Low-frequency EEG Activity Research Articles

Neural adaptation and fractional dynamics as a window to underlying neural excitability.

The relationship between macroscale electrophysiological recordings and the dynamics of underlying neural activity remains unclear. We have previously shown that low frequency EEG activity (<1 Hz) is decreased at the seizure onset zone (SOZ), while higher frequency activity (1-50 Hz) is increased. These changes result in power spectral densities (PSDs) with flattened slopes near the SOZ, which are assumed to be areas of increased excitability. We wanted to understand possible mechanisms underlying PSD changes in brain regions of increased excitability. We hypothesized that these observations are consistent with changes in adaptation within the neural circuit. We developed a theoretical framework and tested the effect of adaptation mechanisms, such as spike frequency adaptation and synaptic depression, on excitability and PSDs using filter-based neural mass models and conductance-based models. We compared the contribution of single timescale adaptation and multiple timescale adaptation. We found that adaptation with multiple timescales alters the PSDs. Multiple timescales of adaptation can approximate fractional dynamics, a form of calculus related to power laws, history dependence, and non-integer order derivatives. Coupled with input changes, these dynamics changed circuit responses in unexpected ways. Increased input without synaptic depression increases broadband power. However, increased input with synaptic depression may decrease power. The effects of adaptation were most pronounced for low frequency activity (< 1Hz). Increased input combined with a loss of adaptation yielded reduced low frequency activity and increased higher frequency activity, consistent with clinical EEG observations from SOZs. Spike frequency adaptation and synaptic depression, two forms of multiple timescale adaptation, affect low frequency EEG and the slope of PSDs. These neural mechanisms may underlie changes in EEG activity near the SOZ and relate to neural hyperexcitability. Neural adaptation may be evident in macroscale electrophysiological recordings and provide a window to understanding neural circuit excitability.

EEG biomarkers of activation of the lymphatic drainage system of the brain during sleep and opening of the blood-brain barrier

The lymphatic drainage system of the brain (LDSB) is the removal of metabolites and wastes from its tissues. A dysfunction of LDSB is an important sign of aging, brain oncology, the Alzheimer's and Parkinson's diseases. The development of new strategies for diagnosis of LDSB injuries can improve prevention of age-related cerebral amyloid angiopathy, neurodegenerative and cerebrovascular diseases. There are two conditions, such as deep sleep and opening of the blood-brain-barrier (OBBB) associated with the LDSB activation. A promising candidate for measurement of LDSB could be electroencephalography (EEG). In this pilot study on rats, we tested the hypothesis, whether deep sleep and OBBB can be an informative platform for an effective extracting of information about the LDSB functions. Using the nonlinear analysis of EEG dynamics and machine learning technology, we discovered that the LDSB activation during OBBB and sleep is associated with similar changes in the EEG θ-activity. The OBBB causes the higher LDSB activation vs. sleep that is accompanied by specific changes in the low frequency EEG activity extracted by the power spectra analysis of the EEG dynamics combined with the coherence function. Thus, our findings demonstrate a link between neural activity associated with the LDSB activation during sleep and OBBB that is an important informative platform for extraction of the EEG-biomarkers of the LDSB activity. These results open new perspectives for the development of technology for the LDSB diagnostics that would open a novel era in the prognosis of brain diseases caused by the LDSB disorders, including OBBB.

Expectations boost the reconstruction of auditory features from electrophysiological responses to noisy speech.

