Thalamic mechanisms of EEG alpha rhythms and their pathological implications

Atypical Relationships Between Spontaneous EEG and fMRI Activity in Autism

Autism spectrum disorders (ASDs) have been linked to atypical communication among distributed brain networks. However, despite decades of research, the exact nature of these differences between typically developing (TD) individuals and those with ASDs remains unclear. ASDs have been widely studied using resting-state neuroimaging methods, including both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). However, little is known about how fMRI and EEG measures of spontaneous brain activity are related in ASDs. In the present study, two cohorts of children and adolescents underwent resting-state EEG (n = 38 per group) or fMRI (n = 66 ASD, 57 TD), with a subset of individuals in both the EEG and fMRI cohorts (n = 17 per group). In the EEG cohort, parieto-occipital EEG alpha power was found to be reduced in ASDs. In the fMRI cohort, blood oxygen level-dependent (BOLD) power was regionally increased in right temporal regions and there was widespread overconnectivity between the thalamus and cortical regions in the ASD group relative to the TD group. Finally, multimodal analyses indicated that while TD children showed consistently positive relationships between EEG alpha power and regional BOLD power, these associations were weak or negative in ASDs. These findings suggest atypical links between alpha rhythms and regional BOLD activity in ASDs, possibly implicating neural substrates and processes that coordinate thalamocortical regulation of the alpha rhythm.

Effects of Cholinergic Neuromodulation on Thalamocortical Rhythms During NREM Sleep: A Model Study

It has been suggested that cholinergic neurons shape the oscillatory activity of the thalamocortical (TC) network in behavioral and electrophysiological experiments. However, theoretical modeling demonstrating how cholinergic neuromodulation of thalamocortical rhythms during non-rapid eye movement (NREM) sleep might occur has been lacking. In this paper, we first develop a novel computational model (TC-ACH) by incorporating a cholinergic neuron population (CH) into the classical thalamo-cortical circuitry, where connections between populations are modeled in accordance with existing knowledge. The neurotransmitter acetylcholine (ACH) released by neurons in CH, which is able to change the discharge activity of thalamocortical neurons, is the primary focus of our work. Simulation results with our TC-ACH model reveal that the cholinergic projection activity is a key factor in modulating oscillation patterns in three ways: (1) transitions between different patterns of thalamocortical oscillations are dramatically modulated through diverse projection pathways; (2) the model expresses a stable spindle oscillation state with certain parameter settings for the cholinergic projection from CH to thalamus, and more spindles appear when the strength of cholinergic input from CH to thalamocortical neurons increases; (3) the duration of oscillation patterns during NREM sleep including K-complexes, spindles, and slow oscillations is longer when cholinergic input from CH to thalamocortical neurons becomes stronger. Our modeling results provide insights into the mechanisms by which the sleep state is controlled, and provide a theoretical basis for future experimental and clinical studies.

Human Neocortical Neurosolver (HNN), a new software tool for interpreting the cellular and network origin of human MEG/EEG data

Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNN's core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal's origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNN's ability to associate signals across scales makes it a unique tool for translational neuroscience research.

Decoding Movement From Electrocorticographic Activity: A Review

Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.

Evidence that alpha blocking is due to increases in system-level oscillatory damping not neuronal population desynchronisation

The attenuation of the alpha rhythm following eyes-opening (alpha blocking) is among the most robust features of the human electroencephalogram with the prevailing view being that it is caused by changes in neuronal population synchrony. To further study the basis for this phenomenon we use theoretically motivated fixed-order Auto-Regressive Moving-Average (ARMA) time series modelling to study the oscillatory dynamics of spontaneous alpha-band electroencephalographic activity in eyes-open and eyes-closed conditions and its modulation by the NMDA antagonist ketamine. We find that the reduction in alpha-band power between eyes-closed and eyes-open states is explicable in terms of an increase in the damping of stochastically perturbed alpha-band relaxation oscillatory activity. These changes in damping are putatively modified by the antagonism of NMDA-mediated glutamatergic neurotransmission but are not directly driven by changes in input to cortex nor by reductions in the phase synchronisation of populations of near identical oscillators. These results not only provide a direct challenge to the dominant view of the role that thalamus and neuronal population de-/synchronisation have in the genesis and modulation of alpha electro-/magnetoencephalographic activity but also suggest potentially important physiological determinants underlying its dynamical control and regulation.

Distinct Montages of Slow Oscillatory Transcranial Direct Current Stimulation (so-tDCS) Constitute Different Mechanisms during Quiet Wakefulness

Slow oscillatory- (so-) tDCS has been applied in many sleep studies aimed to modulate brain rhythms of slow wave sleep and memory consolidation. Yet, so-tDCS may also modify coupled oscillatory networks. Efficacy of weak electric brain stimulation is however variable and dependent upon the brain state at the time of stimulation (subject and/or task-related) as well as on stimulation parameters (e.g., electrode placement and applied current. Anodal so-tDCS was applied during wakefulness with eyes-closed to examine efficacy when deviating from the dominant brain rhythm. Additionally, montages of different electrodes size and applied current strength were used. During a period of quiet wakefulness bilateral frontolateral stimulation (F3, F4; return electrodes at ipsilateral mastoids) was applied to two groups: ‘Group small’ (n = 16, f:8; small electrodes: 0.50 cm²; maximal current per electrode pair: 0.26 mA) and ‘Group Large’ (n = 16, f:8; 35 cm²; 0.35 mA). Anodal so-tDCS (0.75 Hz) was applied in five blocks of 5 min epochs with 1 min stimulation-free epochs between the blocks. A finger sequence tapping task (FSTT) was used to induce comparable cortical activity across sessions and subject groups. So-tDCS resulted in a suppression of alpha power over the parietal cortex. Interestingly, in Group Small alpha suppression occurred over the standard band (8–12 Hz), whereas for Group Large power of individual alpha frequency was suppressed. Group Small also revealed a decrease in FSTT performance at retest after stimulation. It is essential to include concordant measures of behavioral and brain activity to help understand variability and poor reproducibility in oscillatory-tDCS studies.

The generation and propagation of the human alpha rhythm

The alpha rhythm is the longest-studied brain oscillation and has been theorized to play a key role in cognition. Still, its physiology is poorly understood. In this study, we used microelectrodes and macroelectrodes in surgical epilepsy patients to measure the intracortical and thalamic generators of the alpha rhythm during quiet wakefulness. We first found that alpha in both visual and somatosensory cortex propagates from higher-order to lower-order areas. In posterior cortex, alpha propagates from higher-order anterosuperior areas toward the occipital pole, whereas alpha in somatosensory cortex propagates from associative regions toward primary cortex. Several analyses suggest that this cortical alpha leads pulvinar alpha, complicating prevailing theories of a thalamic pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortical layers. Together, these results suggest that the alpha rhythm likely reflects short-range supragranular feedback, which propagates from higher- to lower-order cortex and cortex to thalamus. These physiological insights suggest how alpha could mediate feedback throughout the thalamocortical system.

