Shaping functional architecture by oscillatory alpha activity: gating by inhibition

Speech outcomes in cochlear implant users depend on visual cross-modal cortical activity measured before or after implantation

Cochlear implants can partially restore hearing function in deaf individuals, but long-term speech listening outcomes vary widely across cochlear implant users. Visual cross-modal plasticity, where auditory cortical neurons upregulate visual inputs to assist visual processing, is one factor proposed to worsen cochlear implant users' speech outcomes because it may limit auditory processing capability. However, evidence for this view is conflicting, and the relationship of cross-modal activity to speech perception may depend on other variables such as the type of visual activity and when it is assessed. To clarify, we measured visual cross-modal activity during a silent lip reading task using EEG in a cross-sectional, observational study. The study tested visual brain activation in 14 individuals prior to receiving a cochlear implant, 15 individuals tested at least 1 year after receiving and using a cochlear implant and 13 typical hearing controls who did not use a cochlear implant or hearing aid. Cross-modal responses to the onset of a visual event were positively correlated to speech outcomes in cochlear implant users tested after surgery but were negatively correlated in those tested prior to cochlear implant surgery. In addition, cross-modal increases in neural oscillatory power in the alpha band (8-12 Hz) arising in the lip reading task were associated with worse speech outcomes in both cochlear implant user groups. Taken together, results redress claims that cross-modal plasticity is maladaptive for speech outcomes and instead suggest that this relationship depends on the time point of testing, stage of sensory processing and likely the relevance of the stimulus for speech. In addition, findings form the basis for new neural markers that are predictive of cochlear implant users' long-term speech ability.

Dynamic changes in large-scale functional connectivity prior to stimulation determine performance in a multisensory task

Complex behavior and task execution require fast changes of local activity and functional connectivity in cortical networks at multiple scales. The roles that changes of power and connectivity play during these processes are still not well understood. Here, we study how fluctuations of functional cortical coupling across different brain areas determine performance in an audiovisual, lateralized detection task in the ferret. We hypothesized that dynamic variations in the network's state determine the animals' performance. We evaluated these by quantifying changes of local power and of phase coupling across visual, auditory and parietal regions. While power for hit and miss trials showed significant differences only during stimulus and response onset, phase coupling already differed before stimulus onset. An analysis of principal components in coupling at the single-trial level during this period allowed us to reveal the subnetworks that most strongly determined performance. Whereas higher global phase coupling of visual and auditory regions to parietal cortex was predictive of task performance, a second component revealed a reduction in coupling between subnetworks of different sensory modalities, probably to allow a better detection of the unimodal signals. Furthermore, we observed that long-range coupling became more predominant during the task period compared to the pre-stimulus baseline. Taken together, our results show that fluctuations in the network state, as reflected in large-scale coupling, are key determinants of the animals' behavior.

A Case Study on Neural Activity Characteristics in a Shooting Competition

Background: Sexual characteristics in brain neurophysiological activity are a significant area of research in cognitive neuroscience. As a sport that involves minimal physical movement, shooters remain largely stationary during aiming, facilitating the collection of their neural activity compared to athletes in other sports. Objectives: To investigate the neural characteristics of novice shooters of different genders under competitive conditions. Methods: Sixteen subjects participated in a shooting competition following four weeks of training. Electroencephalogram (EEG) data and behavioral data (shooting scores, aiming curves, and pressure curves) were recorded during the competition, and the power spectral density (PSD) and phase-locking value (PLV) network features were extracted to explore further the correlation between the shooting scores and neural activity. Results: In our sample, (1) there were no significant differences in shooting scores between males and females; (2) there were differences in PSD values across the theta, alpha, alpha-2, beta, and gamma frequency bands between males and females; and (3) there were differences in PLV network properties in the theta, alpha, beta, and gamma frequency bands between males and females. Correlation analysis revealed associations between shooting scores and neural activity in male and female novices. Conclusions: The case study demonstrated that males and females exhibited different neural activity characteristics in the shooting competition, providing a foundation for further investigation into the sex differences in neural activity in shooting competition.

EEG during dynamic facial emotion processing reveals neural activity patterns associated with autistic traits in children

Altered brain connectivity and atypical neural oscillations have been observed in autism, yet their relationship with autistic traits in nonclinical populations remains underexplored. Here, we employ electroencephalography to examine functional connectivity, oscillatory power, and broadband aperiodic activity during a dynamic facial emotion processing task in 101 typically developing children aged 4 to 12 years. We investigate associations between these electrophysiological measures of brain dynamics and autistic traits as assessed by the Social Responsiveness Scale, 2nd Edition (SRS-2). Our results revealed that increased facial emotion processing-related connectivity across theta (4 to 7 Hz) and beta (13 to 30 Hz) frequencies correlated positively with higher SRS-2 scores, predominantly in right-lateralized (theta) and bilateral (beta) cortical networks. Additionally, a steeper 1/f-like aperiodic slope (spectral exponent) across fronto-central electrodes was associated with higher SRS-2 scores. Greater aperiodic-adjusted theta and alpha oscillatory power further correlated with both higher SRS-2 scores and steeper aperiodic slopes. These findings underscore important links between facial emotion processing-related brain dynamics and autistic traits in typically developing children. Future work could extend these findings to assess these electroencephalography-derived markers as potential mechanisms underlying behavioral difficulties in autism.

Similarities and differences between chronic primary pain and depression in brain activities: Evidence from resting-state microstates and auditory Oddball task

BACKGROUND

In 2019, the International Association for the Study of Pain introduced the concept of 'chronic primary pain (CPP)', characterized by persistent non-organic pain with emotional and functional abnormalities. Underdiagnosed and linked to depression, CPP has poorly understood neural characteristics. Electroencephalogram (EEG) microstates enable detailed examination of brain network dynamics at the millisecond level. Incorporating task-related EEG features offers a comprehensive neurophysiological signature of brain dysfunction, facilitating exploration of potential neural mechanisms.

METHODS

This study employed resting-state and task-related auditory Oddball EEG paradigm to evaluate 20 healthy controls, 20 patients with depression, and 20 patients with CPP. An 8-minute recording of resting-state EEG was conducted to identify four typical microstates (A-D). Additionally, power spectral density (PSD) features were examined during an auditory Oddball paradigm.

RESULTS

Both CPP and Major Depressive Disorder (MDD) patients exhibited reduced occurrence rate and transition probabilities of other microstates to microstate C during resting-state EEG. Furthermore, more pronounced increase in Gamma PSD was observed in the occipital region of CPP during the Oddball task. In CPP, both resting-state microstate C and task-related Gamma PSD correlated with pain and emotional indicators. Notably, microstate C occurrence positively correlated with occipital Gamma PSD in MDD.

CONCLUSION

Conclusively, both CPP and MDD display dynamic abnormalities within the salient network, closely associated with pain and depressive symptoms in CPP. Unlike MDD, CPPs' dynamic network changes appear unrelated to perceptual integration function, indicating differing microstate functional impacts. Combining resting-state microstates and Oddball tasks may offer a promising avenue for identifying potential biomarkers in objectively assessing chronic primary pain.

Metacognition in the listening brain

How do you know you have heard right? Metacognition, the ability to assess and monitor one's own cognitive state, is key to understanding human communication in complex environments. However, the foundational role of metacognition in hearing and communication is only beginning to be explored, and the neuroscience behind it is an emerging field: how does confidence express in neural dynamics of the listening brain? What is known about auditory metaperceptual alterations as a hallmark phenomenon in psychosis, dementia, or hearing loss? Building on Bayesian ideas of auditory perception and auditory neuroscience, 'meta-listening' offers a framework for more comprehensive research into how metacognition in humans and non-humans shapes the listening brain.

