Thalamic model of awake alpha oscillations and implications for stimulus processing

Focal Infrared Neural Stimulation Propagates Dynamical Transformations in Auditory Cortex

Significance

Infrared neural stimulation (INS) has emerged as a potent neuromodulation technology, offering safe and focal stimulation with superior spatial recruitment profiles compared to conventional electrical methods. However, the neural dynamics induced by INS stimulation remain poorly understood. Elucidating these dynamics will help develop new INS stimulation paradigms and advance its clinical application.

Aim

In this study, we assessed the local network dynamics of INS entrainment in the auditory thalamocortical circuit using the chronically implanted rat model; our approach focused on measuring INS energy-based local field potential (LFP) recruitment induced by focal thalamocortical stimulation. We further characterized linear and nonlinear oscillatory LFP activity in response to single-pulse and periodic INS and performed spectral decomposition to uncover specific LFP band entrainment to INS. Finally, we examined spike-field transformations across the thalamocortical synapse using spike-LFP coherence coupling.

Results

We found that INS significantly increases LFP amplitude as a log-linear function of INS energy per pulse, primarily entraining to LFP β and γ bands with synchrony extending to 200 Hz in some cases. A subset of neurons demonstrated nonlinear, chaotic oscillations linked to information transfer across cortical circuits. Finally, we utilized spike-field coherences to correlate spike coupling to LFP frequency band activity and suggest an energy-dependent model of network activation resulting from INS stimulation.

Conclusions

We show that INS reliably drives robust network activity and can potently modulate cortical field potentials across a wide range of frequencies in a stimulus parameter-dependent manner. Based on these results, we propose design principles for developing full coverage, all-optical thalamocortical auditory neuroprostheses.

Monitoring Sleep Quality Through Low α-Band Activity in the Prefrontal Cortex Using a Portable Electroencephalogram Device: Longitudinal Study

BACKGROUND

The pursuit of sleep quality has become an important aspect of people's global quest for overall health. However, the objective neurobiological features corresponding to subjective perceptions of sleep quality remain poorly understood. Although previous studies have investigated the relationship between electroencephalogram (EEG) and sleep, the lack of longitudinal follow-up studies raises doubts about the reproducibility of their findings.

OBJECTIVE

Currently, there is a gap in research regarding the stable associations between EEG data and sleep quality assessed through multiple data collection sessions, which could help identify potential neurobiological targets related to sleep quality.

METHODS

In this study, we used a portable EEG device to collect resting-state prefrontal cortex EEG data over a 3-month follow-up period from 42 participants (27 in the first month, 25 in the second month, and 40 in the third month). Each month, participants' sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) to estimate their recent sleep quality.

RESULTS

We found that there is a significant and consistent positive correlation between low α band activity in the prefrontal cortex and PSQI scores (r=0.45, P<.001). More importantly, this correlation remained consistent across all 3-month follow-up recordings (P<.05), regardless of whether we considered the same cohort or expanded the sample size. Furthermore, we discovered that the periodic component of the low α band primarily contributed to this significant association with PSQI.

CONCLUSIONS

These findings represent the first identification of a stable and reliable neurobiological target related to sleep quality through multiple follow-up sessions. Our results provide a solid foundation for future applications of portable EEG devices in monitoring sleep quality and screening for sleep disorders in a broad population.

Fast Attentional Information Routing via High-Frequency Bursts in the Human Brain

Brain-wide communication supporting flexible behavior requires coordination between sensory and associative regions but how brain networks route sensory information at fast timescales to guide action remains unclear. Using spiking neural networks and human intracranial electrophysiology during spatial attention tasks, where participants detected targets at cued locations, we show that high-frequency activity bursts (HFAb) serve as information-carrying events, facilitating fast, long-range communications. HFAbs were evoked by sensory cues and targets, dynamically linked to low-frequency rhythms. Notably, both HFAb responses following cues and their decoupling from slow rhythms predicted performance accuracy. HFAbs were synchronized at the network-level, identifying distinct cue- and target-activated subnetworks. These subnetworks exhibited a temporal lead-lag organization following target onset, with cue-sactivated subnetworks preceding target-activated subnetworks when the cue provided relevant target information. Computational modeling indicated that HFAbs reflect transitions to coherent population spiking and are coordinated across networks through distinct mechanisms. Together, these findings establish HFAbs as neural mechanisms for fast, large-scale communication supporting attentional performance.

Correlation of muscle strength, information processing speed and cognitive function in the elderly with cognitive impairment--evidence from EEG

Objective

This study investigates the interplay between muscle strength, information processing speed, EEG-specific biomarkers, and cognitive function in elderly individuals with cognitive impairments, emphasizing the mediating roles of information processing speed and EEG-specific biomarkers.

Method

A cross-sectional study design was employed to recruit 151 elderly participants. The participants underwent grip strength and 30-s sit-to-stand tests to assess muscle strength, completed the Trail Making Test part A (TMT-A) and the Symbol Digit Modality Test (SDMT) to evaluate information processing speed, and utilized the Montreal Cognitive Assessment (MOCA) to gauge cognitive function. Additionally, EEG signals were recorded for 5 min to capture neural activity.

Results

The difference in information processing speed among elderly individuals with varying degrees of cognitive impairment was statistically significant (p < 0.001). A significant negative correlation was observed between the MoCA score and the time consumption of TMT-A (r = -0.402, p < 0.01), and a significant positive correlation was found between the MoCA score and the SDMT score (r = 0.609, p < 0.01). Grip strength was negatively correlated with the time consumption of TMT-A (r = -0.336, p < 0.01) and positively correlated with the SDMT score (r = 0.336, p < 0.01). A significant negative correlation was found between the 30-s sit-to-stand test and the time consumption of TMT-A (r = -0.273, p < 0.01), and a significant positive correlation was observed between the 30-s sit-to-stand test and the SDMT score (r = 0.372, p < 0.01). Additionally, we observed that the α1 power value indicators were significantly correlated with the MoCA score, the time consumption of TMT-A, and the SDMT score (all p < 0.01). The α1 power values at F7 + F8 and T5 + T6 were identified as sensitive EEG indicators for muscle strength and information processing speed. The EEG-specific indicators (B = 0.019, 95% CI: 0.003, 0.047) and information processing speed (B = 0.137, 95% CI: 0.096, 0.292) were found to partially mediate the relationship between grip strength and MoCA scores, with information processing speed exerting a stronger mediating effect.

Conclusion

Specific patterns were observed in the EEG of elderly individuals with cognitive impairments, which could objectively assess the risk of cognitive decline in this population. Muscle strength, information processing speed, and EEG-specific biomarkers were closely associated with cognitive function in elderly individuals. The potential pathway of interaction-muscle strength → EEG-specific biomarkers → information processing speed → cognitive function-provides valuable insights into advancing the field of cognitive research in the elderly.

Site- and electroencephalogram-frequency-specific effects of 800-nm prefrontal transcranial photobiomodulation on electroencephalogram global network topology in young adults

Significance

Transcranial photobiomodulation (tPBM) is an optical intervention that effectively enhances human cognition. However, limited studies have reported the effects of tPBM on electrophysiological brain networks.

Aim

We aimed to investigate the site- and electroencephalogram (EEG)-frequency-specific effects of 800-nm prefrontal tPBM on the EEG global network topology of the human brain, so a better understanding of how tPBM alters EEG brain networks can be achieved.

Approach

A total of 26 healthy young adults participated in the study, with multiple visits when either active or sham tPBM interventions were delivered to either the left or right forehead. A 19-channel EEG cap recorded the time series before and after the 8-min tPBM/sham. We used graph theory analysis (GTA) and formulated adjacency matrices in five frequency bands, followed by quantification of normalized changes in GTA-based global topographical metrics induced by the respective left and right tPBM/sham interventions.

Results

Statistical analysis indicated that the effects of 800-nm prefrontal tPBM on the EEG global topological networks are both site- and EEG-frequency-dependent. Specifically, our results demonstrated that the left 800-nm tPBM primarily enhanced the alpha network efficiency and information transmission, whereas the right 800-nm tPBM augmented the clustering ability of the EEG topological networks and improved the formation of small-worldness of the beta waves across the entire brain.

