Brain oscillations in neuropsychiatric disease

EEG microstate biomarkers for schizophrenia: a novel approach using deep neural networks

Schizophrenia remains a challenging neuropsychiatric disorder with complex diagnostic processes. Current clinical approaches often rely on subjective assessments, highlighting the critical need for objective, quantitative diagnostic methods. This study aimed to develop a robust classification approach for schizophrenia using EEG microstate analysis and advanced machine learning techniques. We analyzed EEG signals from 14 healthy individuals and 14 patients with schizophrenia during a 15-min resting-state session across 19 EEG channels. A data augmentation strategy expanded the dataset to 56 subjects in each group. The signals were preprocessed and segmented into five frequency bands (delta, theta, alpha, beta, gamma) and five microstates (A, B, C, D, E) using k-means clustering. Five key features were extracted from each microstate: duration, occurrence, standard deviation, coverage, and frequency. A Deep Neural Network (DNN) model, along with other machine learning classifiers, was developed to classify the data. A comprehensive fivefold cross-validation approach evaluated model performance across various EEG channels, frequency bands, and feature combinations. Significant alterations in microstate transition probabilities were observed, particularly in higher frequency bands. The gamma band showed the most pronounced differences, with a notable disruption in D → A transitions (absolute difference = 0.100). The Random Forest classifier achieved the highest accuracy of 99.94% ± 0.12%, utilizing theta band features from the F8 frontal channel. The deep neural network model demonstrated robust performance with 98.31% ± 0.68% accuracy, primarily in the occipital region. Feature size 2 consistently provided optimal classification across most models. Our study introduces a novel, high-precision EEG microstate analysis approach for schizophrenia diagnosis, offering an objective diagnostic tool with potential applications in neuropsychiatric disorders. The findings reveal critical insights into neural dynamics associated with schizophrenia, demonstrating the potential for transforming clinical diagnostic practices through advanced machine learning and neurophysiological feature extraction.

The evolution of N, N-Dimethyltryptamine: from metabolic pathways to brain connectivity

RATIONALE

N, N-Dimethyltryptamine (DMT), a potent serotonergic psychedelic, bridges ancient wisdom and modern science. The mechanisms underlying its powerful psychedelic effects and out-of-body experiences continue to intrigue scientists. The functional role of DMT remains ambiguous. This paper explores the endogenous presence of DMT in the human body and its diverse neuroregulatory functions, which influence hierarchical brain connectivity, and the mechanisms driving its psychedelic effects.

OBJECTIVE

This paper aims to analyze DMT-receptor binding, its effects on neuronal modulation, brain oscillations, and connectivity, and its influence on hallucinations, out-of-body experiences, and cognitive functions.

RESULTS

DMT administration induces significant changes in brain wave dynamics, including reduced alpha power, increased delta power, and heightened Lempel-Ziv complexity, reflecting enhanced neural signal diversity. Functional neuroimaging studies reveal that DMT enhances global functional connectivity (GFC), particularly in transmodal association cortices such as the salience network, frontoparietal network, and default mode network, correlating with ego dissolution. The receptor density-dependent effects of DMT were mapped to brain regions rich in serotonin 5-HT2A receptors, supporting its role in modulating consciousness and neuroplasticity.

CONCLUSION

This integrated analysis provides insights into the profound effects of DMT on human cognition, and consciousness, and its role in enhancing natural well-being. As we uncover the endogenous functions of DMT, it becomes clear that the study of its biology reveals a complex interplay between brain chemistry and consciousness.

A comprehensive investigation of intracortical and corticothalamic models of the alpha rhythm

The electroencephalographic alpha rhythm is one of the most robustly observed and widely studied empirical phenomena in all of neuroscience. However, despite its extensive implication in a wide range of cognitive processes and clinical pathologies, the mechanisms underlying alpha generation in neural circuits remain poorly understood. In this paper we offer a renewed foundation for research on this question, by undertaking a systematic comparison and synthesis of the most prominent theoretical models of alpha rhythmogenesis in the published literature. We focus on four models, each studied intensively by multiple authors over the past three decades: (i) Jansen-Rit, (ii) Moran-David-Friston, (iii) Robinson-Rennie-Wright, and (iv) Liley-Wright. Several common elements are identified, such as the use of second-order differential equations and sigmoidal potential-to-rate operators to represent population-level neural activity. Major differences are seen in other features such as wiring topologies and conduction delays. Through a series of mathematical analyses and numerical simulations, we nevertheless demonstrate that the selected models can be meaningfully compared, by associating parameters and circuit motifs of analogous biological significance. With this established, we conduct explorations of rate constant and synaptic connectivity parameter spaces, with the aim of identifying common patterns in key behaviours, such as the role of excitatory-inhibitory interactions in the generation of oscillations. Finally, using linear stability analysis we identify two qualitatively different alpha-generating dynamical regimes across the models: (i) noise-driven fluctuations and (ii) self-sustained limit-cycle oscillations, emerging due to an Andronov-Hopf bifurcation. The comprehensive survey and synthesis developed here can, we suggest, be used to help guide future theoretical and experimental work aimed at disambiguating these and other candidate theories of alpha rhythmogenesis.

Impact of transcranial alternating current stimulation on psychological stress: A functional near-infrared spectroscopy study

This pilot study investigates the impact of transcranial alternating current stimulation (tACS) on psychological stress using functional near-infrared spectroscopy (fNIRS). Forty volunteers were randomly assigned to two groups: the tACS and the control. The experiment was divided into three distinct stages: pre-stimulation, stimulation, and post-stimulation. The Stroop Color-Word Task (SCWT) was employed as a validated stress-inducing paradigm to assess pre- and post-stimulation changes. During the initial phase, the participants completed the SCWT. This was followed by either tACS or sham. In the third session, the individuals solved the task again. The anode and cathode for the transcranial tACS were placed on the dorsolateral prefrontal cortex (DLPFC). tACS, was applied with current intensity of 1.5 mA at 16 Hz over the dorsolateral prefrontal cortex (DLPFC), aimed to modulate cortical activation and mitigate stress. Sham included 5-second ramp periods. Physiological data using alpha amylase and the NASA Task Load Index (NASA-TLX) were utilized. The results revealed significant hemodynamic changes and reduced stress levels in the tACS group compared to the sham group (p <  0.001). The connectivity network changed significantly (p <  0.001) following tACS. In addition, the NASA-TLX results showed a statistically significant difference between the pre-and post-tACS sessions. In contrary, no statistical significance was noticed for the sham control group. An increase in the blood flow in the prefrontal cortex region of the brain was observed, demonstrating the potential of tACS as a non-invasive neuromodulation technique for stress mitigation.

Prestimulus EEG Oscillations and Pink Noise Affect Go/No-Go ERPs

This study builds on the early brain dynamics work of Erol Başar, focusing on the human electroencephalogram (EEG) in relation to the generation of event-related potentials (ERPs) and behaviour. Scalp EEG contains not only oscillations but non-wave noise elements that may not relate to functional brain activity. These require identification and removal before the true impacts of brain oscillations can be assessed. We examined EEG/ERP/behaviour linkages in young adults during an auditory equiprobable Go/No-Go task. Forty-seven university students participated while continuous EEG was recorded. Using the PaWNextra algorithm, valid estimates of pink noise (PN) and white noise (WN) were obtained from each participant's prestimulus EEG spectra; within-participant subtraction revealed noise-free oscillation spectra. Frequency principal component analysis (f-PCA) was used to obtain noise-free frequency oscillation components. Go and No=Go ERPs were obtained from the poststimulus EEG, and separate temporal (t)-PCAs obtained their components. Exploratory multiple regression found that alpha and beta prestimulus oscillations predicted Go N2c, P3b, and SW1 ERP components related to the imperative Go response, while PN impacted No-Go N1b and N1c, facilitating early processing and identification of the No-Go stimulus. There were no direct effects of prestimulus EEG measures on behaviour, but the EEG-affected Go N2c and P3b ERPs impacted Go performance measures. These outcomes, derived via our mix of novel methodologies, encourage further research into natural frequency components in the noise-free oscillations immediately prestimulus, and how these affect task ERP components and behaviour.