Developmental abnormalities in cortical GABAergic system in mice lacking mGlu3 metabotropic glutamate receptors

Polymorphic variants of the gene encoding for metabotropic glutamate receptor 3 (mGlu3) are linked to schizophrenia. Because abnormalities of cortical GABAergic interneurons lie at the core of the pathophysiology of schizophrenia, we examined whether mGlu3 receptors influence the developmental trajectory of cortical GABAergic transmission in the postnatal life. mGlu3^-/- mice showed robust changes in the expression of interneuron-related genes in the prefrontal cortex (PFC), including large reductions in the expression of parvalbumin (PV) and the GluN1 subunit of NMDA receptors. The number of cortical cells enwrapped by perineuronal nets was increased in mGlu3^-/- mice, suggesting that mGlu3 receptors shape the temporal window of plasticity of PV⁺ interneurons. Electrophysiological measurements of GABA_A receptor-mediated responses revealed a more depolarized reversal potential of GABA currents in the somata of PFC pyramidal neurons in mGlu3^-/- mice at postnatal d 9 associated with a reduced expression of the K⁺/Cl^- symporter. Finally, adult mGlu3^-/- mice showed lower power in electroencephalographic rhythms at 1-45 Hz in quiet wakefulness as compared with their wild-type counterparts. These findings suggest that mGlu3 receptors have a strong impact on the development of cortical GABAergic transmission and cortical neural synchronization mechanisms corroborating the concept that genetic variants of mGlu3 receptors may predispose to psychiatric disorders.-Imbriglio, T., Verhaeghe, R., Martinello, K., Pascarelli, M. T., Chece, G., Bucci, D., Notartomaso, S., Quattromani, M., Mascio, G., Scalabrì, F., Simeone, A., Maccari, S., Del Percio, C., Wieloch, T., Fucile, S., Babiloni, C., Battaglia, G., Limatola, C., Nicoletti, F., Cannella, M. Developmental abnormalities in cortical GABAergic system in mice lacking mGlu3 metabotropic glutamate receptors.

Thalamic arousal network disturbances in temporal lobe epilepsy and improvement after surgery

OBJECTIVE

The effects of temporal lobe epilepsy (TLE) on subcortical arousal structures remain incompletely understood. Here, we evaluate thalamic arousal network functional connectivity in TLE and examine changes after epilepsy surgery.

METHODS

We examined 26 adult patients with TLE and 26 matched control participants and used resting-state functional MRI (fMRI) to measure functional connectivity between the thalamus (entire thalamus and 19 bilateral thalamic nuclei) and both neocortex and brainstem ascending reticular activating system (ARAS) nuclei. Postoperative imaging was completed for 19 patients >1 year after surgery and compared with preoperative baseline.

RESULTS

Before surgery, patients with TLE demonstrated abnormal thalamo-occipital functional connectivity, losing the normal negative fMRI correlation between the intralaminar central lateral (CL) nucleus and medial occipital lobe seen in controls (p < 0.001, paired t-test). Patients also had abnormal connectivity between ARAS and CL, lower ipsilateral intrathalamic connectivity, and smaller ipsilateral thalamic volume compared with controls (p < 0.05 for each, paired t-tests). Abnormal brainstem-thalamic connectivity was associated with impaired visuospatial attention (ρ = -0.50, p = 0.02, Spearman's rho) while lower intrathalamic connectivity and volume were related to higher frequency of consciousness-sparing seizures (p < 0.02, Spearman's rho). After epilepsy surgery, patients with improved seizures showed partial recovery of thalamo-occipital and brainstem-thalamic connectivity, with values more closely resembling controls (p < 0.01 for each, analysis of variance).

CONCLUSIONS

Overall, patients with TLE demonstrate impaired connectivity in thalamic arousal networks that may be involved in visuospatial attention, but these disturbances may partially recover after successful epilepsy surgery. Thalamic arousal network dysfunction may contribute to morbidity in TLE.

Alpha rhythm collapse predicts iso-electric suppressions during anesthesia

Could an overly deep sedation be anticipated from ElectroEncephaloGram (EEG) patterns? We report here motifs hidden in the EEG signal that predict the appearance of Iso-Electric Suppressions (IES), observed during epileptic encephalopathies, drug intoxications, comatose, brain death or during anesthetic over-dosage that are considered to be detrimental. To show that IES occurrences can be predicted from EEG traces dynamics, we focus on transient suppression of the alpha rhythm (8-14 Hz) recorded for 80 patients, that had a Propofol target controlled infusion of 5 μg/ml during a general anesthesia. We found that the first time of appearance as well as changes in duration of these Alpha-Suppressions (αS) are two parameters that anticipate the appearance of IES. Using machine learning, we predicted IES appearance from the first 10 min of EEG (AUC of 0.93). To conclude, transient motifs in the alpha rhythm predict IES during anesthesia and can be used to identify patients, with higher risks of post-operative complications.

Effects of Task Complexity on Motor Imagery-Based Brain-Computer Interface

The performance of electroencephalogram (EEG)-based brain-computer interfaces (BCIs) still needs improvements for real world applications. An improvement on BCIs could be achieved by enhancing brain signals from the source via subject intention-based modulation. In this work, we aim to investigate the effects of task complexity on performance of motor imagery (MI) based BCIs. In specific, we studied the effects of motor imagery of a complex task versus a simple task on discriminability of brain activation patterns using EEG. The results show an increase of up to 7.25% in BCI classification accuracy for motor imagery of the complex task in comparison to the simple task. Furthermore, spectral power analysis in low frequency bands, alpha and beta, shows a significant decrease in power value for the complex task. However, high frequency gamma band analysis unveils a significant increase for the complex task. These findings may lead to designing better BCIs with high performance.

Electroencephalogram Microstate Abnormalities in Early-Course Psychosis

BACKGROUND

Microstates are periods of characteristic electroencephalographic signal topography that are related to activity in brain networks. Previous work has identified abnormal microstate parameters in individuals with psychotic disorders. We combined microstate analysis with sample entropy analysis to study the dynamics of resting-state networks in patients with early-course psychosis.

METHODS

We used microstate analysis to transform resting-state high-density electroencephalography data from 22 patients with early-course psychosis and 22 healthy control subjects into sequences of characteristic scalp topographies. Sample entropy was used to calculate the complexity of microstate sequences across a range of template lengths.

