermeasures. No one has beaten a BF test with countermeasures, despite a $100,000 reward for doing so. Principles of applying BF in the laboratory and the field are discussed.

Traveling EEG slow oscillation along the dorsal attention network initiates spontaneous perceptual switching

An ambiguous figure such as the Necker cube causes spontaneous perceptual switching (SPS). The mechanism of SPS in multistable perception has not yet been determined. Although early psychological studies suggested that SPS may be caused by fatigue or satiation of orientation, the neural mechanism of SPS is still unknown. Functional magnetic resonance imaging (fMRI) has shown that the dorsal attention network (DAN), which mainly controls voluntary attention, is involved in bistable perception of the Necker cube. To determine whether neural dynamics along the DAN cause SPS, we performed simultaneous electroencephalography (EEG) and fMRI during an SPS task with the Necker cube, with every SPS reported by pressing a button. This EEG–fMRI integrated analysis showed that (a) 3–4 Hz spectral EEG power modulation at fronto-central, parietal, and centro-parietal electrode sites sequentially appeared from 750 to 350 ms prior to the button press; and (b) activations correlating with the EEG modulation traveled along the DAN from the frontal to the parietal regions. These findings suggest that slow oscillation initiates SPS through global dynamics along the attentional system such as the DAN.

Dynamic characteristics of multisensory facilitation and inhibition

Multimodal integration, which mainly refers to multisensory facilitation and multisensory inhibition, is the process of merging multisensory information in the human brain. However, the neural mechanisms underlying the dynamic characteristics of multimodal integration are not fully understood. The objective of this study is to investigate the basic mechanisms of multimodal integration by assessing the intermodal influences of vision, audition, and somatosensory sensations (the influence of multisensory background events to the target event). We used a timed target detection task, and measured both behavioral and electroencephalographic responses to visual target events (green solid circle), auditory target events (2 kHz pure tone) and somatosensory target events (1.5 ± 0.1 mA square wave pulse) from 20 normal participants. There were significant differences in both behavior performance and ERP components when comparing the unimodal target stimuli with multimodal (bimodal and trimodal) target stimuli for all target groups. Significant correlation among reaction time and P3 latency was observed across all target conditions. The perceptual processing of auditory target events (A) was inhibited by the background events, while the perceptual processing of somatosensory target events (S) was facilitated by the background events. In contrast, the perceptual processing of visual target events (V) remained impervious to multisensory background events.

Dipole source analysis of auditory P300 response in depressive and anxiety disorders

This paper is to study auditory event-related potential P300 in patients with anxiety and depressive disorders using dipole source analysis. Auditory P300 using 2-stimulus oddball paradigm was collected from 35 patients with anxiety disorder, 32 patients with depressive disorder, and 30 healthy controls. P300 dipole sources and peak amplitude of dipole activities were analyzed. The source analysis resulted in a 4-dipole configuration, where temporal dipoles displayed greater P300 amplitude than that of frontal dipoles. In addition, a right-greater-than-left hemispheric asymmetry of dipole magnitude was found in patients with anxiety disorder, whereas a left-greater-than-right hemispheric asymmetry of dipole magnitude was observed in depressed patients. Results indicated that the asymmetry was more prominent over the temporal dipole than that of frontal dipoles in patients. Patients with anxiety disorder may increase their efforts to enhance temporal dipole activity to compensate for a deficit in frontal cortex processing, while depressed patients show dominating reduction of right temporal activity. The opposite nature of results observed with hemispheric asymmetry in depressive and anxiety disorders could serve to be valuable information for psychiatric studies.

Sensory evoked and event related oscillations in Alzheimer's disease: a short review

Diagnosis and treatment of Alzheimer's disease (AD) depend on clinical evaluation and there is a strong need for an objective tool as a biomarker. Our group has investigated brain oscillatory responses in a small group of AD subjects. We found that the de novo (untreated) AD group differs from both the cholinergically-treated AD group and aged-matched healthy controls in theta and delta responses over left frontal-central areas after cognitive stimulation. On the contrary, the difference observed in AD groups upon a sensory visual stimulation includes response increase over primary or secondary visual sensorial areas compared to controls. These findings imply at least two different neural networks, depending on type of stimulation (i.e. cognitive or sensory). The default mode defined as activity in resting state in AD seems to be affected electrophysiologically. Coherences are also very valuable in observing the group differences, especially when a cognitive stimulus is applied. In healthy controls, higher coherence values are elicited after a cognitive stimulus than after a sensory task. Our findings support the notion of disconnectivity of cortico-cortical connections in AD. The differences in comparison of oscillatory responses upon sensory and cognitive stimulations and their role as a biomarker in AD await further investigation in series with a greater number of subjects.