Brain Waves Research Articles

Alterations of the IKZF1-IKZF2 tandem in immune cells of schizophrenia patients regulate associated phenotypes

Schizophrenia is a complex multifactorial disorder and increasing evidence suggests the involvement of immune dysregulations in its pathogenesis. We observed that IKZF1 and IKZF2, classic immune-related transcription factors (TFs), were both downregulated in patients’ peripheral blood mononuclear cells (PBMCs) but not in their brain. We generated a new mutant mouse model with a reduction in Ikzf1 and Ikzf2 to study the impact of those changes. Such mice developed deficits in the three dimensions (positive–negative-cognitive) of schizophrenia-like phenotypes associated with alterations in structural synaptic plasticity. We then studied the secretomes of cultured PBMCs obtained from patients and identified potentially secreted molecules, which depended on IKZF1 and IKZF2 mRNA levels, and that in turn have an impact on neural synchrony, structural synaptic plasticity and schizophrenia-like symptoms in in vivo and in vitro models. Our results point out that IKZF1-IKZF2-dependent immune signals negatively impact on essential neural circuits involved in schizophrenia.

Chemogenetic activation of astrocytes modulates sleep/wakefulness states in a brain region-dependent manner

Abstract Study objectives Astrocytes change their intracellular calcium (Ca2+) concentration during sleep/wakefulness states in mice. Furthermore, the Ca2+ dynamics in astrocytes vary depending on the brain region. However, it remains unclear whether alterations in astrocyte activity can affect sleep/wake states and cortical oscillations in a brain region-dependent manner. Methods Astrocyte activity was artificially manipulated in mice using chemogenetics. Astrocytes in the hippocampus and pons, which are 2 brain regions previously classified into different clusters based on their Ca2+ dynamics during sleep/wakefulness, were focused on to compare whether there are differences in the effects of astrocytes from different brain regions. Results The chemogenetic activation of astrocytes in the hippocampus significantly decreased the total time of wakefulness and increased the total time of sleep. This had little effect on cortical oscillations in all sleep/wakefulness states. On the other hand, the activation of astrocytes in the pons substantially suppressed rapid eye movement (REM) sleep in association with a decreased number of REM episodes, indicating strong inhibition of REM onset. Regarding cortical oscillations, the delta wave component during non-REM sleep was significantly enhanced. Conclusions These results suggest that astrocytes modulate sleep/wakefulness states and cortical oscillations. Furthermore, the role of astrocytes in sleep/wakefulness states appears to vary among brain regions.

Change on the Brain? The Neuroscience of Organizational Transformation

True transformations aim to change the core identity of an organization, are often disruptive, and rarely result in their intended outcomes. The objective of this paper is to propose a theoretical approach for more effective transformations via the syntheses of emerging findings in managerial science, organizational psychology, and social cognitive neuroscience. The authored conducted a literature review of traditional methods and the application of neuroscience to organizational transformation, proposing that consideration to leader and employee neuroanatomy can significantly impact transformation success. The emergent five-phase approach - Exploration & Discovery, Surfacing & Co-Creation, Enablement & Prioritization, Implementation, and Empowerment - integrates practices informed by neuroscience to enhance leadership alignment, employee engagement, and change sustainability. By focusing on activities such as vision alignment, co-creation, and leadership development, the approach seeks to optimize brain functions related to trust, motivation, and adaptability. Neuroscientific concepts like neural synchrony, hormone and neurotransmitter release, and specific neural circuit activations are utilized to improve team dynamics, decision-making, and learning. This neuro-informed approach challenges conventional practices by emphasizing co-creative solutioning with employees, piloting programs, and empowering middle managers to lead transformation efforts. Data from case studies demonstrate significant improvements in employee experience and sustainable shifts in organizational behavior. The paper concludes with a call for further research to solidify the emerging intersection of neuroscience and organizational transformation.

Can emphasis on temporal processing inform literacy intervention design?