RESULTS

Patients and control subjects produced similar sets of 4 microstates that agree with a widely reported canonical set (A, B, C, and D). Relative to control subjects, patients had decreased frequency of microstate A. In control subjects, sample entropy decreased as template length increased, suggesting that sequence of microstate transitions is self-similar across multiple transitions. In patients, sample entropy did not decrease, suggesting a lack of self-similarity in transition sequences. This finding was unrelated to data length or microstate topography. Entropy was elevated in unmedicated patients, and it decreased in patients who were administered medication. We identified patterns of transitions between microstates that were overrepresented in control data compared with representation in patient data.

CONCLUSIONS

Our findings suggest that patients with early-course psychosis have abnormally chaotic transitions between brain networks. This chaos may reflect an underlying abnormality in allocating neural resources and effecting appropriate transitions between distinct activity states in psychosis.

Sleep deprivation and Modafinil affect cortical sources of resting state electroencephalographic rhythms in healthy young adults

OBJECTIVE

It has been reported that sleep deprivation affects the neurophysiological mechanisms underpinning the vigilance. Here, we tested the following hypotheses in the PharmaCog project (www.pharmacog.org): (i) sleep deprivation may alter posterior cortical delta and alpha sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms in healthy young adults; (ii) after the sleep deprivation, a vigilance enhancer may recover those rsEEG source markers.

METHODS

rsEEG data were recorded in 36 healthy young adults before (Pre-sleep deprivation) and after (Post-sleep deprivation) one night of sleep deprivation. In the Post-sleep deprivation, these data were collected after a single dose of PLACEBO or MODAFINIL. rsEEG cortical sources were estimated by eLORETA freeware.

RESULTS

In the PLACEBO condition, the sleep deprivation induced an increase and a decrease in posterior delta (2-4 Hz) and alpha (8-13 Hz) source activities, respectively. In the MODAFINIL condition, the vigilance enhancer partially recovered those source activities.

CONCLUSIONS

The present results suggest that posterior delta and alpha source activities may be both related to the regulation of human brain arousal and vigilance in quiet wakefulness.

SIGNIFICANCE

Future research in healthy young adults may use this methodology to preselect new symptomatic drug candidates designed to normalize brain arousal and vigilance in seniors with dementia.

Lasting connectivity increase and anxiety reduction via transcranial alternating current stimulation

Growing evidence of transcranial alternating current stimulation (tACS) modulating intrinsic neural oscillations has spawned interest in applying tACS to treat psychiatric disorders associated with aberrant neural oscillations. The alpha rhythmic activity is known to dominate neural oscillations at the awake, restful state, while attenuated resting-state alpha activity has been implicated in anxious mood. Administering repeated alpha-frequency tACS (α-tACS; at individual peak alpha frequency; 8–12 Hz) over four consecutive days (in the experiment group, sham stimulation in the control group), we demonstrated immediate and lasting (>24 h) increases in resting-state posterior ➔frontal connectivity in the alpha frequency, quantified by Granger causality. Critically, this connectivity enhancement was accompanied by sustained reductions in both anxious arousal and negative perception of sensory stimuli. Resting-state alpha power also increased, albeit only transiently, reversing to the baseline level within 24 h after tACS. Therefore, the lasting enhancement of long-range alpha connectivity due to α-tACS differs from local alpha activity that is nonetheless conserved, highlighting the adaptability of alpha oscillatory networks. In light of increasing recognition of large-scale network dysfunctions as a transdiagnostic pathophysiology of psychiatric disorders, this enduring connectivity plasticity, along with the behavioral improvements, paves the way for tACS applications in clinical interventions of psychiatric ‘oscillopathies’.

Effect of short-term transcutaneous trigeminal nerve stimulation on EEG activity in drug-resistant epilepsy

BACKGROUND

Transcutaneous trigeminal nerve stimulation (TNS) has antiepileptic effects in patients with drug-resistant epilepsy (DRE). However, whether and how TNS is able to modulate the electroencephalogram (EEG) background activity in patients with DRE is still unknown.

OBJECTIVES

To investigate the effect of short-term TNS on EEG background activity in DRE by qualitative and quantitative analyses.

METHODS

Twenty-nine DRE patients participated in the study. Twenty-two were randomly divided into a "sham-TNS" or "real-TNS" group; seven patients underwent stimulation of the median nerve (MNS) at the wrist. Real-TNS was delivered bilaterally to the infraorbital nerve (trains of 1-20 mA, 120 Hz, cyclic modality for 20 min). The sham-TNS protocol mimicked the real-TNS one but at a zero intensity. For MNS, the same parameters as real-TNS were used. EEG was continuously acquired for 40 min: 10' pre, 20' during and 10' post stimulation. EEG was visually inspected for interictal epileptiform discharge (IEDs) changes and processed by spectral analysis for changes in mean frequency and absolute power of each frequency band.

RESULTS

A significant increase of EEG absolute alpha power was observed during real-TNS compared with the sham-TNS (F_34,680 = 1.748; p = 0.006). Conversely, no significant effects were noticed either for quantitative analysis of other frequency bands or for IEDs detection. MNS proved unable to modulate EEG activity.

CONCLUSIONS

Short-term TNS induces an acute and specific effect on background EEG of DRE by increasing the absolute alpha band power. EEG alpha rhythm enhancement may index a cortical functional inhibition and act as a seizure-preventing mechanism.

Frequency and power of human alpha oscillations drift systematically with time-on-task

Oscillatory neural activity is a fundamental characteristic of the mammalian brain spanning multiple levels of spatial and temporal scale. Current theories of neural oscillations and analysis techniques employed to investigate their functional significance are based on an often implicit assumption: In the absence of experimental manipulation, the spectral content of any given EEG- or MEG-recorded neural oscillator remains approximately stationary over the course of a typical experimental session (∼1 h), spontaneously fluctuating only around its dominant frequency. Here, we examined this assumption for ongoing neural oscillations in the alpha-band (8-13 Hz). We found that alpha peak frequency systematically decreased over time, while alpha-power increased. Intriguingly, these systematic changes showed partial independence of each other: Statistical source separation (independent component analysis) revealed that while some alpha components displayed concomitant power increases and peak frequency decreases, other components showed either unique power increases or frequency decreases. Interestingly, we also found these components to differ in frequency. Components that showed mixed frequency/power changes oscillated primarily in the lower alpha-band (∼8-10 Hz), while components with unique changes oscillated primarily in the higher alpha-band (∼9-13 Hz). Our findings provide novel clues on the time-varying intrinsic properties of large-scale neural networks as measured by M/EEG, with implications for the analysis and interpretation of studies that aim at identifying functionally relevant oscillatory networks or at driving them through external stimulation.