Conclusions

The study concluded that 800-nm prefrontal tPBM can enhance global connectivity patterns and information transmission in the human brain, with effects that are site- and EEG-frequency-specific. To further confirm and better understand these findings, future research should correlate post-tPBM cognitive assessments with EEG network analysis.

Increased visual alpha-band activity during self-paced finger tapping does not affect early visual stimulus processing

Alpha-band activity is thought to be involved in orchestrating neural processing within and across brain regions relevant to various functions such as perception, cognition, and motor activity. Across different studies, attenuated alpha-band activity has been linked to increased neural excitability. Yet, there have been conflicting results concerning the consequences of alpha-band modulations for early sensory processing. We here examined whether movement-related alterations in visual alpha-band activity affected the early sensory processing of visual stimuli. For this purpose, in an EEG experiment, participants were engaged in a voluntary finger-tapping task while passively viewing flickering dots. We found extensive and expected movement-related amplitude modulations of motor alpha- and beta-band activity with event-related-desynchronization (ERD) before and during, and event-related-synchronization (ERS) after single voluntary finger taps. Crucially, while a visual alpha-band ERS accompanied the motor alpha-ERD before and during each finger tap, flicker-evoked Steady-State-Visually-Evoked-Potentials (SSVEPs), as a marker of early visual sensory gain, were not modulated in amplitude. As early sensory stimulus processing was unaffected by amplitude-modulated visual alpha-band activity, this argues against the idea that alpha-band activity represents a mechanism by which early sensory gain modulation is implemented. The distinct neural dynamics of visual alpha-band activity and early sensory processing may point to distinct and multiplexed neural selection processes in visual processing.

Exploring easily accessible neurophysiological biomarkers for predicting Alzheimer's disease progression: a systematic review

Alzheimer disease (AD) remains a significant global health concern. The progression from preclinical stages to overt dementia has become a crucial point of interest for researchers. This paper reviews the potential of neurophysiological biomarkers in predicting AD progression, based on a systematic literature search following PRISMA guidelines, including 55 studies. EEG-based techniques have been predominantly employed, whereas TMS studies are less common. Among the investigated neurophysiological measures, spectral power measurements and event-related potentials-based measures, including P300 and N200 latencies, have emerged as the most consistent and reliable biomarkers for predicting the likelihood of conversion to AD. In addition, TMS-based indices of cortical excitability and synaptic plasticity have also shown potential in assessing the risk of conversion to AD. However, concerns persist regarding the methodological discrepancies among studies, the accuracy of these neurophysiological measures in comparison to established AD biomarkers, and their immediate clinical applicability. Further research is needed to validate the predictive capabilities of EEG and TMS measures. Advancements in this area could lead to cost-effective, reliable biomarkers, enhancing diagnostic processes and deepening our understanding of AD pathophysiology.

Harnessing Brainwave Entrainment: A Non-invasive Strategy To Alleviate Neurological Disorder Symptoms

From 1990-2019, the burden of neurological disorders varied considerably across countries and regions. Psychiatric disorders, often emerging in early to mid-adulthood, are linked to late-life neurodegenerative diseases like Alzheimer's disease and Parkinson's disease. Individuals with conditions such as Major Depressive Disorder, Anxiety Disorder, Schizophrenia, and Bipolar Disorder face up to four times higher risk of developing neurodegenerative disorders. Contrarily, 65 % of those with neurodegenerative conditions experience severe psychiatric symptoms during their illness. Further, the limitation of medical resources continues to make this burden a significant global and local challenge. Therefore, brainwave entrainment provides therapeutic avenues for improving the symptoms of diseases. Brainwaves are rhythmic oscillations produced either spontaneously or in response to stimuli. Key brainwave patterns include gamma, beta, alpha, theta, and delta waves, yet the underlying physiological mechanisms and the brain's ability to shift between these dynamic states remain areas for further exploration. In neurological disorders, brainwaves are often disrupted, a phenomenon termed "oscillopathy". However, distinguishing these impaired oscillations from the natural variability in brainwave activity across different regions and functional states poses significant challenges. Brainwave-mediated therapeutics represents a promising research field aimed at correcting dysfunctional oscillations. Herein, we discuss a range of non-invasive techniques such as non-invasive brain stimulation (NIBS), neurologic music therapy (NMT), gamma stimulation, and somatosensory interventions using light, sound, and visual stimuli. These approaches, with their minimal side effects and cost-effectiveness, offer potential therapeutic benefits. When integrated, they may not only help in delaying disease progression but also contribute to the development of innovative medical devices for neurological care.

Oscillations in an artificial neural network convert competing inputs into a temporal code

The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development of convolutional neural networks (CNNs), for example, was informed by the properties of simple and complex cells in early visual cortex. However, the computational relevance of oscillatory dynamics experimentally observed in the visual system are typically not considered in artificial neural networks (ANNs). Computational models of neocortical dynamics, on the other hand, rarely take inspiration from computer vision. Here, we combine methods from computational neuroscience and machine learning to implement multiplexing in a simple ANN using oscillatory dynamics. We first trained the network to classify individually presented letters. Post-training, we added temporal dynamics to the hidden layer, introducing refraction in the hidden units as well as pulsed inhibition mimicking neuronal alpha oscillations. Without these dynamics, the trained network correctly classified individual letters but produced a mixed output when presented with two letters simultaneously, indicating a bottleneck problem. When introducing refraction and oscillatory inhibition, the output nodes corresponding to the two stimuli activate sequentially, ordered along the phase of the inhibitory oscillations. Our model implements the idea that inhibitory oscillations segregate competing inputs in time. The results of our simulations pave the way for applications in deeper network architectures and more complicated machine learning problems.

Modulation of brain activity in brain-injured patients with a disorder of consciousness in intensive care with repeated 10-Hz transcranial alternating current stimulation (tACS): a randomised controlled trial protocol

INTRODUCTION

Therapeutic interventions for disorders of consciousness lack consistency; evidence supports non-invasive brain stimulation, but few studies assess neuromodulation in acute-to-subacute brain-injured patients. This study aims to validate the feasibility and assess the effect of a multi-session transcranial alternating current stimulation (tACS) intervention in subacute brain-injured patients on recovery of consciousness, related brain oscillations and brain network dynamics.

METHODS AND ANALYSES

The study is comprised of two phases: a validation phase (n=12) and a randomised controlled trial (n=138). Both phases will be conducted in medically stable brain-injured adult patients (traumatic brain injury and hypoxic-ischaemic encephalopathy), with a Glasgow Coma Scale score ≤12 after continuous sedation withdrawal. Recruitment will occur at the intensive care unit of a Level 1 Trauma Centre in Montreal, Quebec, Canada. The intervention includes a 20 min 10 Hz tACS at 1 mA intensity or a sham session over parieto-occipital cortical sites, repeated over five consecutive days. The current's frequency targets alpha brain oscillations (8-13 Hz), known to be associated with consciousness. Resting-state electroencephalogram (EEG) will be recorded four times daily for five consecutive days: pre and post-intervention, at 60 and 120 min post-tACS. Two additional recordings will be included: 24 hours and 1-week post-protocol. Multimodal measures (blood samples, pupillometry, behavioural consciousness assessments (Coma Recovery Scale-revised), actigraphy measures) will be acquired from baseline up to 1 week after the stimulation. EEG signal analysis will focus on the alpha bandwidth (8-13 Hz) using spectral and functional network analyses. Phone assessments at 3, 6 and 12 months post-tACS, will measure long-term functional recovery, quality of life and caregivers' burden.

ETHICS AND DISSEMINATION

Ethical approval for this study has been granted by the Research Ethics Board of the CIUSSS du Nord-de-l'Île-de-Montréal (Project ID 2021-2279). The findings of this two-phase study will be submitted for publication in a peer-reviewed academic journal and submitted for presentation at conferences. The trial's results will be published on a public trial registry database (ClinicalTrials.gov).

TRIAL REGISTRATION NUMBER

NCT05833568.