Online speech processing imposes significant computational demands on the listening brain, the underlying mechanisms of which remain poorly understood. Here, we exploit the perceptual "pop-out" phenomenon (i.e. the dramatic improvement of speech intelligibility after receiving information about speech content) to investigate the neurophysiological effects of prior expectations on degraded speech comprehension. We recorded electroencephalography (EEG) and pupillometry from 21 adults while they rated the clarity of noise-vocoded and sine-wave synthesized sentences. Pop-out was reliably elicited following visual presentation of the corresponding written sentence, but not following incongruent or neutral text. Pop-out was associated with improved reconstruction of the acoustic stimulus envelope from low-frequency EEG activity, implying that improvements in perceptual clarity were mediated via top-down signals that enhanced the quality of cortical speech representations. Spectral analysis further revealed that pop-out was accompanied by a reduction in theta-band power, consistent with predictive coding accounts of acoustic filling-in and incremental sentence processing. Moreover, delta-band power, alpha-band power, and pupil diameter were all increased following the provision of any written sentence information, irrespective of content. Together, these findings reveal distinctive profiles of neurophysiological activity that differentiate the content-specific processes associated with degraded speech comprehension from the context-specific processes invoked under adverse listening conditions.

Towards real-world neuroscience using mobile EEG and augmented reality

Our visual environment impacts multiple aspects of cognition including perception, attention and memory, yet most studies traditionally remove or control the external environment. As a result, we have a limited understanding of neurocognitive processes beyond the controlled lab environment. Here, we aim to study neural processes in real-world environments, while also maintaining a degree of control over perception. To achieve this, we combined mobile EEG (mEEG) and augmented reality (AR), which allows us to place virtual objects into the real world. We validated this AR and mEEG approach using a well-characterised cognitive response—the face inversion effect. Participants viewed upright and inverted faces in three EEG tasks (1) a lab-based computer task, (2) walking through an indoor environment while seeing face photographs, and (3) walking through an indoor environment while seeing virtual faces. We find greater low frequency EEG activity for inverted compared to upright faces in all experimental tasks, demonstrating that cognitively relevant signals can be extracted from mEEG and AR paradigms. This was established in both an epoch-based analysis aligned to face events, and a GLM-based approach that incorporates continuous EEG signals and face perception states. Together, this research helps pave the way to exploring neurocognitive processes in real-world environments while maintaining experimental control using AR.

Disentangling human grasping type from the object's intrinsic properties using low-frequency EEG signals

Grasping movements are known to activate the fronto-parietal brain networks both in human and non-human primates. However, it is unclear if these activations represent properties of the objects or hand postures or both at different stages of the movement. We manipulated the intrinsic properties of the objects and the grasping types in order to create twelve unique combinations of grasping movements and we investigated, in healthy adult humans, the low-frequency time-domain EEG representation of grasping over different stages of the movement. Next, we implemented two multiclass decoders for the grasp type and objects' properties and evaluated them over time. Furthermore, we investigated the similarity between these grasping EEG representations and categorical models that encode properties of the movement and intrinsic properties of the objects. We found that properties of the grasping movement (grasp types, number of fingers) and intrinsic object properties (shape and size) as represented in EEG are encoded in different brain areas throughout the movement stages. Both object properties and grasp types can be decoded significantly above chance level using low-frequency EEG activity during the planning and execution of the movement. Moreover, we found that this preferential time-wise encoding allows the decoding of object properties already from the observation stage, while the grasp type can also be accurately decoded at the object release stage. These findings contribute to the understanding of the grasping representation based on noninvasive EEG brain signals, and its evolution over the course of movement in relation to categorical models that describe the grasped object's properties or that encode properties of the grasping movement. Moreover, our multiclass grasping decoders are informative for the design and implementation of noninvasive motor control strategies.

The relationship between resting electroencephalogram oscillatory abnormalities and schizotypal personality traits in the first-degree relatives of schizophrenia patients.

