Electroencephalographic Studies Research Articles

Distinct Neural Connectivity Patterns During Music Listening and Imagination: An Electroencephalography Study.

Background: The brain's function changes during various activities, and numerous studies have explored this field. An intriguing and significant area of research is the brain's functioning during imagination and periods of inactivity. Objective: This study explores the differences in brain connectivity during music listening and imagination: by identifying distinct neural connectivity patterns and providing insights into the cognitive mechanisms underlying auditory imagination. Methods: Effective connectivity matrices were generated using generalized partial directed coherence (GPDC) and directed Directed Transfer Function (dDTF) methods applied to non-invasive electroencephalography data from these two conditions. Statistical tests were performed to illustrate the differences in brain connectivity, followed by the creation of brain graphs and the application of a non-parametric permutation test to demonstrate statistical significance. Data classification between listening to music and imagining it was performed using an Support Vector Machine (SVM) classifier with different feature vectors. Results: Combining features extracted from GPDC and dDTF achieved an accuracy of 71.3% while using GPDC and dDTF features individually yielded accuracies of 60% and 62.1%, respectively. Among all the graph's global features, only modularity and small-worldness showed statistically significant differences in dDTF and GPDC. Overall, findings reveal that information flows from the left hemisphere to the right hemisphere increases during music imagination compared with listening, highlighting distinct neural connectivity patterns associated with imaginative processes. Conclusion: The study provides novel insights into the distinct neural connectivity patterns during music listening and imagination, contributing to the broader understanding of cognitive processes associated with auditory imagination and perception.

Word-selective EEG/MEG responses in the English language obtained with Fast Periodic Visual Stimulation (FPVS)

Abstract Fast periodic visual stimulation (FPVS) allows the objective measurement of brain responses of human word discrimination (i.e., reproducible word-category-selective responses) with a high signal-to-noise ratio. This approach has been successfully employed over the last decade in a number of scalp electroencephalography (EEG) studies. Three important advances for research on word-selective brain responses were achieved in the present study: (1) we extend previous evidence of robust word-category-selective responses to the English language, (2) report results for combined EEG and MEG signals, and (3) source estimation results. English words were presented periodically (2 Hz) among different types of letter strings (10Hz; consonant strings, non-words, pseudowords) whilst recording simultaneous EEG and MEG in 25 participants who performed a simple non-linguistic color detection task. Data were analyzed in sensor and in source space. With only 4 minutes of stimulation we observed a robust word discrimination response in each condition, even when words were embedded in sequences of word-like pseudowords. This response was larger in nonwords and largest in consonant strings. We observed left-lateralized responses in all conditions in the majority of our participants. Cluster-based permutation tests revealed that these responses were left-lateralized in sensor as well as in source space, with peaks in left posterior regions. Our results demonstrate that the FPVS approach can elicit robust English word-discrimination responses in EEG and MEG within only a few minutes of recording time. Together with source estimation, this can provide novel insights into the neural basis of visual word recognition in healthy and clinical populations.

High-intensity physiological activation disrupts the neural signatures of conflict processing

Physiological activation fluctuates throughout the day. Previous studies have shown that during periods of reduced activation, cognitive control remains resilient due to neural compensatory mechanisms. In this study, we investigate the effects of high physiological activation on both behavioural and neural markers of cognitive control. We hypothesize that while behavioural measures of cognitive control would remain intact during periods of high activation, there would be observable changes in neural correlates. In our electroencephalography study, we manipulate levels of physiological activation through physical exercise. Although we observe no significant impact on behavioural measures of cognitive conflict, both univariate and multivariate time-frequency markers prove unreliable under conditions of high activation. Moreover, we observe no modulation of whole-brain connectivity measures by physiological activation. We suggest that this dissociation between behavioural and neural measures indicates that the human cognitive control system remains resilient even at high activation, possibly due to underlying neural compensatory mechanisms.