Brain Wave Oscillations as an Objective Neurophysiological Biomarker of Homeopathic Subjective Well-Being

BACKGROUND

 Homeopathy uses the "similitude principle" to arouse a therapeutic reaction in the body against its own disorders. For this to occur optimally, the medicinal pathogenetic effects must present similarity with the totality of the individual's symptoms. To assess if this similarity has been successfully achieved, Hahnemann states that "improvement in the disposition and mind"-i.e., subjective well-being-is the most important parameter to consider.

AIM

 Our aim was to perform a narrative review of the literature, exploring what is known about subjective well-being as a marker of therapeutic action, and to formulate ways in which subjective well-being might be quantifiable and applied in future homeopathy research.

RESULTS

 The concept of subjective well-being has been extensively studied in the complementary and conventional medical literature. Improved well-being has been observed in clinical trials, including those in the fields of positive psychology and meditation. Positive subjective outcomes of this nature are supported by objective evidence through associated changes in brain oscillatory activity using electroencephalography and/or "brain mapping" by functional magnetic resonance imaging. Neurophysiological responses in the brain have been identified in subjects after they ingested a homeopathic medicine.

CONCLUSIONS

 The concept of subjective well-being is supported by a body of literature and is a measurable entity. When viewed from the perspective of electrophysiological changes, brain activity is an objective neurophysiological biomarker with a potential to quantify individual well-being in the context of homeopathy research.

Decoding Pain: A Comprehensive Review of Computational Intelligence Methods in Electroencephalography-Based Brain-Computer Interfaces

Objective pain evaluation is crucial for determining appropriate treatment strategies in clinical settings. Studies have demonstrated the potential of using brain-computer interface (BCI) technology for pain classification and detection. Collating knowledge and insights from prior studies, this review explores the extensive work on pain detection based on electroencephalography (EEG) signals. It presents the findings, methodologies, and advancements reported in 20 peer-reviewed articles that utilize machine learning and deep learning (DL) approaches for EEG-based pain detection. We analyze various ML and DL techniques, support vector machines, random forests, k-nearest neighbors, and convolution neural network recurrent neural networks and transformers, and their effectiveness in decoding pain neural signals. The motivation for combining AI with BCI technology lies in the potential for significant advancements in the real-time responsiveness and adaptability of these systems. We reveal that DL techniques effectively analyze EEG signals and recognize pain-related patterns. Moreover, we discuss advancements and challenges associated with EEG-based pain detection, focusing on BCI applications in clinical settings and functional requirements for effective pain classification systems. By evaluating the current research landscape, we identify gaps and opportunities for future research to provide valuable insights for researchers and practitioners.

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.

Spatiotemporal Dynamics of Periodic and Aperiodic Brain Activity Under Peripheral Nerve Stimulation With Acupuncture

Brain activities are a mixture of periodic and aperiodic components, manifesting in the power spectral density (PSD) as rhythmic oscillations with spectral peaks and broadband fluctuations. Periodic oscillatory properties of brain response to external stimulation are widely studied, while aperiodic component responses remain unclear. Here, we investigate spatiotemporal dynamics of periodic and aperiodic brain activity under peripheral nerve stimulation with acupuncture by parameterization of power spectra of EEG signals. Regarding periodic brain activity, spectral peak in delta band emerges in frontal and central brain regions indicates a typical phenomenon of neural entrainment, which is formed by coupling periodic brain activity to external rhythmic acupuncture stimulation. In addition, the statistical results show that alpha periodic power is an important indicator for characterizing the modulatory effects of acupuncture on periodic brain activity. As for aperiodic brain activity, broadband EEG spectral trend analysis demonstrates a steeper aperiodic slope in left parietal lobe and a stronger negative correlation with the aperiodic offset under acupuncture compared with resting state, with the absolute value of correlation coefficient increasing from 0.27 to 0.50. Based on the two parameters that can best characterize the acupuncture effect, alpha periodic power and aperiodic slope, the accurate decoding of acupuncture manipulation is realized with AUC = 0.87. This work shows the modulatory effect of peripheral nerve stimulation with acupuncture on the brain activity by characterizing the periodic and aperiodic spectrum features of EEG, providing new insights into the comprehensive understanding of the response processes of human brain to acupuncture stimulation.

Theta-gamma-coupling as predictor of working memory performance in young and elderly healthy people

The relationship between working memory (WM) and neuronal oscillations can be studied in detail using brain stimulation techniques, which provide a method for modulating these oscillations and thus influencing WM. The endogenous coupling between the amplitude of gamma oscillations and the phase of theta oscillations is crucial for cognitive control. Theta/gamma peak-coupled transcranial alternating current stimulation (TGCp-tACS) can modulate this coupling and thus influence WM performance. This study investigated the effects of TGCp-tACS on WM in older adults and compared their responses with those of younger participants from our previous work who underwent the same experimental design. Twenty-eight older subjects underwent both TGCp-tACS and sham stimulation sessions at least 72 h apart. Resting-state electroencephalography (EEG) was recorded before and after the interventions, and a WM task battery with five different WM tasks was performed during the interventions to assess various WM components. Outcomes measured included WM task performance (e.g., accuracy, reaction time (RT)) and changes in power spectral density (PSD) in different frequency bands. TGCp-tACS significantly decreased accuracy and RT on the 10- and 14-point Sternberg tasks and increased RT on the Digit Symbol Substitution Test in older adults. In contrast, younger participants showed a significant increase in accuracy only on the 14-item Sternberg task. Electrophysiological analysis revealed a decrease in delta and theta PSD and an increase in high gamma PSD in both younger and older participants after verum stimulation. In conclusion, theta-gamma coupling is essential for WM and modulation of this coupling affects WM performance. The effects of TGCp-tACS on WM vary with age due to natural brain changes. To better support older adults, the study suggests several strategies to improve cognitive function, including: Adjusting stimulation parameters, applying stimulation to two sites, conducting multiple sessions, and using brain imaging techniques for precise targeting.

Challenges and Approaches in the Study of Neural Entrainment

When exposed to rhythmic stimulation, the human brain displays rhythmic activity across sensory modalities and regions. Given the ubiquity of this phenomenon, how sensory rhythms are transformed into neural rhythms remains surprisingly inconclusive. An influential model posits that endogenous oscillations entrain to external rhythms, thereby encoding environmental dynamics and shaping perception. However, research on neural entrainment faces multiple challenges, from ambiguous definitions to methodological difficulties when endogenous oscillations need to be identified and disentangled from other stimulus-related mechanisms that can lead to similar phase-locked responses. Yet, recent years have seen novel approaches to overcome these challenges, including computational modeling, insights from dynamical systems theory, sophisticated stimulus designs, and study of neuropsychological impairments. This review outlines key challenges in neural entrainment research, delineates state-of-the-art approaches, and integrates findings from human and animal neurophysiology to provide a broad perspective on the usefulness, validity, and constraints of oscillatory models in brain-environment interaction.

Improving working memory by electrical stimulation and cross-frequency coupling

Working memory (WM) is essential for the temporary storage and processing of information required for complex cognitive tasks and relies on neuronal theta and gamma oscillations. Given the limited capacity of WM, researchers have investigated various methods to improve it, including transcranial alternating current stimulation (tACS), which modulates brain activity at specific frequencies. One particularly promising approach is theta-gamma peak-coupled-tACS (TGCp-tACS), which simulates the natural interaction between theta and gamma oscillations that occurs during cognitive control in the brain. The aim of this study was to improve WM in healthy young adults with TGCp-tACS, focusing on both behavioral and neurophysiological outcomes. Thirty-one participants completed five WM tasks under both sham and verum stimulation conditions. Electroencephalography (EEG) recordings before and after stimulation showed that TGCp-tACS increased power spectral density (PSD) in the high-gamma region at the stimulation site, while PSD decreased in the theta and delta regions throughout the cortex. From a behavioral perspective, although no significant changes were observed in most tasks, there was a significant improvement in accuracy in the 14-item Sternberg task, indicating an improvement in phonological WM. In conclusion, TGCp-tACS has the potential to promote and improve the phonological component of WM. To fully realize the cognitive benefits, further research is needed to refine the stimulation parameters and account for individual differences, such as baseline cognitive status and hormonal factors.