Increase in slow frequency and decrease in alpha and beta power during post-learning rest predict long-term memory success

Formation of episodic memories is linked to cortico-hippocampal interactions during learning, practice, and post-learning rest, although the role of cortical activity itself in such processes remains elusive. Behaviorally, long-term retention of episodic memories has been shown to be aided by several different practice strategies involving memory reencounters, such as repeated retrieval and repeated study. In a two-session resting state electroencephalography (EEG) experiment, using data from 68 participants, we investigated the electrophysiological predictors of long-term memory success in situations where such reencounters occurred after learning. Participants learned word pairs which were subsequently practiced either by cued recall or repeated studying in a between-subjects design. Participants' cortical activity was recorded before learning (baseline) and after practice during 15-min resting periods. Long-term memory retention after a 7-day period was measured. To assess cortical activity, we analyzed the change in spectral power from the pre-learning baseline to the post-practice resting state recordings. From baseline to post-practice, changes in alpha and beta power were negatively, while slow frequency power change was positively associated with long-term memory performance, regardless of practice strategy. These results are in line with previous observations pointing to the role of specific frequency bands in memory formation and extend them to situations where memory reencounters occur after learning. Our results also highlight that the effectiveness of practice by repeated testing seems to be independent from the beneficial neural mechanisms mirrored by EEG frequency power changes.

Hemispheric alpha asymmetry differentiates within-participants social power states: high social power increases and low social power decreases left frontal cortical activity

Social power is linked to approach and withdrawal motivational systems, with frontal alpha asymmetry (FAA) in the electroencephalogram (EEG) potentially reflecting these tendencies. Higher left-frontal activity suggests approach, while lower levels indicate withdrawal. In this study, we used a novel within-subject design to explore how social power affects FAA. Twenty-five participants completed an episodic recall task inducing high or low social power, or a neutral condition, in random order. EEG alpha power (8-12 hz) was measured to calculate FAA indices for frontal and parietal-occipital regions and compared to resting-state asymmetry. Results showed a significant increase in left-hemispheric activity during high social power recall, affecting both frontal and non-frontal regions, compared to low power and control conditions. Low social power was associated with the least left hemispheric activity. These findings highlight strong effects of social power on brain systems related to approach and avoidance but challenge the notion that FAA is confined to frontal regions. The study enhances understanding of the neural mechanisms behind social power and underscores the value of within-subject designs and baseline measurements in studying neural activity related alpha asymmetry and social power.

The Interplay Between Multisensory Processing and Attention in Working Memory: Behavioral and Neural Indices of Audiovisual Object Storage

Although real-life events are multisensory, how audio-visual objects are stored in working memory is an open question. At a perceptual level, evidence shows that both top-down and bottom-up attentional processes can play a role in multisensory interactions. To understand how attention and multisensory processes interact in working memory, we designed an audiovisual delayed match-to-sample task in which participants were presented with one or two audiovisual memory items, followed by an audiovisual probe. In different blocks, participants were instructed to either (a) attend to the auditory features, (b) attend to the visual features, or (c) attend to both auditory and visual features. Participants were instructed to indicate whether the task-relevant features of the probe matched one of the task-relevant feature(s) or objects in working memory. Behavioral results showed interference from task-irrelevant features, suggesting bottom-up integration of audiovisual features and their automatic encoding into working memory, irrespective of task relevance. Yet, event-related potential analyses revealed no evidence for active maintenance of these task-irrelevant features, while they clearly taxed greater attentional resources during recall. Notably, alpha oscillatory activity revealed that linking information between auditory and visual modalities required more attentional demands at retrieval. Overall, these results offer critical insights into how and at which processing stage multisensory interactions occur in working memory.

Takeover and non-driving related task performance in conditional automated driving: EEG and behavior Parameters interaction

In this study, a conditional automated driving scenario is simulated using virtual reality (VR) technology to explore whether office works presented through augmented reality (AR) affect task and takeover performance, and the neural mechanism was revealed. Sixty-four participants were recruited and their electroencephalography (EEG) was used to measure the brain activities. The results indicated that non-driving-related tasks (NDRTs) requiring higher internal attention focus resulted in poorer task and takeover performance. The alpha power decline magnitude in the parietotemporal (PT) was positively correlated with the takeover time; and the greater the alpha power decline in the right centroparietal (CP) hemisphere, the worse is the participants' memory quality for NDRTs. The ventral attention network (VAN) and right parietal cortex, which are active during working memory, are more likely to explain these findings. The results can provide suggestions for the design of AR-ADS and help improve the safety in L3 driving automation systems.

Be ready to manage stress "Before" and "After" a critical event. What the EEG and autonomic correlates tell us

This study examined behavioral, electrophysiological (EEG), and autonomic responses to stress during the preparation and speech stages of five discourses among 26 adults. Participants underwent an increasingly stressful job-interview based on a modified Trier Social Stress Test, receiving feedback from an evaluative board. Findings showed increased RTs, higher cardiovascular responses [Pulse Volume Amplitude (PVA), and Heart Rate Variability (HRV)] and generalized increases in EEG frequency bands (delta, theta, alpha, beta, gamma) during the speech compared to the preparation stage. The rising emotional salience of the discourses induced a negativity bias and extensive low-frequency band activation (delta and theta) across the scalp in response to emotional demands. High-frequency bands exhibited a plateau effect, indicating less cognitive involvement as the discourses progressed. In our opinion, a possible interpretation is that this effect could be due to habituation mechanisms or coping strategies. Autonomic results revealed significant variations in PVA, with higher levels during the first discourse preparation, indicating substantial cognitive effort. Despite increased emotional arousal, participants managed stress effectively, as evidenced by increased HRV during the speech stage. Overall, during progressively increasing ecological psychosocial stress, individuals displayed marked emotional reactions in terms of low-frequency bands and cardiovascular indices, particularly during the first speeches rather than the preparation stages of an interview.

Memory load influences our preparedness to act on visual representations in working memory without affecting their accessibility

It is well established that when we hold more content in working memory, we are slower to act upon part of that content when it becomes relevant for behavior. Here, we asked whether this load-related slowing is due to slower access to the sensory representations held in working memory (as predicted by serial working-memory search), or by a reduced preparedness to act upon those sensory representations once accessed. To address this, we designed a visual-motor working-memory task in which participants memorized the orientation of two or four colored bars, of which one was cued for reproduction. We independently tracked EEG markers associated with the selection of visual (cued item location) and motor (relevant manual action) information from the EEG time-frequency signal, and compared their latencies as a function of memory load. We confirm slower memory-guided behavior with higher working-memory load and show that this is associated with delayed motor selection. In contrast, we find no evidence for a concomitant delay in the latency of visual selection. Moreover, we show that variability in decision times within each memory-load condition is associated with corresponding changes in the latency of motor, but not visual selection. These results reveal how memory load affects our preparedness to act on sensory representations in working memory, while leaving sensory access itself unaffected. This posits action readiness as a key factor that shapes the speed of memory-guided behavior and that underlies delayed responding with higher working-memory load.

Meditation expertise influences response bias and prestimulus alpha activity in the somatosensory signal detection task

This study investigates the proposed mechanism of mindfulness, its impact on body awareness and interoception, and its potential benefits for mental and physical health. Using psychophysical assessments, we compared 31 expert meditators with 33 matched controls (non-meditators who engage in regular reading, more than 5 h per week) in terms of somatosensory accuracy with a somatosensory signal detection task (SSDT) and interoceptive sensibility via self-report measures. We hypothesized that meditators would demonstrate superior somatosensory accuracy, indicative of heightened body awareness, potentially linked to increased alpha modulation in the somatosensory cortex, as observed via electroencephalography (EEG). In the SSDT, participants attempted to detect near-threshold tactile stimuli presented with a non-informative light in half of the trials. Contrary to our expectations, the findings showed that meditators had a lower decision threshold rather than higher accuracy. EEG results corroborated earlier research, indicating reduced prestimulus alpha power in meditators, suggesting enhanced alpha modulation. Furthermore, a trial-by-trial analysis revealed a negative correlation between prestimulus alpha activity and tactile perception. Compared to controls, meditators also reported greater interoceptive sensibility, less emotional suppression, and fewer difficulties in describing feelings. These findings may imply that enhanced tactile perception is associated with lower prestimulus alpha activity by reducing sensory filtering in the somatosensory cortex, thus increasing response rates without necessarily improving accuracy among meditators.