Sleep Fragmentation Modulates the Neurophysiological Correlates of Cognitive Fatigue.

Cognitive fatigue (CF) is a critical factor affecting performance and well-being. It can be altered in suboptimal sleep quality conditions, e.g., in patients suffering from obstructive sleep apnea who experience both intermittent hypoxia and sleep fragmentation (SF). Understanding the neurophysiological basis of SF in healthy individuals can provide insights to improve cognitive functioning in disrupted sleep conditions. In this electroencephalographical (EEG) study, we investigated in 16 healthy young participants the impact of experimentally induced SF on the neurophysiological correlates of CF measured before, during, and after practice on the TloadDback, a working memory task tailored to each individual's maximal cognitive resources. The participants spent three consecutive nights in the laboratory two times, once in an undisrupted sleep (UdS) condition and once in an SF condition induced by non-awakening auditory stimulations, counterbalanced and performed the TloadDback task both in a high (HCL) and a low (LCL) cognitive load condition. EEG activity was recorded during wakefulness in the 5 min resting state immediately before and after, as well as during the 16 min of the TloadDback task practice. In the high cognitive load under a sleep-fragmentation (HCL/SF) condition, high beta power increased during the TloadDback, indicating heightened cognitive effort, and the beta and alpha power increased in the post- vs. pre-task resting state, suggesting a relaxation rebound. In the low cognitive load/undisturbed sleep (LCL/UdS) condition, low beta activity increased, suggesting a relaxed focus, as well as mid beta activity associated with active thinking. These findings highlight the dynamic impact of SF on the neurophysiological correlates of CF and underscore the importance of sleep quality and continuity to maintain optimal cognitive functioning.

Neurophysiological markers of early cognitive decline in older adults: a mini-review of electroencephalography studies for precursors of dementia.

The early detection of cognitive decline in older adults is crucial for preventing dementia. This mini-review focuses on electroencephalography (EEG) markers of early dementia-related precursors, including subjective cognitive decline, subjective memory complaints, and cognitive frailty. We present recent findings from EEG analyses identifying high dementia risk in older adults, with an emphasis on conditions that precede mild cognitive impairment. We also cover event-related potentials, quantitative EEG markers, microstate analysis, and functional connectivity approaches. Moreover, we discuss the potential of these neurophysiological markers for the early detection of cognitive decline as well as their correlations with related biomarkers. The integration of EEG data with advanced artificial intelligence technologies also shows promise for predicting the trajectory of cognitive decline in neurodegenerative disorders. Although challenges remain in its standardization and clinical application, EEG-based approaches offer non-invasive, cost-effective methods for identifying individuals at risk of dementia, which may enable earlier interventions and personalized treatment strategies.

Impact of sleep deprivation on aperiodic activity: a resting-state EEG study.

Sleep deprivation (SD) has been shown to have a negative impact on alertness, as evidenced by behavioral and electroencephalographic studies. Nevertheless, in prior studies utilizing conventional fixed-bandwidth spectral analysis the aperiodic and periodic components were often confused, and some important periodic parameters (i.e., center frequency, bandwidth) were ignored. Here, based on a large open-access dataset of SD, we employed a standardized process for multiple-electrode analysis and group inference. We found that, compared to the healthy sleep control state (SC), the aperiodic offset shifted overall after SD, primarily in the occipital region. This shift was associated with a reduction in subjective alertness. Regarding periodic components, we did not find any power change in the alpha rhythm, but there was an increase in bandwidth of alpha within different regions distributed in the occipital and temporal lobes. These findings highlight the potential significance and value of aperiodic parameters in behavioral and electrophysiological research.NEW & NOTEWORTHY Aperiodic and periodic components were separated in a large open-access EEG dataset of sleep deprivation. Aperiodic offsets increase after deprivation, particularly in the occipital region, reflecting a decline in self-reported vigilance. Parameterized alpha bandwidth, which was ignored in previous studies, is found to be relevant to sleep deprivation. Increase in bandwidth of alpha was focused in the occipital and temporal lobes.