The neural oscillatory mechanism underlying human brain fingerprint recognition using a portable EEG acquisition device

In recent years, brainprint recognition has emerged as a novel method of personal identity verification. Although studies have demonstrated the feasibility of this technology, some limitations hinder its further development into the society, such as insufficient efficiency (extended wear time for multi-channel EEG cap), complex experimental paradigms (more time in learning and completing experiments), and unclear neurobiological characteristics (lack of intuitive biomarkers and an inability to eliminate the impact of noise on individual differences). Overall, these limitations are due to the incomplete understanding of the underlying neural mechanisms. Therefore, this study aims to investigate the neural mechanisms behind brainwave recognition and simplify the operation process. We recorded prefrontal resting-state EEG data from 40 participants, which is followed up over nine months using a single-channel portable brainwave device. We found that portable devices can effectively and stably capture the characteristics of different subjects in the alpha band (8-13Hz) over long periods, as well as capturing their individual differences (no alpha peak, 1 alpha peak, or 2 alpha peaks). Through correlation analysis, alpha-band activity can reveal the uniqueness of the subjects compared to others within one minute. We further used a descriptive model to dissect the oscillatory and non-oscillatory components in the alpha band, demonstrating the different contributions of fine oscillatory features to individual differences (especially amplitude and bandwidth). Our study validated the feasibility of portable brainwave devices in brainwave recognition and the underlying neural oscillation mechanisms. The fine characteristics of various alpha oscillations will contribute to the accuracy of brainwave recognition, providing new insights for the development of future brainwave recognition technology.

Mechanism of an Intrinsic Oscillation in Rat Geniculate Interneurons

Depolarizing current injections produced a rhythmic bursting of action potentials - a bursting oscillation - in a set of local interneurons in the lateral geniculate nucleus (LGN) of rats. The current dynamics underlying this firing pattern have not been determined, though this cell type constitutes an important cellular component of thalamocortical circuitry, and contributes to both pathologic and non-pathologic brain states. We thus investigated the source of the bursting oscillation using pharmacological manipulations in LGN slices in vitro and in silico. 1. Selective blockade of calcium channel subtypes revealed that high-threshold calcium currentsI L andI P contributed strongly to the oscillation. 2. Increased extracellular K+ concentration (decreased K+currents) eliminated the oscillation. 3. Selective blockade of K+ channel subtypes demonstrated that the calcium-sensitive potassium current (I A H P ) was of primary importance. A morphologically simplified, multicompartment model of the thalamic interneuron characterized the oscillation as follows: 1. The low-threshold calcium currentI T provided the strong initial burst characteristic of the oscillation. 2. Alternating fluxes through high-threshold calcium channels andI A H P then provided the continuing oscillation's burst and interburst periods respectively. This interplay betweenI L andI A H P contrasts with the current dynamics underlying oscillations in thalamocortical and reticularis neurons, which primarily involveI T andI H , orI T andI A H P respectively. These findings thus point to a novel electrophysiological mechanism for generating intrinsic oscillations in a major thalamic cell type. Because local interneurons can sculpt the behavior of thalamocortical circuits, these results suggest new targets for the manipulation of ascending thalamocortical network activity.

Development of the Alpha Rhythm Is Linked to Visual White Matter Pathways and Visual Detection Performance

Alpha is the strongest electrophysiological rhythm in awake humans at rest. Despite its predominance in the EEG signal, large variations can be observed in alpha properties during development, with an increase in alpha frequency over childhood and adulthood. Here, we tested the hypothesis that these changes in alpha rhythm are related to the maturation of visual white matter pathways. We capitalized on a large diffusion MRI (dMRI)-EEG dataset (dMRI n = 2,747, EEG n = 2,561) of children and adolescents of either sex (age range, 5-21 years old) and showed that maturation of the optic radiation specifically accounts for developmental changes of alpha frequency. Behavioral analyses also confirmed that variations of alpha frequency are related to maturational changes in visual perception. The present findings demonstrate the close link between developmental variations in white matter tissue properties, electrophysiological responses, and behavior.

Evaluation of putative signatures of consciousness using specific definitions of responsiveness, connectedness, and consciousness

BACKGROUND

Understanding the neural correlates of consciousness has important ramifications for the theoretical understanding of consciousness and for clinical anaesthesia. A major limitation of prior studies is the use of responsiveness as an index of consciousness. We identified a collection of measures derived from unresponsive subjects and more specifically their association with consciousness (any subjective experience) or connectedness (specific experience of environmental stimuli).

METHODS

Using published data generated through the UNderstanding Consciousness Connectedness and Intra-Operative Unresponsiveness Study (NCT03284307), we evaluated 10 previously published resting-state EEG-based measures that were derived using unresponsiveness as a proxy for unconsciousness. Measures were tested across dexmedetomidine and propofol sedation and natural sleep. These markers represent the complexity, connectivity, cross-frequency coupling, graph theory, and power spectrum measures.

RESULTS

Although many of the proposed markers were associated with consciousness per se (reported subjective experience), none were specific to consciousness alone; rather, each was also associated with connectedness (i.e. awareness of the environment). In addition, multiple markers showed no association with consciousness and were associated only with connectedness. Of the markers tested, loss of normalised-symbolic transfer entropy (front to back) was associated with connectedness across all three experimental conditions, whereas the transition from disconnected consciousness to unconsciousness was associated with significant decreases in permutation entropy and spectral exponent (P<0.05 for all conditions).

CONCLUSIONS

None of the proposed EEG-based neural correlates of unresponsiveness corresponded solely to consciousness, highlighting the need for a more conservative use of the term (un)consciousness when assessing unresponsive participants.

CLINICAL TRIAL REGISTRATION

NCT03284307.

EEG in Down Syndrome-A Review and Insights into Potential Neural Mechanisms

Introduction: Down syndrome (DS) stands out as one of the most prevalent genetic disorders, imposing a significant burden on both society and the healthcare system. Scientists are making efforts to understand the neural mechanisms behind the pathophysiology of this disorder. Among the valuable methods for studying these mechanisms is electroencephalography (EEG), a non-invasive technique that measures the brain's electrical activity, characterised by its excellent temporal resolution. This review aims to consolidate studies examining EEG usage in individuals with DS. The objective was to identify shared elements of disrupted EEG activity and, crucially, to elucidate the neural mechanisms underpinning these deviations. Searches were conducted on Pubmed/Medline, Research Gate, and Cochrane databases. Results: The literature search yielded 17 relevant articles. Despite the significant time span, small sample size, and overall heterogeneity of the included studies, three common features of aberrant EEG activity in people with DS were found. Potential mechanisms for this altered activity were delineated. Conclusions: The studies included in this review show altered EEG activity in people with DS compared to the control group. To bolster these current findings, future investigations with larger sample sizes are imperative.

Alpha and SSVEP power outperform gamma power in capturing attentional modulation in human EEG

Attention typically reduces power in the alpha (8-12 Hz) band and increases power in gamma (>30 Hz) band in brain signals, as reported in macaque local field potential (LFP) and human electro/magneto-encephalogram (EEG/MEG) studies. In addition, EEG studies often use flickering stimuli that produce a specific measure called steady-state-visually-evoked-potential (SSVEP), whose power also increases with attention. However, effectiveness of these neural measures in capturing attentional modulation is unknown since stimuli and task paradigms vary widely across studies. In a recent macaque study, attentional modulation was more salient in the gamma band of the LFP, compared to alpha or SSVEP. To compare this with human EEG, we designed an orientation change detection task where we presented both static and counterphasing stimuli of matched difficulty levels to 26 subjects and compared attentional modulation of various measures under similar conditions. We report two main results. First, attentional modulation was comparable for SSVEP and alpha. Second, non-foveal stimuli produced weak gamma despite various stimulus optimizations and showed negligible attentional modulation although full-screen gratings showed robust gamma activity. Our results are useful for brain-machine-interfacing studies where suitable features are used for decoding attention, and also provide clues about spatial scales of neural mechanisms underlying attention.

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.

Induced synchronization by endogenous noise modulation in finite-size random neural networks: A stochastic mean-field study

Event-related synchronization and desynchronization (ERS/ERD) are well-known features found experimentally in brain signals during cognitive tasks. Their understanding promises to have much better insights into neural information processes in cognition. Under the hypothesis that neural information affects the endogenous neural noise level in populations, we propose to employ a stochastic mean-field model to explain ERS/ERD in the γ-frequency range. The work extends previous mean-field studies by deriving novel effects from finite network size. Moreover, numerical simulations of ERS/ERD and their analytical explanation by the mean-field model suggest several endogenous noise modulation schemes, which may modulate the system's synchronization.

Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics

We developed a detailed model of macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus, utilizing the NEURON simulator and NetPyNE tool. The A1 model simulates a cortical column with over 12,000 neurons and 25 million synapses, incorporating data on cell-type-specific neuron densities, morphology, and connectivity across six cortical layers. It is reciprocally connected to the MGB thalamus, which includes interneurons and core and matrix-layer-specific projections to A1. The model simulates multiscale measures, including physiological firing rates, local field potentials (LFPs), current source densities (CSDs), and electroencephalography (EEG) signals. Laminar CSD patterns, during spontaneous activity and in response to broadband noise stimulus trains, mirror experimental findings. Physiological oscillations emerge spontaneously across frequency bands comparable to those recorded in vivo. We elucidate population-specific contributions to observed oscillation events and relate them to firing and presynaptic input patterns. The model offers a quantitative theoretical framework to integrate and interpret experimental data and predict its underlying cellular and circuit mechanisms.

Effect of transcranial photobiomodulation on electrophysiological activity of brain in healthy individuals: A scoping review

BACKGROUND OBJECTIVE

Transcranial photobiomodulation (tPBM) is a safe and non-invasive treatment that has recently emerged as an effective technique to apply near-infrared or red light to activate neural tissues. The objective is to review the literature on the effect of tPBM on electrophysiological activity in healthy individuals.

METHODS

Literature was searched through PubMed, Scopus, Web of Science, Cumulated Index to Nursing and Allied Health Literature (CINAHL), Embase, and Ovid for transcranial photobiomodulation therapy in healthy individuals age group 18-80 years of either gender having electroencephalography as an outcome. Critical appraisal of included Randomized Controlled Trials and non-randomized experimental studies was done using Joanna Briggs Institute (JBI) critical appraisal tool.

RESULTS

A database search yielded a total of 4156 results. After eliminating 2626 duplicates, 1530 records were left. 32 articles were considered for full-text screening after 1498 records were excluded through title and abstract screening. 10 articles were included in this review. tPBM has been found to increase the higher electrophysiological oscillations and there is inconclusive evidence targeting the lower oscillatory electrophysiological frequencies.

CONCLUSION

Transcranial photobiomodulation can have promising effects on the electrophysiological activity of the brain in healthy individuals.

Spectral and phase-coherence correlates of impaired auditory mismatch negativity (MMN) in schizophrenia: A MEG study

BACKGROUND

Reduced auditory mismatch negativity (MMN) is robustly impaired in schizophrenia. However, mechanisms underlying dysfunctional MMN generation remain incompletely understood. This study aimed to examine the role of evoked spectral power and phase-coherence towards deviance detection and its impairments in schizophrenia.

METHODS

Magnetoencephalography data was collected in 16 male schizophrenia patients and 16 male control participants during an auditory MMN paradigm. Analyses of event-related fields (ERF), spectral power and inter-trial phase-coherence (ITPC) focused on Heschl's gyrus, superior temporal gyrus, inferior/medial frontal gyrus and thalamus.

RESULTS

MMNm ERF amplitudes were reduced in patients in temporal, frontal and subcortical regions, accompanied by decreased theta-band responses, as well as by a diminished gamma-band response in auditory cortex. At theta/alpha frequencies, ITPC to deviant tones was reduced in patients in frontal cortex and thalamus. Patients were also characterized by aberrant responses to standard tones as indexed by reduced theta-/alpha-band power and ITPC in temporal and frontal regions. Moreover, stimulus-specific adaptation was decreased at theta/alpha frequencies in left temporal regions, which correlated with reduced MMNm spectral power and ERF amplitude. Finally, phase-reset of alpha-oscillations after deviant tones in left thalamus was impaired, which correlated with impaired MMNm generation in auditory cortex. Importantly, both non-rhythmic and rhythmic components of spectral activity contributed to the MMNm response.

CONCLUSIONS

Our data indicate that deficits in theta-/alpha- and gamma-band activity in cortical and subcortical regions as well as impaired spectral responses to standard sounds could constitute potential mechanisms for dysfunctional MMN generation in schizophrenia, providing a novel perspective towards MMN deficits in the disorder.

Beyond pulsed inhibition: Alpha oscillations modulate attenuation and amplification of neural activity in the awake resting state

Alpha oscillations are a distinctive feature of the awake resting state of the human brain. However, their functional role in resting-state neuronal dynamics remains poorly understood. Here we show that, during resting wakefulness, alpha oscillations drive an alternation of attenuation and amplification bouts in neural activity. Our analysis indicates that inhibition is activated in pulses that last for a single alpha cycle and gradually suppress neural activity, while excitation is successively enhanced over a few alpha cycles to amplify neural activity. Furthermore, we show that long-term alpha amplitude fluctuations-the "waxing and waning" phenomenon-are an attenuation-amplification mechanism described by a power-law decay of the activity rate in the "waning" phase. Importantly, we do not observe such dynamics during non-rapid eye movement (NREM) sleep with marginal alpha oscillations. The results suggest that alpha oscillations modulate neural activity not only through pulses of inhibition (pulsed inhibition hypothesis) but also by timely enhancement of excitation (or disinhibition).

Rapid thalamocortical network switching mediated by cortical synchronization underlies propofol-induced EEG signatures: a biophysical model

Propofol-mediated unconsciousness elicits strong alpha/low-beta and slow oscillations in the electroencephalogram (EEG) of patients. As anesthetic dose increases, the EEG signal changes in ways that give clues to the level of unconsciousness; the network mechanisms of these changes are only partially understood. Here, we construct a biophysical thalamocortical network involving brain stem influences that reproduces transitions in dynamics seen in the EEG involving the evolution of the power and frequency of alpha/low-beta and slow rhythm, as well as their interactions. Our model suggests that propofol engages thalamic spindle and cortical sleep mechanisms to elicit persistent alpha/low-beta and slow rhythms, respectively. The thalamocortical network fluctuates between two mutually exclusive states on the timescale of seconds. One state is characterized by continuous alpha/low-beta-frequency spiking in thalamus (C-state), whereas in the other, thalamic alpha spiking is interrupted by periods of co-occurring thalamic and cortical silence (I-state). In the I-state, alpha colocalizes to the peak of the slow oscillation; in the C-state, there is a variable relationship between an alpha/beta rhythm and the slow oscillation. The C-state predominates near loss of consciousness; with increasing dose, the proportion of time spent in the I-state increases, recapitulating EEG phenomenology. Cortical synchrony drives the switch to the I-state by changing the nature of the thalamocortical feedback. Brain stem influence on the strength of thalamocortical feedback mediates the amount of cortical synchrony. Our model implicates loss of low-beta, cortical synchrony, and coordinated thalamocortical silent periods as contributing to the unconscious state.NEW & NOTEWORTHY GABAergic anesthetics induce alpha/low-beta and slow oscillations in the EEG, which interact in dose-dependent ways. We constructed a thalamocortical model to investigate how these interdependent oscillations change with propofol dose. We find two dynamic states of thalamocortical coordination, which change on the timescale of seconds and dose-dependently mirror known changes in EEG. Thalamocortical feedback determines the oscillatory coupling and power seen in each state, and this is primarily driven by cortical synchrony and brain stem neuromodulation.

Excitation-Inhibition Imbalance in Migraine: From Neurotransmitters to Brain Oscillations

Migraine is among the most common and debilitating neurological disorders typically affecting people of working age. It is characterised by a unilateral, pulsating headache often associated with severe pain. Despite the intensive research, there is still little understanding of the pathophysiology of migraine. At the electrophysiological level, altered oscillatory parameters have been reported within the alpha and gamma bands. At the molecular level, altered glutamate and GABA concentrations have been reported. However, there has been little cross-talk between these lines of research. Thus, the relationship between oscillatory activity and neurotransmitter concentrations remains to be empirically traced. Importantly, how these indices link back to altered sensory processing has to be clearly established as yet. Accordingly, pharmacologic treatments have been mostly symptom-based, and yet sometimes proving ineffective in resolving pain or related issues. This review provides an integrative theoretical framework of excitation-inhibition imbalance for the understanding of current evidence and to address outstanding questions concerning the pathophysiology of migraine. We propose the use of computational modelling for the rigorous formulation of testable hypotheses on mechanisms of homeostatic imbalance and for the development of mechanism-based pharmacological treatments and neurostimulation interventions.