The Neurophysiological Costs of Learning in a Noisy Classroom: An Ecological Virtual Reality Study

Many real-life situations can be extremely noisy, which makes it difficult to understand what people say. Here, we introduce a novel audiovisual virtual reality experimental platform to study the behavioral and neurophysiological consequences of background noise on processing continuous speech in highly realistic environments. We focus on a context where the ability to understand speech is particularly important: the classroom. Participants (n = 32) experienced sitting in a virtual reality classroom and were told to pay attention to a virtual teacher giving a lecture. Trials were either quiet or contained background construction noise, emitted from outside the classroom window. Two realistic types of noise were used: continuous drilling and intermittent air hammers. Alongside behavioral outcomes, we measured several neurophysiological metrics, including neural activity (EEG), eye-gaze and skin conductance (galvanic skin response). Our results confirm the detrimental effect of background noise. Construction noise, and particularly intermittent noise, was associated with reduced behavioral performance, reduced neural tracking of the teacher's speech and an increase in skin conductance, although it did not have a significant effect on alpha-band oscillations or eye-gaze patterns. These results demonstrate the neurophysiological costs of learning in noisy environments and emphasize the role of temporal dynamics in speech-in-noise perception. The finding that intermittent noise was more disruptive than continuous noise supports a "habituation" rather than "glimpsing" hypothesis of speech-in-noise processing. These results also underscore the importance of increasing the ecologically relevance of neuroscientific research and considering acoustic, temporal, and semantic features of realistic stimuli as well as the cognitive demands of real-life environments.

Pre-stimulus activities affect subsequent visual processing: Empirical evidence and potential neural mechanisms

PURPOSE

Humans obtain most of their information from visual stimuli. The perception of these stimuli may be modulated by the ongoing pre-stimulus brain activities. Depending on the task design, the processing of different cognitive functions such as spatial attention, feature-based attention, temporal attention, arousal, and mental imagery may start prior to the stimulus onset.

METHOD

This process is typically accompanied by changes in pre-stimulus oscillatory activities including power, phase, or connectivity in different frequency bands. To explain the effect of these changes, several mechanisms have been proposed. In this article, we review these changes and the potential mechanisms in the context of the pre-stimulus enabled cognitive functions. We provide evidence both in favor of and against the most documented mechanisms and conclude that no single mechanism can solely delineate the effects of pre-stimulus brain activities on later processing. Instead, multiple mechanisms may work in tandem to guide pre-stimulus brain activities.

FINDING

Additionally, our findings indicate that in many studies a combination of these cognitive functions begins prior to stimulus onset.

CONCLUSION

Thus, dissociating these cognitive functions is challenging based on the current literature, and the need for precise task designs in later studies to differentiate between them is crucial.

The Suppression Mechanisms of Passive Memory in Visual Working Memory: The Evidence from Electroencephalography

Recent studies of visual working memory (VWM) underscore a structured hierarchy of storage states. Memories that are not immediately relevant to the task at hand but are essential for later use are transferred to a passive state, which operates independently of actively maintaining and manipulating current memories. Note that stimulating passive memory forcefully can reactivate it into an active state, resulting in a competition with active memory. Thus, to remain stable representations for both states within VWM, passive memory might involve sustained suppression during activity-silent maintenance to prevent reactivation from disrupting the current active storage. To investigate this, we analyzed lateralized EEG signals while human participants (both women and men) were engaged in a sequential presentation memory task across two experiments. The results revealed positive contralateral delayed activity components and lateralized alpha enhancement for passive memory, neural indicative of suppression on passive storage. In addition, the suppression effect was independent of the memory load in both the active and the passive states. These findings support the notion of sustained suppression during activity-silent maintenance of passive memory, facilitating the stable maintenance of distinct storage states and advancing our understanding of the dynamic coding framework in VWM.

Alpha oscillations protect auditory working memory against distractors in the encoding phase

Alpha oscillations are proposed to serve the function of inhibition to protect items in working memory from intruding information. In a modified Sternberg paradigm, alpha power was initially found to increase at the anticipation of strong compared to weak distractors, reflecting the active gating of distracting information from interfering with the memory trace. However, there was a lack of evidence supporting the inhibition account of alpha oscillations in later studies using similar experimental design with greater temporal disparity between the encoding phase and the presentation of the distractors. This temporal disparity might have dampened the demands for inhibition. To test the hypothesis that alpha inhibition takes place when distractors are temporally close to the encoding phase, here we designed a modified Sternberg paradigm where distractors were sandwiched between targets in the encoding phase to ensure that they compete for working memory resources. Using electroencephalography (EEG), we replicated the finding that alpha power increased for strong compared to weak distractors. The effect was present throughout the encoding phase, not only upon the presentation of distractors but also before and after the presentation of distractors, providing evidence for both proactive and reactive inhibition of distractors at the neuronal level. Meanwhile, the effect was restricted to the context of high but not low target-to-distractor ratio. The results suggest that the distractors being temporally close to the encoding phase of more targets might be a boundary condition of the generation of alpha oscillations for gating.

Beta oscillations predict the envelope sharpness in a rhythmic beat sequence

Periodic sensory inputs entrain oscillatory brain activity, reflecting a neural mechanism that might be fundamental to temporal prediction and perception. Most environmental rhythms and patterns in human behavior, such as walking, dancing, and speech do not, however, display strict isochrony but are instead quasi-periodic. Research has shown that neural tracking of speech is driven by modulations of the amplitude envelope, especially via sharp acoustic edges, which serve as prominent temporal landmarks. In the same vein, research on rhythm processing in music supports the notion that perceptual timing precision varies systematically with the sharpness of acoustic onset edges, conceptualized in the beat bin hypothesis. Increased envelope sharpness induces increased precision in localizing a sound in time. Despite this tight relationship between envelope shape and temporal processing, it is currently unknown how the brain uses predictive information about envelope features to optimize temporal perception. With the current EEG study, we show that the predicted sharpness of the amplitude envelope is encoded by pre-target neural activity in the beta band (15-25 Hz), and has an impact on the temporal perception of target sounds. We used probabilistic sound cues in a timing judgment task to inform participants about the sharpness of the amplitude envelope of an upcoming target sound embedded in a beat sequence. The predictive information about the envelope shape modulated task performance and pre-target beta power. Interestingly, these conditional beta-power modulations correlated positively with behavioral performance in the timing judgment task and with perceptual temporal precision in a click-alignment task. This study provides new insight into the neural processes underlying prediction of the sharpness of the amplitude envelope during beat perception, which modulate the temporal perception of sounds. This finding could reflect a process that is involved in temporal prediction, exerting top-down control on neural entrainment via the prediction of acoustic edges in the auditory stream.

Interhemispheric paired associative stimulation targeting the bilateral prefrontal cortex of subjects with obesity and food addiction modulates food-related emotional reactivity and associated brain activity

PURPOSE

Behavioral and neurobiological abnormalities in addiction and obesity have led to the theory of food addiction in obesity (FAOB) and brain-behavior association studies. Transcranial magnetic stimulation (TMS) studies and treats various brain disorders. Cortico-cortical paired associative stimulation TMS protocol, in which left lateral prefrontal cortex (LPFC) stimulation follows right LPFC stimulation, can reduce emotional reactivity to visual triggers and modulate prefrontal asymmetry in healthy adults. Accordingly, we examined the effects of acute ccPAS on food cravings and brain responses in FAOB.

METHODS

Twenty-two adults (12 Active, 10 Sham) with FAOB participated in this single-blind, sham-controlled pilot study. Electroencephalogram was recorded during rest and a Food Stroop task, which were conducted before and after a single active or sham ccPAS session, consisting of 600 paired stimulation pulses of the right, then left LPFC, with inter-pulse interval of 8ms and a 3sec inter-pair-interval. Stroop bias changes following exposure to food images, alterations in the associated (emotionally laden) late positive event-related component (LPPb) total brain activity power, and frontal alpha band asymmetry during rest and task performance were investigated.

RESULTS

No baseline differences were detected between the groups, except for education level. Active (but not Sham) ccPAS elevated the Stroop bias and the total brain activity power over the left LPFC while no stimulation-related influence was found on the LPPb or prefrontal brain asymmetry during task and the resting state. However, the stimulation-induced change in the Stroop bias was negatively correlated with the change in LPPb magnitude, positively correlated with changes in asymmetrical activity during the task, and negatively with left frontal alpha asymmetry during rest.