Parameter estimation and identifiability in a neural population model for electro-cortical activity

Electroencephalography (EEG) provides a non-invasive measure of brain electrical activity. Neural population models, where large numbers of interacting neurons are considered collectively as a macroscopic system, have long been used to understand features in EEG signals. By tuning dozens of input parameters describing the excitatory and inhibitory neuron populations, these models can reproduce prominent features of the EEG such as the alpha-rhythm. However, the inverse problem, of directly estimating the parameters from fits to EEG data, remains unsolved. Solving this multi-parameter non-linear fitting problem will potentially provide a real-time method for characterizing average neuronal properties in human subjects. Here we perform unbiased fits of a 22-parameter neural population model to EEG data from 82 individuals, using both particle swarm optimization and Markov chain Monte Carlo sampling. We estimate how much is learned about individual parameters by computing Kullback-Leibler divergences between posterior and prior distributions for each parameter. Results indicate that only a single parameter, that determining the dynamics of inhibitory synaptic activity, is directly identifiable, while other parameters have large, though correlated, uncertainties. We show that the eigenvalues of the Fisher information matrix are roughly uniformly spaced over a log scale, indicating that the model is sloppy, like many of the regulatory network models in systems biology. These eigenvalues indicate that the system can be modeled with a low effective dimensionality, with inhibitory synaptic activity being prominent in driving system behavior.

Abnormal Phase Coupling in Parkinson's Disease and Normalization Effects of Subthreshold Vestibular Stimulation

The human brain is a highly dynamic structure requiring dynamic coordination between different neural systems to perform numerous cognitive and behavioral tasks. Emerging perspectives on basal ganglia (BG) and thalamic functions have highlighted their role in facilitating and mediating information transmission among cortical regions. Thus, changes in BG and thalamic structures can induce aberrant modulation of cortico-cortical interactions. Recent work in deep brain stimulation (DBS) has demonstrated that externally applied electrical current to BG structures can have multiple downstream effects in large-scale brain networks. In this work, we identified EEG-based altered resting-state cortical functional connectivity in Parkinson's disease (PD) and examined effects of dopaminergic medication and electrical vestibular stimulation (EVS), a non-invasive brain stimulation (NIBS) technique capable of stimulating the BG and thalamus through vestibular pathways. Resting EEG was collected from 16 PD subjects and 18 age-matched, healthy controls (HC) in four conditions: sham (no stimulation), EVS1 (4-8 Hz multisine), EVS2 (50-100 Hz multisine) and EVS3 (100-150 Hz multisine). The mean, variability, and entropy were extracted from time-varying phase locking value (PLV), a non-linear measure of pairwise functional connectivity, to probe abnormal cortical couplings in the PD subjects. We found the mean PLV of Cz and C3 electrodes were important for discrimination between PD and HC subjects. In addition, the PD subjects exhibited lower variability and entropy of PLV (mostly in theta and alpha bands) compared to the controls, which were correlated with their clinical characteristics. While levodopa medication was effective in normalizing the mean PLV only, all EVS stimuli normalized the mean, variability and entropy of PLV in the PD subject, with the exact extent and duration of improvement a function of stimulus type. These findings provide evidence demonstrating both low- and high-frequency EVS exert widespread influences on cortico-cortical connectivity, likely via subcortical activation. The improvement observed in PD in a stimulus-dependent manner suggests that EVS with optimized parameters may provide a new non-invasive means for neuromodulation of functional brain networks.

Abnormalities of Resting State Cortical EEG Rhythms in Subjects with Mild Cognitive Impairment Due to Alzheimer's and Lewy Body Diseases

The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) score was matched between the ADMCI and DLBMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROCC) classified these sources across individuals. Compared to Nold, IAF showed marked slowing in DLBMCI and moderate in ADMCI. Furthermore, the posterior alpha 2 and alpha 3 source activities were more abnormal in the ADMCI than the DLBMCI group, while widespread delta source activities were more abnormal in the DLBMCI than the ADMCI group. The posterior delta and alpha sources correlated with the MMSE score and correctly classified the Nold and MCI individuals (area under the ROCC >0.85). In conclusion, the ADMCI and DLBMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test the clinical validity of these rsEEG markers.

Hierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics

The large-scale organization of dynamical neural activity across cortex emerges through long-range interactions among local circuits. We hypothesized that large-scale dynamics are also shaped by heterogeneity of intrinsic local properties across cortical areas. One key axis along which microcircuit properties are specialized relates to hierarchical levels of cortical organization. We developed a large-scale dynamical circuit model of human cortex that incorporates heterogeneity of local synaptic strengths, following a hierarchical axis inferred from magnetic resonance imaging (MRI)-derived T1- to T2-weighted (T1w/T2w) mapping and fit the model using multimodal neuroimaging data. We found that incorporating hierarchical heterogeneity substantially improves the model fit to functional MRI (fMRI)-measured resting-state functional connectivity and captures sensory-association organization of multiple fMRI features. The model predicts hierarchically organized higher-frequency spectral power, which we tested with resting-state magnetoencephalography. These findings suggest circuit-level mechanisms linking spatiotemporal levels of analysis and highlight the importance of local properties and their hierarchical specialization on the large-scale organization of human cortical dynamics.

Decreased peak alpha frequency and impaired visual evoked potentials in first episode psychosis

Abnormal spontaneous and evoked oscillations have been reported in several studies of patients with psychotic disorders. Resting alpha power and peak alpha frequency may be decreased in patients with psychosis. We used high-density EEG (hd-EEG) to record resting-state data and steady-state visual evoked potentials (SSVEPs) in patients with first episode psychosis (FEP) and healthy controls to compare brain resonances across multiple frequencies. We recorded hd-EEG (128 channels) from 22 FEP patients and 22 healthy controls during eyes-closed resting state and eyes-closed photic stimulation at 1 Hz, 4 Hz, 10 Hz, 20 Hz, and 40 Hz. Alpha power, peak alpha frequency, and SSVEP amplitude were analyzed using ANOVA and statistical non-parametric mapping. We found that FEP patients had lower peak alpha frequencies (9.72 Hz vs 10.40 Hz, p = .02, Cohen's d = 0.73) and this decrease was driven by slowing over the central and posterior scalp. There was no difference in alpha power. Alpha waves propagated primarily from anterior to posterior and that propagation was slowed in patients. During SSVEP, patients had smaller increases in EEG power in the stimulation band (F(1,184) = 5.3, p = .02). Patients had attenuated responses to SSVEP stimulation at alpha, beta and gamma frequencies. The gamma response was partially preserved in patients who also had depressive symptoms. We conclude that even in early stages of illness, psychotic disorders are associated with decreased alpha peak frequency and impaired evoked resonances. These findings implicate multiple patterns of dysconnectivity in cortico-cortico and cortico-thalamic networks in FEP.