Corticocortical and corticomuscular connectivity dynamics in standing posture: electroencephalography study.

Cortical mechanism is necessary for human standing control. Previous research has demonstrated that cortical oscillations and corticospinal excitability respond flexibly to postural demands. However, it is unclear how corticocortical and corticomuscular connectivity changes dynamically during standing with spontaneous postural sway and over time. This study investigated the dynamics of sway- and time-varying connectivity using electroencephalography and electromyography. Electroencephalography and electromyography were recorded in sitting position and 3 standing postures with varying base-of-support: normal standing, one-leg standing, and standing on a piece of wood. For sway-varying connectivity, corticomuscular connectivity was calculated based on the timing of peak velocity in anteroposterior sway. For time-varying connectivity, corticocortical connectivity was measured using the sliding-window approach. This study found that corticomuscular connectivity was strengthened at the peak velocity of postural sway in the γ- and β-frequency bands. For time-varying corticocortical connectivity, the θ-connectivity in all time-epoch was classified into 7 clusters including posture-relevant component. In one of the 7 clusters, strong connectivity pairs were concentrated in the mid-central region, and the proportion of epochs under narrow-base standing conditions was significantly higher, indicating a functional role for posture balance. These findings shed light on the connectivity dynamics and cortical oscillation that govern standing balance.

Musical Expertise Influences the Processing of Short and Long Auditory Time Intervals: An Electroencephalography Study.

Musical expertise has been proven to be beneficial for time perception abilities, with musicians outperforming nonmusicians in several explicit timing tasks. However, it is unclear how musical expertise impacts implicit time perception. Twenty nonmusicians and 15 expert musicians participated in an EEG recording during a passive auditory oddball paradigm with 0.8- and 1.6-sec standard time intervals and deviant intervals that were either played earlier or delayed relative to the standard interval. We first confirmed that, as was the case for nonmusicians, musicians use different neurofunctional processes to support the perception of short (below 1.2 sec) and long (above 1.2 sec) time intervals: Whereas deviance detection for long intervals elicited a N1 component, P2 was associated with deviance detection for short time intervals. Interestingly, musicians did not elicit a contingent negative variation (CNV) for longer intervals but show additional components of deviance detection such as (i) an attention-related N1 component, even for deviants occurring during short intervals; (ii) a N2 component for above and below 1.2-sec deviance detection, and (iii) a P2 component for above 1.2-sec deviance detection. We propose that the N2 component is a marker of explicit deviance detection and acts as an inhibitory/conflict monitoring of the deviance. This hypothesis was supported by a positive correlation between CNV and N2 amplitudes: The CNV reflects the temporal accumulator and can predict explicit detection of the deviance. In expert musicians, a N2 component is observable without CNV, suggesting that deviance detection is optimized and does not require the temporal accumulator. Overall, this study suggests that musical expertise is associated with optimized implicit time perception.

Distinct and additive effects of visual and vibratory feedback for motor rehabilitation: an EEG study in healthy subjects