CONCLUSIONS

The ccPAS affected food-related emotional regulation, probably due to general reduction of inhibitory control during task performance. Further studies are needed to affirm the results with larger samples and to elucidate the development of beneficial ccPAS protocol for obesity with food addiction.

qEEG Neuromarkers of Complex Childhood Trauma in Adolescents

Introduction. Complex childhood trauma (CCT) involves prolonged exposure to severe interpersonal stressors, leading to deficits in executive functioning and self-regulation during adolescence, a critical period for neurodevelopment. While qEEG parameters, particularly alpha oscillations, have been proposed as potential biomarkers for trauma, empirical documentation in developmental samples is limited. Aim. This preregistered study investigated whether adolescents with CCT exhibit qEEG patterns similar to those reported for PTSD, such as reduced posterior alpha power, increased individual alpha peak frequency (iAPF), right-lateralized alpha frequencies, and lower total EEG power (RMS) compared to controls. Materials and Methods. EEG data from 26 trauma-exposed adolescents and 28 controls, sourced from an open database, underwent similar preprocessing. qEEG features, including alpha power, iAPF, alpha asymmetry, and RMS, were extracted from eyes-open and eyes-closed conditions and analyzed using mixed ANOVAs. Results. Significant group differences were found in total EEG power, with trauma-exposed adolescents showing lower RMS than controls. No significant differences were found in posterior absolute alpha power, iAPF, or alpha asymmetry. However, we observed that posterior relative alpha power was higher in the trauma group, though the difference was not statistically significant but showing a small to medium effect size. Additionally, a negative correlation between CPTSD severity and EEG power in the EO condition was observed, suggesting trauma-related cortical hypoactivation. Conclusion. Reduced total EEG power and modified alpha dynamics may serve as candidate neuromarkers of CCT. These findings underscore the need for further research to validate qEEG biomarkers for understanding and diagnosing trauma-related disorders in developmental populations.

Evaluation of Machine Learning Algorithms for Classification of Visual Stimulation-Induced EEG Signals in 2D and 3D VR Videos

BACKGROUNDS

Virtual reality (VR) has become a transformative technology with applications in gaming, education, healthcare, and psychotherapy. The subjective experiences in VR vary based on the virtual environment's characteristics, and electroencephalography (EEG) is instrumental in assessing these differences. By analyzing EEG signals, researchers can explore the neural mechanisms underlying cognitive and emotional responses to VR stimuli. However, distinguishing EEG signals recorded by two-dimensional (2D) versus three-dimensional (3D) VR environments remains underexplored. Current research primarily utilizes power spectral density (PSD) features to differentiate between 2D and 3D VR conditions, but the potential of other feature parameters for enhanced discrimination is unclear. Additionally, the use of machine learning techniques to classify EEG signals from 2D and 3D VR using alternative features has not been thoroughly investigated, highlighting the need for further research to identify robust EEG features and effective classification methods.

METHODS

This study recorded EEG signals from participants exposed to 2D and 3D VR video stimuli to investigate the neural differences between these conditions. Key features extracted from the EEG data included PSD and common spatial patterns (CSPs), which capture frequency-domain and spatial-domain information, respectively. To evaluate classification performance, several classical machine learning algorithms were employed: ssupport vector machine (SVM), k-nearest neighbors (KNN), random forest (RF), naive Bayes, decision Tree, AdaBoost, and a voting classifier. The study systematically compared the classification performance of PSD and CSP features across these algorithms, providing a comprehensive analysis of their effectiveness in distinguishing EEG signals in response to 2D and 3D VR stimuli.

RESULTS

The study demonstrated that machine learning algorithms can effectively classify EEG signals recorded during watching 2D and 3D VR videos. CSP features outperformed PSD in classification accuracy, indicating their superior ability to capture EEG signals differences between the VR conditions. Among the machine learning algorithms, the Random Forest classifier achieved the highest accuracy at 95.02%, followed by KNN with 93.16% and SVM with 91.39%. The combination of CSP features with RF, KNN, and SVM consistently showed superior performance compared to other feature-algorithm combinations, underscoring the effectiveness of CSP and these algorithms in distinguishing EEG responses to different VR experiences.

CONCLUSIONS

This study demonstrates that EEG signals recorded during watching 2D and 3D VR videos can be effectively classified using machine learning algorithms with extracted feature parameters. The findings highlight the superiority of CSP features over PSD in distinguishing EEG signals under different VR conditions, emphasizing CSP's value in VR-induced EEG analysis. These results expand the application of feature-based machine learning methods in EEG studies and provide a foundation for future research into the brain cortical activity of VR experiences, supporting the broader use of machine learning in EEG-based analyses.

A Computational Account of the Development and Evolution of Psychotic Symptoms

The mechanisms of psychotic symptoms such as hallucinations and delusions are often investigated in fully formed illness, well after symptoms emerge. These investigations have yielded key insights but are not well positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing a compensatory relative overreliance on prior beliefs. This overreliance on priors predisposes to hallucinations and covaries with hallucination severity. An overreliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptoms as a point of equilibrium among competing biological forces.

Investigating the effect of mindfulness training for stress management in military training: the relationship between the autonomic nervous system and emotional regulation

BACKGROUND

Military personnel face an increased risk of developing mental disorders owing to the stressful environments they encounter. Effective stress management strategies are crucial to mitigate this risk. Mindfulness training (MT) is promising as a stress management approach in such demanding settings. This study uses a quantitative approach to investigate the impact of MT on the relationship between the autonomic nervous system (ANS) and emotional regulation.

METHODS

The study evaluated the effectiveness of MT in reducing stress among 86 military personnel. Participants were divided into two groups: MT (n = 42) and non-MT (n = 38). The study compared the two groups using measures of heart rate variability (HRV), a reliable indicator of ANS activity.

RESULTS

The MT group exhibited a significant increase in HRV (14.4%, p = 0.001) and alpha asymmetry (AA) in the frontal lobe (45.7%, p < 0.001) compared to the non-MT group. Notably, the MT group achieved significantly higher scores on the parachute landing fall (PLF) training performance (p < 0.001). These improvements in HRV, AA, and PLF performance were strongly correlated. Furthermore, AA fully mediated the relationship between HRV and PLF training performance.

CONCLUSIONS

The findings suggest that MT has a positive impact on stress resilience, potentially by mitigating anxiety and attention deficits induced by extreme stressors. These positive effects are facilitated by concurrent modulation of the frontal cortex and autonomic nervous system. Our findings provide insight into the neural mechanisms behind MT-induced stress reduction from the perspective of neuromodulation.

Optimizing electrode configurations for EEG mild cognitive impairment detection

The Optimal electrode configuration of Electroencephalograms (EEG) systems for mild cognitive impairment (MCI) detection and monitoring in non-clinical settings, i.e. number of electrodes and the positions of the electrodes, remains to be explored. In the current study, we explored the optimization of electrode configuration for MCI detection. We used a 32-channel EEG device to record the data of 21 MCI patients and 20 cognitively normal elderly (NC) undergoing working memory (WM) tasks. Based on the differential value (MCI group vs. NC group) from the Power Spectral Density (PSD) value of each electrode in θ and α frequency band during WM coding stage, six different electrode configurations were obtained: (1) four electrodes in the occipital lobe (OCL4); (2) three electrodes in the prefrontal lobe (PRL3); (3) four electrodes in the parietal lobe (PLL4), (4) eight electrodes in occipital combined parietal lobe (OPL8), (5) seven electrodes in occipital combined prefrontal lobe (OPL7); and (6) seven electrodes in parietal combined prefrontal lobe (PPL7). A multi-parameter combination-assisted binary logistic regression model was established to distinguish two groups. Receiver operating characteristic (ROC) curves were used to evaluate the MCI diagnostic power of each electrode configuration. The area under curve (AUC) of the ROC of electrode configurations OCL4, PRL3, PLL4, OPL8, OPL7 and PPL7 were 0.765, 0.683, 0.729, 0.83, 0.788, and 0.769, respectively. And the sensitivity of six electrode configurations were 0.962, 0.794, 0.873, 0.943, 0.859, and 0.938, respectively. Among these six configurations, OCL4, i.e. PO3, PO4, PO8, and PO7, had the highest sensitivity 96.2%, which meant that relying solely on these four electrodes of the occipital lobe had the potential to serve as an objective tool for preliminary screening of MCI. The abnormal brain rhythm characteristics of the frontal, parietal, and occipital lobes in the memory encoding stage of MCI provide a new perspective for MCI-WM impairment, which has the potential to be a novel biomarker for the early detection of pathological age-related cognitive decline. Further, a potential four-electrode configuration may be used for a novel detecting and monitoring EEG system of MCI in non-clinical settings.