Rebound or Entrainment? The Influence of Alternating Current Stimulation on Individual Alpha

Alternating current stimulation (ACS) is an established means to manipulate intrinsic cortical oscillations. While working towards clinical impact, ACS mechanisms of action remain unclear. For ACS’s well-documented influence on occipital alpha, hypotheses include neuronal entrainment as well as rebound phenomena. As a retinal origin is also discussed, we employed a novel form of ACS with the advantage that it specifically targets occipital alpha-oscillations via retinofugal pathways retinofugal ACS (rACS). We aimed to confirm alpha-enhancement outlasting the duration of stimulation with 10 Hz rACS. To distinguish entrainment from rebound effects, we investigated the correlation between alpha peak frequency change and alpha-enhancement strength. We quantified the alpha band power before and after 10 Hz rACS in 15 healthy subjects. Alpha power enhancement and alpha peak frequency change were assessed over the occipital electrodes and compared to sham stimulation. RACS significantly enhanced occipital alpha power in comparison to sham stimulation (p < 0.05). Alpha peak frequency changed by a mean 0.02 Hz (± 0.04). A greater change in alpha peak frequency did not correlate with greater effects on alpha power. Our findings show an alpha-enhancement consistent with studies conducted for transcranial ACS (tACS) and contribute evidence for a retinal involvement in tACS effects on occipital alpha. Furthermore, the lack of correlation between alpha peak frequency change and alpha-enhancement strength provides an argument against entrainment effects and in favor of a rebound phenomenon.

EEG may serve as a biomarker in Huntington's disease using machine learning automatic classification

Reliable markers measuring disease progression in Huntington’s disease (HD), before and after disease manifestation, may guide a therapy aimed at slowing or halting disease progression. Quantitative electroencephalography (qEEG) may provide a quantification method for possible (sub)cortical dysfunction occurring prior to or concomitant with motor or cognitive disturbances observed in HD. In this pilot study we construct an automatic classifier distinguishing healthy controls from HD gene carriers using qEEG and derive qEEG features that correlate with clinical markers known to change with disease progression in HD, with the aim of exploring biomarker potential. We included twenty-six HD gene carriers (49.7 ± 8.5 years) and 25 healthy controls (52.7 ± 8.7 years). EEG was recorded for three minutes with subjects at rest. An EEG index was created by applying statistical pattern recognition to a large set of EEG features, which was subsequently tested using 10-fold cross-validation. The index resulted in a continuous variable ranging from 0 to 1: a low value indicating a state close to normal and a high value pointing to HD. qEEG features that correlate specifically with commonly used clinical markers in HD research were derived. The classification index had a specificity of 83%, a sensitivity of 83% and an accuracy of 83%. The area under the curve of the receiver operator characteristic curve was 0.9. qEEG analysis on subsets of electrophysiological features resulted in two highly significant correlations with clinical scores. The results of this pilot study suggest that qEEG may serve as a biomarker in HD. The indices correlating with modalities changing with the progression of the disease may lead to tools based on qEEG that help monitor efficacy in intervention studies.

Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics

OBJECTIVE

Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulation interacts with endogenous neural activity as a function of the brain state and target.

APPROACH

To address this critical issue, we applied periodic stimulation to a unified biophysical thalamic network model that generates multiple distinct oscillations, and examined thoroughly the impact of rhythmic stimulation on different oscillatory states.

MAIN RESULTS

We found that rhythmic perturbation induces four basic response mechanisms: entrainment, acceleration, resonance and suppression. Importantly, the appearance and expression of these mechanisms depend highly on the intrinsic cellular dynamics in each state. Specifically, the low-threshold bursting of thalamocortical cells (TCs) in delta (δ) oscillation renders the network relatively insensitive to entrainment; the high-threshold bursting of TCs in alpha (α) oscillation leads to widespread oscillation suppression while the tonic spiking of TC cells in gamma (γ) oscillation results in prominent entrainment and resonance. In addition, we observed entrainment discontinuity during α oscillation that is mediated by firing pattern switching of high-threshold bursting TC cells. Furthermore, we demonstrate that direct excitatory stimulation of the lateral geniculate nucleus (LGN) entrains thalamic oscillations via an asymmetric Arnold tongue that favors higher frequency entrainment and resonance, while stimulation of the inhibitory circuit, the reticular nucleus, induces much weaker and more symmetric entrainment and resonance. These results support the notion that rhythmic stimulation engages brain oscillations in a state- and target-dependent manner.

SIGNIFICANCE

Overall, our study provides, for the first time, insights into how the biophysics of thalamic oscillations guide the emergence of complex, state-dependent mechanisms of target engagement, which can be leveraged for the future rational design of novel therapeutic stimulation modalities.

Effects of 8 weeks of modified hatha yoga training on resting-state brain activity and the p300 ERP in patients with physical disability-related stress

[Purpose] We examined the effects of Hatha yoga on EEG and ERP in patients with physical disability-related stress. [Participants and Methods] Eighteen male and female injured workers with high stress levels, aged between 18 to 55 years, were evenly divided into two groups: untrained (CG) and trained (TG) modified hatha yoga groups. A modified Hatha yoga protocol was designed for this population by two certified yoga instructors, approved by a physical therapist, and conducted for one hour, three times weekly for 8 weeks. [Results] The results indicated a significant increase in alpha EEG activity over the frontal, central, and parietal electrodes and the delta EEG activity over the centroparietal electrode from pre- to post-training in TG. In addition, significantly faster auditory reaction time for target stimuli, as well as lower P300 peak latency of ERP in auditory oddball paradigm were obtained in TG after 8 weeks of yoga training compare to CG. [Conclusion] Changes in brain activity and ERP components following yoga training would support the psychophysiological effects of hatha yoga as an adjunct to routine rehabilitation.

Value and mechanisms of EEG reactivity in the prognosis of patients with impaired consciousness: a systematic review

Background

Electroencephalography (EEG) is a well-established tool for assessing brain function that is available at the bedside in the intensive care unit (ICU). This review aims to discuss the relevance of electroencephalographic reactivity (EEG-R) in patients with impaired consciousness and to describe the neurophysiological mechanisms involved.

Methods

We conducted a systematic search of the term “EEG reactivity and coma” using the PubMed database. The search encompassed articles published from inception to March 2018 and produced 202 articles, of which 42 were deemed relevant, assessing the importance of EEG-R in relationship to outcomes in patients with impaired consciousness, and were therefore included in this review.