IntroductionThe use of visual and proprioceptive feedback is a key property of motor rehabilitation techniques. This feedback can be used alone, for example, for vision in mirror or video therapy, for proprioception in focal tendon vibration therapy, or in combination, for example, in robot-assisted training. This Electroencephalographic (EEG) study in healthy subjects explored the distinct neurophysiological impact of adding visual (video therapy), proprioceptive (focal tendinous vibration), or combined feedback (video therapy and focal tendinous vibration) to a motor imagery task.MethodsSixteen healthy volunteers performed 20 mental imagery (MI) tasks involving right wrist extension and flexion under four conditions: MI alone (IA), MI + video feedback observation (IO), MI + vibratory feedback (IV), and MI + observation + vibratory feedback (IOV). Brain activity was monitored with EEG, and time-frequency neurophysiological markers of movement were computed. The emotions of the patients were also measured during the task.ResultsIn the alpha band, we observed bilateral ERD in the visual feedback conditions (IO, IOV). In the beta band, the ERD was bilateral in the IA, IV and IOV but more lateralized in the IV and IOV. After movement, we observed strong ERS in the IO and IOV but not in the IA or IV. Embodiment was stronger in conditions with vibratory feedback (IOV > IV > IA and IO)ConclusionConditions with visual feedback (IO, IOV) recruit the mirror neurons system (alpha ERD) and provide more accurate feedback of the task than IA and IV, which triggers motor validation pathways (beta rebound analysis). Vibratory feedback enhances the recruitment of the left sensorimotor areas, with a synergistic effect in the IOV (beta ERD analysis), thus maximizing embodiment. Visual and vibratory feedback recruits the sensorimotor cortex during motor imagery in different ways and can be combined to maximize the benefits of both techniquesTrial registrationhttps://clinicaltrials.gov/study/NCT04449328.

The impact of isoflurane anesthesia on brain metabolism in mice: An MRI and electroencephalography study.

Isoflurane is one of the most widely used anesthetic agents in rodent imaging studies. However, the impact of isoflurane on brain metabolism has not been fully characterized to date, primarily due to a scarcity of noninvasive technologies to quantitatively measure the brain's metabolic rate in vivo. In this study, using noncontrast MRI techniques, we dynamically measured cerebral metabolic rate of oxygen (CMRO2) under varying doses of isoflurane anesthesia in mice. Concurrently, systemic parameters of heart and respiration rates were recorded alongside CMRO2. Additionally, electroencephalogram (EEG) recording was used to identify changes in neuronal activities under the same anesthetic regimen employed in the MRI experiments. We found suppression of the CMRO2 by isoflurane in a dose-dependent manner, concomitant with a diminished high-frequency EEG activity. The degree of metabolic suppression by isoflurane was strongly correlated with the respiration rate, which offers a potential approach to calibrate CMRO2 measurements. Furthermore, the metabolic level associated with neural responses of the somatosensory and motor cortices in mice was estimated as 308.2μmol/100 g/min. These findings may facilitate the integration of metabolic parameters into future studies involving animal disease models and anesthesia usage.

Resting-State EEG Alterations of Practice-Related Spectral Activity and Connectivity Patterns in Depression.

Depression presents with altered energy regulation and neural plasticity. Previous electroencephalography (EEG) studies showed that practice in learning tasks increases power in beta range (13-30 Hz) in healthy subjects but not in those with impaired plasticity. Here, we ascertain whether depression presents with alterations of spectral activity and connectivity before and after a learning task. We used publicly available resting-state EEG recordings (64 electrodes) from 122 subjects. Based on Beck Depression Inventory (BDI) scores, they were assigned to either a high BDI (hBDI, BDI > 13, N = 46) or a control (CTL, BDI < 7, N = 75) group. We analyzed spectral activity, theta-beta, and theta-gamma phase-amplitude coupling (PAC) of EEG recorded at rest before and after a learning task. At baseline, compared to CTL, hBDI exhibited greater power in beta over fronto-parietal regions and in gamma over the right parieto-occipital area. At post task, power increased in all frequency ranges only in CTL. Theta-beta and theta-gamma PAC were greater in hBDI at baseline but not after the task. The lack of substantial post-task growth of beta power in depressed subjects likely represents power saturation due to greater baseline values. We speculate that inhibitory/excitatory imbalance, altered plasticity mechanisms, and energy dysregulation present in depression may contribute to this phenomenon.