The role of brain oscillatory activity in processing the informative value of feedback during rule acquisition

Information conveyed through feedback enables individuals to learn new routines and better adapt to their environment. However, the neural mechanisms of rule-related information of feedback have not been fully elucidated. Herein, we quantified the effect of informative value on feedback via a rule induction task (RIT), in which participants were required to find the correct sorting rule based on feedback. To disengage the effects of informative value and valence on feedback in the RIT, a control task was developed in which feedback only involved the valence aspect and no reference for subsequent selections. We measured power and intertrial phase clustering (ITPC) values via EEG to determine the neural mechanisms of rule-related feedback. The results revealed that (1) differences in oscillatory activities between positive and negative feedback were only observed during the control task, and no such effect was found in the RIT task. This finding suggests that the participants paid more attention to rule-related information than to the correctness of feedback during rule learning. (2) The task differences under positive or negative feedback were associated with the delta-theta and alpha-beta bands, and this pattern was similar within the frontal and parietal regions. These findings suggest that the processing of rule-related information of feedback relies on broad frequency bands within the frontoparietal cortex to facilitate rule information integration. In summary, these findings indicate that multiple frequency bands are involved in encoding the informative value aspect of feedback, and individuals rely on this aspect of feedback rather than valence during rule learning.

The impact of speaker accent on discourse processing: A frequency investigation

Previous studies indicate differences in native and foreign speech processing (Lev-Ari, 2018), with mixed evidence for differences between dialectal and foreign accent processing (Adank, Evans, Stuart-Smith, & Scott, 2009; Floccia et al., 2006, 2009; Girard, Floccia, & Goslin, 2008). Two theories have been proposed: The Perceptual Distance Hypothesis suggests that dialectal accent processing is an attenuated version of foreign accent processing (Clarke & Garrett, 2004), while the Different Processes Hypothesis argues that foreign and dialectal accents are processed via distinct mechanisms (Floccia, Butler, Girard, & Goslin, 2009). A recent single-word ERP study suggested flexibility in these mechanisms (Thomas, Martin, & Caffarra, 2022). The present study deepens this investigation by investigating differences in native, dialectal, and foreign accent processing across frequency bands during extended speech. Electroencephalographic data was recorded from 30 participants who listened to dialogues of approximately six minutes spoken in native, dialectal and foreign accents. Power spectral density estimation (1-35 Hz) was performed. Linear mixed models were done in frequency windows of particular relevance to discourse processing. Frequency bands associated with phoneme [gamma], syllable [theta], and prosody [delta] were considered along with those of general cognitive mechanisms [alpha and beta]. Results show power differences in the Gamma frequency range. While in higher frequency ranges foreign accent processing is differentiated from power amplitudes of native and dialectal accent processing, in low frequencies we do not see any accent-related power amplitude modulations. This suggests that there may be a difference in phoneme processing for native accent types and foreign accent, while we speculate that top-down mechanisms during discourse processing may mitigate the effects observed with short units of speech.

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

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

Optimizing the identification of long-interval intracortical inhibition from the dorsolateral prefrontal cortex

OBJECTIVE

This study aimed to optimally evaluate the effect of the long-interval intracortical inhibition (LICI) in the dorsolateral prefrontal cortex (DLPFC) through transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) by eliminating the volume conductance with signal source estimation and using a realistic sham coil as a control.

METHODS

We compared the LICI effects from the DLPFC between the active and sham stimulation conditions in 27 healthy participants. Evoked responses between the two conditions were evaluated at the sensor and source levels.

RESULTS

At the sensor level, a significant LICI effect was confirmed in the active condition in the global mean field power analysis; however, in the local mean field power analysis focused on the DLPFC, no LICI effect was observed in the active condition. However, in the signal source estimation analysis for the DLPFC, we could reconfirm a significant LICI effect (p = 0.023) in the interval 30-250 ms post-stimulus, compared to the sham condition.

CONCLUSIONS

Our results demonstrate that application of realistic sham stimulation condition and source estimation method allows for a robust and optimal identification of the LICI effect in the DLPFC.

SIGNIFICANCE

The optimal DLPFC-LICI effect was identified by the use of the sophisticated sham coil.

Reduced resting and task-related alpha activity in mine workers: Implications for occupational health and neurodegenerative risk

Underground mine workers face many risk factors at work sites that are known to affect the neural system. Observational studies report that these risk factors precede neuromuscular and neurodegenerative disorders, especially in old-age miners. Neurodegenerative disorders have electrophysiological, anatomical, and functional changes long before symptoms are seen in older adults. Therefore, this study investigated whether risks faced by miners at young ages were reflected in electrophysiological signals. Twenty-one underground miners and twenty-two above-ground workers matched with them in terms of age, education, and working duration were included in this study. Participants were recorded with a 20-channel EEG during the resting-state (eyes open and closed; EO-EC) and the perception of the International Affective Picture System Paradigm (IAPS). Time-frequency analyses were performed for alpha frequency. Rs-EEG results showed a statistically significant difference in alpha power between the EO and EC states in the control group. However, there was no statistical difference in alpha power between these two conditions in the miners. Additionally, we noted a more pronounced decrease in alpha responses in the posterior region during EC in the miners. The group's main effects were statistically significant in event-related alpha responses during emotional responses. Accordingly, event-related alpha responses of the miner group were lower than the control group in terms of both power spectrum and phase-locking. Underground mine workers are cognitively and emotionally affected by risks in the work environment. Electrophysiological changes seen in young underground workers may be a harbinger of neurodegenerative disorders in miners' old age. Our research findings may lead to the development of occupational neuroscience, social policies, and worker health, which are necessary to improve working conditions for mineworkers.

Parietal alpha stimulation causally enhances attentional information coding in evoked and oscillatory activity

BACKGROUND

Selective attention is a fundamental cognitive mechanism that allows people to prioritise task-relevant information while ignoring irrelevant information. Previous research has suggested key roles of parietal event-related potentials (ERPs) and alpha oscillatory responses in attention tasks. However, the informational content of these signals is less clear, and their causal effects on the coding of multiple task elements are yet unresolved.

OBJECTIVE

To test the causal roles of alpha oscillations and ERPs in coding different types of attentional information (where to attend, what to attend to, and features of thevisual stimulus).

METHODS

We first used EEG to examine the temporal dynamics of alpha oscillations and ERPs in coding attentional information. Then, we applied rhythmic-TMS (rh-TMS) at individual alpha frequency over the right intraparietal sulcus (IPS), while concurrently measuring EEG, to causally manipulate parietal alpha power and ERPs and investigate their roles in coding multiple task features in a selective attention task.

RESULTS

EEG-only data suggested that ERPs coded all three types of task-relevant information with distinct temporal dynamics, while alpha oscillations carried information regarding both where to attend and what to attend to. TMS-EEG results indicated that, compared to arrhythmic-TMS, alpha rh-TMS increased alpha power and inter-trial phase coherence and yielded more negative posterior-contralateral ERPs. Moreover, alpha rh-TMS specifically and causally improved multivariate decoding of information about where to attend (but not what to attend to or visual feature information) during task performance, with decoding improvements predicting changes in behavioural performance.

CONCLUSIONS

These findings illuminate the dynamics with which the complementary aspects of a selective attention task are encoded in evoked and oscillatory brain activity. Moreover, they reveal a specific and causal role of IPS-controlled evoked and oscillatory activity in carrying behaviour-driving information exclusively about where to focus attention.