Exploring the potential of combining transcranial magnetic stimulation and electroencephalography to investigate mild cognitive impairment and Alzheimer's disease: a systematic review

Transcranial magnetic stimulation (TMS) and electroencephalography (EEG) are non-invasive techniques used for neuromodulation and recording brain electrical activity, respectively. The integration of TMS-EEG has emerged as a valuable tool for investigating the complex mechanisms involved in age-related disorders, such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). By systematically synthesizing TMS-EEG studies, this review aims to shed light on the neurophysiological mechanisms underlying MCI and AD, while also exploring the practical applications of TMS-EEG in clinical settings. PubMed, ScienceDirect, and PsychInfo were selected as the databases for this review. The 22 eligible studies included a total of 592 individuals with MCI or AD as well as 301 cognitively normal adults. TMS-EEG assessments unveiled specific patterns of corticospinal excitability, plasticity, and brain connectivity that distinguished individuals on the AD spectrum from cognitively normal older adults. Moreover, the TMS-induced EEG features were observed to be correlated with cognitive performance and the presence of AD pathological biomarkers. The comprehensive examination of the existing studies demonstrates that the combination of TMS and EEG has yielded valuable insights into the neurophysiology of MCI and AD. This integration shows great potential for early detection, monitoring disease progression, and anticipating response to treatment. Future research is of paramount importance to delve into the potential utilization of TMS-EEG for treatment optimization in individuals with MCI and AD.

Effects of tDCS on emotion recognition and brain oscillations

INTRODUCTION

Emotion recognition, the ability to interpret the emotional state of individuals by looking at their facial expressions, is essential for healthy social interactions and communication. There is limited research on the effects of tDCS on emotion recognition in the literature. This study aimed to investigate the effects of anodal stimulation of the ventromedial prefrontal cortex (vmPFC), a key region for emotion recognition from facial expressions, on emotion recognition and brain oscillations.

METHOD

A single-blind randomized-controlled study was conducted with 54 healthy participants. Before and after brain stimulation emotion recognition tasks were administered and resting-state EEG were recorded. The changes in task performances and brain oscillations were analyzed using repeated-measures two-way ANOVA analysis.

RESULTS

There was no significant difference in the emotion recognition tasks between groups in pre-post measurements. The changes in delta, theta, alpha, beta and gamma frequency bands in the frontal, temporal, and posterio-occipital regions, which were determined as regions of interest in resting state EEG data before and after tDCS, were compared between groups. The results showed that there was a significant difference between groups only in delta frequency before and after tDCS in the frontal and temporal regions. While an increase in delta activity was observed in the experimental group in the frontal and temporal regions, a decrease was observed in the control group.

CONCLUSIONS

The tDCS may not have improved emotion recognition because it may not have had the desired effect on the vmPFC, which is in the lower part of the prefrontal lobe. The changes in EEG frequencies observed section tDCS may be similar to those seen in some pathological processes, which could explain the lack of improvement in emotion recognition. Future studies to be carried out for better understand this effect are important.

Adaptive and Compensatory Neural Signatures in Fibromyalgia: An Analysis of Resting-State and Stimulus-Evoked EEG Oscillations

This study aimed to investigate clinical and physiological predictors of brain oscillatory activity in patients with fibromyalgia (FM), assessing resting-state power, event-related desynchronization (ERD), and event-related synchronization (ERS) during tasks. We performed a cross-sectional analysis, including clinical and neurophysiological data from 78 subjects with FM. Multivariate regression models were built to explore predictors of electroencephalography bands. Our findings show a negative correlation between beta oscillations and pain intensity; fibromyalgia duration is positively associated with increased oscillatory power at low frequencies and in the beta band; ERS oscillations in the theta and alpha bands seem to be correlated with better symptoms of FM; fatigue has a signature in the alpha band-a positive relationship in resting-state and a negative relationship in ERS oscillations. Specific neural signatures lead to potential clusters of neural adaptation, in which beta oscillatory activity in the resting state represents a more adaptive activity when pain levels are low and stimulus-evoked oscillations at lower frequencies are likely brain compensatory mechanisms. These neurophysiological changes may help to understand the impact of long-term chronic pain in the central nervous system and the descending inhibitory system in fibromyalgia subjects.

The neuron mixer and its impact on human brain dynamics

A signal mixer facilitates rich computation, which has been the building block of modern telecommunication. This frequency mixing produces new signals at the sum and difference frequencies of input signals, enabling powerful operations such as heterodyning and multiplexing. Here, we report that a neuron is a signal mixer. We found through ex vivo and in vivo whole-cell measurements that neurons mix exogenous (controlled) and endogenous (spontaneous) subthreshold membrane potential oscillations, producing new oscillation frequencies, and that neural mixing originates in voltage-gated ion channels. Furthermore, we demonstrate that mixing is evident in human brain activity and is associated with cognitive functions. We found that the human electroencephalogram displays distinct clusters of local and inter-region mixing and that conversion of the salient posterior alpha-beta oscillations into gamma-band oscillations regulates visual attention. Signal mixing may enable individual neurons to sculpt the spectrum of neural circuit oscillations and utilize them for computational operations.

Therapeutic potential of gamma entrainment using sensory stimulation for cognitive symptoms associated with schizophrenia

Schizophrenia is a complex neuropsychiatric disorder with significant morbidity. Treatment options that address the spectrum of symptoms are limited, highlighting the need for innovative therapeutic approaches. Gamma Entrainment Using Sensory Stimulation (GENUS) is an emerging treatment for neuropsychiatric disorders that uses sensory stimulation to entrain impaired oscillatory network activity and restore brain function. Aberrant oscillatory activity often underlies the symptoms experienced by patients with schizophrenia. We propose that GENUS has therapeutic potential for schizophrenia. This paper reviews the current status of schizophrenia treatment and explores the use of sensory stimulation as an adjunctive treatment, specifically through gamma entrainment. Impaired gamma frequency entrainment is observed in patients, particularly in response to auditory and visual stimuli. Thus, sensory stimulation, such as music listening, may have therapeutic potential for individuals with schizophrenia. GENUS holds novel therapeutic potential to improve the lives of individuals with schizophrenia, but further research is required to determine the efficacy of GENUS, optimize its delivery and therapeutic window, and develop strategies for its implementation in specific patient populations.

Decreased Resting-State Alpha Self-Synchronization in Depressive Disorder

Background. Depression disorder has been associated with altered oscillatory brain activity. The common methods to quantify oscillatory activity are Fourier and wavelet transforms. Both methods have difficulties distinguishing synchronized oscillatory activity from nonrhythmic and large-amplitude artifacts. Here we proposed a method called self-synchronization index (SSI) to quantify synchronized oscillatory activities in neural data. The method considers temporal characteristics of neural oscillations, amplitude, and cycles, to estimate the synchronization value for a specific frequency band. Method. The recorded electroencephalography (EEG) data of 45 depressed and 55 healthy individuals were used. The SSI method was applied to each EEG electrode filtered in the alpha frequency band (8-13 Hz). The multiple linear regression model was used to predict depression severity (Beck Depression Inventory-II scores) using alpha SSI values. Results. Patients with severe depression showed a lower alpha SSI than those with moderate depression and healthy controls in all brain regions. Moreover, the alpha SSI values negatively correlated with depression severity in all brain regions. The regression model showed a significant performance of depression severity prediction using alpha SSI. Conclusion. The findings support the SSI measure as a powerful tool for quantifying synchronous oscillatory activity. The data examined in this article support the idea that there is a strong link between the synchronization of alpha oscillatory neural activities and the level of depression. These findings yielded an objective and quantitative depression severity prediction.