Results

Although definitions, characteristics and methods used to assess EEG-R are heterogeneous, several studies underline that a lack of EEG-R is associated with mortality and unfavorable outcome in patients with impaired consciousness. However, preserved EEG-R is linked to better odds of survival. Exploring EEG-R to nociceptive, auditory, and visual stimuli enables a noninvasive trimodal functional assessment of peripheral and central sensory ascending pathways that project to the brainstem, the thalamus and the cerebral cortex. A lack of EEG-R in patients with impaired consciousness may result from altered modulation of thalamocortical loop activity by afferent sensory input due to neural impairment. Assessing EEG-R is a valuable tool for the diagnosis and outcome prediction of severe brain dysfunction in critically ill patients.

Conclusions

This review emphasizes that whatever the etiology, patients with impaired consciousness featuring a reactive electroencephalogram are more likely to have a favorable outcome, whereas those with a nonreactive electroencephalogram are prone to having an unfavorable outcome. EEG-R is therefore a valuable prognostic parameter and warrants a rigorous assessment. However, current assessment methods are heterogeneous, and no consensus exists. Standardization of stimulation and interpretation methods is needed.

High-intensity binge drinking is associated with alterations in spontaneous neural oscillations in young adults

Heavy episodic alcohol consumption (also termed binge drinking) contributes to a wide range of health and cognitive deficits, but the associated brain-based indices are poorly understood. The current study used electroencephalography (EEG) to examine spontaneous neural oscillations in young adults as a function of quantity, frequency, and the pattern of their alcohol consumption. Sixty-one young adults (23.4 ± 3.4 years of age) were assigned to binge drinking (BD) and light drinking (LD) groups that were equated on gender, race/ethnic identity, age, educational background, and family history of alcoholism. EEG activity was recorded during eyes-open and eyes-closed resting conditions. Each participant's alpha peak frequency (APF) was used to calculate absolute power in individualized theta and alpha frequency bands, with a canonical frequency range used for beta. APF was slower by 0.7 Hz in BD, especially in individuals engaging in high-intensity drinking, but there were no changes in alpha power. BD also exhibited higher frontal theta and beta power than LD. Alpha slowing and increased theta power in BD remained after accounting for depression, anxiety, and personality characteristics, while elevated beta power covaried with sensation seeking. Furthermore, APF slowing and theta power correlated with various measures of alcohol consumption, including binge episodes and blackouts, but not with measures of working and episodic memory, cognitive flexibility, processing speed, or personality variables, suggesting that these physiological changes may be modulated by high-intensity alcohol intake. These results are consistent with studies of alcohol-use disorder (AUD) and support the hypothesis that binge drinking is a transitional stage toward alcohol dependence. The observed thalamocortical dysrhythmia may be indicative of an excitatory-inhibitory imbalance in BD and may potentially serve as an index of the progressive development of AUD, with a goal of informing possible interventions to minimize alcohol's deleterious effects on the brain.

Subjective Vividness of Kinesthetic Motor Imagery Is Associated With the Similarity in Magnitude of Sensorimotor Event-Related Desynchronization Between Motor Execution and Motor Imagery

In the field of psychology, it has been well established that there are two types of motor imagery such as kinesthetic motor imagery (KMI) and visual motor imagery (VMI), and the subjective evaluation for vividness of motor imagery each differs across individuals. This study aimed to examine how the motor imagery ability assessed by the psychological scores is associated with the physiological measure using electroencephalogram (EEG) sensorimotor rhythm during KMI task. First, 20 healthy young individuals evaluated subjectively how vividly they can perform each of KMI and VMI by using the Kinesthetic and Visual Imagery Questionnaire (KVIQ). We assessed their motor imagery abilities by summing each of KMI and VMI scores in KVIQ (KMI_total and VMI_total). Second, in physiological experiments, they repeated two strengths (10 and 40% of maximal effort) of isometric voluntary wrist-dorsiflexion. Right after each contraction, they also performed its KMI. The scalp EEGs over the sensorimotor cortex were recorded during the tasks. The EEG power is known to decrease in the alpha-and-beta band (7–35 Hz) from resting state to performing state of voluntary contraction (VC) or motor imagery. This phenomenon is referred to as event-related desynchronization (ERD). For each strength of the tasks, we calculated the maximal peak of ERD during VC, and that during its KMI, and measured the degree of similarity (ERD_sim) between them. The results showed significant negative correlations between KMI_total and ERD_sim for both strengths (p < 0.05) (i.e., the higher the KMI_total, the smaller the ERD_sim). These findings suggest that in healthy individuals with higher motor imagery ability from a first-person perspective, KMI efficiently engages the shared cortical circuits corresponding with motor execution, including the sensorimotor cortex, with high compliance.

Quantitative Analysis of the Antiepileptogenic Effects of Low Frequency Stimulation Applied Prior or After Kindling Stimulation in Rats

Background and Objective: Developing quantitative measures based on spectral analysis of electroencephalograph (EEG) recordings of neural activities plays an important role in developing efficient treatments for epilepsy. Such biomarkers can be used for developing open or closed loop approaches for seizure prediction or prevention. This study aims to quantitatively evaluate antiepileptogenic effects of low frequency stimulation (LFS) applied immediately before or after kindling stimulations using spectral power analysis of extracellular EEG in rat. Methods: Nineteen adult rats were used: seven for kindle, six for LFS+Kindle (LFSK) and six for Kindle+LFS (KLFS). Four packages of LFS (1Hz) were applied immediately before or after rapid kindling stimulations. The power spectral densities of afterdischarge (AD) sections of EEG corresponding to different stages of kindling for delta (0-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-28 Hz), gamma (28-40 Hz) sub-bands, and theta/alpha ratio were comparatively investigated. Moreover, correlation between AD duration (ADD) and its different frequency components was calculated. Results: Both LFSK and KLFS significantly increased delta and reduced beta and gamma oscillations, compared with kindle group. However, just the reduction in LFSK group was significant. Both protocols increased theta/alpha ratio, but just LFSK showed significant increase (p < 0.05). Although LFSK enhanced theta/alpha ratio more than KLFS, the difference was not statistically significant. Furthermore, strong correlation between each frequency sub band and ADD was not observed in kindle and LFS treated groups (both LFSK and KLFS). Conclusion: Although behavioral assessments showed relatively the same level of antiepileptogenic effects for KLFS and LFSK, quantitative assessments showed more significant differences in the quantitative measures between the two protocols. Developing more quantitative EEG based measures correlated with LFS-induced effects can facilitate developing open or closed loop seizure prevention modalities.