Alpha and Theta Oscillations Associated With Behavioral Phenotypes of Pain-Attention Interaction

PURPOSE

Pain is inherently salient and so draws our attention in addition to impacting performance on attention-demanding tasks. Individual variability in pain-attention interactions can be assessed by two kinds of behavioral phenotypes that quantify how individuals prioritize pain versus attentional needs. The intrinsic attention to pain (IAP) measure quantifies the degree to which a person attends to pain (high-IAP) or mind-wanders away from pain (low-IAP). The A/P categorization quantifies how pain impacts cognitive performance during an attention-demanding task classifying individuals into P type (pain dominates, worse performance during pain in comparison to no pain) and A type (attention to task dominates, better performance during pain in comparison to no pain). Although previous MRI-based studies have linked these phenotypes with the dynamic pain connectome (DPC), the underlying neural oscillations are not known. This paper aims to examine the brain-behavior relationship between alpha and theta oscillations within nodes of the DPC and pain-attention phenotypes.

METHOD

Fifty participants (27 F, 23 M) underwent resting-state magnetoencephalography (MEG). Individual IAP scores were determined by assessing mind-wandering during pain and A/P type was based on interference of pain with cognitive task performance.

FINDING

The main findings were: (1) peak alpha frequency (PAF) power did not differ between low/high-IAP individuals or A/P-type individuals within the nodes of the DPC; (2) compared to high-IAP individuals, those with low-IAP have slower PAF in the left primary somatosensory cortex, posterior cingulate cortex and precuneus and higher theta power in the ascending nociceptive pathway and default mode network; (3) males with low-IAP, compared to females, had higher PAF power throughout the DPC.

CONCLUSION

Alpha and theta oscillations within the DPC may underlie aspects of attentional focus and pain-attention interactions.

Oscillatory Brain Activity in the Canonical Alpha-Band Conceals Distinct Mechanisms in Attention

Brain oscillations in the alpha-band (8-14 Hz) have been linked to specific processes in attention and perception. In particular, decreases in posterior alpha-amplitude are thought to reflect activation of perceptually relevant brain areas for target engagement, while alpha-amplitude increases have been associated with inhibition for distractor suppression. Traditionally, these alpha-changes have been viewed as two facets of the same process. However, recent evidence calls for revisiting this interpretation. Here, we recorded MEG/EEG in 32 participants (19 females) during covert visuospatial attention shifts (spatial cues) and two control conditions (neutral cue, no-attention cue), while tracking fixational eye movements. In disagreement with a single, perceptually relevant alpha-process, we found the typical alpha-modulations contra- and ipsilateral to the attention focus to be triple dissociated in their timing, topography, and spectral features: Ipsilateral alpha-increases occurred early, over occipital sensors, at a high alpha-frequency (10-14 Hz) and were expressed during spatial attention (alpha spatial cue > neutral cue). In contrast, contralateral alpha-decreases occurred later, over parietal sensors, at a lower alpha-frequency (7-10 Hz) and were associated with attention deployment in general (alpha spatial and neutral cue < no-attention cue). Additionally, the lateralized early alpha-increases but not alpha-decreases during spatial attention coincided in time with directionally biased microsaccades. Overall, this suggests that the attention-related early alpha-increases and late alpha-decreases reflect distinct, likely reflexive versus endogenously controlled attention mechanisms. We conclude that there is more than one perceptually relevant posterior alpha-oscillation, which need to be dissociated for a detailed account of their roles in perception and attention.

Near-critical corticothalamic eigenmodes: Effects of nonuniform connectivity on modes, activity, and communication channels

The effects of nonuniformities in axonal connectivity on natural modes of brain activity are explored to determine their contributions to modal eigenvalues, structure, and communication and to clarify the limits of validity of widely used uniform-connectivity approximations. Preferred channels of communication are demonstrated that are supported by natural modes of mean connectivity and resulting activity. The effects of axonal tracts on these modes are calculated using perturbation methods, and it is found that modes and their spectra are only moderately perturbed by even the largest white matter tracts. However, perturbations of activity are greatly magnified when modes are near-critical and realistic connectivity and gain perturbations can then enable rapid responses to stimuli on the observed timescales of evoked responses. It is thus argued that dynamic mode-mode communication channels complement ones based on white matter tracts and that both rely on near-criticality to have their observed effects.

Increased alpha power in autistic adults: Relation to sensory behaviors and cortical volume

Alpha-band (~10 Hz) neural oscillations, crucial for gating sensory information, may offer insights into the atypical sensory experiences characteristic of autism spectrum disorder (ASD). We investigated alpha-band EEG activity in autistic adults (n = 29) compared with a nonautistic group (n = 23) under various stimulus-driven and resting-state conditions. The autistic group showed consistently higher alpha amplitude across all time points. In addition, there was proportionally more suppression of alpha at stimulus onset in the autistic group, and alpha amplitude in this stimulus-onset period correlated with sensory behaviors. Recent research suggests a link between subcortical structures' volume and cortical alpha magnitude. Prompted by this, we explored the association between alpha power and the volume of subcortical structures and total cortical volume in ASD. Our findings indicate a significant correlation with total cortical volume and a group by hippocampal volume interaction, pointing to the potential role of anatomical structural characteristics as potential modulators of cortical alpha oscillations in ASD. Overall, the results highlight altered alpha in autistic individuals as potentially contributing to the heightened sensory symptoms in autistic compared with nonautistic adults.

Neurofeedback and attention modulate somatosensory alpha oscillations but not pain perception

Pain is closely linked to alpha oscillations (8 < 13 Hz) which are thought to represent a supra-modal, top-down mediated gating mechanism that shapes sensory processing. Consequently, alpha oscillations might also shape the cerebral processing of nociceptive input and eventually the perception of pain. To test this mechanistic hypothesis, we designed a sham-controlled and double-blind electroencephalography (EEG)-based neurofeedback study. In a short-term neurofeedback training protocol, healthy participants learned to up- and down-regulate somatosensory alpha oscillations using attention. Subsequently, we investigated how this manipulation impacts experimental pain applied during neurofeedback. Using Bayesian statistics and mediation analysis, we aimed to test whether alpha oscillations mediate attention effects on pain perception. The results showed that attention and neurofeedback successfully up- and down-regulated the asymmetry of somatosensory alpha oscillations. However, attention and neurofeedback did not modulate pain ratings or related brain responses. Accordingly, somatosensory alpha oscillations did not mediate attention effects on pain perception. Thus, our results challenge the hypothesis that somatosensory alpha oscillations shape pain perception. A causal relationship between alpha oscillations and pain perception might not exist or be more complex than hypothesized. Trial registration: Following Stage 1 acceptance, the study was registered at ClinicalTrials.gov NCT05570695.

Naturalistic reading of multi-page texts elicits spatially extended modulation of oscillatory activity in the right hemisphere

The study of the cortical basis of reading has greatly benefited from the use of naturalistic paradigms that permit eye movements. However, due to the short stimulus lengths used in most naturalistic reading studies, it remains unclear how reading of texts comprising more than isolated sentences modulates cortical processing. To address this question, we used magnetoencephalography to study the spatiospectral distribution of oscillatory activity during naturalistic reading of multi-page texts. In contrast to previous results, we found abundant activity in the right hemisphere in several frequency bands, whereas reading-related modulation of neural activity in the left hemisphere was quite limited. Our results show that the role of the right hemisphere may be importantly emphasized as the reading process extends beyond single sentences.

Physiological Entrainment: A Key Mind-Body Mechanism for Cognitive, Motor and Affective Functioning, and Well-Being

BACKGROUND

The human sensorimotor system can naturally synchronize with environmental rhythms, such as light pulses or sound beats. Several studies showed that different styles and tempos of music, or other rhythmic stimuli, have an impact on physiological rhythms, including electrocortical brain activity, heart rate, and motor coordination. Such synchronization, also known as the "entrainment effect", has been identified as a crucial mechanism impacting cognitive, motor, and affective functioning.

OBJECTIVES

This review examines theoretical and empirical contributions to the literature on entrainment, with a particular focus on the physiological mechanisms underlying this phenomenon and its role in cognitive, motor, and affective functions. We also address the inconsistent terminology used in the literature and evaluate the range of measurement approaches used to assess entrainment phenomena. Finally, we propose a definition of "physiological entrainment" that emphasizes its role as a fundamental mechanism that encompasses rhythmic interactions between the body and its environment, to support information processing across bodily systems and to sustain adaptive motor responses.

METHODS

We reviewed the recent literature through the lens of the "embodied cognition" framework, offering a unified perspective on the phenomenon of physiological entrainment.