The oscillatory features of visual processing are altered in healthy aging

The temporal features of visual processing were compared between young and elderly healthy participants in visual object and word recognition tasks using the technique of random temporal sampling. The target stimuli were additively combined with a white noise field and were exposed very briefly (200 ms). Target visibility oscillated randomly throughout exposure duration by manipulating the signal-to-noise ratio (SNR). Classification images (CIs) based on response accuracy were calculated to reflect processing efficiency according to the time elapsed since target onset and the power of SNR oscillations in the 5-55 Hz range. CIs differed substantially across groups whereas individuals of the same group largely shared crucial features such that a machine learning algorithm reached 100% accuracy in classifying the data patterns of individual participants into their proper group. These findings demonstrate altered perceptual oscillations in healthy aging and are consistent with previous investigations showing brain oscillation anomalies in the elderly.

Test-retest reliability of spectral parameterization by 1/f characterization using SpecParam

SpecParam (formally known as FOOOF) allows for the refined measurements of electroencephalography periodic and aperiodic activity, and potentially provides a non-invasive measurement of excitation: inhibition balance. However, little is known about the psychometric properties of this technique. This is integral for understanding the usefulness of SpecParam as a tool to determine differences in measurements of cognitive function, and electroencephalography activity. We used intraclass correlation coefficients to examine the test-retest reliability of parameterized activity across three sessions (90 minutes apart and 30 days later) in 49 healthy young adults at rest with eyes open, eyes closed, and during three eyes closed cognitive tasks including subtraction (Math), music recall (Music), and episodic memory (Memory). Intraclass correlation coefficients were good for the aperiodic exponent and offset (intraclass correlation coefficients > 0.70) and parameterized periodic activity (intraclass correlation coefficients > 0.66 for alpha and beta power, central frequency, and bandwidth) across conditions. Across all three sessions, SpecParam performed poorly in eyes open (40% of participants had poor fits over non-central sites) and had poor test-retest reliability for parameterized periodic activity. SpecParam mostly provides reliable metrics of individual differences in parameterized neural activity. More work is needed to understand the suitability of eyes open resting data for parameterization using SpecParam.

Astrocytes in Pain Perception: A Systems Neuroscience Approach

Astrocytes play an active role in the function of the brain integrating neuronal activity and regulating back neuronal dynamic. They have recently emerged as active contributors of brain's emergent properties such as perceptions. Here, we analyzed the role of astrocytes in pain perception from the lens of systems neuroscience, and we do this by analyzing how astrocytes encode nociceptive information within brain processing areas and how they are key regulators of the internal state that determines pain perception. Specifically, we discuss the dynamic interactions between astrocytes and neuromodulators, such as noradrenaline, highlighting their role in shaping the level of activation of the neuronal ensemble, thereby influencing the experience of pain. Also, we will discuss the possible implications of an "Astro-NeuroMatrix" in the integration of pain across sensory, affective, and cognitive dimensions of pain perception.

rTMS reduces delta and increases theta oscillations in Alzheimer's disease: A visual-evoked and event-related potentials study

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising alternative therapy for Alzheimer's disease (AD) due to its ability to modulate neural networks and enhance cognitive function. This treatment offers the unique advantage of enabling real-time monitoring of immediate cognitive effects and dynamic brain changes through electroencephalography (EEG).

OBJECTIVE

This study focused on exploring the effects of left parietal rTMS stimulation on visual-evoked potentials (VEP) and visual event-related potentials (VERP) in AD patients.

METHODS

Sixteen AD patients were recruited for this longitudinal study. EEG data were collected within a Faraday cage both pre- and post-rTMS to evaluate its impact on potentials.

RESULTS

Significant alterations were found in both VEP and VERP oscillations. Specifically, delta power in VEP decreased, while theta power in VERP increased post-rTMS, indicating a modulation of brain activities.

DISCUSSION

These findings confirm the positive modulatory impact of rTMS on brain activities in AD, evidenced by improved cognitive scores. They align with previous studies highlighting the potential of rTMS in managing hyperexcitability and oscillatory disturbances in the AD cortex.

CONCLUSION

Cognitive improvements post-rTMS endorse its potential as a promising neuromodulatory treatment for cognitive enhancement in AD, thereby providing critical insights into the neurophysiological anomalies in AD and possible therapeutic avenues.

Transcranial Alternating Current Stimulation to Modulate Alpha Activity: A Systematic Review

BACKGROUND

Transcranial alternating current stimulation (tACS) has been one of numerous investigation methods used for their potential to modulate brain oscillations; however, such investigations have given contradictory results and a lack of standardization.

OBJECTIVES

In this systematic review, we aimed to assess the potential of tACS to modulate alpha spectral power. The secondary outcome was the identification of tACS methodologic key parameters, adverse effects, and sensations.

MATERIALS AND METHODS

Studies in healthy adults who were receiving active and sham tACS intervention or any differential condition were included. The main outcome assessed was the increase/decrease of alpha spectral power through either electroencephalography or magnetoencephalography. Secondary outcomes were methodologic parameters, sensation reporting, and adverse effects. Risks of bias and the study quality were assessed with the Cochrane assessment tool.

RESULTS

We obtained 1429 references, and 20 met the selection criteria. A statistically significant alpha-power increase was observed in nine studies using continuous tACS stimulation and two using intermittent tACS stimulation set at a frequency within the alpha range. A statistically significant alpha-power increase was observed in three more studies using a stimulation frequency outside the alpha range. Heterogeneity among stimulation parameters was recognized. Reported adverse effects were mild. The implementation of double blind was identified as challenging using tACS, in part owing to electrical artifacts generated by stimulation on the recorded signal.

CONCLUSIONS

Most assessed studies reported that tACS has the potential to modulate brain alpha power. The optimization of this noninvasive brain stimulation method is of interest mostly for its potential clinical applications with neurological conditions associated with perturbations in alpha brain activity. However, more research efforts are needed to standardize optimal parameters to achieve lasting modulation effects, develop methodologic alternatives to reduce experimental bias, and improve the quality of studies using tACS to modulate brain activity.

Effectiveness assessment of repetitive transcranial alternating current stimulation with concurrent EEG and fNIRS measurement

Transcranial alternating current stimulation (tACS) exhibits the capability to interact with endogenous brain oscillations using an external low-intensity sinusoidal current and influences cerebral function. Despite its potential benefits, the physiological mechanisms and effectiveness of tACS are currently a subject of debate and disagreement. The aims of our study are to (i) evaluate the neurological and behavioral impact of tACS by conducting repetitive sham-controlled experiments and (ii) propose criteria to evaluate effectiveness, which can serve as a benchmark to determine optimal individual-based tACS protocols. In this study, 15 healthy adults participated in the experiment over two visiting: sham and tACS (i.e., 5 Hz, 1 mA). During each visit, we used multimodal recordings of the participants' brain, including simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), along with a working memory (WM) score to quantify neurological effects and cognitive changes immediately after each repetitive sham/tACS session. Our results indicate increased WM scores, hemodynamic response strength, and EEG power in theta and delta bands both during and after the tACS period. Additionally, the observed effects do not increase with prolonged stimulation time, as the effects plateau towards the end of the experiment. In conclusion, our proposed closed-loop scheme offers a promising advance for evaluating the effectiveness of tACS during the stimulation session. Specifically, the assessment criteria use participant-specific brain-based signals along with a behavioral output. Moreover, we propose a feedback efficacy score that can aid in determining the optimal stimulation duration based on a participant-specific brain state, thereby preventing the risk of overstimulation.

