Thalamic mechanisms of EEG alpha rhythms and their pathological implications

The serotonin hallucinogen 5-MeO-DMT alters cortico-thalamic activity in freely moving mice: Regionally-selective involvement of 5-HT1A and 5-HT2A receptors

5-MeO-DMT is a natural hallucinogen acting as serotonin 5-HT_1A/5-HT_2A receptor agonist. Its ability to evoke hallucinations could be used to study the neurobiology of psychotic symptoms and to identify new treatment targets. Moreover, recent studies revealed the therapeutic potential of serotonin hallucinogens in treating mood and anxiety disorders. Our previous results in anesthetized animals show that 5-MeO-DMT alters cortical activity via 5-HT_1A and 5-HT_2A receptors. Here, we examined 5-MeO-DMT effects on oscillatory activity in prefrontal (PFC) and visual (V1) cortices, and in mediodorsal thalamus (MD) of freely-moving wild-type (WT) and 5-HT_2A-R knockout (KO2A) mice. We performed local field potential multi-recordings evaluating the power at different frequency bands and coherence between areas. We also examined the prevention of 5-MeO-DMT effects by the 5-HT_1A-R antagonist WAY-100635. 5-MeO-DMT affected oscillatory activity more in cortical than in thalamic areas. More marked effects were observed in delta power in V1 of KO2A mice. 5-MeO-DMT increased beta band coherence between all examined areas. In KO2A mice, WAY100635 prevented most of 5-MeO-DMT effects on oscillatory activity. The present results indicate that hallucinatory activity of 5-MeO-DMT is likely mediated by simultaneous alteration of prefrontal and visual activities. The prevention of these effects by WAY-100635 in KO2A mice supports the potential usefulness of 5-HT_1A receptor antagonists to treat visual hallucinations. 5-MeO-DMT effects on PFC theta activity and cortico-thalamic coherence may be related to its antidepressant activity. This article is part of the Special Issue entitled 'Psychedelics: New Doors, Altered Perceptions'.

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain.

Real-time fMRI neurofeedback of the mediodorsal and anterior thalamus enhances correlation between thalamic BOLD activity and alpha EEG rhythm

Real-time fMRI neurofeedback (rtfMRI-nf) with simultaneous EEG allows volitional modulation of BOLD activity of target brain regions and investigation of related electrophysiological activity. We applied this approach to study correlations between thalamic BOLD activity and alpha EEG rhythm. Healthy volunteers in the experimental group (EG, n = 15) learned to upregulate BOLD activity of the target region consisting of the mediodorsal (MD) and anterior (AN) thalamic nuclei using rtfMRI-nf during retrieval of happy autobiographical memories. Healthy subjects in the control group (CG, n = 14) were provided with a sham feedback. The EG participants were able to significantly increase BOLD activities of the MD and AN. Functional connectivity between the MD and the inferior precuneus was significantly enhanced during the rtfMRI-nf task. Average individual changes in the occipital alpha EEG power significantly correlated with the average MD BOLD activity levels for the EG. Temporal correlations between the occipital alpha EEG power and BOLD activities of the MD and AN were significantly enhanced, during the rtfMRI-nf task, for the EG compared to the CG. Temporal correlations with the alpha power were also significantly enhanced for the posterior nodes of the default mode network, including the precuneus/posterior cingulate, and for the dorsal striatum. Our findings suggest that the temporal correlation between the MD BOLD activity and posterior alpha EEG power is modulated by the interaction between the MD and the inferior precuneus, reflected in their functional connectivity. Our results demonstrate the potential of the rtfMRI-nf with simultaneous EEG for noninvasive neuromodulation studies of human brain function.

Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation

The thalamus plays a critical role in the genesis of thalamocortical oscillations, yet the underlying mechanisms remain elusive. To understand whether the isolated thalamus can generate multiple distinct oscillations, we developed a biophysical thalamic model to test the hypothesis that generation of and transition between distinct thalamic oscillations can be explained as a function of neuromodulation by acetylcholine (ACh) and norepinephrine (NE) and afferent synaptic excitation. Indeed, the model exhibited four distinct thalamic rhythms (delta, sleep spindle, alpha and gamma oscillations) that span the physiological states corresponding to different arousal levels from deep sleep to focused attention. Our simulation results indicate that generation of these distinct thalamic oscillations is a result of both intrinsic oscillatory cellular properties and specific network connectivity patterns. We then systematically varied the ACh/NE and input levels to generate a complete map of the different oscillatory states and their transitions. Lastly, we applied periodic stimulation to the thalamic network and found that entrainment of thalamic oscillations is highly state-dependent. Our results support the hypothesis that ACh/NE modulation and afferent excitation define thalamic oscillatory states and their response to brain stimulation. Our model proposes a broader and more central role of the thalamus in the genesis of multiple distinct thalamo-cortical rhythms than previously assumed.

Computational modeling has served as an important tool to understand the cellular and circuit mechanisms of thalamocortical oscillations. However, most of the existing thalamic models focus on only one particular oscillatory pattern such as alpha or spindle oscillations. Thus, it remains unclear whether the same thalamic circuitry on its own could generate all major oscillatory patterns and if so what mechanisms underlie the transition among these distinct states. Here we present a unified model of the thalamus that is capable of independently generating multiple distinct oscillations corresponding to different physiological conditions. We then mapped out the different thalamic oscillations by varying the ACh/NE modulatory level and input level systematically. Our simulation results offer a mechanistic understanding of thalamic oscillations and support the long standing notion of a thalamic “pacemaker”. It also suggests that pathological oscillations associated with neurological and psychiatric disorders may stem from malfunction of the thalamic circuitry.

The Role of Oscillatory Phase in Determining the Temporal Organization of Perception: Evidence from Sensory Entrainment

Recent behavioral, neuroimaging, and neurophysiological studies have renewed the idea that the information processing within different temporal windows is linked to the phase and/or frequency of the ongoing oscillations, predominantly in the theta/alpha band (∼4–7 and 8–12 Hz, respectively). However, being correlational in nature, this evidence might reflect a nonfunctional byproduct rather than having a causal role. A more direct link can be shown with methods that manipulate oscillatory activity. Here, we used audiovisual entrainment at different frequencies in the prestimulus period of a temporal integration/segregation task. We hypothesized that entrainment would align ongoing oscillations and drive them toward the stimulation frequency. To reveal behavioral oscillations in temporal perception after the entrainment, we sampled the segregation/integration performance densely in time. In Experiment 1, two groups of human participants (both males and females) received stimulation either at the lower or the upper boundary of the alpha band (∼8.5 vs 11.5 Hz). For both entrainment frequencies, we found a phase alignment of the perceptual oscillation across subjects, but with two different power spectra that peaked near the entrainment frequency. These results were confirmed when perceptual oscillations were characterized in the time domain with sinusoidal fittings. In Experiment 2, we replicated the findings in a within-subject design, extending the results for frequencies in the theta (∼6.5 Hz), but not in the beta (∼15 Hz), range. Overall, these findings show that temporal segregation can be modified by sensory entrainment, providing evidence for a critical role of ongoing oscillations in the temporal organization of perception.

SIGNIFICANCE STATEMENT The continuous flow of sensory input is not processed in an analog fashion, but rather is grouped by the perceptual system over time. Recent studies pinpointed the phase and/or frequency of the neural oscillations in the theta/alpha band (∼4–12 Hz) as possible mechanisms underlying temporal windows in perception. Here, we combined two innovative methodologies to provide more direct support for this evidence. We used sensory entrainment to align neural oscillations to different frequencies and then characterized the resultant perceptual oscillation with a temporal dense sampling of the integration/segregation performance. Our results provide the first evidence that the frequency of temporal segregation can be modified by sensory entrainment, supporting a critical role of ongoing oscillations in the integration/segregation of information over time.