Stress Induction and Release: Electroencephalography Study on Brain Networks and Cortisol

Acute stress in a long period of time could drastically influence one's behavioral and cognitive performances. Therefore, it is important to control the stressful situation and release it after a stressful event. In this regard, understanding of brain mechanism of the stress release will help to introduce new practical approaches. In this study, we hypothesized that induction and release of stress will change the brain functional connectivity pattern. Therefore, by recruiting 20 healthy-subjects and exposing them to stressful events using the trier social stress paradigm, we aimed to investigate patterns of these changes. In a session consist of 23 minutes of psychological stress induction and 20 minutes of recovery, subjects' stress was scored by visual analogue scale (VAS). In addition, salivary cortisol level and EEG data of the subjects were also recorded. Subsequently, brain functional connectivity (FC) maps were calculated in a frequency-specific manner. Then, the effects of inducing and release of stress on the changes of VAS, cortisol level, and FC maps were assessed. Our results revealed that inter-hemispheric FCs of the right frontal regions with other regions of the brain decrease; while it increases at the left frontal regions during inducing of mental stress. Interestingly, the release of stress presented a recovery pattern of inter-hemispheric FCs and meaningful FC changes significantly correlate with changes in the cortisol level. our findings highlight important roles of bihemispheric associations in adaptation and coping with stressful conditions.

Frontal EEG alpha asymmetry predicts foreign language anxiety while speaking a foreign language

Engaging in dialog requires interlocutors to coordinate sending and receiving linguistic signals to build a discourse based upon interpretations and perceptions interconnected with a range of emotions. Conversing in a foreign language may induce emotions such as anxiety which influence the quality communication. The neural processes underpinning these interactions are crucial to understanding foreign language anxiety (FLA). Electroencephalography (EEG) studies reveal that anxiety is often displayed via hemispheric frontal alpha asymmetry (FAA). To examine the neural mechanisms underlying FLA, we collected self-reported data on the listening and speaking sections of the Second language skill specific anxiety scale (L2AS) over behavioral, cognitive, and somatic domains and recorded EEG signals during participation in word chain turn-taking activities in first (L1, Chinese) and second (L2, English) languages. Regression analysis showed FAA for the L2 condition was a significant predictor primarily of the behavioral and somatic domains on the L2AS speaking section. The results are discussed along with implications for improving communication during L2 interactions.

From Infancy to Childhood: A Comprehensive Review of Event- and Task-Related Brain Oscillations.

Brain development from infancy through childhood involves complex structural and functional changes influenced by both internal and external factors. This review provides a comprehensive analysis of event and task-related brain oscillations, focusing on developmental changes across different frequency bands, including delta, theta, alpha, beta, and gamma. Electroencephalography (EEG) studies highlight that these oscillations serve as functional building blocks for sensory and cognitive processes, with significant variations observed across different developmental stages. Delta oscillations, primarily associated with deep sleep and early cognitive demands, gradually diminish as children age. Theta rhythms, crucial for attention and memory, display a distinct pattern in early childhood, evolving with cognitive maturation. Alpha oscillations, reflecting thalamocortical interactions and cognitive performance, increase in complexity with age. Beta rhythms, linked to active thinking and problem-solving, show developmental differences in motor and cognitive tasks. Gamma oscillations, associated with higher cognitive functions, exhibit notable changes in response to sensory stimuli and cognitive tasks. This review underscores the importance of understanding oscillatory dynamics to elucidate brain development and its implications for sensory and cognitive processing in childhood. The findings provide a foundation for future research on developmental neuroscience and potential clinical applications.

Cortical activation in REM behavior disorder mimics voluntary movement. An electroencephalography study