Gender-Specific Interactions in a Visual Object Recognition Task in Persons with Opioid Use Disorder

Opioid use disorder (OUD)-associated overdose deaths have reached epidemic proportions worldwide over the past two decades, with death rates for men reported at twice the rate for women. Using a controlled, cross-sectional, age-matched (18-56 y) design to better understand the cognitive neuroscience of OUD, we evaluated the electroencephalographic (EEG) responses of male and female participants with OUD vs. age- and gender-matched non-OUD controls during a simple visual object recognition Go/No-Go task. Overall, women had significantly slower reaction times (RTs) than men. In addition, EEG N200 and P300 event-related potential (ERP) amplitudes for non-OUD controls were significantly larger for men, while their latencies were significantly shorter than for women. However, while N200 and P300 amplitudes were not significantly affected by OUD for either men or women in this task, latencies were also affected differentially in men vs. women with OUD. Accordingly, for both N200 and P300, male OUD participants exhibited longer latencies while female OUD participants exhibited shorter ones than in non-OUD controls. Additionally, robust oscillations were found in all participants during a feedback message associated with performance in the task. Although alpha and beta power during the feedback message were significantly greater for men than women overall, both alpha and beta oscillations exhibited significantly lower power in all participants with OUD. Taken together, these findings suggest important gender by OUD differences in cognitive processing and reflection of performance in this simple visual task.

Pattern breaking: a complex systems approach to psychedelic medicine

Recent research has demonstrated the potential of psychedelic therapy for mental health care. However, the psychological experience underlying its therapeutic effects remains poorly understood. This paper proposes a framework that suggests psychedelics act as destabilizers, both psychologically and neurophysiologically. Drawing on the 'entropic brain' hypothesis and the 'RElaxed Beliefs Under pSychedelics' model, this paper focuses on the richness of psychological experience. Through a complex systems theory perspective, we suggest that psychedelics destabilize fixed points or attractors, breaking reinforced patterns of thinking and behaving. Our approach explains how psychedelic-induced increases in brain entropy destabilize neurophysiological set points and lead to new conceptualizations of psychedelic psychotherapy. These insights have important implications for risk mitigation and treatment optimization in psychedelic medicine, both during the peak psychedelic experience and during the subacute period of potential recovery.

Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study

Mental disorders are among the top most demanding challenges in world-wide health. A large number of mental disorders exhibit pathological rhythms, which serve as the disorders characteristic biomarkers. These rhythms are the targets for neurostimulation techniques. Open-loop neurostimulation employs stimulation protocols, which are rather independent of the patients health and brain state in the moment of treatment. Most alternative closed-loop stimulation protocols consider real-time brain activity observations but appear as adaptive open-loop protocols, where e.g., pre-defined stimulation sets in if observations fulfil pre-defined criteria. The present theoretical work proposes a fully-adaptive closed-loop neurostimulation setup, that tunes the brain activities power spectral density (PSD) according to a user-defined PSD. The utilized brain model is non-parametric and estimated from the observations via magnitude fitting in a pre-stimulus setup phase. Moreover, the algorithm takes into account possible conduction delays in the feedback connection between observation and stimulation electrode. All involved features are illustrated on pathological α- and γ-rhythms known from psychosis. To this end, we simulate numerically a linear neural population brain model and a non-linear cortico-thalamic feedback loop model recently derived to explain brain activity in psychosis.

Event-related Oscillations to Emotional Faces are Related to a History of Internalizing Disorders

Event-related oscillations (EROs) may represent sensitive biomarkers or endophenotypes for disorders that underlie risk behaviors such as suicidal thoughts and actions. In this study, young adults of American Indian (AI) (n = 821) and Mexican American (MA) (n = 721) ancestry (age 18-30 yrs) were clinically assessed for internalizing and externalizing disorders, and an internalizing scale was generated by extracting core diagnostic items from 6 lifetime DSM5-compatible diagnoses (social phobia, panic disorder, agoraphobia, obsessive compulsive disorder, post-traumatic stress disorder, major depressive episode) and symptoms of suicidality. EROs were generated to sad, happy and neutral faces, and energy and phase locking of delta ERO oscillations were assessed in frontal areas. An increase in delta ERO energy was found in the frontal lead (FZ) following presentation of the sad facial expressions in those with a history of 10 or more internalizing symptoms compared to those with no symptoms. Increases in delta ERO energy in FZ were also associated with a diagnosis of major depressive disorder (MDD), but not with anxiety disorders or antisocial personality disorder/conduct disorders (ASP). Major depression was also associated with increases in cross-cortical phase-locking (FZ-PZ). A decrease in the percentage of correctly identified neutral faces also was seen among those with 10 or more internalizing symptoms compared to those without internalizing symptoms, and in those with anxiety disorders, but not in those with ASP or MDD as compared to their controls. These findings suggest ERO measures may represent important potential biomarkers of depressive disorders as well as risk indicators for suicidal behaviors.

Chemical suppression of harmaline-induced body tremor yields recovery of pairwise neuronal coherence in cerebellar nuclei neurons

Neuronal oscillations occur in health and disease; however, their characteristics can differ across conditions. During voluntary movement in freely moving rats, cerebellar nuclei (CN) neurons display intermittent but coherent oscillations in the theta frequency band (4-12 Hz). However, in the rat harmaline model of essential tremor, a disorder attributed to cerebellar malfunction, CN neurons display aberrant oscillations concomitantly with the emergence of body tremor. To identify the oscillation features that may underlie the emergence of body tremor, we analyzed neuronal activity recorded chronically from the rat CN under three conditions: in freely behaving animals, in harmaline-treated animals, and during chemical suppression of the harmaline-induced body tremor. Suppression of body tremor did not restore single neuron firing characteristics such as firing rate, the global and local coefficients of variation, the likelihood of a neuron to fire in bursts or their tendency to oscillate at a variety of dominant frequencies. Similarly, the fraction of simultaneously recorded neuronal pairs oscillating at a similar dominant frequency (<1 Hz deviation) and the mean frequency deviation within pairs remained similar to the harmaline condition. Moreover, the likelihood that pairs of CN neurons would co-oscillate was not only significantly lower than that measured in freely moving animals, but was significantly worse than chance. By contrast, the chemical suppression of body tremor fully restored pairwise neuronal coherence; that is, unlike in the harmaline condition, pairs of neurons that oscillated at the same time and frequency displayed high coherence, as in the controls. We suggest that oscillation coherence in CN neurons is essential for the execution of smooth movement and its loss likely underlies the emergence of body tremor.

Neuromodulation of Neural Oscillations in Health and Disease

Using EEG and local field potentials (LFPs) as an index of large-scale neural activities, research has been able to associate neural oscillations in different frequency bands with markers of cognitive functions, goal-directed behavior, and various neurological disorders. While this gives us a glimpse into how neurons communicate throughout the brain, the causality of these synchronized network activities remains poorly understood. Moreover, the effect of the major neuromodulatory systems (e.g., noradrenergic, cholinergic, and dopaminergic) on brain oscillations has drawn much attention. More recent studies have suggested that cross-frequency coupling (CFC) is heavily responsible for mediating network-wide communication across subcortical and cortical brain structures, implicating the importance of neurotransmitters in shaping coordinated actions. By bringing to light the role each neuromodulatory system plays in regulating brain-wide neural oscillations, we hope to paint a clearer picture of the pivotal role neural oscillations play in a variety of cognitive functions and neurological disorders, and how neuromodulation techniques can be optimized as a means of controlling neural network dynamics. The aim of this review is to showcase the important role that neuromodulatory systems play in large-scale neural network dynamics, informing future studies to pay close attention to their involvement in specific features of neural oscillations and associated behaviors.

Sex differences in amygdalohippocampal oscillations and neuronal activation in a rodent anxiety model and in response to infralimbic deep brain stimulation

Introduction

Depression and anxiety are highly comorbid mental disorders with marked sex differences. Both disorders show altered activity in the amygdala, hippocampus, and prefrontal cortex. Infralimbic deep brain stimulation (DBS-IL) has anxiolytic and antidepressant effects, but the underlying mechanisms remain unclear. We aimed to contribute to understanding sex differences in the neurobiology of these disorders.