Thalamocortical synchronization during induction and emergence from propofol-induced unconsciousness

General anesthesia (GA) is a reversible drug-induced state of altered arousal required for more than 60,000 surgical procedures each day in the United States alone. Sedation and unconsciousness under GA are associated with stereotyped electrophysiological oscillations that are thought to reflect profound disruptions of activity in neuronal circuits that mediate awareness and cognition. Computational models make specific predictions about the role of the cortex and thalamus in these oscillations. In this paper, we provide in vivo evidence in rats that alpha oscillations (10-15 Hz) induced by the commonly used anesthetic drug propofol are synchronized between the thalamus and the medial prefrontal cortex. We also show that at deep levels of unconsciousness where movement ceases, coherent thalamocortical delta oscillations (1-5 Hz) develop, distinct from concurrent slow oscillations (0.1-1 Hz). The structure of these oscillations in both cortex and thalamus closely parallel those observed in the human electroencephalogram during propofol-induced unconsciousness. During emergence from GA, this synchronized activity dissipates in a sequence different from that observed during loss of consciousness. A possible explanation is that recovery from anesthesia-induced unconsciousness follows a "boot-up" sequence actively driven by ascending arousal centers. The involvement of medial prefrontal cortex suggests that when these oscillations (alpha, delta, slow) are observed in humans, self-awareness and internal consciousness would be impaired if not abolished. These studies advance our understanding of anesthesia-induced unconsciousness and altered arousal and further establish principled neurophysiological markers of these states.

A study of problems encountered in Granger causality analysis from a neuroscience perspective

Granger causality methods were developed to analyze the flow of information between time series. These methods have become more widely applied in neuroscience. Frequency-domain causality measures, such as those of Geweke, as well as multivariate methods, have particular appeal in neuroscience due to the prevalence of oscillatory phenomena and highly multivariate experimental recordings. Despite its widespread application in many fields, there are ongoing concerns regarding the applicability of Granger causality methods in neuroscience. When are these methods appropriate? How reliably do they recover the system structure underlying the observed data? What do frequency-domain causality measures tell us about the functional properties of oscillatory neural systems? In this paper, we analyze fundamental properties of Granger-Geweke (GG) causality, both computational and conceptual. Specifically, we show that (i) GG causality estimates can be either severely biased or of high variance, both leading to spurious results; (ii) even if estimated correctly, GG causality estimates alone are not interpretable without examining the component behaviors of the system model; and (iii) GG causality ignores critical components of a system's dynamics. Based on this analysis, we find that the notion of causality quantified is incompatible with the objectives of many neuroscience investigations, leading to highly counterintuitive and potentially misleading results. Through the analysis of these problems, we provide important conceptual clarification of GG causality, with implications for other related causality approaches and for the role of causality analyses in neuroscience as a whole.

Diminished modulation of preparatory sensorimotor mu rhythm predicts attention-deficit/hyperactivity disorder severity

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is characterized by problems in regulating attention and in suppressing disruptive motor activity, i.e. hyperactivity and impulsivity. We recently found evidence that aberrant distribution of posterior α band oscillations (8-12 Hz) is associated with attentional problems in ADHD. The sensorimotor cortex also produces strong 8-12 Hz band oscillations, namely the μ rhythm, and is thought to have a similar inhibitory function. Here, we now investigate whether problems in distributing α band oscillations in ADHD generalize to the μ rhythm in the sensorimotor domain.

METHOD

In a group of adult ADHD (n = 17) and healthy control subjects (n = 18; aged 21-40 years) oscillatory brain activity was recorded using magnetoencephalography during a visuo-spatial attention task. Subjects had to anticipate a target with unpredictable timing and respond by pressing a button.

RESULTS

Preparing a motor response, the ADHD group failed to increase hemispheric μ lateralization with relatively higher μ power in sensorimotor regions not engaged in the task, as the controls did (F 1,33 = 8.70, p = 0.006). Moreover, the ADHD group pre-response μ lateralization not only correlated positively with accuracy (r s = 0.64, p = 0.0052) and negatively with intra-individual reaction time variability (r s = -0.52, p = 0.033), but it also correlated negatively with the score on an ADHD rating scale (r s = -0.53, p = 0.028).

CONCLUSIONS

We suggest that ADHD is associated with an inability to sufficiently inhibit task-irrelevant sensorimotor areas by means of modulating μ oscillatory activity. This could explain disruptive motor activity in ADHD. These results provide further evidence that impaired modulation of α band oscillations is involved in the pathogenesis of ADHD.

Characterization of the Sensorimotor Rhythm in 4-Month-Old Infants Born at Term and Premature

The sensorimotor rhythm (SMR) is an electroencephalographic rhythm associated with motor and cognitive development observed in the central brain regions during wakefulness in the absence of movement, and it reacts contralaterally to generalized and hemibody movements. The purpose of this work was to characterize the SMR of 4-month-old infants, born either healthy at term or prematurely with periventricular leukomalacia (PVL). Two groups of infants were formed: healthy and premature with PVL. Their electroencephalograms (EEGs) were recorded in four conditions: rest, free movement, right-hand grasping and left-hand grasping, in order to explore general reactivity to free movement and contralateral reactivity in hand-grasping conditions. Associations between SMR, and cognitive and motor performance were analyzed. The healthy infants showed a SMR between 5.47 and 7.03 Hz, with clear contralateral reactivity to free movement and right-hand grasping. However, the premature infants with PVL did not show enough electroencephalographic characteristics to evidence the presence of SMR. Poor performance, characteristic of children with PVL, was related to low-frequency SMR, while good performance was associated with a higher frequency rhythm in the left hemisphere. The presence of SMR in the group of healthy infants could be considered a sign of health at this age. Thus, poor SMR evidence in the EEG of infants with PVL is probably a sign of brain immaturity or brain dysfunction. Our results provide data on infant SMR development that is needed to design neurofeedback protocols for infants with PVL.

Diversity of functional connectivity patterns is reduced in propofol-induced unconsciousness

INTRODUCTION

Recent evidence suggests that the conscious brain is characterized by a diverse repertoire of functional connectivity patterns while the anesthetized brain shows stereotyped activity. However, classical time-averaged methods of connectivity dismiss dynamic and temporal characteristics of functional configurations. Here we demonstrate a new approach which characterizes time-varying patterns of functional connectivity at the subsecond time scale.

METHODS

We introduce phase-lag entropy (PLE), a measure of the diversity of temporal patterns in the phase relationships between two signals. The proposed measure was applied to multichannel electroencephalogram (EEG), which were recorded from two distinct experimental settings: (1) propofol was administrated at a constant infusion rate for 60 min (n = 96); (2) administration of propofol by a target effect-site concentration-controlled infusion with simultaneous assessment of the level of consciousness (n = 10).

RESULTS

From the first dataset, two substantial changes of the phase relationship during anesthesia was found: (1) the dynamics of the phase relationship between frontal channels became progressively less diverse and more stereotyped during unconsciousness, quantified as a reduction in PLE; and (2) the reduction in PLE was consistent across subjects. Furthermore, PLE provided better performance in the classification of states of consciousness than did phase-lag index, a classical time-averaged connectivity method. From the second dataset, PLE showed the highest agreement with the level of consciousness, compared to existing anesthetic depth indicators.

CONCLUSIONS

This study suggests that a scarcity of functional configurations is closely associated with anesthetically induced unconsciousness, and shows promise as a basis for a new consciousness monitoring system during general anesthesia. Hum Brain Mapp 38:4980-4995, 2017. © 2017 Wiley Periodicals, Inc.

Transcallosal Inhibition during Motor Imagery: Analysis of a Neural Mass Model

The EEG rhythmic activities of the somato-sensory cortex reveal event-related desynchronization (ERD) or event-related synchronization (ERS) in beta band (14–30 Hz) as subjects perform certain tasks or react to specific stimuli. Data reported for imagination of movement support the hypothesis that activation of one sensorimotor area (SMA) can be accompanied by deactivation of the other. In order to improve our understanding of beta ERD/ERS generation, two neural mass models (NMM) of a cortical column taken from Wendling et al. (2002) were interconnected to simulate the transmission of information from one cortex to the other. The results show that the excitation of one cortex leads to inhibition of the other and vice versa, enforcing the Theory of Inhibition. This behavior strongly depends on the initial working point (WP) of the neural populations (between the linear and the upper saturation region of a sigmoidal function) and on how the cortical activation or deactivation can move the WP in the upper saturation region ERD or in the linear region ERS, respectively.