Propofol disrupts alpha dynamics in functionally distinct thalamocortical networks during loss of consciousness

During propofol-induced general anesthesia, alpha rhythms measured using electroencephalography undergo a striking shift from posterior to anterior, termed anteriorization, where the ubiquitous waking alpha is lost and a frontal alpha emerges. The functional significance of alpha anteriorization and the precise brain regions contributing to the phenomenon are a mystery. While posterior alpha is thought to be generated by thalamocortical circuits connecting nuclei of the sensory thalamus with their cortical partners, the thalamic origins of the propofol-induced alpha remain poorly understood. Here, we used human intracranial recordings to identify regions in sensory cortices where propofol attenuates a coherent alpha network, distinct from those in the frontal cortex where it amplifies coherent alpha and beta activities. We then performed diffusion tractography between these identified regions and individual thalamic nuclei to show that the opposing dynamics of anteriorization occur within two distinct thalamocortical networks. We found that propofol disrupted a posterior alpha network structurally connected with nuclei in the sensory and sensory associational regions of the thalamus. At the same time, propofol induced a coherent alpha oscillation within prefrontal cortical areas that were connected with thalamic nuclei involved in cognition, such as the mediodorsal nucleus. The cortical and thalamic anatomy involved, as well as their known functional roles, suggests multiple means by which propofol dismantles sensory and cognitive processes to achieve loss of consciousness.

Decomposing age effects in EEG alpha power

Increasing life expectancy is prompting the need to understand how the brain changes during healthy aging. Research utilizing electroencephalography (EEG) has found that the power of alpha oscillations decrease from adulthood on. However, non-oscillatory (aperiodic) components in the data may confound results and thus require re-investigation of these findings. Thus, the present report analyzed a pilot and two additional independent samples (total N = 533) of resting-state EEG from healthy young and elderly individuals. A newly developed algorithm was utilized that allows the decomposition of the measured signal into periodic and aperiodic signal components. By using multivariate sequential Bayesian updating of the age effect in each signal component, evidence across the datasets was accumulated. It was hypothesized that previously reported age-related alpha power differences will largely diminish when total power is adjusted for the aperiodic signal component. First, the age-related decrease in total alpha power was replicated. Concurrently, decreases of the intercept and slope (i.e. exponent) of the aperiodic signal component were observed. Findings on aperiodic-adjusted alpha power indicated that this general shift of the power spectrum leads to an overestimation of the true age effects in conventional analyses of total alpha power. Thus, the importance of separating neural power spectra into periodic and aperiodic signal components is highlighted. However, also after accounting for these confounding factors, the sequential Bayesian updating analysis provided robust evidence that aging is associated with decreased aperiodic-adjusted alpha power. While the relation of the aperiodic component and aperiodic-adjusted alpha power to cognitive decline demands further investigation, the consistent findings on age effects across independent datasets and high test-retest reliabilities support that these newly emerging measures are reliable markers of the aging brain. Hence, previous interpretations of age-related decreases in alpha power are reevaluated, incorporating changes in the aperiodic signal.

Emotional Memory Processing during REM Sleep with Implications for Post-Traumatic Stress Disorder

REM sleep is important for the processing of emotional memories, including fear memories. Rhythmic interactions, especially in the theta band, between the medial prefrontal cortex (mPFC) and limbic structures are thought to play an important role, but the ways in which memory processing occurs at a mechanistic and circuits level are largely unknown. To investigate how rhythmic interactions lead to fear extinction during REM sleep, we used a biophysically based model that included the infralimbic cortex (IL), a part of the mPFC with a critical role in suppressing fear memories. Theta frequency (4-12 Hz) inputs to a given cell assembly in IL, representing an emotional memory, resulted in the strengthening of connections from the IL to the amygdala and the weakening of connections from the amygdala to the IL, resulting in the suppression of the activity of fear expression cells for the associated memory. Lower frequency (4 Hz) theta inputs effected these changes over a wider range of input strengths. In contrast, inputs at other frequencies were ineffective at causing these synaptic changes and did not suppress fear memories. Under post-traumatic stress disorder (PTSD) REM sleep conditions, rhythmic activity dissipated, and 4 Hz theta inputs to IL were ineffective, but higher-frequency (10 Hz) theta inputs to IL induced changes similar to those seen with 4 Hz inputs under normal REM sleep conditions, resulting in the suppression of fear expression cells. These results suggest why PTSD patients may repeatedly experience the same emotionally charged dreams and suggest potential neuromodulatory therapies for the amelioration of PTSD symptoms.SIGNIFICANCE STATEMENT Rhythmic interactions in the theta band between the mPFC and limbic structures are thought to play an important role in processing emotional memories, including fear memories, during REM sleep. The infralimbic cortex (IL) in the mPFC is thought to play a critical role in suppressing fear memories. We show that theta inputs to the IL, unlike other frequency inputs, are effective in producing synaptic changes that suppress the activity of fear expression cells associated with a given memory. Under PTSD REM sleep conditions, lower-frequency (4 Hz) theta inputs to the IL do not suppress the activity of fear expression cells associated with the given memory but, surprisingly, 10 Hz inputs do. These results suggest potential neuromodulatory therapies for PTSD.

The brain time toolbox, a software library to retune electrophysiology data to brain dynamics

Human thought is highly flexible, achieved by evolving patterns of brain activity across groups of cells. Neuroscience aims to understand cognition in the brain by analysing these intricate patterns. We argue that this goal is impeded by the time format of our data-clock time. The brain is a system with its own dynamics and regime of time, with no intrinsic concern for the human-invented second. Here, we present the Brain Time Toolbox, a software library that retunes electrophysiology data in line with oscillations that orchestrate neural patterns of cognition. These oscillations continually slow down, speed up and undergo abrupt changes, introducing a disharmony between the brain's internal regime and clock time. The toolbox overcomes this disharmony by warping the data to the dynamics of coordinating oscillations, setting oscillatory cycles as the data's new time axis. This enables the study of neural patterns as they unfold in the brain, aiding neuroscientific enquiry into dynamic cognition. In support of this, we demonstrate that the toolbox can reveal results that are absent in a default clock time format.

Alpha oscillations reflect suppression of distractors with increased perceptual load

Attention serves an essential role in cognition and behavior allowing us to focus on behaviorally-relevant objects while ignoring distraction. Perceptual load theory states that attentional resources are allocated according to the requirements of the task, i.e., its 'load'. The theory predicts that the resources left to process irrelevant, possibly distracting stimuli, are reduced when the perceptual load is high. However, it remains unclear how this allocation of attentional resources specifically relates to neural excitability and suppression mechanisms. In this magnetoencephalography (MEG) study, we show that brain oscillations in the alpha band (8-13 Hz) implemented the suppression of distracting objects when the perceptual load was high. In parallel, high load increased the neuronal excitability for target objects, as reflected by rapid invisible frequency tagging. We suggest that the allocation of resources in tasks with high perceptual load is implemented by a gain increase for targets, complemented by distractor suppression reflected by alpha-band oscillations closing the 'gate' for interference.

Quantitative Electroencephalography Findings in Patients With Diabetes Mellitus

Objective. Diabetes mellitus (DM) causes structural central nervous system (CNS) impairment, and this situation can be detected by quantitative electroencephalography (QEEG) findings before cognitive impairment is clinically observed. The main aim of this study is to uncover the effect of DM on brain function. Since QEEG reflects the CNS functioning, particularly in cognitive aspects, we expected electrophysiological clues to be found for prevention and follow-up in DM-related cognitive decline. Since a majority of the psychiatric population have cognitive dysfunction, we have given particular attention to those people. It was stated that a decrease was observed in the posterior cortical alpha power due to the hippocampal atrophy by several previous studies and we hypothesize that decreased alpha power will be observed also in DM. Methods. This study included 2094 psychiatric patients, 207 of whom were diagnosed with DM and 1887 of whom were not diagnosed with DM, and QEEG recordings were performed. Eyes-closed electroencephalography data were segmented into consecutive 2 s epochs. Fourier analysis was performed by averaging across 2 s epochs without artifacts. The absolute alpha power in the occipital regions (O1 and O2) of patients with and without DM was compared. Results. In the DM group, a decrease in the absolute alpha, alpha 1, and alpha 2 power in O1 and O2 was observed in comparison with the control group. It was determined that the type of psychiatric diagnosis did not affect QEEG findings. Conclusion. The decrease in absolute alpha power observed in patients diagnosed with DM may be related to the CNS impairment in DM. QEEG findings in DM can be useful while monitoring the CNS impairment, diagnosing DM-related dementia, in the follow-up of the cognitive process, constructing the protocols for electrophysiological interventions like neurofeedback and transcranial magnetic stimulation and monitoring the response to treatment.