Although a large amount of studies have manifested resting state electroencephalogram oscillatory abnormalities in schizophrenia and their first-degree relatives and in schizotype, the results are far from consistent and no research found any relationship between electroencephalograph (EEG) abnormalities and schizotypal personality in first-degree relatives. The present study is to verify the modifications of EEG power spectra in eyes-open resting state of schizophrenia and first-degree relatives, and to investigate associations between EEG band power and schizotypal personality traits in first-degree relatives of schizophrenia patients. Participant samples in this study consisted of 33 healthy normal controls, 35 unaffected first-degree relatives of schizophrenia patients and 35 schizophrenia patients. Group differences in resting EEG band power were examined via repeated-measures analysis of variance, and correlation between EEG power and schizotypal personality traits via Pearson Correlation analysis. The results showed that patients with schizophrenia exhibited increased delta, theta and alpha activity over anterior and central regions in eyes-open resting state compared with that of normal control. Gamma band power was found for the first time to be negatively correlated to schizotypal personality traits in first-degree relatives of schizophrenia patients. To conclusion, these findings suggested that low-frequency EEG activity might be neural manifestations of pathophysiological changes in the brain of schizophrenia, and gamma band activity might be an approach to measure the genetic liability of the disorder.

The effects of acute, short-term visual deprivation on low-frequency EEG activity during wakefulness and sleep

The effects of acute, short-term visual deprivation on low-frequency EEG activity during wakefulness and sleep

Evaluation of filtering techniques to extract movement intention information from low-frequency EEG activity.

Low-frequency electroencephalographic (EEG) activity provides relevant information for decoding movement commands in healthy subjects and paralyzed patients. Brainmachine interfaces (BMI) exploiting these signals have been developed to provide closed-loop feedback and induce neuroplasticity. Several offline and online studies have already demonstrated that discriminable information related to movement can be decoded from low-frequency EEG activity. However, there is still not a well-established procedure to guarantee that this activity is optimally filtered from the background noise. This work compares different configurations of non-causal (i.e., offline) and causal (i.e., online) filters to classify movement-related cortical potentials (MRCP) with six healthy subjects during reaching movements. Our results reveal important differences in MRCP decoding accuracy dependent on the selected frequency band for both offline and online approaches. In summary, this paper underlines the importance of optimally choosing filter parameters, since their variable response has an impact on the classification of low EEG frequencies for BMI.

Reduced event-related low frequency EEG activity in patients with early onset schizophrenia and their unaffected siblings

Low-frequency oscillations in the electroencephalogram (EEG) have been found to be abnormal in patients with schizophrenia. It is unclear, however, whether these abnormalities are related to severity of illness or are a marker for risk. This study investigated total and evoked theta and delta activity in schizophrenia patients, unaffected siblings, and healthy controls (HCs). EEG data were recorded whilst 24 individuals with schizophrenia, 26 unaffected siblings of individuals with schizophrenia and 26 healthy control participants completed a Go/No-Go task. Event-related total activity and evoked theta and delta activity were calculated for correct hits (CH), failed inhibitions (FI) and correct inhibitions (CI) trials. Patients displayed significantly less total delta, evoked delta, total theta and evoked theta activity when compared with healthy controls. Unaffected siblings displayed abnormalities of evoked delta, but other measures were similar to those in control participants. The findings of this study add to evidence that abnormal low-frequency EEG oscillations contribute to impairments in information processing seen in schizophrenia. These findings also suggest abnormal evoked delta oscillations are associated with an increased familial risk of developing the disorder.

Altered overnight modulation of spontaneous waking EEG reflects altered sleep homeostasis in major depressive disorder: A high-density EEG investigation

BackgroundPrior investigations have suggested sleep homeostasis is altered in major depressive disorder (MDD). Low frequency activity (LFA) in the electroencephalogram during waking has been correlated with sleep slow wave activity (SWA), suggesting that waking LFA reflects sleep homeostasis in healthy individuals. This study investigated whether the overnight change in waking LFA and its relationship with sleep SWA are altered in MDD. Methods256-channel high-density electroencephalography (hdEEG) recordings during waking (pre- and post-sleep) and during sleep were collected in 14 unmedicated, unipolar MDD subjects (9 women) and age- and sex-matched healthy controls (HC). ResultsWaking LFA (3.25–6.25Hz) declined significantly overnight in the HC group, but not in the group of MDD subjects. Overnight decline of waking LFA correlated with sleep SWA in frontal brain regions in HC, but a comparable relationship was not found in MDD. LimitationsThis study is not able to definitely segregate overnight changes in the waking EEG that may occur due to homeostatic and/or circadian factors. ConclusionsMDD involves altered overnight modulation of waking low frequency EEG activity that may reflect altered sleep homeostasis in the disorder. Future research is required to determine the functional significance and clinical implications of these findings.