The aim of this minireview is to explore the relationship between auditory (AP) and phonological processing and to probe potential ‘cascade effects’ on literacy development. The overall purpose of this study is to specify auditory deficits in language and literacy outcomes to inform intervention. Important underpinnings of language and literacy development and characteristics of AP, phonological processing, and phonological awareness in children with literacy disorders in light of auditory processing skills. Children with language and literacy impairments experience difficulties processing temporal and/or spectral changes in acoustic stimuli resulting from atypical neural synchronization. On a behavioural level, studies have revealed a relationship between temporal processing skills (e.g., rise time discrimination, frequency modulation sensitivity) and literacy development. While research remains inconclusive on intervention efficacy centred on auditory processing, this review serves as the stepping stone for investigating intervention methods focused specifically on temporal processing. Frameworks associated with literacy deficits and interventions may benefit from auditory modality-specific assessment and interventions.

Prefrontal electrophysiological biomarkers and mechanism-based drug effects in a rat model of alcohol addiction

Patients with alcohol use disorder (AUD) who seek treatment show highly variable outcomes. A precision medicine approach with biomarkers responsive to new treatments is warranted to overcome this limitation. Promising biomarkers relate to prefrontal control mechanisms that are severely disturbed in AUD. This results in reduced inhibitory control of compulsive behavior and, eventually, relapse. We reasoned here that prefrontal dysfunction, which underlies vulnerability to relapse, is evidenced by altered neuroelectric signatures and should be restored by pharmacological interventions that specifically target prefrontal dysfunction. To test this, we applied our recently developed biocompatible neuroprosthesis to measure prefrontal neural function in a well-established rat model of alcohol addiction and relapse. We monitored neural oscillations and event-related potentials in awake alcohol-dependent rats during abstinence and following treatment with psilocybin or LY379268, agonists of the serotonin 2A receptor (5-HT2AR), and the metabotropic glutamate receptor 2 (mGluR2), that are known to reduce prefrontal dysfunction and relapse. Electrophysiological impairments in alcohol-dependent rats are reduced amplitudes of P1N1 and N1P2 components and attenuated event-related oscillatory activity. Psilocybin and LY379268 were able to restore these impairments. Furthermore, alcohol-dependent animals displayed a dominance in higher beta frequencies indicative of a state of hyperarousal that is prone to relapse, which particularly psilocybin was able to counteract. In summary, we provide prefrontal markers indicative of relapse and treatment response, especially for psychedelic drugs.

The Role of Neuropathology Evaluation in the Nonclinical Assessment of Seizure Liability.

Test article (TA)-induced seizures represent a major safety concern in drug development. Seizures (altered brain wave [electrophysiological] patterns) present clinically as abnormal consciousness with or without tonic/clonic convulsions (where "tonic" = stiffening and "clonic" = involuntary rhythmical movements). Neuropathological findings following seizures may be detected using many methods. Neuro-imaging may show a structural abnormality underlying seizures, such as focal cortical dysplasia or hippocampal sclerosis in patients with chronic epilepsy. Neural cell type-specific biomarkers in blood or cerebrospinal fluid may highlight neuronal damage and/or glial reactions but are not specific indicators of seizures while serum electrolyte and glucose imbalances may induce seizures. Gross observations and brain weights generally are unaffected by TAs with seizurogenic potential, but microscopic evaluation may reveal seizure-related neuron death in some brain regions (especially neocortex, hippocampus, and/or cerebellum). Current globally accepted best practices for neural sampling in nonclinical general toxicity studies provide a suitable screen for brain regions that are known sites of electrical disruption and/or display seizure-induced neural damage. Conventional nonclinical studies can afford an indication that a TA has a potential seizure liability (via in-life signs and/or microscopic evidence of neuron necrosis), but confirmation requires measuring brain electrical (electroencephalographic) activity in a nonclinical study.

Sustained Clinical Benefit of Adaptive Deep Brain Stimulation in Parkinson's Disease Using Gamma Oscillations: A Case Report.