Functional Connectivity States of Alpha Rhythm Sources in the Human Cortex at Rest: Implications for Real-Time Brain State Dependent EEG-TMS

Alpha is the predominant rhythm of the human electroencephalogram, but its function, multiple generators and functional coupling patterns are still relatively unknown. In this regard, alpha connectivity patterns can change between different cortical generators depending on the status of the brain. Therefore, in the light of the communication through coherence framework, an alpha functional network depends on the functional coupling patterns in a determined state. This notion has a relevance for brain-state dependent EEG-TMS because, beyond the local state, a network connectivity overview at rest could provide further and more comprehensive information for the definition of 'instantaneous state' at the stimulation moment, rather than just the local state around the stimulation site. For this reason, we studied functional coupling at rest in 203 healthy subjects with MEG data. Sensor signals were source localized and connectivity was studied at the Individual Alpha Frequency (IAF) between three different cortical areas (occipital, parietal and prefrontal). Two different and complementary phase-coherence metrices were used. Our results show a consistent connectivity between parietal and prefrontal regions whereas occipito-prefrontal connectivity is less marked and occipito-parietal connectivity is extremely low, despite physical closeness. We consider our results a relevant add-on for informed, individualized real-time brain state dependent stimulation, with possible contributions to novel, personalized non-invasive therapeutic approaches.

Using a new phase-locked visual feedback protocol to affirm simpler models for alpha dynamics

Alpha band oscillations are the most prominent rhythmic oscillations in EEG, which are related to various types of mental diseases, such as attention deficit hyperactivity disorder, anxiety, and depression. However, the dynamics of alpha oscillations, especially how the endogenous alpha oscillations be entrained by exogenous stimulus, are still unclear. Recently, a newly-developed phase-locked visual feedback (PLVF) protocol has shown effectiveness in modulating alpha rhythm, which provides empirical evidence for the further investigation of the neural mechanism of alpha dynamics. In this work, extensive numerical simulations based on four well-studied models were used to investigate the questions that (1) What kind of dynamic model exhibits a modulation phenomenon of PLVF? (2) What is the dynamic mechanism of PLVF for alpha modulation? (3) Which factors affect the modulation effects in PLVF? The result indicates that the dynamics of endogenous alpha oscillations are close to a simpler dynamic structure, like fixed-point attractor or limit-cycle attractor, which shows a global consistent dynamic behavior at different phases of the alpha oscillation. The further analysis explains the dynamic mechanism of PLVF for amplitude and frequency modulation of the alpha rhythm, as well as the influence of parameter settings in the modulation. All these findings provide a deeper understanding of the endogenous alpha oscillations entrained by exogenous phased locked visual stimulus and lead in turn to the refinement of a control strategy for alpha modulation, which could potentially be used in developing new neural modulation methods for cognitive enhancement and mental diseases treatment.

Arousal Fluctuations Govern Oscillatory Transitions Between Dominant γ and α Occipital Activity During Eyes Open/Closed Conditions

Arousal results in widespread activation of brain areas to increase their response in task and behavior relevant ways. Mediated by the Ascending Reticular Arousal System (ARAS), arousal-dependent inputs interact with neural circuitry to shape their dynamics. In the occipital cortex, such inputs may trigger shifts between dominant oscillations, whereα activity is replaced byγ activity, or vice versa. A salient example of this are spectral power alternations observed while eyes are opened and/or closed. These transitions closely follow fluctuations in arousal, suggesting a common origin. To better understand the mechanisms at play, we developed and analyzed a computational model composed of two modules: a thalamocortical feedback circuit coupled with a superficial cortical network. Upon activation by noise-like inputs originating from the ARAS, our model is able to demonstrate that noise-driven non-linear interactions mediate transitions in dominant peak frequency, resulting in the simultaneous suppression ofα limit cycle activity and the emergence ofγ oscillations through coherence resonance. Reduction in input provoked the reverse effect - leading to anticorrelated transitions betweenα andγ power. Taken together, these results shed a new light on how arousal shapes oscillatory brain activity.

Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model

Strategically located between the thalamus and the cortex, the inhibitory thalamic reticular nucleus (TRN) is a hub to regulate selective attention during wakefulness and control the thalamic and cortical oscillations during sleep. A salient feature of TRN neurons contributing to these functions is their characteristic firing patterns, ranging in a continuum from tonic spiking to bursting spiking. However, the dynamical mechanism under these firing behaviors is not well understood. In this study, by applying a reduction method to a full conductance-based neuron model, we construct a reduced three-variable model to investigate the dynamics of TRN neurons. We show that the reduced model can effectively reproduce the spiking patterns of TRN neurons as observed in vivo and in vitro experiments, and meanwhile allow us to perform bifurcation analysis of the spiking dynamics. Specifically, we demonstrate that the rebound bursting of a TRN neuron is a type of “fold/homo-clinic” bifurcation, and the tonic spiking is the fold cycle bifurcation. Further one-parameter bifurcation analysis reveals that the transition between these discharge patterns can be controlled by the external current. We expect that this reduced neuron model will help us to further study the complicated dynamics and functions of the TRN network.

A causal role for the pulvinar in coordinating task-independent cortico-cortical interactions

The pulvinar is the largest nucleus in the primate thalamus and has topographically organized connections with multiple cortical areas, thereby forming extensive cortico-pulvino-cortical input-output loops. Neurophysiological studies have suggested a role for these transthalamic pathways in regulating information transmission between cortical areas. However, evidence for a causal role of the pulvinar in regulating cortico-cortical interactions is sparse and it is not known whether pulvinar's influences on cortical networks are task-dependent or, alternatively, reflect more basic large-scale network properties that maintain functional connectivity across networks regardless of active task demands. In the current study, under passive viewing conditions, we conducted simultaneous electrophysiological recordings from ventral (area V4) and dorsal (lateral intraparietal area [LIP]) nodes of macaque visual system, while reversibly inactivating the dorsal part of the lateral pulvinar (dPL), which shares common anatomical connectivity with V4 and LIP, to probe a causal role of the pulvinar. Our results show a significant reduction in local field potential phase coherence between LIP and V4 in low frequencies (4-15 Hz) following muscimol injection into dPL. At the local level, no significant changes in firing rates or LFP power were observed in LIP or in V4 following dPL inactivation. Synchronization between pulvinar spikes and cortical LFP phase decreased in low frequencies (4-15 Hz) both in LIP and V4, while the low frequency synchronization between LIP spikes and pulvinar phase increased. These results indicate a causal role for pulvinar in synchronizing neural activity between interconnected cortical nodes of a large-scale network, even in the absence of an active task state.

Occipital alpha-TMS causally modulates temporal order judgements: Evidence for discrete temporal windows in vision

Recent advances in neuroscience have challenged the view of conscious visual perception as a continuous process. Behavioral performance, reaction times and some visual illusions all undergo periodic fluctuations that can be traced back to oscillatory activity in the brain. These findings have given rise to the idea of a discrete sampling mechanism in the visual system. In this study we seek to investigate the causal relationship between occipital alpha oscillations and Temporal Order Judgements using neural entrainment via rhythmic TMS in 18 human subjects (9 females). We find that certain phases of the entrained oscillation facilitate temporal order perception of two visual stimuli, whereas others hinder it. Our findings support the idea that the visual system periodically compresses information into discrete packages within which temporal order information is lost. SIGNIFICANCE STATEMENT: Neural entrainment via TMS serves as a valuable tool to interfere with cortical rhythms and observe changes in perception. Here, using α-rhythmic TMS-pulses, we demonstrate the effect of the phase of entrained oscillations on performance in a temporal order judgment task. In extension of previous work, we 1. causally influenced brain rhythms far more directly using TMS, and 2. showed that previous results on discrete perception cannot simply be explained by rhythmic fluctuations in visibility. Our findings support the idea that the temporal organization of visual processing is discrete rather than continuous, and is causally modulated by cortical rhythms. To our knowledge, this is the first study providing causal evidence via TMS for an endogenous periodic modulation of time perception.