ObjectivesMotor symptoms of Parkinson’s disease improve during REM sleep behavior disorder movement episodes. Our aim was to study cortical activity during these movement episodes, in patients with and without Parkinson’s disease, in order to investigate the cortical involvement in the generation of its electromyographic activity and its potential relationship with Parkinson’s disease. MethodsWe looked retrospectively in our polysomnography database for patients with REM sleep behavior disorder, analyzing fifteen patients in total, seven with idiopathic REM sleep behavior disorder and eight associated with Parkinson’s disease. We selected segments of REM sleep with the presence of movements (evidenced by electromyographic activation), and studied movement-related changes in cortical activity by averaging the electroencephalographic signal (premotor potential) and by means of time/frequency transforms. ResultsWe found a premotor potential and an energy decrease of alpha–beta oscillatory activity preceding the onset of electromyographic activity, together with an increase of gamma activity for the duration of the movement. All these changes were similarly present in REM sleep behavior disorder patients with and without Parkinson’s disease. ConclusionsMovement-related changes in electroencephalographic activity observed in REM sleep behavior disorder are similar to those observed during voluntary movements, regardless of the presence of Parkinson’s disease motor symptoms. SignificanceThese results suggest a main involvement of the cortex in the generation of the movements during REM sleep.

A Pilot Electroencephalography Study of the Effect of CT1812 Treatment on Synaptic Activity in Patients with Mild to Moderate Alzheimer’s Disease

BackgroundCT1812 is a first-in-class, sigma-2 receptor ligand, that prevents and displaces binding of amyloid beta (Aβ) oligomers. Normalization of quantitative electroencephalography (qEEG) markers suggests that CT1812 protects synapses from Aβ oligomer toxicity.ObjectivesEvaluate CT1812 impact on synaptic function using qEEG measurements.DesignPhase 2, randomized, double-blind, placebo-controlled, 4-week crossover study.SettingVU University Medical Center and Brain Research Center Amsterdam, The Netherlands.ParticipantsAdults with mild or moderate Alzheimer’s disease (AD).InterventionA daily 300 mg dose of CT1812 or placebo for 4 weeks.MeasurementsA resting-state, eyes closed qEEG assessment occurred on Day 1 and on Day 29 of Treatment Periods 1 and 2, and at follow-up. The primary endpoint was global relative theta power (4–8 Hz), along with secondary EEG measures including global alpha corrected Amplitude Envelope Correlation (AEC-c). Cognitive and functional assessments, fluid biomarkers, and safety and tolerability were assessed.Results16 patients were randomized, and 15 completed. A non-significant (p=0.123) but consistent reduction occurred in global relative theta power and in relative theta power in frontal, temporal, parietal, occipital and central (p<0.006) brain regions with CT1812. A nominally significant (p=0.034) improvement was observed in global alpha AEC-c. Adverse events occurred in 11 patients with CT1812 and 6 with placebo -most commonly nausea, diarrhea, and procedural headache. No severe or serious AEs, deaths or discontinuations were reported.ConclusionCT1812 improved established EEG markers of spontaneous brain activity (spectral power, functional connectivity) in patients with mild-to-moderate AD, suggesting improved neuronal/synaptic function within a 4-week timespan.

Conflict Detection in Language Processing: Using Affect Control Theory to Predict Neural Correlates of Affective Incongruency in Social Interactions

Affect control theory (ACT) is a sociological theory of meaning processing in social interactions. Meaning, according to ACT, derives from cultural institutions and situational affordances, having denotative (declarative) as well as connotative (affective) properties. Mathematical formalizations of ACT allow predictions of affective incongruency (in the terminology of ACT, deflection), which arises from conflicting institutional and situational meanings in a given interaction context. Although ACT is theoretically consistent, its propositions regarding cognitive and affective processing have rarely been tested. The present study fills this gap by investigating the neural processing of affective incongruency in linguistic descriptions of social interactions. Following a neurosociological paradigm, the study draws on neurocognitive evidence on the effects of words’ affective content on word processing as well as on a previous electroencephalography study that investigated processing of affective incongruency using event-related brain potentials. We hypothesized that affective incongruency is associated with activation in the anterior cingulate cortex (ACC), a brain area known for conflict processing. To test this hypothesis, we replicated the electroencephalography study using functional magnetic resonance imaging: We visually presented sentences describing social interactions to 23 participants in a silent reading task while measuring differences in the hemodynamic response in two conditions of affective congruency. Results show expected increases in neural activity for affectively incongruent sentences in the left ACC, supporting the assumption that affective language content influences meaning-making at very early semantic processing stages. The results also add to the emerging neuroscientific evidence for ACT’s mathematical model of impression formation.