Methods

In male and female rats, we recorded neural oscillations along the dorsoventral axis of the hippocampus and the amygdala in response to an anxiogenic drug, FG-7142. Following this, we applied DBS-IL.

Results

Surprisingly, in females, the anxiogenic drug failed to induce most of the changes observed in males. We found sex differences in slow, delta, theta, and beta oscillations, and the amygdalo-hippocampal communication in response to FG-7142, with modest changes in females. Females had a more prominent basal gamma, and the drug altered this band only in males. We also analyzed c-Fos expression in both sexes in stress-related structures in response to FG-7142, DBS-IL, and combined interventions. With the anxiogenic drug, females showed reduced expression in the nucleus incertus, amygdala, septohippocampal network, and neocortical levels. In both experiments, the DBS-IL reversed FG-7142-induced effects, with a more substantial effect in males than females.

Discussion

Here, we show a reduced response in female rats which contrasts with the higher prevalence of anxiety in women but is consistent with other studies in rodents. Our results open compelling questions about sex differences in the neurobiology of anxiety and depression and their study in animal models.

Development of network oscillations through adolescence in male and female rats

The primary aim of this research was to study the developmental trajectory of oscillatory synchronization in neural networks of normal healthy rats during adolescence, corresponding to the vulnerable age of schizophrenia prodrome in human. To monitor the development of oscillatory networks through adolescence we used a "pseudo-longitudinal" design. Recordings were performed in terminal experiments under urethane anesthesia, every day from PN32 to PN52 using rats-siblings from the same mother, to reduce individual innate differences between subjects. We found that hippocampal theta power decreased and delta power in prefrontal cortex increased through adolescence, indicating that the oscillations in the two different frequency bands follow distinct developmental trajectories to reach the characteristic oscillatory activity found in adults. Perhaps even more importantly, theta rhythm showed age-dependent stabilization toward late adolescence. Furthermore, sex differences was found in both networks, more prominent in the prefrontal cortex compared with hippocampus. Delta increase was stronger in females and theta stabilization was completed earlier in females, in postnatal days PN41-47, while in males it was only completed in late adolescence. Our finding of a protracted maturation of theta-generating networks in late adolescence is overall consistent with the findings of longitudinal studies in human adolescents, in which oscillatory networks demonstrated a similar pattern of maturation.

10 Minutes Frontal 40 Hz tACS-Effects on Working Memory Tested by Luck-Vogel Task

Working memory is a cognitive process that involves short-term active maintenance, flexible updating, and processing of goal- or task-relevant information. All frequency bands are involved in working memory. The activities of the theta and gamma frequency bands in the frontoparietal network are highly involved in working memory processes; theta oscillations play a role in the temporal organization of working memory items, and gamma oscillations influence the maintenance of information in working memory. Transcranial alternating current stimulation (tACS) results in frequency-specific modulation of endogenous oscillations and has shown promising results in cognitive neuroscience. The electrophysiological and behavioral changes induced by the modulation of endogenous gamma frequency in the prefrontal cortex using tACS have not been extensively studied in the context of working memory. Therefore, we aimed to investigate the effects of frontal gamma-tACS on working memory outcomes. We hypothesized that a 10-min gamma tACS administered over the frontal cortex would significantly improve working memory outcomes. Young healthy participants performed Luck-Vogel cognitive behavioral tasks with simultaneous pre- and post-intervention EEG recording (Sham versus 40 Hz tACS). Data from forty-one participants: sham (15 participants) and tACS (26 participants), were used for the statistical and behavioral analysis. The relative changes in behavioral outcomes and EEG due to the intervention were analyzed. The results show that tACS caused an increase in the power spectral density in the high beta and low gamma EEG bands and a decrease in left-right coherence. On the other hand, tACS had no significant effect on success rates and response times. Conclusion: 10 min of frontal 40 Hz tACS was not sufficient to produce detectable behavioral effects on working memory, whereas electrophysiological changes were evident. The limitations of the current stimulation protocol and future directions are discussed in detail in the following sections.

The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.

Oscillatory Activities in Multiple Frequency Bands in Patients with Schizophrenia During Motion Perception

Patients with schizophrenia show impairment in binding stimulus features into coherent objects, which are reflected in disturbed oscillatory activities. This study aimed to identify disturbances in multiple oscillatory bands during perceptual organization of motion perception in patients with schizophrenia. EEG was recorded from healthy controls and patients with schizophrenia during continuous presentation of a motion stimulus which induces reversals between two exogenously generated perceptions. This stimulus was used to investigate differences in motion binding processes between healthy controls and patients with schizophrenia. EEG signals were transformed into frequency components by means of the Morlet wavelet transformation in order to analyse inter-trial coherences (ITC) in the delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), and gamma (28-48 Hz) frequency bands during exogenous motion binding. Patients showed decreased delta-ITC in occipital and theta-ITC in central and parietal areas, while no significant differences were found for neither alpha nor gamma-ITCs. The present study provides one of the first insights on the oscillatory synchronizations related with the motion perception in schizophrenia. The ITC differences revealed alterations in the consistency of large-scale integration and transfer functions in patients with schizophrenia.

Modulation of Hippocampal Network Oscillation by PICK1-Dependent Cell Surface Expression of mGlu3 Receptors

Metabotropic glutamate receptor Type 3 (mGlu3) controls the sleep/wake architecture, which plays a role in the glutamatergic pathophysiology of schizophrenia. Interestingly, mGlu3 receptor expression is decreased in the brain of schizophrenic patients. However, little is known about the molecular mechanisms regulating mGlu3 receptors at the cell membrane. Subcellular receptor localization is strongly dependent on protein-protein interactions. Here we show that mGlu3 interacts with PICK1 and that this scaffolding protein is important for mGlu3 surface expression and function in hippocampal primary cultures. Disruption of their interaction via an mGlu3 C-terminal mimicking peptide or an inhibitor of the PDZ domain of PICK1 altered the functional expression of mGlu3 receptors in neurons. We next investigated the impact of disrupting the mGlu3-PICK1 interaction on hippocampal theta oscillations in vitro and in vivo in WT male mice. We found a decreased frequency of theta oscillations in organotypic hippocampal slices, similar to what was previously observed in mGlu3 KO mice. In addition, hippocampal theta power was reduced during rapid eye movement sleep, non-rapid eye movement (NREM) sleep, and wake states after intraventricular administration of the mGlu3 C-terminal mimicking peptide. Targeting the mGlu3-PICK1 complex could thus be relevant to the pathophysiology of schizophrenia.SIGNIFICANCE STATEMENT Dysregulation of the glutamatergic system might play a role in the pathophysiology of schizophrenia. Metabotropic glutamate receptors Type 3 (mGlu3) have been proposed as potential targets for schizophrenia. Understanding the molecular mechanisms regulating mGlu3 receptor at the cell membrane is critical toward comprehending how their dysfunction contributes to the pathogenesis of schizophrenia. Here we describe that the binding of the signaling and scaffolding protein PICK1 to mGlu3 receptors is important for their localization and physiological functions. The identification of new proteins that associate specifically to mGlu3 receptors will advance our understanding of the regulatory mechanisms associated with their targeting and function and ultimately might provide new therapeutic strategies to counter these psychiatric conditions.