RESULTS

Evidence from the current literature suggests that physiological entrainment produces measurable effects, especially on neural oscillations, heart rate variability, and motor synchronization. Eventually, such physiological changes can impact cognitive processing, affective functioning, and motor coordination.

CONCLUSIONS

Physiological entrainment emerges as a fundamental mechanism underlying the mind-body connection. Entrainment-based interventions may be used to promote well-being by enhancing cognitive, motor, and affective functions, suggesting potential rehabilitative approaches to enhancing mental health.

The Brain Waves During Reaching Tasks in People with Subacute Low Back Pain: A Cross-Sectional Study

Subacute low back pain (sLBP) is a critical transitional phase between acute and chronic stages and is key in determining the progression to chronic pain. While persistent pain has been linked to changes in brain activity, studies have focused mainly on acute and chronic phases, leaving neural changes during the subacute phase-especially during movement-under-researched. This cross-sectional study aimed to investigate changes in brain activity and the impact of pain intensity in individuals with sLBP during rest and reaching movements. Using a 28-electrode EEG, we measured motor-related brain waves, including theta, alpha, beta, and gamma oscillations. Transitioning from rest to movement phases resulted in significant reductions (> 80%) in mean power across all frequency bands, indicating dynamic brain activation in response to movement. Furthermore, pain intensity was significantly correlated with brain wave activity. During rest, pain intensity was positively correlated with alpha oscillation activity in the central brain area (r = 0.40, p < 0.05). In contrast, during movement, pain intensity was negatively correlated with changes in brain activity (r = -0.36 to -0.40, p < 0.05). These findings suggest that pain influences brain activity differently during rest and movement, underscoring the impact of pain levels on neural networks related to the sensorimotor system in sLBP and highlighting the importance of understanding neural changes during this critical transitional phase.

Broadscale dampening of uncertainty adjustment in the aging brain

The ability to prioritize among input features according to relevance enables adaptive behaviors across the human lifespan. However, relevance often remains ambiguous, and such uncertainty increases demands for dynamic control. While both cognitive stability and flexibility decline during healthy ageing, it is unknown whether aging alters how uncertainty impacts perception and decision-making, and if so, via which neural mechanisms. Here, we assess uncertainty adjustment across the adult lifespan (N = 100; cross-sectional) via behavioral modeling and a theoretically informed set of EEG-, fMRI-, and pupil-based signatures. On the group level, older adults show a broad dampening of uncertainty adjustment relative to younger adults. At the individual level, older individuals whose modulation more closely resembled that of younger adults also exhibit better maintenance of cognitive control. Our results highlight neural mechanisms whose maintenance plausibly enables flexible task-set, perception, and decision computations across the adult lifespan.

The Effect of Left Temporal EEG Neurofeedback Training on Cerebral Cortical Activity and Precision Cognitive-Motor Performance

Objectives: The present study employed individualized magnitudes of electroencephalographic (EEG) alpha (8-12 hz) power in the left temporal (T3) region as a neurofeedback target parameter during the aiming period in pre-elite air pistol shooters to determine its effectiveness on cerebral cortical activation and performance accuracy compared to physical skill training, only. Method: Shooting scores and EEG activity in the left and right temporal regions were collected from 20 healthy air pistol shooters (10 assigned to neurofeedback training) before and after a 16-session intervention completed within 6 weeks. Specifically, EEG low-alpha (8-10 hz), high-alpha (10-13 hz) power, and coherence obtained at the T3-Fz and T4-Fz recording sites over three consecutive 1-s intervals prior to trigger pull, were subjected to three separate 2 × 2 × 2 × 3 (Group x Hemisphere x Time x Epoch) ANOVAs. Results: The neurofeedback group exhibited elevated low- and high-alpha EEG power across both temporal regions, but no differences in EEG broad-band alpha coherence, accompanied by enhanced performance after the intervention compared to the control group. Conclusions: The findings support the influence of neurofeedback training on cerebral cortical arousal and performance of a precision-aiming task, however, the influence of the neurofeedback on brain dynamics (i.e. alpha power) extended beyond the targeted region as a nonspecific manifestation of cerebral cortical inhibition leading to neural efficiency at the homologous sites.

Aperiodic and oscillatory systems underpinning human domain-general cognition

Domain-general cognitive systems are essential for adaptive human behaviour, supporting various cognitive tasks through flexible neural mechanisms. While fMRI studies link frontoparietal network activation to increasing demands across various tasks, the electrophysiological mechanisms underlying this domain-general response to demand remain unclear. Here, we used MEG/EEG, and separated the aperiodic and oscillatory components of the signals to examine their roles in domain-general cognition across three cognitive tasks using multivariate analysis. We found that both aperiodic (broadband power, slope, and intercept) and oscillatory (theta, alpha, and beta power) components coded task demand and content across all subtasks. Aperiodic broadband power in particular strongly coded task demand, in a manner that generalised across all subtasks. Source estimation suggested that increasing cognitive demand decreased aperiodic broadband power across the brain, with the strongest modulations overlapping with the frontoparietal network. In contrast, oscillatory activity showed more localised patterns of modulation, primarily in frontal or occipital regions. These results provide insights into the electrophysiological underpinnings of human domain-general cognition, highlighting the critical role of aperiodic broadband power.

Lateralized alpha oscillatory activity in the inferior parietal lobule to the right hemisphere during left-side visual stimulation

Understanding the neural mechanisms underlying spatial attention is crucial for unraveling the pathogenesis of unilateral spatial neglect (USN). However, the neural link between spatial attention and USN remains unclear. Thus, the neural mechanisms of spatial attention in the left and right hemispheres were compared. Twenty healthy volunteers participated in a hand mental rotation task in which they determined whether images depicted as left or right hands. The hand images were randomly displayed in the upper, lower, left, and right directions, centered on a fixation point. The laterality index for the alpha oscillatory activity was determined to assess the lateralization of neural activity during visual stimulation. Our results revealed a significant shift in alpha oscillatory neural activity in the inferior parietal lobule (IPL) towards the right hemisphere when visual stimulation occurred on the left side. In contrast, no significant oscillatory shift in the alpha band towards the left hemisphere was observed in the IPL when the visual stimulus was presented on the right side. These findings indicate that the spatial attention on the left side depends on oscillatory alpha activity in the right IPL, whereas that on the right side doesn't depend on either hemispheric alpha activity. These results provide valuable insights into the neural mechanisms of hemispatial neglect.

EEG correlates of static and dynamic face perception: The role of naturalistic motion

Much of our understanding of how the brain processes dynamic faces comes from research that compares static photographs to dynamic morphs, which exhibit simplified, computer-generated motion. By comparing static, video recorded, and dynamic morphed expressions, we aim to identify the neural correlates of naturalistic facial dynamism, using time-domain and time-frequency analysis. Dynamic morphs were made from the neutral and peak frames of video recorded transitions of happy and fearful expressions, which retained expression change and removed asynchronous and non-linear features of naturalistic facial motion. We found that dynamic morphs elicited increased N400 amplitudes and lower LPP amplitudes compared to other stimulus types. Video recordings elicited higher LPP amplitudes and greater frontal delta activity compared to other stimuli. Thematic analysis of participant interviews using a large language model revealed that participants found it difficult to assess the genuineness of morphed expressions, and easier to analyse the genuineness of happy compared to fearful expressions. Our findings suggest that animating real faces with artificial motion may violate expectations (N400) and reduce the social salience (LPP) of dynamic morphs. Results also suggest that delta oscillations in the frontal region may be involved with the perception of naturalistic facial motion in happy and fearful expressions. Overall, our findings highlight the sensitivity of neural mechanisms required for face perception to subtle changes in facial motion characteristics, which has important implications for neuroimaging research using faces with simplified motion.