Adaptive deep brain stimulation (aDBS) dynamically adjusts stimulation parameters according to patient needs. We recently showed that chronic aDBS utilizing invasive neural signals for feedback control is superior to conventional DBS (cDBS) during normal daily life in a 2-month trial. The stability of aDBS over longer periods remains unclear. To assess the effects of aDBS on motor symptoms and quality of life (QoL) in one individual with Parkinson's disease over 8 months. We used stimulation-entrained cortical gamma oscillations as a control signal for aDBS in the subthalamic nucleus and quantified benefits using motor diary ratings, QoL scales, and wearable metrics. We found that aDBS delivered superior and consistent benefits compared with baseline cDBS in measures of bradykinesia and QoL. aDBS can achieve prolonged, stable improvement over clinically optimized cDBS. The neural signal remains stable, and aDBS parameters remain appropriate over extended periods. © 2024 International Parkinson and Movement Disorder Society.

Cortical beta oscillations map to shared brain networks modulated by dopamine

Brain rhythms can facilitate neural communication for the maintenance of brain function. Beta rhythms (13–35 Hz) have been proposed to serve multiple domains of human ability, including motor control, cognition, memory, and emotion, but the overarching organisational principles remain unknown. To uncover the circuit architecture of beta oscillations, we leverage normative brain data, analysing over 30 hr of invasive brain signals from 1772 channels from cortical areas in epilepsy patients, to demonstrate that beta is the most distributed cortical brain rhythm. Next, we identify a shared brain network from beta-dominant areas with deeper brain structures, like the basal ganglia, by mapping parametrised oscillatory peaks to whole-brain functional and structural MRI connectomes. Finally, we show that these networks share significant overlap with dopamine uptake as indicated by positron emission tomography. Our study suggests that beta oscillations emerge in cortico-subcortical brain networks that are modulated by dopamine. It provides the foundation for a unifying circuit-based conceptualisation of the functional role of beta activity beyond the motor domain and may inspire an extended investigation of beta activity as a feedback signal for closed-loop neurotherapies for dopaminergic disorders.

Healthy Aging is Associated with Altered Visual Gamma Band Onset and Offset Responses

Abstract Gamma oscillations have been shown to be critical for basic sensory processing, as well as visual attention and several other higher-order cognitive functions. Aberrant gamma oscillations have also been shown in neuropsychiatric and neurodegenerative diseases. Despite the possible clinical implications of altered gamma activity and emerging stimulation-based interventions targeting gamma, research into age-related changes in gamma oscillatory activity in healthy adults remains sparce. In the current study, we examined the neural oscillations underlying basic visual processing in 87 healthy aging adults using magnetoencephalography (MEG) and a visual grating stimulus. Neural activity elicited by the visual stimulus was imaged using a time-frequency resolved beamformer and peak voxel time series were computed to characterize the visual oscillatory dynamics underlying these responses. We found significant age-related changes in visual gamma oscillations, but not in visual theta, alpha, or beta oscillations. Specifically, we found age-related increases in gamma band amplitude and inter-trial phase-locking (ITPL) immediately following stimulus presentation (i.e., gamma onset response). Conversely, gamma band amplitude and ITPL following stimulus removal (i.e., gamma offset response) were found to be decreased as a function of healthy aging. Critically, we demonstrated that the decreases in the gamma offset response predicted slower overall processing speed across all participants. Taken together, these findings indicate that healthy aging is uniquely associated with alterations in visual gamma oscillations and that these changes predict participant processing speed.

Cortical tracking of postural sways during standing balance

Maintaining an upright stance requires the integration of sensory inputs from the visual, vestibular and somatosensory-proprioceptive systems by the central nervous system to develop a corrective postural strategy. However, it is unclear whether and how the cerebral cortex monitors and controls postural sways. Here, we asked whether postural sways are encoded in ongoing cortical oscillations, giving rise to a form of corticokinematic coherence (CKC) in the context of standing balance. Center-of-pressure (CoP) fluctuations and electroencephalographic cortical activity were recorded as young healthy participants performed balance tasks during which sensory information was manipulated, by either removal or alteration. We found that postural sways are represented in ongoing cortical activity during challenging balance conditions, in the form of CKC at 1–6 Hz. Time delays between cortical activity and CoP features indicated that both afferent and efferent pathways contribute to CKC, wherein the brain would monitor the CoP velocity and control its position. Importantly, CKC was behaviorally relevant, as it predicted the increase in instability brought by alteration of sensory information. Our results suggest that human sensorimotor cortical areas take part in the closed-loop control of standing balance in challenging conditions. Importantly, CKC could serve as a neurophysiological marker of cortical involvement in maintaining balance.