Anesthetic action on the transmission delay between cortex and thalamus explains the beta-buzz observed under propofol anesthesia

In recent years, more and more surgeries under general anesthesia have been performed with the assistance of electroencephalogram (EEG) monitors. An increase in anesthetic concentration leads to characteristic changes in the power spectra of the EEG. Although tracking the anesthetic-induced changes in EEG rhythms can be employed to estimate the depth of anesthesia, their precise underlying mechanisms are still unknown. A prominent feature in the EEG of some patients is the emergence of a strong power peak in the β-frequency band, which moves to the α-frequency band while increasing the anesthetic concentration. This feature is called the beta-buzz. In the present study, we use a thalamo-cortical neural population feedback model to reproduce observed characteristic features in frontal EEG power obtained experimentally during propofol general anesthesia, such as this beta-buzz. First, we find that the spectral power peak in the α- and δ-frequency ranges depend on the decay rate constant of excitatory and inhibitory synapses, but the anesthetic action on synapses does not explain the beta-buzz. Moreover, considering the action of propofol on the transmission delay between cortex and thalamus, the model reveals that the beta-buzz may result from a prolongation of the transmission delay by increasing propofol concentration. A corresponding relationship between transmission delay and anesthetic blood concentration is derived. Finally, an analytical stability study demonstrates that increasing propofol concentration moves the systems resting state towards its stability threshold.

Sleep stage distribution in persons with mild traumatic brain injury: a polysomnographic study according to American Academy of Sleep Medicine standards

OBJECTIVE AND BACKGROUND

Sleep stage disruption in persons with mild traumatic brain injury (mTBI) has received little research attention. We examined deviations in sleep stage distribution in persons with mTBI relative to population age- and sex-specific normative data and the relationships between such deviations and brain injury-related, medical/psychiatric, and extrinsic factors.

PATIENTS AND METHODS

We conducted a cross-sectional polysomnographic investigation in 40 participants diagnosed with mTBI (mean age 47.54 ± 11.30 years; 56% males).

MEASUREMENTS

At the time of investigation, participants underwent comprehensive clinical and neuroimaging examinations and one full-night polysomnographic study. We used the 2012 American Academy of Sleep Medicine recommendations for recording, scoring, and summarizing sleep stages. We compared participants' sleep stage data with normative data stratified by age and sex to yield z-scores for deviations from available population norms and then employed stepwise multiple regression analyses to determine the factors associated with the identified significant deviations.

RESULTS

In patients with mTBI, the mean duration of nocturnal wakefulness was higher and consolidated sleep stage N2 and REM were lower than normal (p < 0.0001, p = 0.018, and p = 0.010, respectively). In multivariate regression analysis, several covariates accounted for the variance in the relative changes in sleep stage duration. No sex differences were observed in the mean proportion of non-REM or REM sleep.

CONCLUSIONS

We observed longer relative nocturnal wakefulness and shorter relative N2 and REM sleep in patients with mTBI, and these outcomes were associated with potentially modifiable variables. Addressing disruptions in sleep architecture in patients with mTBI could improve their health status.

Changes in Alpha Frequency and Power of the Electroencephalogram during Volatile-Based General Anesthesia

Oscillations in the electroencephalogram (EEG) at the alpha frequency (8–12 Hz) are thought to be ubiquitous during surgical anesthesia, but the details of how this oscillation responds to ongoing changes in volatile anesthetic concentration have not been well characterized. It is not known how often alpha oscillations are absent in the clinical context, how sensitively alpha frequency and power respond to changes in anesthetic concentration, and what effect increased age has on alpha frequency. Bipolar EEG was recorded frontally from 305 patients undergoing surgery with sevoflurane or desflurane providing general anesthesia. A new method of detecting the presence of alpha oscillations based on the stability of the rate of change of the peak frequency in the alpha range was developed. Linear concentration-response curves were fitted to assess the sensitivity of alpha power and frequency measures to changing levels of anesthesia. Alpha oscillations were seen to be inexplicably absent in around 4% of patients. Maximal alpha power increased with increasing volatile anesthetic concentrations in half of the patients, and decreased in the remaining patients. Alpha frequency decreased with increasing anesthetic concentrations in near to 90% of patients. Increasing age was associated with decreased sensitivity to volatile anesthesia concentrations, and with decreased alpha frequency, which sometimes transitioned into the theta range (5–7 Hz). While peak alpha frequency shows a consistent slowing to increasing volatile concentrations, the peak power of the oscillation does not, suggesting that frequency might be more informative of depth of anesthesia than traditional power based measures during volatile-based anesthesia. The alpha oscillation becomes slower with increasing age, even when the decreased anesthetic needs of older patients were taken into account.

Intraoperative Frontal Alpha-Band Power Correlates with Preoperative Neurocognitive Function in Older Adults

Each year over 16 million older Americans undergo general anesthesia for surgery, and up to 40% develop postoperative delirium and/or cognitive dysfunction (POCD). Delirium and POCD are each associated with decreased quality of life, early retirement, increased 1-year mortality, and long-term cognitive decline. Multiple investigators have thus suggested that anesthesia and surgery place severe stress on the aging brain, and that patients with less ability to withstand this stress will be at increased risk for developing postoperative delirium and POCD. Delirium and POCD risk are increased in patients with lower preoperative cognitive function, yet preoperative cognitive function is not routinely assessed, and no intraoperative physiological predictors have been found that correlate with lower preoperative cognitive function. Since general anesthesia causes alpha-band (8–12 Hz) electroencephalogram (EEG) power to decrease occipitally and increase frontally (known as “anteriorization”), and anesthetic-induced frontal alpha power is reduced in older adults, we hypothesized that lower intraoperative frontal alpha power might correlate with lower preoperative cognitive function. Here, we provide evidence that such a correlation exists, suggesting that lower intraoperative frontal alpha power could be used as a physiological marker to identify older adults with lower preoperative cognitive function. Lower intraoperative frontal alpha power could thus be used to target these at-risk patients for possible therapeutic interventions to help prevent postoperative delirium and POCD, or for increased postoperative monitoring and follow-up. More generally, these results suggest that understanding interindividual differences in how the brain responds to anesthetic drugs can be used as a probe of neurocognitive function (and dysfunction), and might be a useful measure of neurocognitive function in older adults.

Top-down control of cortical gamma-band communication via pulvinar induced phase shifts in the alpha rhythm

Selective routing of information between cortical areas is required in order to combine different sources of information according to cognitive demand. Recent experiments have suggested that alpha band activity originating from the pulvinar coordinates this inter-areal cortical communication. Using a computer model we investigated whether top-down induced shifts in the relative alpha phase between two cortical areas could modulate cortical communication, quantified in terms of changes in gamma band coherence between them. The network model was comprised of two uni-directionally connected neuronal populations of spiking neurons, each representing a cortical area. We find that the phase difference of the alpha oscillations modulating the two neuronal populations strongly affected the interregional gamma-band neuronal coherence. We confirmed that a higher gamma band coherence also resulted in more efficient transmission of spiking information between cortical areas, thereby confirming the value of gamma coherence as a proxy for cortical information transmission. In a model where both neuronal populations were connected bi-directionally, the relative alpha phase determined the directionality of communication between the populations. Our results show the feasibility of a physiological realistic mechanism for routing information in the brain based on coupled oscillations. Our model results in a set of testable predictions regarding phase shifts in alpha oscillations under different task demands requiring experimental quantification of neuronal oscillations in different regions in e.g. attention paradigms.

Cortical oscillations have been linked to the process of communication between two brain areas. Here we investigated how a third area could control communication between two other brain areas. We find that the phase of a slower alpha-band oscillation is able to influence the power of faster gamma oscillations. By changing phase differences between the slower oscillation in two areas, a third area is able to control the amount of information flow. In a network with bi-directional connections, the direction of communication is also controlled by this phase difference. Our results suggest that the pulvinar could coordinate communication between different brain areas. This area could have a central role in prioritizing the processing of sensory information that is most relevant for the task at hand.