Role of synaptic nonlinearity in persistent firing rate shifts caused by external periodic forcing

Information storage and processing in the brain largely relies on the neural population coding principle. In this framework, information is reflected in the population firing rate that reflects asynchronous irregular spiking of its constituent neurons. Periodic modulations of neural activity can lead to neural activity oscillations. Data indicate that such oscillations are ubiquitous in brain activity and are modulated, in frequency and amplitude, in a functionally meaningful manner. The relationship between oscillations and the population rate code remains an open issue. While ample works show how changes in the mean firing rate may alter neural oscillations, the reverse connection is unclear. One notable possibility is that oscillatory activity impinging on a neural population modulates its mean firing rate, thereby impacting information processing. We suggest that such modulation requires nonlinearities and propose nonlinear excitatory coupling via slow N-methyl-D-aspartate (NMDA) receptors as the prevalent mechanism. The aim of our paper is to theoretically explore to what extent the NMDA-related mechanism could account for oscillation-induced mean firing rate changes. We consider a mean-field model of a neural circuit containing an excitatory and an inhibitory population with linear transfer functions. Along with NMDA excitation, the model included fast recurrent excitatory and inhibitory connectivity. To explicitly study the effects of impinging oscillation on the rate dynamics, we subjected the circuit to a sinusoidal input signal imitating an input from distant brain regions or from a larger network into which the circuit is embedded. Using time-scale separation and time-averaging techniques, we developed a geometric method to determine the oscillation-induced mean firing rate shifts and validated it by numeric simulations of the model. Our results indicate that a large-amplitude stable firing rate shift requires nonlinear NMDA synapses on both the excitatory and the inhibitory populations. Our results delineate specific neural synaptic properties that enable neural oscillations to act as flexible modulators of the population rate code.

Fast-spiking Interneurons Contribute to Propofol-induced Facilitation of Firing Synchrony in Pyramidal Neurons of the Rat Insular Cortex

BACKGROUND

The general anesthetic propofol induces frontal alpha rhythm in the cerebral cortex at a dose sufficient to induce loss of consciousness. The authors hypothesized that propofol-induced facilitation of unitary inhibitory postsynaptic currents would result in firing synchrony among postsynaptic pyramidal neurons that receive inhibition from the same presynaptic inhibitory fast-spiking neurons.

METHODS

Multiple whole cell patch clamp recordings were performed from one fast-spiking neuron and two or three pyramidal neurons with at least two inhibitory connections in rat insular cortical slices. The authors examined how inhibitory inputs from a presynaptic fast-spiking neuron modulate the timing of spontaneous repetitive spike firing among pyramidal neurons before and during 10 μM propofol application.

RESULTS

Responding to activation of a fast-spiking neuron with 150-ms intervals, pyramidal cell pairs that received common inhibitory inputs from the presynaptic fast-spiking neuron showed propofol-dependent decreases in average distance from the line of identity, which evaluates the coefficient of variation in spike timing among pyramidal neurons: average distance from the line of identity just after the first activation of fast-spiking neuron was 29.2 ± 24.1 (mean ± SD, absolute value) in control and 19.7 ± 19.2 during propofol application (P < 0.001). Propofol did not change average distance from the line of identity without activating fast-spiking neurons and in pyramidal neuron pairs without common inhibitory inputs from presynaptic fast-spiking neurons. The synchronization index, which reflects the degree of spike synchronization among pyramidal neurons, was increased by propofol from 1.4 ± 0.5 to 2.3 ± 1.5 (absolute value, P = 0.004) and from 1.5 ± 0.5 to 2.2 ± 1.0 (P = 0.030) when a presynaptic fast-spiking neuron was activated at 6.7 and 10 Hz, respectively, but not at 1, 4, and 13.3 Hz.

CONCLUSIONS

These results suggest that propofol facilitates pyramidal neuron firing synchrony by enhancing inhibitory inputs from fast-spiking neurons. This synchrony of pyramidal neurons may contribute to the alpha rhythm associated with propofol-induced loss of consciousness.

EDITOR’S PERSPECTIVE

Dynamic pulvino-cortical interactions in the primate attention network

While research in previous decades demonstrated a link between the pulvinar nucleus of the thalamus and visual selective attention, the pulvinar's specific functional role has remained elusive. However, methodological advances in electrophysiological recordings in non-human primates, including simultaneous recordings in multiple brain regions, have recently begun to reveal the pulvinar's functional contributions to selective attention. These new findings suggest that the pulvinar is critical for the efficient transmission of sensory information within and between cortical regions, both synchronizing cortical activity across brain regions and controlling cortical excitability. These new findings further suggest that the pulvinar's influence on cortical processing is embedded in a dynamic selection process that balances sensory and motor functions within the large-scale network that directs selective attention.

Alpha Power and Functional Connectivity in Cognitive Decline: A Systematic Review and Meta-Analysis

Background:

Mild cognitive impairment (MCI) is a stage between expected age-related cognitive decline and dementia. Dementias have been associated with changes in neural oscillations across the frequency spectrum, including the alpha range. Alpha is the most prominent rhythm in human EEG and is best detected during awake resting state (RS). Though several studies measured alpha power and synchronization in MCI, findings have not yet been integrated.

Objective:

To consolidate findings on power and synchronization of alpha oscillations across stages of cognitive decline.

Methods:

We included studies published until January 2020 that compared power or functional connectivity between 1) people with MCI and cognitively healthy older adults (OA) or people with a neurodegenerative dementia, and 2) people with progressive and stable MCI. Random-effects meta-analyses were performed when enough data was available.

Results:

Sixty-eight studies were included in the review. Global RS alpha power was lower in AD than in MCI (ES = –0.30; 95% CI = –0.51, –0.10; k = 6), and in MCI than in OA (ES = –1.49; 95% CI = –2.69, –0.29; k = 5). However, the latter meta-analysis should be interpreted cautiously due to high heterogeneity. The review showed lower RS alpha power in progressive than in stable MCI, and lower task-related alpha reactivity in MCI than in OA. People with MCI had both lower and higher functional connectivity than OA. Publications lacked consistency in MCI diagnosis and EEG measures.

Conclusion:

Research indicates that RS alpha power decreases with increasing impairment, and could—combined with measures from other frequency bands—become a biomarker of early cognitive decline.

Fxr1 regulates sleep and synaptic homeostasis

The fragile X autosomal homolog 1 (Fxr1) is regulated by lithium and has been GWAS-associated with schizophrenia and insomnia. Homeostatic regulation of synaptic strength is essential for the maintenance of brain functions and involves both cell-autonomous and system-level processes such as sleep. We examined the contribution of Fxr1 to cell-autonomous homeostatic synaptic scaling and neuronal responses to sleep loss, using a combination of gene overexpression and Crispr/Cas9-mediated somatic knockouts to modulate gene expression. Our findings indicate that Fxr1 is downregulated during both scaling and sleep deprivation via a glycogen synthase kinase 3 beta (GSK3β)-dependent mechanism. In both conditions, downregulation of Fxr1 is essential for the homeostatic modulation of surface AMPA receptors and synaptic strength. Preventing the downregulation of Fxr1 during sleep deprivation results in altered EEG signatures. Furthermore, sequencing of neuronal translatomes revealed the contribution of Fxr1 to changes induced by sleep deprivation. These findings uncover a role of Fxr1 as a shared signaling hub between cell-autonomous homeostatic plasticity and system-level responses to sleep loss, with potential implications for neuropsychiatric illnesses and treatments.