Electroencephalographic Predictors of Neuropathic Pain in Subacute Spinal Cord Injury

It is widely believed that cortical changes are a consequence of longstanding neuropathic pain (NP). In this article, we demonstrate that NP in individuals with subacute spinal cord injury (SCI) has characteristic electroencephalography markers (EEG) that precede the onset of pain. EEG was recorded in a relaxed state and during motor imagination tasks in 10 able-bodied participants and 31 patients with subacute SCI (11 with NP, 10 without NP, and 10 who had pain develop within 6 months of EEG recording). All 20 patients with SCI initially without NP were tested for mechanically induced allodynia, but only 1 patient, who later had pain develop, reported an unpleasant sensation. The EEG reactivity to eye opening was reduced in the alpha band and absent in the theta and beta bands in the patients who later developed pain and was reduced in those who already had pain. Alpha band power was reduced at BA7 in both the relaxed state and during motor imagination in patients who either had or later developed pain compared with those without pain. All SCI groups had reduced dominant alpha frequency and beta band power at BA7. EEG reactivity to eye opening and reduced spontaneous and induced alpha activity over the parietal cortex were predictors of future NP, as well as markers of existing NP. Clinical Trial Registration Number: NCT02178917 PERSPECTIVE: We demonstrate that brain activity in patients with subacute SCI reveals both early markers and predictors of NP, which may manifest before sensory discomfort. These markers and predictors may complement known sensory phenotypes of NP. They may exist in other patient groups suffering from NP of central origin.

Ultra-slow mechanical stimulation of olfactory epithelium modulates consciousness by slowing cerebral rhythms in humans

The coupling between respiration and neural activity within olfactory areas and hippocampus has recently been unambiguously demonstrated, its neurophysiological basis sustained by the well-assessed mechanical sensitivity of the olfactory epithelium. We herein hypothesize that this coupling reverberates to the whole brain, possibly modulating the subject's behavior and state of consciousness. The olfactory epithelium of 12 healthy subjects was stimulated with periodical odorless air-delivery (frequency 0.05 Hz, 8 s on, 12 off). Cortical electrical activity (High Density-EEG) and perceived state of consciousness have been studied. The stimulation induced i) an enhancement of delta-theta EEG activity over the whole cortex mainly involving the Limbic System and Default Mode Network structures, ii) a reversal of the overall information flow directionality from wake-like postero-anterior to NREM sleep-like antero-posterior, iii) the perception of having experienced an Altered State of Consciousness. These findings could shed further light via a neurophenomenological approach on the links between respiration, cerebral activity and subjective experience, suggesting a plausible neurophysiological basis for interpreting altered states of consciousness induced by respiration-based meditative practices.

Abnormalities of Cortical Neural Synchronization Mechanisms in Subjects with Mild Cognitive Impairment due to Alzheimer's and Parkinson's Diseases: An EEG Study

The aim of this retrospective and exploratory study was that the cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms might reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and Parkinson's disease (PDMCI) as compared to healthy subjects. Clinical and rsEEG data of 75 ADMCI, 75 PDMCI, and 75 cognitively normal elderly (Nold) subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) was matched between the ADMCI and PDMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROC) classified these sources across individuals. Results showed that compared to the Nold group, the posterior alpha2 and alpha3 source activities were more abnormal in the ADMCI than the PDMCI group, while the parietal delta source activities were more abnormal in the PDMCI than the ADMCI group. The parietal delta and alpha sources correlated with MMSE score and correctly classified the Nold and diseased individuals (area under the ROC = 0.77-0.79). In conclusion, the PDMCI and ADMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test these rsEEG markers for clinical applications and drug discovery.

On the Physiological Modulation and Potential Mechanisms Underlying Parieto-Occipital Alpha Oscillations

The parieto-occipital alpha (8–13 Hz) rhythm is by far the strongest spectral fingerprint in the human brain. Almost 90 years later, its physiological origin is still far from clear. In this Research Topic I review human pharmacological studies using electroencephalography (EEG) and magnetoencephalography (MEG) that investigated the physiological mechanisms behind posterior alpha. Based on results from classical and recent experimental studies, I find a wide spectrum of drugs that modulate parieto-occipital alpha power. Alpha frequency is rarely affected, but this might be due to the range of drug dosages employed. Animal and human pharmacological findings suggest that both GABA enhancers and NMDA blockers systematically decrease posterior alpha power. Surprisingly, most of the theoretical frameworks do not seem to embrace these empirical findings and the debate on the functional role of alpha oscillations has been polarized between the inhibition vs. active poles hypotheses. Here, I speculate that the functional role of alpha might depend on physiological excitation as much as on physiological inhibition. This is supported by animal and human pharmacological work showing that GABAergic, glutamatergic, cholinergic, and serotonergic receptors in the thalamus and the cortex play a key role in the regulation of alpha power and frequency. This myriad of physiological modulations fit with the view that the alpha rhythm is a complex rhythm with multiple sources supported by both thalamo-cortical and cortico-cortical loops. Finally, I briefly discuss how future research combining experimental measurements derived from theoretical predictions based of biophysically realistic computational models will be crucial to the reconciliation of these disparate findings.

Targeting alpha-band oscillations in a cortical model with amplitude-modulated high-frequency transcranial electric stimulation

Non-invasive brain stimulation to target specific network activity patterns, e.g. transcranial alternating current stimulation (tACS), has become an essential tool to understand the causal role of neuronal oscillations in cognition and behavior. However, conventional sinusoidal tACS limits the ability to record neuronal activity during stimulation and lacks spatial focality. One particularly promising new tACS stimulation paradigm uses amplitude-modulated (AM) high-frequency waveforms (AM-tACS) with a slow signal envelope that may overcome the limitations. Moreover. AM-tACS using high-frequency carrier signals is more tolerable than conventional tACS, e.g. in terms of skin irritation and occurrence of phosphenes, when applied at the same current intensities (e.g. 1-2 mA). Yet, the fundamental mechanism of neuronal target-engagement by AM-tACS waveforms has remained unknown. We used a computational model of cortex to investigate how AM-tACS modulates endogenous oscillations and compared the target engagement mechanism to the case of conventional (unmodulated) low-frequency tACS. Analysis of stimulation amplitude and frequency indicated that cortical oscillations were phase-locked to the envelope of the AM stimulation signal, which thus exhibits the same target engagement mechanism as conventional (unmodulated) low frequency tACS. However, in the computational model substantially higher current intensities were needed for AM-tACS than for low-frequency (unmodulated) tACS waveforms to achieve pronounced phase synchronization. Our analysis of the carrier frequency suggests that there might be a trade-off between the use of high-frequency carriers and the stimulation amplitude required for successful entrainment. Together, our computational simulations support the use of slow-envelope high frequency carrier AM waveforms as a tool for noninvasive modulation of brain oscillations. More empirical data will be needed to identify the optimal stimulation parameters and to evaluate tolerability and safety of both, AM- and conventional tACS.