Prestimulus delta and theta determinants of ERP responses in the Go/NoGo task

Ongoing low-frequency EEG activity has long been associated with ERP components and their cognitive processing interpretations, yet few studies have directly investigated the prestimulus low-frequency EEG–ERP relationships, particularly within the auditory domain. The present study assessed the delta (1–3Hz) and theta (4–7Hz) bands individually, and their prestimulus influence on five subsequent components (P1, N1, P2, N2, and P3) within an equiprobable auditory Go/NoGo paradigm. At the nine central sites, accepted trials were sorted according to their ascending vertex prestimulus spectral band amplitude, and ERPs were derived from the upper and lower sorted thirds. The within-subjects analyses included amplitudes and latencies for both Go and NoGo responses, and Go response speed. Only component amplitudes showed effects of high/low prestimulus EEG level. Delta globally modulated the five components — all amplitudes were more positive with high prestimulus delta, regardless of stimulus condition. Theta did not influence P1, but inversely modulated P2 and P3 regionally, and produced stimulus-specific effects in N1, N2, and P3. Low prestimulus theta produced greater NoGo N2 and Go P3, and reduced NoGo P3 responses, each of these suggesting appropriately enhanced cognitive processing. Taken together, these effect patterns differentially implicate prestimulus delta and theta band activity in the determination of ERP component amplitudes and the cognitive processing associated with them.

Background Gamma Activity in the Electroencephalogram as a Measure of the Level of Sustained (tonic) Attention during Execution of the “Active Oddball” Paradigm in Rabbits

works in supporting the body’s appropriate responses to sensory stimuli has been demonstrated and analyzed in detail by recording spike activity from single neurons and low-frequency EEG activity in the range 4–10 Hz [3] during the formation and execution of conditioned reflex tasks of different levels of difficulty. Current physiological studies of brain activation, as well as attention and perception, made wide use of recording of the high-frequency component of the EEG spectrum – the gamma rhythm, i.e., oscillations of cortical potentials in the range 30–70 Hz and above [1, 2, 6, 14, 16, 18, 21]. Tonic gamma activity is known to change in accordance with the ongoing state of the subject and the task being executed. In particular, generation of gamma activity increases in the state of attention and/or mental loading. Thus, studies in 1980 showed that increases in the EEG gamma rhythm in cats occurred at the time point at which they paid full attention to their target prey [12]. Similarly, gamma rhythm power in humans increased during cognitive loading as compared with the resting state; gamma activity differed in this way from activity in the beta range – which, conversely, decreased when cognitive loading increased [20]. Existing data indicate that the level of background, i.e., spontaneous, gamma activity and the subject’s response to sensory stimuli are related to each other. For example, psychophysical experiments have shown that correct responses to target stimuli are preceded by a higher background gamma level than missed responses to these stimuli [22]. Expectation of a stimulus and preparation to execute a reaction in response to a stimulus also lead to increases in gamma activity [2, 18]. On the other hand, episodes of significant increases and synchronization of the gamma rhythm to above the baseline level are accompanied by the so-called inattention blindness, in which responses to sensory stimuli are blocked [15]. Neuroscience and Behavioral Physiology, Vol. 42, No. 6, July, 2012

Eating breakfast enhances the efficiency of neural networks engaged during mental arithmetic in school-aged children