Neural Oscillations: Understanding a Neural Code of Pain

Neural oscillations play an important role in the integration and segregation of brain regions that are important for brain functions, including pain. Disturbances in oscillatory activity are associated with several disease states, including chronic pain. Studies of neural oscillations related to pain have identified several functional bands, especially alpha, beta, and gamma bands, implicated in nociceptive processing. In this review, we introduce several properties of neural oscillations that are important to understand the role of brain oscillations in nociceptive processing. We also discuss the role of neural oscillations in the maintenance of efficient communication in the brain. Finally, we discuss the role of neural oscillations in healthy and chronic pain nociceptive processing. These data and concepts illustrate the key role of regional and interregional neural oscillations in nociceptive processing underlying acute and chronic pains.

Modulation of Individual Alpha Frequency with tACS shifts Time Perception

Previous studies have linked brain oscillation and timing, with evidence suggesting that alpha oscillations (10 Hz) may serve as a "sample rate" for the visual system. However, direct manipulation of alpha oscillations and time perception has not yet been demonstrated. To test this, we had 18 human subjects perform a time generalization task with visual stimuli. Additionally, we had previously recorded resting-state EEG from each subject and calculated their individual alpha frequency (IAF), estimated as the peak frequency from the mean spectrum over posterior electrodes between 8 and 13 Hz. Participants first learned a standard interval (600 ms) and were then required to judge if a new set of temporal intervals were equal or different compared with that standard. After learning the standard, participants performed this task while receiving occipital transcranial Alternating Current Stimulation (tACS). Crucially, for each subject, tACS was administered at their IAF or at off-peak alpha frequencies (IAF ± 2 Hz). Results demonstrated a linear shift in the psychometric function indicating a modification of perceived duration, such that progressively "faster" alpha stimulation led to longer perceived intervals. These results provide the first evidence that direct manipulations of alpha oscillations can shift perceived time in a manner consistent with a clock speed effect.

A roadmap for development of neuro-oscillations as translational biomarkers for treatment development in neuropsychopharmacology

New treatment development for psychiatric disorders depends critically upon the development of physiological measures that can accurately translate between preclinical animal models and clinical human studies. Such measures can be used both as stratification biomarkers to define pathophysiologically homogeneous patient populations and as target engagement biomarkers to verify similarity of effects across preclinical and clinical intervention. Traditional "time-domain" event-related potentials (ERP) have been used translationally to date but are limited by the significant differences in timing and distribution across rodent, monkey and human studies. By contrast, neuro-oscillatory responses, analyzed within the "time-frequency" domain, are relatively preserved across species permitting more precise translational comparisons. Moreover, neuro-oscillatory responses are increasingly being mapped to local circuit mechanisms and may be useful for investigating effects of both pharmacological and neuromodulatory interventions on excitatory/inhibitory balance. The present paper provides a roadmap for development of neuro-oscillatory responses as translational biomarkers in neuropsychiatric treatment development.

An Attempt at a Unified Theory of the Neocortical Microcircuit in Sensory Cortex

The neocortex performs a wide range of functions, including working memory, sensory perception, and motor planning. Despite this diversity in function, evidence suggests that the neocortex is made up of repeating subunits ("macrocolumns"), each of which is largely identical in circuitry. As such, the specific computations performed by these macrocolumns are of great interest to neuroscientists and AI researchers. Leading theories of this microcircuit include models of predictive coding, hierarchical temporal memory (HTM), and Adaptive Resonance Theory (ART). However, these models have not yet explained: (1) how microcircuits learn sequences input with delay (i.e., working memory); (2) how networks of columns coordinate processing on precise timescales; or (3) how top-down attention modulates sensory processing. I provide a theory of the neocortical microcircuit that extends prior models in all three ways. Additionally, this theory provides a novel working memory circuit that extends prior models to support simultaneous multi-item storage without disrupting ongoing sensory processing. I then use this theory to explain the functional origin of a diverse set of experimental findings, such as cortical oscillations.

The neurophysiology of ketamine: an integrative review

The drug ketamine has been extensively studied due to its use in anaesthesia, as a model of psychosis and, most recently, its antidepressant properties. Understanding the physiology of ketamine is complex due to its rich pharmacology with multiple potential sites at clinically relevant doses. In this review of the neurophysiology of ketamine, we focus on the acute effects of ketamine in the resting brain. We ascend through spatial scales starting with a complete review of the pharmacology of ketamine and then cover its effects on in vitro and in vivo electrophysiology. We then summarise and critically evaluate studies using EEG/MEG and neuroimaging measures (MRI and PET), integrating across scales where possible. While a complicated and, at times, confusing picture of ketamine’s effects are revealed, we stress that much of this might be caused by use of different species, doses, and analytical methodologies and suggest strategies that future work could use to answer these problems.

Effects of the unilateral dynamic handgrip on resting cortical activity levels: A replication and extension

Previous studies have linked unilateral hand contractions to subsequent changes in hemispheric asymmetric activity, as reflected in the electroencephalographic alpha (8-12 Hz) range in each hemisphere. However, debate continues regarding the state of asymmetry induced by unilateral contractions. We have previously found a bilateral enhancement of alpha amplitude that occurs after contractions, reflecting cortical downregulation instead of changes in asymmetric activity. To corroborate our observations, we examined the effects of 45 s of unilateral dynamic handgrip contractions on subsequent resting alpha activity. Twenty-two right-handed participants were recruited (M = 25 years, 17 female). The study used a within-subjects design consisting of a pre- and post-test (2 min resting; eyes open) for the intervention (dynamic handgrip; at a self-determined pace of approximately twice a second for 45 s for each hand). Following the handgrip task, an increase in alpha amplitude above the baseline was observed over the entire cortex, which was greater after left-hand squeezing. This observation confirms our previous findings and we have extended them by adding more electrodes to gain further insights into the handgrip exercise as an external brain stimulator. Moreover, we grouped electrodes according to scalp regions to facilitate the visualization of the effects on the frequency spectrum. Our findings can be used to develop targeted interventions aimed at modifying behavioral outcomes affected by alpha activity.

Dynamic Modulation of Cortical Excitability during Visual Active Sensing

Visual physiology is traditionally investigated by presenting stimuli with gaze held constant. However, during active viewing of a scene, information is actively acquired using systematic patterns of fixations and saccades. Prior studies suggest that during such active viewing, both nonretinal, saccade-related signals and “extra-classical” receptive field inputs modulate visual processing. This study used a set of active viewing tasks that allowed us to compare visual responses with and without direct foveal input, thus isolating the contextual eye movement-related influences. Studying nonhuman primates, we find strong contextual modulation in primary visual cortex (V1): excitability and response amplification immediately after fixation onset, transiting to suppression leading up to the next saccade. Time-frequency decomposition suggests that this amplification and suppression cycle stems from a phase reset of ongoing neuronal oscillatory activity. The impact of saccade-related contextual modulation on stimulus processing makes active visual sensing fundamentally different from the more passive processes investigated in traditional paradigms.

By isolating contextual eye movement-related influences during active vision, Barczak et al. show that eye movements affect excitability in V1 such that responses are amplified immediately after fixation onset and suppressed as the next saccade approaches. This amplification and suppression cycle stems from a phase reset of ambient oscillatory activity in V1.

Layer 4 pyramidal neuron dendritic bursting underlies a post-stimulus visual cortical alpha rhythm

Alpha rhythms (9–11 Hz) are a dominant feature of EEG recordings, particularly over occipital cortex on cessation of a visual stimulation. Little is known about underlying neocortical mechanisms so here we constructed alpha rhythm models that follow cessation of cortical stimulation. The rhythm manifests following a period of gamma frequency activity in local V1 networks in layer 4. It associates with network level bias of excitatory synaptic activity in favour of NMDA- rather than AMPA-mediated signalling and reorganisation of synaptic inhibition in favour of fast GABA_A receptor-mediated events. At the cellular level the alpha rhythm depended upon the generation of layer 4 pyramidal neuron dendritic bursting mediated primarily by PPDA-sensitive NR2C/D-containing NMDA receptors, which lack the magnesium-dependent open channel block. Subthreshold potassium conductances are also critical. The rhythm dynamically filters outputs from sensory relay neurons (stellate neurons in layer 4) such that they become temporally uncoupled from downstream population activity.

The authors combine computational and electrophysiological approaches to study the neocortical mechanisms underlying alpha rhythms generated after visual stimuli cessation. They show that layer 4 pyramidal neuron bursting, as well as a shift towards NMDA- and GABA_A- receptor transmission is critical for the generation of these alpha oscillations.