Alpha Traveling Waves during Working Memory: Disentangling Bottom-Up Gating and Top-Down Gain Control

While previous works established the inhibitory role of alpha oscillations during working memory maintenance, it remains an open question whether such an inhibitory control is a top-down process. Here, we attempted to disentangle this issue by considering the spatiotemporal component of waves in the alpha band, i.e., alpha traveling waves. We reanalyzed two pre-existing and open-access EEG datasets (N = 180, 90 males, 80 females, 10 unknown) where participants performed lateralized, visual delayed match-to-sample working memory tasks. In the first dataset, the distractor load was manipulated (2, 4, or 6), whereas in the second dataset, the memory span varied between 1, 3, and 6 items. We focused on the propagation of alpha waves on the anterior-posterior axis during the retention period. Our results reveal an increase in alpha-band forward waves as the distractor load increased, but also an increase in forward waves and a decrease in backward waves as the memory set size increased. Our results also showed a lateralization effect: alpha forward waves exhibited a more pronounced increase in the hemisphere contralateral to the distractors, whereas the reduction in backward waves was stronger in the hemisphere contralateral to the targets. In short, the forward waves were regulated by distractors, whereas targets inversely modulated backward waves. Such a dissociation of goal-related and goal-irrelevant physiological signals suggests the coexistence of bottom-up and top-down inhibitory processes: alpha forward waves might convey a gating effect driven by distractor load, while backward waves may represent direct top-down gain control of downstream visual areas.

Alpha rhythm slowing in temporal lobe epilepsy across scalp EEG and MEG

EEG slowing is reported in various neurological disorders including Alzheimer's, Parkinson's and Epilepsy. Here, we investigate alpha rhythm slowing in individuals with refractory temporal lobe epilepsy compared with healthy controls, using scalp EEG and magnetoencephalography. We retrospectively analysed data from 17 (46) healthy controls and 22 (24) individuals with temporal lobe epilepsy who underwent scalp EEG and magnetoencephalography recordings as part of presurgical evaluation. Resting-state, eyes-closed recordings were source reconstructed using the standardized low-resolution brain electrographic tomography method. We extracted slow 6-9 Hz and fast 10-11 Hz alpha relative band power and calculated the alpha power ratio by dividing slow alpha by fast alpha. This ratio was computed for all brain regions in all individuals. Alpha oscillations were slower in individuals with temporal lobe epilepsy than controls (P< 0.05). This effect was present in both the ipsilateral and contralateral hemispheres and across widespread brain regions. Alpha slowing in temporal lobe epilepsy was found in both EEG and magnetoencephalography recordings. We interpret greater slow alpha as greater deviation from health.

Arousal effects on oscillatory dynamics in the non-human primate brain

Arousal states are thought to influence many aspects of cognition and behavior by broadly modulating neural activity. Many studies have observed arousal-related modulations of alpha (~8 to 15 Hz) and gamma (~30 to 50 Hz) power and coherence in local field potentials across relatively small groups of brain regions. However, the global pattern of arousal-related oscillatory modulation in local field potentials is yet to be fully elucidated. We simultaneously recorded local field potentials in numerous cortical and subcortical regions in the primate brain and assessed oscillatory activity and inter-regional coherence associated with arousal state. In high arousal states, we found a uniquely strong and coherent gamma oscillation between the amygdala and basal forebrain. In low arousal rest-like states, a relative increase in coherence at alpha frequencies was present across sampled brain regions, with the notable exception of the medial temporal lobe. We consider how these patterns of activity may index arousal-related brain states that support the processing of incoming sensory stimuli during high arousal states and memory-related functions during rest.

A comparative analysis of face and object perception in 2D laboratory and virtual reality settings: insights from induced oscillatory responses

In psychophysiological research, the use of Virtual Reality (VR) for stimulus presentation allows for the investigation of how perceptual processing adapts to varying degrees of realism. Previous time-domain studies have shown that perceptual processing involves modality-specific neural mechanisms, as evidenced by distinct stimulus-locked components. Analyzing induced oscillations across different frequency bands can provide further insights into neural processes that are not strictly phase-locked to stimulus onset. This study uses a simple perceptual paradigm presenting images of faces and cars on both a standard 2D monitor and in an immersive VR environment. To investigate potential modality-dependent differences in attention, cognitive load, and task-related post-movement processing, the induced alpha, theta and beta band responses are compared between the two modalities. No evidence was found for differences in stimulus-dependent attention or task-related post-movement processing between the 2D conditions and the realistic virtual conditions in electrode space, as posterior alpha suppression and re-synchronization of centro-parietal beta did not differ between conditions. However, source analysis revealed differences in the attention networks engaged during 2D and 3D perception. Midfrontal theta was significantly stronger in laboratory conditions, indicating higher cognitive load than in the VR environment. Exploratory analysis of posterior theta showed stronger responses in VR, possibly reflecting the processing of depth information provided only by the 3D material. In addition, the theta response seems to be generated by distinct neuronal sources under realistic virtual conditions indicating enhanced involvement of semantic information processing and social cognition.

Resting-state EEG correlates of sustained attention in healthy ageing: Cross-sectional findings from the LEISURE study

While structural and biochemical brain changes are well-documented in ageing, functional neuronal network differences, as indicated by electrophysiological markers, are less clear. Moreover, age-related changes in sustained attention and their associated electrophysiological correlates are still poorly understood. To address this, we analysed cross-sectional baseline electroencephalography (EEG) and cognitive data from the Lifestyle Intervention Study for Dementia Risk Reduction (LEISURE). Participants were 96 healthy older adults, aged 50-84. We examined resting-state EEG periodic (individual alpha frequency [IAF], aperiodic-adjusted individual alpha power [aIAP]) and aperiodic (exponent and offset) activity, and their associations with age and sustained attention. Results showed associations between older age and slower IAF, but not aIAP or global aperiodic exponent and offset. Additionally, hierarchical linear regression revealed that after controlling for demographic variables, faster IAF was associated with better Sustained Attention to Response Task performance, and mediation analysis confirmed IAF as a mediator between age and sustained attention performance. These findings indicate that IAF may be an important marker of ageing, and a slower IAF may signal diminished cognitive processing capacity for sustained attention in older adults.

Socioeconomic status (SES) and cognitive outcomes are predicted by resting-state EEG in school-aged children

Children's socioeconomic status (SES) is related to patterns of intrinsic resting-state brain function that subserve relevant cognitive processes over the course of development. Although infant research has demonstrated the association between children's environments, cognitive outcomes, and resting-state electroencephalography (rsEEG), it remains unknown how these aspects of their environment, tied to SES, impact neural and cognitive development throughout the school years. To address this gap, we applied a multivariate pattern analysis (MVPA) to rsEEG data to identify which neural frequencies at rest are differentially associated with unique aspects of socioeconomic status (SES; income and maternal education) and cognitive (vocabulary, working memory) outcomes among school-aged children (8-15 years). We find that the alpha frequency is associated with both income and maternal education, while lower gamma and theta fluctuations are tied to dissociable aspects of SES and cognitive outcomes. Specifically, changes in the gamma frequency are predictive of both maternal education and vocabulary outcome, while changes in the theta frequency are related to both income and working memory ability. The current findings extend our understanding of unique pathways by which SES influences cognitive and neural development in school-aged children.

Dysfunctional Alpha Modulation as a Mechanism of Working Memory Impairment in Serious Mental Illness

BACKGROUND

People with psychosis and mood disorders experience disruptions in working memory; however, the underlying mechanism remains unknown. We focused on 2 potential mechanisms: poor attentional engagement should be associated with elevated levels of prestimulus alpha-band activity within the electroencephalogram (EEG), whereas impaired working memory encoding should be associated with reduced poststimulus alpha suppression.

METHODS

We collected EEG data from 68 people with schizophrenia, 43 people with bipolar disorder with a history of psychosis, 53 people with major depressive disorder, and 90 healthy comparison subjects while they completed a spatial working memory task. We quantified attention lapsing, memory precision, and memory capacity from the behavioral responses, and we quantified alpha using traditional wavelet analysis as well as a novel approach for isolating oscillatory alpha power from aperiodic elements of the EEG signal.

RESULTS

We found that 1) greater prestimulus alpha power estimated using traditional wavelet analysis predicted behavioral errors; 2) poststimulus alpha suppression was reduced in the patient groups; and 3) reduced suppression was associated with a lower likelihood of memory storage. However, we also observed that the prestimulus alpha was larger among healthy control participants than patients, and single-trial analyses showed that it was the aperiodic elements of the prestimulus EEG-not oscillatory alpha-that predicted behavioral errors.

DISCUSSION

These results suggest that working memory impairments in serious mental illness primarily reflect an impairment in the poststimulus encoding processes rather than reduced attentional engagement prior to stimulus onset.