Frequency modulation of neural oscillations according to visual task demands

Temporal integration in visual perception is thought to occur within cycles of occipital alpha-band (8-12 Hz) oscillations. Successive stimuli may be integrated when they fall within the same alpha cycle and segregated for different alpha cycles. Consequently, the speed of alpha oscillations correlates with the temporal resolution of perception, such that lower alpha frequencies provide longer time windows for perceptual integration and higher alpha frequencies correspond to faster sampling and segregation. Can the brain's rhythmic activity be dynamically controlled to adjust its processing speed according to different visual task demands? We recorded magnetoencephalography (MEG) while participants switched between task instructions for temporal integration and segregation, holding stimuli and task difficulty constant. We found that the peak frequency of alpha oscillations decreased when visual task demands required temporal integration compared with segregation. Alpha frequency was strategically modulated immediately before and during stimulus processing, suggesting a preparatory top-down source of modulation. Its neural generators were located in occipital and inferotemporal cortex. The frequency modulation was specific to alpha oscillations and did not occur in the delta (1-3 Hz), theta (3-7 Hz), beta (15-30 Hz), or gamma (30-50 Hz) frequency range. These results show that alpha frequency is under top-down control to increase or decrease the temporal resolution of visual perception.

The relationship between thalamic GABA content and resting cortical rhythm in neuropathic pain

Recurrent thalamocortical connections are integral to the generation of brain rhythms and it is thought that the inhibitory action of the thalamic reticular nucleus is critical in setting these rhythms. Our work and others' has suggested that chronic pain that develops following nerve injury, that is, neuropathic pain, results from altered thalamocortical rhythm, although whether this dysrhythmia is associated with thalamic inhibitory function remains unknown. In this investigation, we used electroencephalography and magnetic resonance spectroscopy to investigate cortical power and thalamic GABAergic concentration in 20 patients with neuropathic pain and 20 pain-free controls. First, we found thalamocortical dysrhythmia in chronic orofacial neuropathic pain; patients displayed greater power than controls over the 4-25 Hz frequency range, most marked in the theta and low alpha bands. Furthermore, sensorimotor cortex displayed a strong positive correlation between cortical power and pain intensity. Interestingly, we found no difference in thalamic GABA concentration between pain subjects and control subjects. However, we demonstrated significant linear relationships between thalamic GABA concentration and enhanced cortical power in pain subjects but not controls. Whilst the difference in relationship between thalamic GABA concentration and resting brain rhythm between chronic pain and control subjects does not prove a cause and effect link, it is consistent with a role for thalamic inhibitory neurotransmitter release, possibly from the thalamic reticular nucleus, in altered brain rhythms in individuals with chronic neuropathic pain.

Dual function of thalamic low-vigilance state oscillations: rhythm-regulation and plasticity

During inattentive wakefulness and non-rapid eye movement (NREM) sleep, the neocortex and thalamus cooperatively engage in rhythmic activities that are exquisitely reflected in the electroencephalogram as distinctive rhythms spanning a range of frequencies from <1 Hz slow waves to 13 Hz alpha waves. In the thalamus, these diverse activities emerge through the interaction of cell-intrinsic mechanisms and local and long-range synaptic inputs. One crucial feature, however, unifies thalamic oscillations of different frequencies: repetitive burst firing driven by voltage-dependent Ca²⁺ spikes. Recent evidence reveals that thalamic Ca²⁺ spikes are inextricably linked to global somatodendritic Ca²⁺ transients and are essential for several forms of thalamic plasticity. Thus, we propose herein that alongside their rhythm-regulation function, thalamic oscillations of low-vigilance states have a plasticity function that, through modifications of synaptic strength and cellular excitability in local neuronal assemblies, can shape ongoing oscillations during inattention and NREM sleep and may potentially reconfigure thalamic networks for faithful information processing during attentive wakefulness.

Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI

Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2-20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Abnormalities of resting-state functional cortical connectivity in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study

Previous evidence showed abnormal posterior sources of resting-state delta (<4 Hz) and alpha (8-12 Hz) rhythms in patients with Alzheimer's disease with dementia (ADD), Parkinson's disease with dementia (PDD), and Lewy body dementia (DLB), as cortical neural synchronization markers in quiet wakefulness. Here, we tested the hypothesis of additional abnormalities in functional cortical connectivity computed in those sources, in ADD, considered as a "disconnection cortical syndrome", in comparison with PDD and DLB. Resting-state eyes-closed electroencephalographic (rsEEG) rhythms had been collected in 42 ADD, 42 PDD, 34 DLB, and 40 normal healthy older (Nold) participants. Exact low-resolution brain electromagnetic tomography (eLORETA) freeware estimated the functional lagged linear connectivity (LLC) from rsEEG cortical sources in delta, theta, alpha, beta, and gamma bands. The area under receiver operating characteristic (AUROC) curve indexed the classification accuracy between Nold and diseased individuals (only values >0.7 were considered). Interhemispheric and intrahemispheric LLCs in widespread delta sources were abnormally higher in the ADD group and, unexpectedly, normal in DLB and PDD groups. Intrahemispheric LLC was reduced in widespread alpha sources dramatically in ADD, markedly in DLB, and moderately in PDD group. Furthermore, the interhemispheric LLC in widespread alpha sources showed lower values in ADD and DLB than PDD groups. At the individual level, AUROC curves of LLC in alpha sources exhibited better classification accuracies for the discrimination of ADD versus Nold individuals (0.84) than for DLB versus Nold participants (0.78) and PDD versus Nold participants (0.75). Functional cortical connectivity markers in delta and alpha sources suggest a more compromised neurophysiological reserve in ADD than DLB, at both group and individual levels.

Stochastic resonance mediates the state-dependent effect of periodic stimulation on cortical alpha oscillations

Brain stimulation can be used to engage and modulate rhythmic activity in brain networks. However, the outcomes of brain stimulation are shaped by behavioral states and endogenous fluctuations in brain activity. To better understand how this intrinsic oscillatory activity controls the susceptibility of the brain to stimulation, we analyzed a computational model of the thalamo-cortical system in two distinct states (rest and task-engaged) to identify the mechanisms by which endogenous alpha oscillations (8Hz–12Hz) are modulated by periodic stimulation. Our analysis shows that the different responses to stimulation observed experimentally in these brain states can be explained by a passage through a bifurcation combined with stochastic resonance — a mechanism by which irregular fluctuations amplify the response of a nonlinear system to weak periodic signals. Indeed, our findings suggest that modulation of brain oscillations is best achieved in states of low endogenous rhythmic activity, and that irregular state-dependent fluctuations in thalamic inputs shape the susceptibility of cortical population to periodic stimulation.