Supplemental Material for How Long-Term Memory Facilitates Working Memory: Evidence From Flexible Responses and Neural Oscillations

Supplemental Material for How Long-Term Memory Facilitates Working Memory: Evidence From Flexible Responses and Neural Oscillations

Trait-level somatic anxiety modulates functional magnetic resonance imaging (fMRI) neural synchrony to naturalistic stimuli.

Somatic anxiety refers to the tendency to appraise situations as threatening, leading to heightened physiological arousal. Symptoms associated with higher levels of somatic anxiety that reflect autonomic arousal and perceptions of threat include elevated heartbeat perception, difficulty breathing, and palpitation. Somatic anxiety is generally associated with increased stimulus-driven attention; however, it is currently unknown how somatic anxiety modulates neural synchrony, measured by intersubject correlations (ISC), in response to complex audiovisual stimuli. The present study seeks to identify how differing levels of somatic anxiety are associated with neural synchrony during psychological processing of audiovisual stimuli, as measured by ISC and intersubject representational similarity analyses. We hypothesize that individuals with higher levels of somatic anxiety will show heightened ISC in response to an audiovisual stimulus in regions associated with stimulus-driven attention, including the superior parietal lobule, supplementary motor area, and precentral gyrus. Results from this study identified that higher levels of somatic anxiety are associated with widespread heightened ISC across the brain, including in regions associated with perceptual processing and stimulus-driven attention. Taken together, this research suggests that higher levels of somatic anxiety are associated with similar processing in brain regions involved in stimulus-driven attention and top-down processing, whereas lower levels of somatic anxiety are associated with similar processing in brain regions associated with higher level visual processing. These results collectively emphasize that somatic anxiety levels should be measured and controlled for during naturalistic functional magnetic resonance imaging paradigms, as this trait may have an influence on synchronous neurological activity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A temporal-spectral graph convolutional neural network model for EEG emotion recognition within and across subjects

EEG-based emotion recognition uses high-level information from neural activities to predict emotional responses in subjects. However, this information is sparsely distributed in frequency, time, and spatial domains and varied across subjects. To address these challenges in emotion recognition, we propose a novel neural network model named Temporal-Spectral Graph Convolutional Network (TSGCN). To capture high-level information distributed in time, spatial, and frequency domains, TSGCN considers both neural oscillation changes in different time windows and topological structures between different brain regions. Specifically, a Minimum Category Confusion (MCC) loss is used in TSGCN to reduce the inconsistencies between subjective ratings and predefined labels. In addition, to improve the generalization of TSGCN on cross-subject variation, we propose Deep and Shallow feature Dynamic Adversarial Learning (DSDAL) to calculate the distance between the source domain and the target domain. Extensive experiments were conducted on public datasets to demonstrate that TSGCN outperforms state-of-the-art methods in EEG-based emotion recognition. Ablation studies show that the mixed neural networks and our proposed methods in TSGCN significantly contribute to its high performance and robustness. Detailed investigations further provide the effectiveness of TSGCN in addressing the challenges in emotion recognition.