Sleep slow oscillation and plasticity

It is well documented that sleep contributes to memory consolidation and it is also accepted that long-term synaptic plasticity plays a critical role in memory formation. The mechanisms of this sleep-dependent memory formation are unclear. Two main hypotheses are proposed. According to the first one, synapses are potentiated during wake; and during sleep they are scaled back to become available for the learning tasks in the next day. The other hypothesis is that sleep slow oscillations potentiate synapses that were depressed due to persistent activities during the previous day and that potentiation provides physiological basis for memory consolidation. The objective of this review is to group information on whether cortical synapses are up-scaled or down-scaled during sleep. We conclude that the majority of cortical synapses are up-regulated by sleep slow oscillation.

Photosensitive epilepsy is associated with reduced inhibition of alpha rhythm generating networks

See Hamandi (doi:10.1093/awx049) for a scientific commentary on this article.Photosensitivity is a condition in which lights induce epileptiform activities. This abnormal electroencephalographic response has been associated with hyperexcitability of the visuo-motor system. Here, we evaluate if intrinsic dysfunction of this network is present in brain activity at rest, independently of any stimulus and of any paroxysmal electroencephalographic activity. To address this issue, we investigated the haemodynamic correlates of the spontaneous alpha rhythm, which is considered the hallmark of the brain resting state, in photosensitive patients and in people without photosensitivity. Second, we evaluated the whole-brain functional connectivity of the visual thalamic nuclei in the various populations of subjects under investigation. Forty-four patients with epilepsy and 16 healthy control subjects underwent an electroencephalography-correlated functional magnetic resonance imaging study, during an eyes-closed condition. The following patient groups were included: (i) genetic generalized epilepsy with photosensitivity, 16 subjects (mean age 25 ± 10 years); (ii) genetic generalized epilepsy without photosensitivity, 13 patients (mean age 25 ± 11 years); (iii) focal epilepsy, 15 patients (mean age 25 ± 9 years). For each subject, the posterior alpha power variations were convolved with the standard haemodynamic response function and used as a regressor. Within- and between-groups second level analyses were performed. Whole brain functional connectivity was evaluated for two thalamic regions of interest, based on the haemodynamic findings, which included the posterior thalamus (pulvinar) and the medio-dorsal thalamic nuclei. Genetic generalized epilepsy with photosensitivity demonstrated significantly greater mean alpha-power with respect to controls and other epilepsy groups. In photosensitive epilepsy, alpha-related blood oxygen level-dependent signal changes demonstrated lower decreases relative to all other groups in the occipital, sensory-motor, anterior cingulate and supplementary motor cortices. Coherently, the same brain regions demonstrated abnormal connectivity with the visual thalamus only in epilepsy patients with photosensitivity. As predicted, our findings indicate that the cortical-subcortical network generating the alpha oscillation at rest is different in people with epilepsy and visual sensitivity. This difference consists of a decreased alpha-related inhibition of the visual cortex and sensory-motor networks at rest. These findings represent the substrate of the clinical manifestations (i.e. myoclonus) of the photoparoxysmal response. Moreover, our results provide the first evidence of the existence of a functional link between the circuits that trigger the visual sensitivity phenomenon and those that generate the posterior alpha rhythm.

Dynamic spatiotemporal variability of alpha-BOLD relationships during the resting-state and task-evoked responses

Accurate characterization of the spatiotemporal relationship between two of the most prominent neuroimaging measures of neuronal activity, the 8-13Hz, occipito-parietal EEG alpha oscillation and the BOLD fMRI signal, must encompass the intrinsically dynamic nature of both alpha power and brain function. Here, during the eyes-open resting state, we use a 16s sliding-window analysis and demonstrate that the mean spatial network of dynamic alpha-BOLD correlations is highly comparable to the static network calculated over six minutes. However, alpha-BOLD correlations showed substantial spatiotemporal variability within-subjects and passed through many different configurations such that the static network was fully represented in only ~10% of 16s epochs, with visual and parietal regions (coherent on average) often opposingly correlated with each other or with alpha. We find that the common assumption of static-alpha BOLD correlations greatly oversimplifies temporal variation in brain network dynamics. Fluctuations in alpha-BOLD coupling significantly depended upon the instantaneous amplitude of alpha power, and primary and lateral visual areas were most strongly negatively correlated with alpha during different alpha power states, possibly suggesting the action of multiple alpha mechanisms. Dynamic alpha-BOLD correlations could not be explained by eye-blinks/movements, head motion or non-neuronal physiological variability. Individual's mean alpha power and frequency were found to contribute to between-subject variability in alpha-BOLD correlations. Additionally, application to a visual stimulation dataset showed that dynamic alpha-BOLD correlations provided functional information pertaining to the brain's response to stimulation by exhibiting spatiotemporal fluctuations related to variability in the trial-by-trial BOLD response magnitude. Significantly weaker visual alpha-BOLD correlations were found both preceding and following small amplitude BOLD response trials compared to large response trials.

Differential modulation of thalamo-parietal interactions by varying depths of isoflurane anesthesia

The thalamus is thought to relay peripheral sensory information to the somatosensory cortex in the parietal lobe. Long-range thalamo-parietal interactions play an important role in inducing the effect of anesthetic. However, whether these interaction changes vary with different levels of anesthesia is not known. In the present study, we investigated the influence of different levels of isoflurane-induced anesthesia on the functional connectivity between the thalamus and the parietal region. Microelectrodes were implanted in rats to record local field potentials (LFPs). The rats underwent different levels of isoflurane anesthesia [deep anesthesia: isoflurane (ISO) 2.5 vol%, light anesthesia (ISO 1 vol%), awake, and recovery state] and LFPs were recorded from four different brain areas (left parietal, right parietal, left thalamus, and right thalamus). Partial directed coherence (PDC) was calculated for these areas. With increasing depth of anesthesia, the PDC in the thalamus-to-parietal direction was significantly increased mainly in the high frequency ranges; however, in the parietal-to-thalamus direction, the increase was mainly in the low frequency band. For both directions, the PDC changes were prominent in the alpha frequency band. Functional interactions between the thalamus and parietal area are augmented proportionally to the anesthesia level. This relationship may pave the way for better understanding of the neural processing of sensory inputs from the periphery under different levels of anesthesia.

Abnormalities of cortical neural synchronization mechanisms in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study

The aim of this retrospective exploratory study was that resting state eyes-closed electroencephalographic (rsEEG) rhythms might reflect brain arousal in patients with dementia due to Alzheimer's disease dementia (ADD), Parkinson's disease dementia (PDD), and dementia with Lewy body (DLB). Clinical and rsEEG data of 42 ADD, 42 PDD, 34 DLB, and 40 healthy elderly (Nold) subjects were available in an international archive. Demography, education, and Mini-Mental State Evaluation score were not different between the patient groups. Individual alpha frequency peak (IAF) determined the delta, theta, alpha 1, alpha 2, and alpha 3 frequency bands. Fixed beta 1, beta 2, and gamma bands were also considered. rsEEG cortical sources were estimated by means of the exact low-resolution brain electromagnetic source tomography and were then classified across individuals, on the basis of the receiver operating characteristic curves. Compared to Nold, IAF showed marked slowing in PDD and DLB and moderate slowing in ADD. Furthermore, all patient groups showed lower posterior alpha 2 source activities. This effect was dramatic in ADD, marked in DLB, and moderate in PDD. These groups also showed higher occipital delta source activities, but this effect was dramatic in PDD, marked in DLB, and moderate in ADD. The posterior delta and alpha sources allowed good classification accuracy (approximately 0.85-0.90) between the Nold subjects and patients, and between ADD and PDD patients. In quiet wakefulness, delta and alpha sources unveiled different spatial and frequency features of the cortical neural synchronization underpinning brain arousal in ADD, PDD, and DLB patients. Future prospective cross-validation studies should test these rsEEG markers for clinical applications and drug discovery.