Neurophysiological Correlates of Near-Wins in Gambling: A Systematic Literature Review.

Identification of specific patterns of brain activity related to problem gambling may provide a deeper understanding of its underlying mechanisms, highlighting the importance of neurophysiological studies to better understand development and persistence of gambling behavior. The patterns of cognitive functioning have been investigated through electroencephalography (EEG) studies based on the near-win/near-miss (NW) effect. The main goal of the present study was to evaluate the neurophysiological basis of NWs and their modulation by gambling problems through a systematic review of event-related potentials (ERP) studies elicited by feedback events. The review followed the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA). A total of 15 studies were included, 12 comprising non-problem gamblers (NPGs) and three comparing problem gamblers (PGs) with matched controls. For the P300 component, the win outcome elicited a larger amplitude than the other outcomes (NW and loss), followed by the NW outcome, which elicited a larger amplitude than loss in some studies. For feedback-related negativity (FRN), the loss outcome evoked a more negative amplitude in several studies, despite eliciting a similar amplitude to NW outcomes in others. For PGs, the NW outcome evoked a higher amplitude of P300 than loss, while NPGs showed a similar amplitude to both outcomes. The present review gathered information from different sources and provides a consistent view of the different studies. However, studies lack systematic and robust methodologies, leading to inconsistent results and making it difficult to reach any definitive conclusions.

Inhibitory control of gait initiation in humans: An electroencephalography study.

Response inhibition is a crucial component of executive control. Although mainly studied in upper limb tasks, it is fully implicated in gait initiation. Here, we assessed the influence of proactive and reactive inhibitory control during gait initiation in healthy adult participants. For this purpose, we measured kinematics and electroencephalography (EEG) activity (event-related potential [ERP] and time-frequency data) during a modified Go/NoGo gait initiation task in 23 healthy adults. The task comprised Go-certain, Go-uncertain, and NoGo conditions. Each trial included preparatory and imperative stimuli. Our results showed that go-uncertainty resulted in delayed reaction time, without any difference for the other parameters of gait initiation. Proactive inhibition, that is, Go uncertain versus Go certain conditions, influenced EEG activity as soon as the preparatory stimulus. Moreover, both proactive and reactive inhibition influenced the amplitude of the ERPs (central P1, occipito-parietal N1, and N2/P3) and theta and alpha/low beta band activities in response to the imperative-Go-uncertain versus Go-certain and NoGo versus Go-uncertain-stimuli. These findings demonstrate that the uncertainty context; induced proactive inhibition, as reflected in delayed gait initiation. Proactive and reactive inhibition elicited extended and overlapping modulations of ERP and time-frequency activities. This study shows the protracted influence of inhibitory control in gait initiation.

Power spectral density-based resting-state EEG classification of first-episode psychosis

Historically, the analysis of stimulus-dependent time–frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during sensory and cognitive tasks have been studied many times. However, any significant dissimilarity in the resting-state low-frequency bands is yet to be established. Spectral analysis of the alpha and delta band waves shows the effectiveness of stimulus-independent EEG in identifying the abnormal activity patterns of pathological brains. A generalized model incorporating multiple frequency bands should be more efficient in associating potential EEG biomarkers with first-episode psychosis (FEP), leading to an accurate diagnosis. We explore multiple machine-learning methods, including random-forest, support vector machine, and Gaussian process classifier (GPC), to demonstrate the practicality of resting-state power spectral density (PSD) to distinguish patients of FEP from healthy controls. A comprehensive discussion of our preprocessing methods for PSD analysis and a detailed comparison of different models are included in this paper. The GPC model outperforms the other models with a specificity of 95.78% to show that PSD can be used as an effective feature extraction technique for analyzing and classifying resting-state EEG signals of psychiatric disorders.