A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment

Substance use disorders (SUDs) constitute a growing global health crisis, yet many limitations and challenges exist in SUD treatment research, including the lack of objective brain-based markers for tracking treatment outcomes. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity, and although much is known about EEG activity in acute and chronic substance use, knowledge regarding EEG in relation to abstinence and treatment outcomes is sparse. We performed a scoping review of longitudinal and pre-post treatment EEG studies that explored putative changes in brain function associated with abstinence and/or treatment in individuals with SUD. Following PRISMA guidelines, we identified studies published between January 2000 and March 2022 from online databases. Search keywords included EEG, addictive substances (e.g., alcohol, cocaine, methamphetamine), and treatment related terms (e.g., abstinence, relapse). Selected studies used EEG at least at one time point as a predictor of abstinence or other treatment-related outcomes; or examined pre- vs. post-SUD intervention (brain stimulation, pharmacological, behavioral) EEG effects. Studies were also rated on the risk of bias and quality using validated instruments. Forty-four studies met the inclusion criteria. More consistent findings included lower oddball P3 and higher resting beta at baseline predicting negative outcomes, and abstinence-mediated longitudinal decrease in cue-elicited P3 amplitude and resting beta power. Other findings included abstinence or treatment-related changes in late positive potential (LPP) and N2 amplitudes, as well as in delta and theta power. Existing studies were heterogeneous and limited in terms of specific substances of interest, brief times for follow-ups, and inconsistent or sparse results. Encouragingly, in this limited but maturing literature, many studies demonstrated partial associations of EEG markers with abstinence, treatment outcomes, or pre-post treatment-effects. Studies were generally of good quality in terms of risk of bias. More EEG studies are warranted to better understand abstinence- or treatment-mediated neural changes or to predict SUD treatment outcomes. Future research can benefit from prospective large-sample cohorts and the use of standardized methods such as task batteries. EEG markers elucidating the temporal dynamics of changes in brain function related to abstinence and/or treatment may enable evidence-based planning for more effective and targeted treatments, potentially pre-empting relapse or minimizing negative lifespan effects of SUD.

Use of electroencephalogram, gait, and their combined signals for classifying cognitive impairment and normal cognition

Background

Early identification of people at risk for cognitive decline is an important step in delaying the occurrence of cognitive impairment. This study investigated whether multimodal signals assessed using electroencephalogram (EEG) and gait kinematic parameters could be used to identify individuals at risk of cognitive impairment.

Methods

The survey was conducted at the Veterans Medical Research Institute in the Veterans Health Service Medical Center. A total of 220 individuals volunteered for this study and provided informed consent at enrollment. A cap-type wireless EEG device was used for EEG recording, with a linked-ear references based on a standard international 10/20 system. Three-dimensional motion capture equipment was used to collect kinematic gait parameters. Mild cognitive impairment (MCI) was evaluated by Seoul Neuropsychological Screening Battery-Core (SNSB-C).

Results

The mean age of the study participants was 73.5 years, and 54.7% were male. We found that specific EEG and gait parameters were significantly associated with cognitive status. Individuals with decreases in high-frequency EEG activity in high beta (25-30 Hz) and gamma (30-40 Hz) bands increased the odds ratio of MCI. There was an association between the pelvic obliquity angle and cognitive status, assessed by MCI or SNSB-C scores. Results from the ROC analysis revealed that multimodal signals combining high beta or gamma and pelvic obliquity improved the ability to discriminate MCI individuals from normal controls.

Conclusion

These findings support prior work on the association between cognitive status and EEG or gait, and offer new insights into the applicability of multimodal signals to distinguish cognitive impairment.

Methodological considerations for studying neural oscillations

Neural oscillations are ubiquitous across recording methodologies and species, broadly associated with cognitive tasks, and amenable to computational modelling that investigates neural circuit generating mechanisms and neural population dynamics. Because of this, neural oscillations offer an exciting potential opportunity for linking theory, physiology and mechanisms of cognition. However, despite their prevalence, there are many concerns-new and old-about how our analysis assumptions are violated by known properties of field potential data. For investigations of neural oscillations to be properly interpreted, and ultimately developed into mechanistic theories, it is necessary to carefully consider the underlying assumptions of the methods we employ. Here, we discuss seven methodological considerations for analysing neural oscillations. The considerations are to (1) verify the presence of oscillations, as they may be absent; (2) validate oscillation band definitions, to address variable peak frequencies; (3) account for concurrent non-oscillatory aperiodic activity, which might otherwise confound measures; measure and account for (4) temporal variability and (5) waveform shape of neural oscillations, which are often bursty and/or nonsinusoidal, potentially leading to spurious results; (6) separate spatially overlapping rhythms, which may interfere with each other; and (7) consider the required signal-to-noise ratio for obtaining reliable estimates. For each topic, we provide relevant examples, demonstrate potential errors of interpretation, and offer suggestions to address these issues. We primarily focus on univariate measures, such as power and phase estimates, though we discuss how these issues can propagate to multivariate measures. These considerations and recommendations offer a helpful guide for measuring and interpreting neural oscillations.

Theta and gamma oscillatory dynamics in mouse models of Alzheimer's disease: A path to prospective therapeutic intervention

Understanding the neural basis of cognitive deficits, a key feature of Alzheimer's disease (AD), is imperative for achieving the therapy of the disease. Rhythmic oscillatory activities in neural systems are a fundamental mechanism for diverse brain functions, including cognition. In several neurological conditions like AD, aberrant neural oscillations have been shown to play a central role. Furthermore, manipulation of brain oscillations in animals has confirmed their impact on cognition and disease. In this article, we review the evidence from mouse models that shows how synchronized oscillatory activity is intricately linked to AD machinery. We primarily focus on recent reports showing abnormal oscillatory activities at theta and gamma frequencies in AD condition and their influence on cellular disturbances and cognitive impairments. A thorough comprehension of the role that neuronal oscillations play in AD pathology should pave the way to therapeutic interventions that can curb the disease.

Where do we stand now regarding treatment of psychiatric and neurodegenerative disorders? Considerations in using magnetoelectric nanoparticles as an innovative approach

Almost 1000 million people have recently been diagnosed with a mental health or substance disorder (Ritchie & Roser, 2018). Psychiatric disorders, and their treatment, represent a big burden to the society worldwide, causing about 8 million deaths per year (Walker et al., 2015). Daily progress in science enables continuous advances in methods to treat patients; however, the brain remains to be the most unknown and complex organ of the body. There is a growing demand for innovative approaches to treat psychiatric as well as neurodegenerative disorders, disorders with unknown curability, and treatments mostly designed to slow disease progression. Based on that need and the peculiarity of the central nervous system, in the present review, we highlight the handicaps of the existing approaches as well as discuss the potential of the recently introduced magnetoelectric nanoparticles (MENPs) to become a game-changing tool in future applications for the treatment of brain alterations. Unlike other stimulation approaches, MENPs have the potential to enable a wirelessly controlled stimulation at a single-neuron level without requiring genetic modification of the neural tissue and no toxicity has yet been reported. Their potential as a new tool for targeting the brain is discussed. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Cardiovascular Disease Therapeutic Approaches and Drug Discovery > Neurological Disease.

Schizophrenia, Bipolar Disorder and Pre-Attentional Inhibitory Deficits

According to recent findings schizophrenia and bipolar disorder as separate disease entities manifest similarities in neuropsychological functioning. Typical disturbances in both disorders are related to sensory gating deficits characterized by decreased inhibitory functions in responses to various insignificant perceptual signals which are experimentally tested by event related potentials (ERP) and measured P50 wave. In this context, recent findings implicate that disrupted binding and disintegration of consciousness in schizophrenia and bipolar disorder that are related to inhibitory deficits reflected in P50 response may explain similarities in psychotic disturbances in both disorders. With this aim, this review summarizes literature about P50 in both schizophrenia and bipolar disorder.

Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood

The neurodevelopmental period spanning early-to-middle childhood represents a time of significant growth and reorganisation throughout the cortex. Such changes are critical for the emergence and maturation of a range of social and cognitive processes. Here, we utilised both eyes open and eyes closed resting-state electroencephalography (EEG) to examine maturational changes in both oscillatory (i.e., periodic) and non-oscillatory (aperiodic, '1/f-like') activity in a large cohort of participants ranging from 4-to-12 years of age (N = 139, average age=9.41 years, SD=1.95). The EEG signal was parameterised into aperiodic and periodic components, and linear regression models were used to evaluate if chronological age could predict aperiodic exponent and offset, as well as well as peak frequency and power within the alpha and beta ranges. Exponent and offset were found to both decrease with age, while aperiodic-adjusted alpha peak frequency increased with age; however, there was no association between age and peak frequency for the beta band. Age was also unrelated to aperiodic-adjusted spectral power within either the alpha or beta bands, despite both frequency ranges being correlated with the aperiodic signal. Overall, these results highlight the capacity for both periodic and aperiodic features of the EEG to elucidate age-related functional changes within the developing brain.