A resting EEG study of neocortical hyperexcitability and altered functional connectivity in fragile X syndrome

BACKGROUND

Cortical hyperexcitability due to abnormal fast-spiking inhibitory interneuron function has been documented in fmr1 KO mice, a mouse model of the fragile X syndrome which is the most common single gene cause of autism and intellectual disability.

METHODS

We collected resting state dense-array electroencephalography data from 21 fragile X syndrome (FXS) patients and 21 age-matched healthy participants.

RESULTS

FXS patients exhibited greater gamma frequency band power, which was correlated with social and sensory processing difficulties. Second, FXS patients showed increased spatial spreading of phase-synchronized high frequency neural activity in the gamma band. Third, we observed increased negative theta-to-gamma but decreased alpha-to-gamma band amplitude coupling, and the level of increased theta power was inversely related to the level of resting gamma power in FXS.

CONCLUSIONS

Increased theta band power and coupling from frontal sources may represent a mechanism providing compensatory inhibition of high-frequency gamma band activity, potentially contributing to the widely varying level of neurophysiological and behavioral abnormalities and treatment response seen in full-mutation FXS patients. These findings extend preclinical observations and provide new mechanistic insights into brain alterations and their variability across FXS patients. Electrophysiological measures may provide useful translational biomarkers for advancing drug development and individualizing treatments for neurodevelopmental disorders with associated neuronal hyperexcitability.

Changes in Neuronal Oscillations Accompany the Loss of Hippocampal LTP that Occurs in an Animal Model of Psychosis

The first-episode of psychosis is followed by a transient time-window of ca. 60 days during which therapeutic interventions have a higher likelihood of being effective than interventions that are started with a greater latency. This suggests that, in the immediate time-period after first-episode psychosis, functional changes occur in the brain that render it increasingly resistant to intervention. The precise mechanistic nature of these changes is unclear, but at the cognitive level, sensory and hippocampus-based dysfunctions become increasingly manifest. In an animal model of first-episode psychosis that comprises acute treatment of rats with the irreversible N-methyl-D-aspartate receptor (NMDAR)-antagonist, MK801, acute but also chronic deficits in long-term potentiation (LTP) and spatial memory occur. Neuronal oscillations, especially in the form of information transfer through θ and γ frequency oscillations are an intrinsic component of normal information processing in the hippocampus. Changes in θ-γ coupling and power are known to accompany deficits in hippocampal plasticity. Here, we examined whether changes in δ, θ, α, β and γ oscillations, or θ-γ coupling accompany the chronic loss of LTP that is observed in the MK801-animal model of psychosis. One and 4 weeks after acute systemic treatment of adult rats with MK801, a potent loss of hippocampal in vivo LTP was evident compared to vehicle-treated controls. Overall, the typical pattern of θ-γ oscillations that are characteristic for the successful induction of LTP was altered. In particular, θ-power was lower and an uncoupling of θ-γ oscillations was evident in MK801-treated rats. The alterations in network oscillations that accompany LTP deficits in this animal model may comprise a mechanism through which disturbances in sensory information processing and hippocampal function occur in psychosis. These data suggest that the hippocampus is likely to comprise a very early locus of functional change after instigation of a first-episode psychosis-like state in rodents.

EEG Signatures of Dynamic Functional Network Connectivity States

The human brain operates by dynamically modulating different neural populations to enable goal directed behavior. The synchrony or lack thereof between different brain regions is thought to correspond to observed functional connectivity dynamics in resting state brain imaging data. In a large sample of healthy human adult subjects and utilizing a sliding windowed correlation method on functional imaging data, earlier we demonstrated the presence of seven distinct functional connectivity states/patterns between different brain networks that reliably occur across time and subjects. Whether these connectivity states correspond to meaningful electrophysiological signatures was not clear. In this study, using a dataset with concurrent EEG and resting state functional imaging data acquired during eyes open and eyes closed states, we demonstrate the replicability of previous findings in an independent sample, and identify EEG spectral signatures associated with these functional network connectivity changes. Eyes open and eyes closed conditions show common and different connectivity patterns that are associated with distinct EEG spectral signatures. Certain connectivity states are more prevalent in the eyes open case and some occur only in eyes closed state. Both conditions exhibit a state of increased thalamocortical anticorrelation associated with reduced EEG spectral alpha power and increased delta and theta power possibly reflecting drowsiness. This state occurs more frequently in the eyes closed state. In summary, we find a link between dynamic connectivity in fMRI data and concurrently collected EEG data, including a large effect of vigilance on functional connectivity. As demonstrated with EEG and fMRI, the stationarity of connectivity cannot be assumed, even for relatively short periods.

Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings

Neural models describe brain activity at different scales, ranging from single cells to whole brain networks. Here, we attempt to reconcile models operating at the microscopic (compartmental) and mesoscopic (neural mass) scales to analyse data from microelectrode recordings of intralaminar neural activity. Although these two classes of models operate at different scales, it is relatively straightforward to create neural mass models of ensemble activity that are equipped with priors obtained after fitting data generated by detailed microscopic models. This provides generative (forward) models of measured neuronal responses that retain construct validity in relation to compartmental models. We illustrate our approach using cross spectral responses obtained from V1 during a visual perception paradigm that involved optogenetic manipulation of the basal forebrain. We find that the resulting neural mass model can distinguish between activity in distinct cortical layers - both with and without optogenetic activation - and that cholinergic input appears to enhance (disinhibit) superficial layer activity relative to deep layers. This is particularly interesting from the perspective of predictive coding, where neuromodulators are thought to boost prediction errors that ascend the cortical hierarchy.

Waking EEG Cortical Markers of Chronic Pain and Sleepiness

Objective

Spectral power analyses of EEG recordings are reported to distinguish the cortical activity of individuals with chronic pain from those of controls. Further study of these spectral patterns may provide a greater understanding of the processes associated with chronic pain, in addition to providing potential biometric markers of chronic pain for use in both clinical and research settings. However, sleep deprived groups have demonstrated similar characteristics in their spectral power characteristics, particularly in alpha bandwidth power activity.

Methods

103 individuals with chronic pain provided resting awake EEG data in addition to ratings of pain and sleep quality. Two Principal Axis Factor analyses using Promax rotation produced one pain and one sleep factor from relevant questionnaire data provided by participants. These factors were then used to test hypothesized relationships with alpha and theta bandwidth power at the frontal and parietal areas of the cortex.

Results

Our findings suggest that reductions in alpha bandwidth power are independently associated with both chronic pain intensity ratings and measures of sleep deficits. Conversely, theta bandwidth power was not found to be associated with either chronic pain or sleep quality measures.

Conclusions

This study's findings support that chronic pain intensity and sleep deficits are related to the Alpha spectral bandwidth activity in individuals with chronic pain.

Escitalopram but not placebo modulates brain rhythmic oscillatory activity in the first week of treatment of Major Depressive Disorder

Serotonin modulates brain oscillatory activity, and serotonergic projections to the thalamus and cortex modulate the frequency of prefrontal rhythmic oscillations. Changes in serotonergic tone have been reported to shift oscillations between the combined delta-theta (2.5-8 Hz) and the alpha (8-12 Hz) frequency ranges. Such frequency shifts may constitute a useful biomarker for the effects of selective serotonin reuptake inhibitor (SSRI) medications in Major Depressive Disorder (MDD). We utilized quantitative electroencephalography (qEEG) to measure shifts in prefrontal rhythmic oscillations early in treatment with either the SSRI escitalopram or placebo, and examined the relationship between these changes and remission of depressive symptoms. Prefrontal delta-theta and alpha power were calculated for 194 subjects with moderate MDD prior to and one week after start of treatment. Changes at one week in delta-theta and alpha power, as well as the delta-theta/alpha ratio, were examined in three cohorts: initial (N = 70) and replication (N = 76) cohorts treated with escitalopram, and a cohort treated with placebo (N = 48). Mean delta-theta power significantly increased and alpha power decreased after one week of escitalopram treatment, but did not significantly change with placebo treatment. The delta-theta/alpha ratio change was a specific predictor of the likelihood of remission after seven weeks of medication treatment: a large increase in this ratio was associated with non-remission in escitalopram-treated subjects, but not placebo-treated subjects. Escitalopram and placebo treatment have differential effects on delta-theta and alpha frequency oscillations. Early increase in delta-theta/alpha may constitute a replicable biomarker for non-remission during SSRI treatment of MDD.