Assessing restorative effects of soundscapes in VR through EEG and HRV

This study aimed to extend the application of soundscape analysis by utilizing electroencephalogram (EEG) analysis as a physiological evaluation tool to determine the actual restorative impact on individual environmental perceptions and psycho-physiological responses stemming from various soundscape experiences. Initially, we constructed three distinct virtual reality (VR) environments: waterfront, urban, and green areas, each accompanied by three content variations. A total of 60 subjects participated in the study. Data were gathered through a survey assessing individual characteristics, psychological restorative responses, and soundscape perceptions. Additionally, quantitative physiological responses such as heart rate variability (HRV) and EEG, were measured. Subsequently, subjects were categorized into restoration and non-restoration groups based on HRV responses using cluster analysis. The analysis revealed positive HRV changes indicative of reduced stress levels. In EEG analysis, differences were observed in network connectivity rather than power spectral density. As a result of connectivity analysis, global efficiency increased overall in the restoration group, and differences in nodal efficiency occurred in a total of eight brain regions, enabling soundscape experience to efficiently process cognitive functions in the cerebrum, thereby having a positive effect on neural communication. This study is significant as it represents the first examination of soundscape restorative responses in terms of brain wave connectivity, underscoring the feasibility of employing physiological evaluations, including brain wave analysis, in the study of soundscapes.

Atypical oscillatory and aperiodic signatures of visual sampling in developmental dyslexia

Temporal processing deficits in Developmental Dyslexia (DD) have been documented extensively at the behavioral level, leading to the formulation of neural theories positing that such anomalies in parsing multisensory input rely on aberrant synchronization of neural oscillations or to an excessive level of neural noise. Despite reading being primarily supported by visual functions, experimental evidence supporting these theories remains scarce. Here, we tested 26 adults with DD (9 females) and 31 neurotypical controls (16 females) with a temporal segregation/integration task that required participants to either integrate or segregate two rapidly presented displays while their EEG activity was recorded. We confirmed behaviorally a temporal sampling deficit in DD, which affected specifically the rapid segregation of visual input. While the ongoing alpha frequency and the excitation/inhibition (E/I) ratio (i.e., an index of neural noise quantified by the aperiodic exponent) were differently modulated based on task demands in typical readers, DD participants exhibited an impairment in alpha speed modulation and an altered E/I ratio that affected their rapid visual sampling. Nonetheless, an association between visual temporal sampling accuracy and both alpha frequency and the E/I ratio measured at rest were evident in the DD group, further confirming an anomalous interplay between alpha synchronization, the E/I ratio and active visual sampling. These results provide evidence that both trait- and state-like differences in alpha-band synchronization and neural noise levels coexist in the dyslexic brain and are synergistically responsible for cascade effects on visual sampling and reading.

Negative Emotion Differentiation Promotes Cognitive Reappraisal: Evidence From Electroencephalogram Oscillations and Phase-Amplitude Coupling.

Cognitive reappraisal, an effective emotion regulation strategy, is influenced by various individual factors. Although previous studies have established a link between negative emotion differentiation (NED) and cognitive reappraisal, the underlying neural mechanisms remain largely unknown. Using electroencephalography, this study investigates the influence and neural basis of NED in cognitive reappraisal by integrating aspects of event-related potentials, neural oscillation rhythms, and cross-frequency coupling. The findings revealed that individuals with high NED demonstrated a significant decrease in parietal late positive potential amplitudes during cognitive reappraisal, suggesting enhanced cognitive reappraisal abilities. Moreover, high NED individuals displayed increased γ synchronization, parietal α-γ coupling, and frontal θ-γ coupling when reappraising negative emotions than those with low emotion differentiation ability. Machine learning analysis of these neural indicators highlighted the superior classification and predictive accuracy of multimodal indicators for NED as opposed to unimodal indicators. Overall, this multimodal evidence provides a comprehensive interpretation of the neurophysiological mechanisms through which NED influences cognitive reappraisal and provides preliminary empirical support for personalized cognitive reappraisal interventions to alleviate emotional problems.

AI-Enabled Neural Stabilizer Devices: A Theoretical Novel Approach to Correcting Pathological Brain Waves in Neurological Disorders

This article explores the development and potential applications of AI-enabled neural stabilizer devices in treating neurological and psychiatric conditions characterized by pathological brain waves, such as drug-resistant epilepsy. By integrating advanced artificial intelligence with neurostimulation technology, these devices continuously monitor brain activity through implanted electrodes, analyze neural signals in real-time to detect abnormal patterns, and deliver targeted electrical stimulation to disrupt pathological activity before or just after it manifests as clinical symptoms. The use of machine learning algorithms allows for personalized treatment tailored to the individual's unique neural patterns, enhancing the effectiveness of interventions. Clinical studies have demonstrated the efficacy of responsive neurostimulation systems in reducing seizure frequency among patients with refractory epilepsy. Beyond epilepsy, the potential applications extend to conditions like depression, obsessive-compulsive disorder, Tourette's syndrome, Parkinson's disease, and chronic pain. The article also addresses the ethical, technical, and regulatory challenges associated with implementing such advanced technology, emphasizing the need for interdisciplinary collaboration to realize the full potential of this innovative approach.