Utility of 7,8-dihydroxyflavone in preventing astrocytic and synaptic deficits in the hippocampus elicited by PTSD

Astrocytic functions and brain-derived neurotrophic factor (BDNF)-tyrosine kinase receptor B (TrkB) signaling pathways are impaired in stress-related neuropsychiatric diseases. Previous studies have reported neuroprotective effects of 7,8-dihydroxyflavone (7,8-DHF), a TrkB activator. Here, we investigated the molecular mechanisms underlying pathogenesis of post-traumatic stress disorder (PTSD) using a modified single-prolonged stress (SPS&S) model and the potential beneficial effects of 7,8-DHF. SPS&S reduced the hippocampal expression of glial fibrillary acidic protein (GFAP), a marker of astrocytes, and induced morphological changes in astrocytes. From the perspective of synaptic function, the SPS&S model displayed reduced expression of BDNF, p-TrkB, postsynaptic density protein 95 (PSD95), AMPA receptor subunit GluR1 (GluA1), NMDA receptor subunit N2A/N2B ratio, calpain-1, phosphorylated protein kinase B (Akt) and phosphorylated mammalian target of rapamycin (mTOR) and conversely, higher phosphatase and tension homolog (PTEN) expression in the hippocampus. Acute or continuous intraperitoneal administration of 7,8-DHF (5 mg/kg) after SPS&S procedures prevented SPS&S-induced fear memory generalization and anxiety-like behaviors as well as abnormalities of hippocampal oscillations. Most importantly, 7,8-DHF attenuated SPS&S-induced abnormal BDNF-TrkB signaling and calpain-1-dependent cascade of synaptic deficits. Furthermore, treatment with a TrkB inhibitor completely blocked while an mTOR inhibitor partially blocked the effects of 7,8-DHF on behavioral changes of SPS&S model mice. Our collective findings suggest that 7,8-DHF effectively alleviates PTSD-like symptoms, including fear generalization and anxiety-like behavior, potentially by preventing astrocytic and synaptic deficits in the hippocampus through targeting of TrkB.

Sleep-Wake Rhythm and Oscillatory Pattern Analysis in a Multiple Hit Schizophrenia Rat Model (Wisket)

Electroencephalography studies in schizophrenia reported impairments in circadian rhythm and oscillatory activity, which may reflect the deficits in cognitive and sensory processing. The current study evaluated the circadian rhythm and the state-dependent oscillatory pattern in control Wistar and a multiple hit schizophrenia rat model (Wisket) using custom-made software for identification of the artifacts and the classification of sleep-wake stages and the active and quiet awake substages. The Wisket animals have a clear light-dark cycle similar to controls, and their sleep-wake rhythm showed only a tendency to spend more time in non-rapid eye movement (NREM) and less in rapid eye movement (REM) stages. In spite of the weak diurnal variation in oscillation in both groups, the Wisket rats had higher power in the low-frequency delta, alpha, and beta bands and lower power in the high-frequency theta and gamma bands in most stages. Furthermore, the significant differences between the two groups were pronounced in the active waking substage. These data suggest that the special changes in the oscillatory pattern of this schizophrenia rat model may have a significant role in the impaired cognitive functions observed in previous studies.

Dependence of Working Memory on Coordinated Activity Across Brain Areas

Neural signatures of working memory (WM) have been reported in numerous brain areas, suggesting a distributed neural substrate for memory maintenance. In the current manuscript we provide an updated review of the literature focusing on intracranial neurophysiological recordings during WM in primates. Such signatures of WM include changes in firing rate or local oscillatory power within an area, along with measures of coordinated activity between areas based on synchronization between oscillations. In comparing the ability of various neural signatures in any brain area to predict behavioral performance, we observe that synchrony between areas is more frequently and robustly correlated with WM performance than any of the within-area neural signatures. We further review the evidence for alteration of inter-areal synchrony in brain disorders, consistent with an important role for such synchrony during behavior. Additionally, results of causal studies indicate that manipulating synchrony across areas is especially effective at influencing WM task performance. Each of these lines of research supports the critical role of inter-areal synchrony in WM. Finally, we propose a framework for interactions between prefrontal and sensory areas during WM, incorporating a range of experimental findings and offering an explanation for the observed link between intra-areal measures and WM performance.

Neuromodulatory effects of HD-tACS/tDCS on the prefrontal cortex: A resting-state fNIRS-EEG study

Transcranial direct and alternating current stimulation (tDCS and tACS, respectively) can modulate human brain dynamics and cognition. However, these modalities have not been compared using multiple imaging techniques concurrently. In this study, 15 participants participated in an experiment involving two sessions with a gap of 10 d. In the first and second sessions, tACS and tDCS were administered to the participants. The anode for tDCS was positioned at point FpZ, and four cathodes were positioned over the left and right prefrontal cortices (PFCs) to target the frontal regions simultaneously. tDCS was administered with 1 mA current. tACS was supplied with a current of 1 mA (zero-to-peak value) at 10 Hz frequency. Stimulation was applied concomitantly with functional near-infrared spectroscopy and electroencephalography acquisitions in the resting-state. The statistical test showed significant alteration (p < 0.001) in the mean hemodynamic responses during and after tDCS and tACS periods. Between-group comparison revealed a significantly less (p < 0.001) change in the mean hemodynamic response caused by tACS compared with tDCS. As hypothesized, we successfully increased the hemodynamics in both left and right PFCs using tDCS and tACS. Moreover, a significant increase in alpha-band power (p < 0.01) and low beta band power (p < 0.05) due to tACS was observed after the stimulation period. Although tDCS is not frequency-specific, it increased but not significantly (p > 0.05) the powers of most bands including delta, theta, alpha, low beta, high beta, and gamma. These findings suggest that both hemispheres can be targeted and that both tACS and tDCS are equally effective in high-definition configurations, which may be of clinical relevance.

Working Memory and Cross-Frequency Coupling of Neuronal Oscillations

Working memory (WM) is the active retention and processing of information over a few seconds and is considered an essential component of cognitive function. The reduced WM capacity is a common feature in many diseases, such as schizophrenia, attention deficit hyperactivity disorder (ADHD), mild cognitive impairment (MCI), and Alzheimer's disease (AD). The theta-gamma neural code is an essential component of memory representations in the multi-item WM. A large body of studies have examined the association between cross-frequency coupling (CFC) across the cerebral cortices and WM performance; electrophysiological data together with the behavioral results showed the associations between CFC and WM performance. The oscillatory entrainment (sensory, non-invasive electrical/magnetic, and invasive electrical) remains the key method to investigate the causal relationship between CFC and WM. The frequency-tuned non-invasive brain stimulation is a promising way to improve WM performance in healthy and non-healthy patients with cognitive impairment. The WM performance is sensitive to the phase and rhythm of externally applied stimulations. CFC-transcranial-alternating current stimulation (CFC-tACS) is a recent approach in neuroscience that could alter cognitive outcomes. The studies that investigated (1) the association between CFC and WM and (2) the brain stimulation protocols that enhanced WM through modulating CFC by the means of the non-invasive brain stimulation techniques have been included in this review. In principle, this review can guide the researchers to identify the most prominent form of CFC associated with WM processing (e.g., theta/gamma phase-amplitude coupling), and to define the previously published studies that manipulate endogenous CFC externally to improve WM. This in turn will pave the path for future studies aimed at investigating the CFC-tACS effect on WM. The CFC-tACS protocols need to be thoroughly studied before they can be considered as therapeutic tools in patients with WM deficits.