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible-elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications.

Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics

Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20–25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR), thalamic reticular nucleus (TRN), to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modeling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterized and tuned to simulate alpha (8–13 Hz) rhythm that is dominant in both Local Field Potential (LFP) of LGN and electroencephalogram (EEG) of visual cortex in an awake resting state with eyes closed. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is observed by progressive decrease of neurotransmitter concentrations in the synaptic clefts; however, the transition is abrupt with removal of the IN circuitry in the model. The results imply a role of IN toward maintaining homeostasis in the LGN by suppressing any instability that may arise due to anomalous synaptic attributes.

Time evolution of interhemispheric coupling in a model of focal neocortical epilepsy in mice

Epilepsy is characterized by substantial network rearrangements leading to spontaneous seizures and little is known on how an epileptogenic focus impacts on neural activity in the contralateral hemisphere. Here, we used a model of unilateral epilepsy induced by injection of the synaptic blocker tetanus neurotoxin (TeNT) in the mouse primary visual cortex (V1). Local field potential (LFP) signals were simultaneously recorded from both hemispheres of each mouse in acute phase (peak of toxin action) and chronic condition (completion of TeNT effects). To characterize the neural electrical activities the corresponding LFP signals were analyzed with several methods of time series analysis. For the epileptic mice, the spectral analysis showed that TeNT determines a power redistribution among the different neurophysiological bands in both acute and chronic phases. Using linear and nonlinear interdependence measures in both time and frequency domains, it was found in the acute phase that TeNT injection promotes a reduction of the interhemispheric coupling for high frequencies (12-30 Hz) and small time lag (<20 ms), whereas an increase of the coupling is present for low frequencies (0.5-4 Hz) and long time lag (>40 ms). On the other hand, the chronic period is characterized by a partial or complete recovery of the interhemispheric interdependence level. Granger causality test and symbolic transfer entropy indicate a greater driving influence of the TeNT-injected side on activity in the contralateral hemisphere in the chronic phase. Lastly, based on experimental observations, we built a computational model of LFPs to investigate the role of the ipsilateral inhibition and exicitatory interhemispheric connections in the dampening of the interhemispheric coupling. The time evolution of the interhemispheric coupling in such a relevant model of epilepsy has been addressed here.

Brain Networks and α-Oscillations: Structural and Functional Foundations of Cognitive Control

The most salient electrical signal measured from the human brain is the α-rhythm, neural activity oscillating at ∼100ms intervals. Recent findings challenge the longstanding dogma of α-band oscillations as the signature of a passively idling brain state but diverge in terms of interpretation. Despite firm correlations with behavior, the mechanistic role of the α-rhythm in brain function remains debated. We suggest that three large-scale brain networks involved in different facets of top-down cognitive control differentially modulate α-oscillations, ranging from power within and synchrony between brain regions. Thereby, these networks selectively influence local signal processing, widespread information exchange, and ultimately perception and behavior.

Classifying amygdala kindling stages using quantitative assessments of extracellular recording of EEG in rats

PURPOSE

Determining different seizure stage specific features in a kindling model is a crucial step in developing efficient objective techniques for early prediction and treatment of seizures. This study identified and categorized kindling stages based on their electrophysiological features through processing extracellular field potentials of Amygdala rapid kindling.

METHODS

Thirteen Wistar rats (200±10g) were divided into 2 groups including kindle (n=7) and sham (n=6) and respectively underwent an amygdala rapid kindling and placebo stimulation. EEG signals in each stage were classified into 7 bands: delta (0-4Hz), theta (4-8Hz), alpha (8-12Hz), low beta (12-16Hz), mid beta (16-20Hz), high beta (20-28Hz) and gamma (28-40Hz). Spectral power and power of sub bands of stage 3 (localized seizure stage (SS)) and stages 4 and 5 (generalized SSs) were compared between kindling and sham groups.

RESULT

Spectral analyses showed larger spikes in delta and theta subbands in the stages of 3, 4, and 5 of kindling, compared with sham animals. Generalized SSs contained more spikes than the localized SS in the kindling. Kindling process was accompanied by reduction in high beta and gamma oscillations and increase in delta sub band power which were significant in the generalized SSs. The theta/alpha ratio in the localized SS was higher than the generalized SSs and sham group, but the difference with the sham group was statistically significant.

CONCLUSION

Our results showed that reduced high beta and gamma and increased delta oscillations power are associated with behavioral seizure progression.

Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice

Human neocortical 15-29-Hz beta oscillations are strong predictors of perceptual and motor performance. However, the mechanistic origin of beta in vivo is unknown, hindering understanding of its functional role. Combining human magnetoencephalography (MEG), computational modeling, and laminar recordings in animals, we present a new theory that accounts for the origin of spontaneous neocortical beta. In our MEG data, spontaneous beta activity from somatosensory and frontal cortex emerged as noncontinuous beta events typically lasting <150 ms with a stereotypical waveform. Computational modeling uniquely designed to infer the electrical currents underlying these signals showed that beta events could emerge from the integration of nearly synchronous bursts of excitatory synaptic drive targeting proximal and distal dendrites of pyramidal neurons, where the defining feature of a beta event was a strong distal drive that lasted one beta period (∼50 ms). This beta mechanism rigorously accounted for the beta event profiles; several other mechanisms did not. The spatial location of synaptic drive in the model to supragranular and infragranular layers was critical to the emergence of beta events and led to the prediction that beta events should be associated with a specific laminar current profile. Laminar recordings in somatosensory neocortex from anesthetized mice and awake monkeys supported these predictions, suggesting this beta mechanism is conserved across species and recording modalities. These findings make several predictions about optimal states for perceptual and motor performance and guide causal interventions to modulate beta for optimal function.

Dysfunction of sensory oscillations in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a highly prevalent developmental disability characterized by deficits in social communication and interaction, restricted interests, and repetitive behaviors. Recently, anomalous sensory and perceptual function has gained an increased level of recognition as an important feature of ASD. A specific impairment in the ability to integrate information across brain networks has been proposed to contribute to these disruptions. A crucial mechanism for these integrative processes is the rhythmic synchronization of neuronal excitability across neural populations; collectively known as oscillations. In ASD there is believed to be a deficit in the ability to efficiently couple functional neural networks using these oscillations. This review discusses evidence for disruptions in oscillatory synchronization in ASD, and how disturbance of this neural mechanism contributes to alterations in sensory and perceptual function. The review also frames oscillatory data from the perspective of prevailing neurobiologically-inspired theories of ASD.

A biologically plausible mechanism for neuronal coding organized by the phase of alpha oscillations

The visual system receives a wealth of sensory information of which only little is relevant for behaviour. We present a mechanism in which alpha oscillations serve to prioritize different components of visual information. By way of simulated neuronal networks, we show that inhibitory modulation in the alpha range (~ 10 Hz) can serve to temporally segment the visual information to prevent information overload. Coupled excitatory and inhibitory neurons generate a gamma rhythm in which information is segmented and sorted according to excitability in each alpha cycle. Further details are coded by distributed neuronal firing patterns within each gamma cycle. The network model produces coupling between alpha phase and gamma (40–100 Hz) amplitude in the simulated local field potential similar to that observed experimentally in human and animal recordings.

Reduced prefrontal MEG alpha-band power in mild traumatic brain injury with associated posttraumatic stress disorder symptoms

OBJECTIVE

To determine if changes in cortical alpha-band power in patients with mild traumatic brain injury (mTBI) are associated with the severity of their post-traumatic stress disorder (PTSD) symptoms, and if injury severity and level of exposure to psychologically traumatic events are predictors of these electrophysiological changes.