Prefrontal excitation/inhibition balance supports adolescent enhancements in circuit signal to noise ratio

The development and refinement of neuronal circuitry allow for stabilized and efficient neural recruitment, supporting adult-like behavioral performance. During adolescence, the maturation of PFC is proposed to be a critical period (CP) for executive function, driven by a break in balance between glutamatergic excitation and GABAergic inhibition (E/I) neurotransmission. During CPs, cortical circuitry fine-tunes to improve information processing and reliable responses to stimuli, shifting from spontaneous to evoked activity, enhancing the SNR, and promoting neural synchronization. Harnessing 7 T MR spectroscopy and EEG in a longitudinal cohort (N = 164, ages 10–32 years, 283 neuroimaging sessions), we outline associations between age-related changes in glutamate and GABA neurotransmitters and EEG measures of cortical SNR. We find developmental decreases in spontaneous activity and increases in cortical SNR during our auditory steady state task using 40 Hz stimuli. Decreases in spontaneous activity were associated with glutamate levels in DLPFC, while increases in cortical SNR were associated with more balanced Glu and GABA levels. These changes were associated with improvements in working memory performance. This study provides evidence of CP plasticity in the human PFC during adolescence, leading to stabilized circuitry that allows for the optimal recruitment and integration of multisensory input, resulting in improved executive function.

Emotion Detection using EEG Signal Analysis

Emotion is a subjective experience-based mental state and emotive response to an event. This feeling is fundamental to everyday human behaviour and communication. Emotion is a psychophysiological process that influences a person's behaviour in a certain setting and is crucial to inter-personal communication. A person's voice, facial expressions, muscles, nervous system activity, and endocrine system activity are all influenced by their emotions. The electroencephalogram (EEG) is one technique for identifying emotions. Furthermore, EEG-based emotion identification has applications in a variety of industries, including marketing, gaming, and e-learning, and it has the potential to improve the intelligence of human-computer interfaces. This project records useful information related to various emotional states by using an EEG sensor to monitor brain waves in realtime. This raw data is transmitted to an ESP8266 micro controller by the EEG sensor. The DF Mini Player and the ESP8266 work together flaw-lessly to playback preset audio files that correlate to the identified emotions. As an Internet of Things device, the ESP8266 allows audio playback information and the detected emotional state to be communicated to the cloud or other devices that are connected. This allows for remote monitor-ing and the initiation of activities based on the user's emotions.

Coupling Up: A Dynamic Investigation of Romantic Partners’ Neurobiological States During Nonverbal Connection

Nonverbal connection is an important aspect of everyday communication. For romantic partners, nonverbal connection is essential for establishing and maintaining feelings of closeness. EEG hyperscanning offers a unique opportunity to examine the link between nonverbal connection and neural synchrony among romantic partners. This current study used an EEG hyperscanning paradigm to collect frontal alpha asymmetry (FAA) signatures from 30 participants (15 romantic dyads) engaged in five different types of nonverbal connection that varied based on physical touch and visual contact. The results suggest that there was a lack of FAA while romantic partners were embracing and positive FAA (i.e., indicating approach) while they were holding hands, looking at each other, or doing both. Additionally, partners’ FAA synchrony was greatest at a four second lag while they were holding hands and looking at each other. Finally, there was a significant association between partners’ weekly negative feelings and FAA such that as they felt more negative their FAA became more positive. Taken together, this study further supports the idea that fleeting moments of interpersonal touch and gaze are important for the biological mechanisms that may underlie affiliative pair bonding in romantic relationships.