METHODS

Resting-state magnetoencephalographic recordings were analyzed in 32 patients with mTBI. Alpha-band power was estimated for each patient in 68 cortical regions and was compared between groups of patients with low versus high PTSD symptoms severity.

RESULTS

Participants with high PTSD symptom severity showed reduced alpha-band power bilaterally in the superior and middle frontal gyri and frontal poles, and in the left inferior frontal gyrus. Alpha-band power in bilateral middle frontal gyri and frontal poles was negatively correlated with scores reflecting symptoms of emotional numbing. Loss of consciousness (LOC) associated with mTBI and level of exposure to psychologically traumatic events were predictors of decreased prefrontal alpha-band power in some of these regions.

CONCLUSION

Altered prefrontal alpha-band activity, shown to be partly explained by mTBI-related LOC, is associated with PTSD symptoms severity.

SIGNIFICANCE

Our findings will guide future studies addressing the electrophysiological mechanisms underlying a higher incidence of PTSD in patients with mTBI.

Supine posture inhibits cortical activity: Evidence from Delta and Alpha EEG bands

Past studies have shown consistent evidence that body position significantly affects brain activity, revealing that both head-down and horizontal bed-rest are associated with cortical inhibition and altered perceptual and cognitive processing. The present study investigates the effects of body position on spontaneous, open-eyes, resting-state EEG cortical activity in 32 young women randomly assigned to one of two conditions, seated position (SP) or horizontal bed rest (BR). A between-group repeated-measure experimental design was used, EEG recordings were made from 38 scalp locations, and low-frequency (delta and alpha) amplitudes of the two groups were compared in four different conditions: when both groups (a) were seated (T0), (b) assumed two different body positions (seated vs. supine conditions, immediate [T1] and 120min later [T2]), and (c) were seated again (T3). Overall, the results showed no a priori between-group differences (T0) before experimental manipulation. As expected, delta amplitude, an index of cortical inhibition in awake resting participants, was significantly increased in group BR, revealing both rapid (T1) and mid-term (T2) inhibitory effects of supine or horizontal positions. Instead, the alpha band was highly sensitive to postural transitions, perhaps due to baroreceptor intervention and, unlike the delta band, underwent habituation and decreased after a 2-h bed rest. These results indicate clear-cut differences at rest between the seated and supine positions, thus supporting the view that the role of body position in the differences found between brain metabolic methods (fMRI and PET) in which participants lie horizontally, and EEG-MEG-TMS techniques with participants in a seated position, has been largely underestimated so far.

The Risk of Sleep Disorder Among Persons with Mild Traumatic Brain Injury

Sleep disorders and mild traumatic brain injury (mTBI) are among the most commonly occurring neurological problems clinicians encounter simultaneously. Each can cause the other, and both share common predisposing factors. An important question that remains to be addressed is whether high-risk groups can be defined. We observed an accumulation of considerable knowledge on sleep dysfunction in mTBI in recently published works. The results highlight sleep disturbances in mTBI as the product of diverse internal and external influences, acting on a genetically determined substrate. This may partially explain the clinical heterogeneity of mTBI, pointing to the importance of establishing an accurate history on the onset and course of a specific sleep disorder in the early stages post-mTBI in the individual patient. Such an approach will aid not only diagnosis and treatment but may also lead to identification of disorders whose symptoms mimic those of TBI and thereby direct the most suitable treatment and management.

The relationship between oscillatory EEG activity and the laminar-specific BOLD signal

Electrophysiological recordings in animals have indicated that visual cortex γ-band oscillatory activity is predominantly observed in superficial cortical layers, whereas α- and β-band activity is stronger in deep layers. These rhythms, as well as the different cortical layers, have also been closely related to feedforward and feedback streams of information. Recently, it has become possible to measure laminar activity in humans with high-resolution functional MRI (fMRI). In this study, we investigated whether these different frequency bands show a differential relation with the laminar-resolved blood-oxygen level-dependent (BOLD) signal by combining data from simultaneously recorded EEG and fMRI from the early visual cortex. Our visual attention paradigm allowed us to investigate how variations in strength over trials and variations in the attention effect over subjects relate to each other in both modalities. We demonstrate that γ-band EEG power correlates positively with the superficial layers' BOLD signal and that β-power is negatively correlated to deep layer BOLD and α-power to both deep and superficial layer BOLD. These results provide a neurophysiological basis for human laminar fMRI and link human EEG and high-resolution fMRI to systems-level neuroscience in animals.

Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation Is State-Dependent

Cortical oscillations play a fundamental role in organizing large-scale functional brain networks. Noninvasive brain stimulation with temporally patterned waveforms such as repetitive transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS) have been proposed to modulate these oscillations. Thus, these stimulation modalities represent promising new approaches for the treatment of psychiatric illnesses in which these oscillations are impaired. However, the mechanism by which periodic brain stimulation alters endogenous oscillation dynamics is debated and appears to depend on brain state. Here, we demonstrate with a static model and a neural oscillator model that recurrent excitation in the thalamo-cortical circuit, together with recruitment of cortico-cortical connections, can explain the enhancement of oscillations by brain stimulation as a function of brain state. We then performed concurrent invasive recording and stimulation of the human cortical surface to elucidate the response of cortical oscillations to periodic stimulation and support the findings from the computational models. We found that (1) stimulation enhanced the targeted oscillation power, (2) this enhancement outlasted stimulation, and (3) the effect of stimulation depended on behavioral state. Together, our results show successful target engagement of oscillations by periodic brain stimulation and highlight the role of nonlinear interaction between endogenous network oscillations and stimulation. These mechanistic insights will contribute to the design of adaptive, more targeted stimulation paradigms.

This study presents mathematical models that explain the effect of temporally patterned electrical stimulation on cortical oscillations and provides supporting evidence using data recorded directly from human cortex during transcranial electrical stimulation.

Rhythms in the brain are believed to play an important role in cognition. Disruptions in these oscillations are associated with a number of neurological and psychiatric disorders. Therefore, noninvasive brain stimulation techniques that target these oscillations offer promise as therapeutic tools. In particular, transcranial alternating current stimulation (tACS) applies a periodic stimulation waveform to engage specific oscillations in the cortex. Although recent studies provide evidence for the modulation of cortical oscillations by tACS, the exact mechanism by which the effects are produced is poorly understood. We propose two mathematical models of interaction between periodic electrical stimulation and ongoing brain activity that may explain the effects of tACS. In addition, we present a unique dataset in which we stimulated the patients’ cortical surface with subdural electrodes and observed the responses to stimulation in neighboring electrodes. We found that stimulation enhanced ongoing oscillations both during and immediately after stimulation. This enhancement depended on the brain state, thereby supporting our proposed models. Our results demonstrate the effect of electrical stimulation on cortical oscillations and highlight the importance of considering the state of the brain when designing electrical stimulation therapies for disorders of the central nervous system.

The phase of pre-stimulus alpha oscillations influences the visual perception of stimulus timing

This study examined the influence of pre-stimulus alpha phase and attention on whether two visual stimuli occurring closely in time were perceived as simultaneous or asynchronous. The results demonstrated that certain phases of alpha in the period immediately preceding stimulus onset were associated with a higher proportion of stimuli judged to be asynchronous. Furthermore, this effect was shown to occur independently of both visuo-spatial attention and alpha amplitude. The findings are compatible with proposals that alpha phase reflects cyclic shifts in neuronal excitability. Importantly, however, the results further suggest that fluctuations in neuronal excitability can create a periodicity in neuronal transfer that can have functional consequences that are decoupled from changes in alpha amplitude. This study therefore provides evidence that perceptual processes fluctuate periodically although it remains uncertain whether this implies the discrete temporal framing of perception.

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Pre-stimulus alpha phase influences the perceived timing of two visual stimuli.

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Phase effects were independent of both spatial attention and alpha amplitude.

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The results are compatible with the neural excitability hypothesis of alpha phase.

Spontaneous Neural Dynamics and Multi-scale Network Organization

Spontaneous neural activity has historically been viewed as task-irrelevant noise that should be controlled for via experimental design, and removed through data analysis. However, electrophysiology and functional MRI studies of spontaneous activity patterns, which have greatly increased in number over the past decade, have revealed a close correspondence between these intrinsic patterns and the structural network architecture of functional brain circuits. In particular, by analyzing the large-scale covariation of spontaneous hemodynamics, researchers are able to reliably identify functional networks in the human brain. Subsequent work has sought to identify the corresponding neural signatures via electrophysiological measurements, as this would elucidate the neural origin of spontaneous hemodynamics and would reveal the temporal dynamics of these processes across slower and faster timescales. Here we survey common approaches to quantifying spontaneous neural activity, reviewing their empirical success, and their correspondence with the findings of neuroimaging. We emphasize invasive electrophysiological measurements, which are amenable to amplitude- and phase-based analyses, and which can report variations in connectivity with high spatiotemporal precision. After summarizing key findings from the human brain, we survey work in animal models that display similar multi-scale properties. We highlight that, across many spatiotemporal scales, the covariance structure of spontaneous neural activity reflects structural properties of neural networks and dynamically tracks their functional repertoire.

Test-retest reliability of resting-state magnetoencephalography power in sensor and source space

Several studies have reported changes in spontaneous brain rhythms that could be used as clinical biomarkers or in the evaluation of neuropsychological and drug treatments in longitudinal studies using magnetoencephalography (MEG). There is an increasing necessity to use these measures in early diagnosis and pathology progression; however, there is a lack of studies addressing how reliable they are. Here, we provide the first test-retest reliability estimate of MEG power in resting-state at sensor and source space. In this study, we recorded 3 sessions of resting-state MEG activity from 24 healthy subjects with an interval of a week between each session. Power values were estimated at sensor and source space with beamforming for classical frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), low beta (13-20 Hz), high beta (20-30 Hz), and gamma (30-45 Hz). Then, test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). We also evaluated the relation between source power and the within-subject variability. In general, ICC of theta, alpha, and low beta power was fairly high (ICC > 0.6) while in delta and gamma power was lower. In source space, fronto-posterior alpha, frontal beta, and medial temporal theta showed the most reliable profiles. Signal-to-noise ratio could be partially responsible for reliability as low signal intensity resulted in high within-subject variability, but also the inherent nature of some brain rhythms in resting-state might be driving these reliability patterns. In conclusion, our results described the reliability of MEG power estimates in each frequency band, which could be considered in disease characterization or clinical trials.

Abnormal cortical sources of resting state electroencephalographic rhythms in single treatment-naïve HIV individuals: A statistical z-score index

OBJECTIVE

This study tested a simple statistical procedure to recognize single treatment-naïve HIV individuals having abnormal cortical sources of resting state delta (<4 Hz) and alpha (8-13 Hz) electroencephalographic (EEG) rhythms with reference to a control group of sex-, age-, and education-matched healthy individuals. Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values were expected to show worse cognitive status.

METHODS

Resting state eyes-closed EEG data were recorded in 82 treatment-naïve HIV (39.8 ys.±1.2 standard error mean, SE) and 59 age-matched cognitively healthy subjects (39 ys.±2.2 SE). Low-resolution brain electromagnetic tomography (LORETA) estimated delta and alpha sources in frontal, central, temporal, parietal, and occipital cortical regions.

RESULTS

Ratio of the activity of parietal delta and high-frequency alpha sources (EEG marker) showed the maximum difference between the healthy and the treatment-naïve HIV group. Z-score of the EEG marker was statistically abnormal in 47.6% of treatment-naïve HIV individuals with reference to the healthy group (p<0.05). Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values exhibited lower mini mental state evaluation (MMSE) score, higher CD4 count, and lower viral load (p<0.05).

CONCLUSIONS

This statistical procedure permitted for the first time to identify single treatment-naïve HIV individuals having abnormal EEG activity.

SIGNIFICANCE

This procedure might enrich the detection and monitoring of effects of HIV on brain function in single treatment-naïve HIV individuals.

Alpha-band EEG activity in perceptual learning

In studies of perceptual learning (PL), subjects are typically highly trained across many sessions to achieve perceptual benefits on the stimuli in those tasks. There is currently significant debate regarding what sources of brain plasticity underlie these PL-based learning improvements. Here we investigate the hypothesis that PL, among other mechanisms, leads to task automaticity, especially in the presence of the trained stimuli. To investigate this hypothesis, we trained participants for eight sessions to find an oriented target in a field of near-oriented distractors and examined alpha-band activity, which modulates with attention to visual stimuli, as a possible measure of automaticity. Alpha-band activity was acquired via electroencephalogram (EEG), before and after training, as participants performed the task with trained and untrained stimuli. Results show that participants underwent significant learning in this task (as assessed by threshold, accuracy, and reaction time improvements) and that alpha power increased during the pre-stimulus period and then underwent greater desynchronization at the time of stimulus presentation following training. However, these changes in alpha-band activity were not specific to the trained stimuli, with similar patterns of posttraining alpha power for trained and untrained stimuli. These data are consistent with the view that participants were more efficient at focusing resources at the time of stimulus presentation and are consistent with a greater automaticity of task performance. These findings have implications for PL, as transfer effects from trained to untrained stimuli may partially depend on differential effort of the individual at the time of stimulus processing.

What works in auditory working memory? A neural oscillations perspective

Working memory is a limited resource: brains can only maintain small amounts of sensory input (memory load) over a brief period of time (memory decay). The dynamics of slow neural oscillations as recorded using magneto- and electroencephalography (M/EEG) provide a window into the neural mechanics of these limitations. Especially oscillations in the alpha range (8-13Hz) are a sensitive marker for memory load. Moreover, according to current models, the resultant working memory load is determined by the relative noise in the neural representation of maintained information. The auditory domain allows memory researchers to apply and test the concept of noise quite literally: Employing degraded stimulus acoustics increases memory load and, at the same time, allows assessing the cognitive resources required to process speech in noise in an ecologically valid and clinically relevant way. The present review first summarizes recent findings on neural oscillations, especially alpha power, and how they reflect memory load and memory decay in auditory working memory. The focus is specifically on memory load resulting from acoustic degradation. These findings are then contrasted with contextual factors that benefit neural as well as behavioral markers of memory performance, by reducing representational noise. We end on discussing the functional role of alpha power in auditory working memory and suggest extensions of the current methodological toolkit. This article is part of a Special Issue entitled SI: Auditory working memory.

Intermediate phenotypes and biomarkers of treatment outcome in major depressive disorder

Major depressive disorder (MDD) is a pleomorphic illness originating from gene x environment interactions. Patients with differing symptom phenotypes receive the same diagnosis and similar treatment recommendations without regard to genomics, brain structure or function, or other physiologic or psychosocial factors. Using this present approach, only one third of patients enter remission with the first medication prescribed, and patients may take longer than 1 year to enter remission with repeated trials. Research to improve treatment effectiveness recently has focused on identification of intermediate phenotypes (IPs) that could parse the heterogeneous population of patients with MDD into subgroups with more homogeneous responses to treatment. Such IPs could be used to develop biomarkers that could be applied clinically to match patients with the treatment that would be most likely to lead to remission. Putative biomarkers include genetic polymorphisms, RNA and protein expression (transcriptome and proteome), neurotransmitter levels (metabolome), additional measures of signaling cascades, oscillatory synchrony, neuronal circuits and neural pathways (connectome), along with other possible physiologic measures. All of these measures represent components of a continuum that extends from proximity to the genome to proximity to the clinical phenotype of depression, and there are many levels along this continuum at which useful IPs may be defined. Because of the highly integrative nature of brain systems and the complex neurobiology of depression, the most useful biomarkers are likely to be those with intermediate proximity both to the genome and the clinical phenotype of MDD. Translation of findings across the spectrum from genotype to phenotype promises to better characterize the complex disruptions in signaling and neuroplasticity that accompany MDD, and ultimately to lead to greater understanding of the causes of depressive illness.