To determine the influence of a morning meal on complex mental functions in children (8–11y), time–frequency analyses were applied to electroencephalographic (EEG) activity recorded while children solved simple addition problems after an overnight fast and again after having either eaten or skipped breakfast. Power of low frequency EEG activity [2Hertz (Hz) bands in the 2–12Hz range] was determined from recordings over frontal and parietal brain regions associated with mathematical thinking during mental calculation of correctly answered problems. Analyses were adjusted for background variables known to influence or reflect the development of mathematical skills, i.e., age and measures of math competence and math fluency. Relative to fed children, those who continued to fast showed greater power increases in upper theta (6–8Hz) and both alpha bands (8–10Hz; 10–12Hz) across sites. Increased theta suggests greater demands on working memory. Increased alpha may facilitate task-essential activity by suppressing non-task-essential activity. Fasting children also had greater delta (2–4Hz) and greater lower-theta (4–6Hz) power in left frontal recordings—indicating a region-specific emphasis on both working memory for mental calculation (theta) and activation of processes that suppress interfering activity (delta). Fed children also showed a significant increase in correct responses while children who continued to fast did not. Taken together the findings suggest that neural network activity involved in processing numerical information is functionally enhanced and performance is improved in children who have eaten breakfast, whereas greater mental effort is required for this mathematical thinking in children who skip breakfast.

Higher frontal EEG synchronization in young women with major depression: a marker for increased homeostatic sleep pressure?

Major depressive disorder (MDD) is often associated with disturbances in circadian and/or sleep-wake dependent processes, which both regulate daytime energy and sleepiness levels. Analysis of continuous electroencephalographic (EEG) recordings during 40 h of extended wakefulness under constant routine conditions. Artifact-free EEG samples derived from 12 locations were subjected to spectral analysis. Additionally, half-hourly ratings of subjective tension and sleepiness levels and salivary melatonin measurements were collected. Centre for Chronobiology, Psychiatric Hospitals of the University of Basel, Switzerland. Eight young healthy women and 8 young untreated women with MDD. N/A. MDD women exhibited higher frontal low-frequency (FLA) EEG activity (0.5-5.0 Hz) during extended wakefulness than controls, particularly during the night. Enhanced FLA was paralleled by higher levels of subjective sleepiness and tension. In MDD women, overall FLA levels correlated positively with depression scores. The timing of melatonin onset did not significantly differ between the two groups, but the nocturnal secretion of salivary melatonin was significantly attenuated in MDD women. Our data imply that young women with MDD live on a higher homeostatic sleep pressure level, as indexed by enhanced FLA during wakefulness. Its positive correlation with depression scores indicates a possible functional relationship. High FLA could reflect a use-dependent phenomenon in depression (enhanced cognitive rumination or tension) and/or an attenuated circadian arousal signal.

Diet and gender are important factors modulating low frequency EEG activity during processing of language sounds in 3 month old infants

Diet and gender are important factors modulating low frequency EEG activity during processing of language sounds in 3 month old infants

Does Greater Low Frequency EEG Activity in Normal Immaturity and in Children with Epilepsy Arise in the Same Neuronal Network?

Greater low frequency power (<8 Hz) in the electroencephalogram (EEG) at rest is normal in the immature developing brain of children when compared to adults. Children with epilepsy also have greater low frequency interictal resting EEG activity. Whether these power elevations reflect brain immaturity due to a developmental lag or the underlying epileptic pathophysiology is unclear. The present study addresses this question by analyzing spectral EEG topographies and sources for normally developing children and children with epilepsy. We first compared the resting EEG of healthy children to that of healthy adults to isolate effects related to normal brain immaturity. Next, we compared the EEG from 10 children with generalized cryptogenic epilepsy to the EEG of 24 healthy children to isolate effects related to epilepsy. Spectral analysis revealed that global low (delta: 1-3 Hz, theta: 4-7 Hz), medium (alpha: 8-12 Hz) and high (beta: 13-25 Hz) frequency EEG activity was greater in children without epilepsy compared to adults, and even further elevated for children with epilepsy. Topographical and tomographic EEG analyses showed that normal immaturity corresponded to greater delta and theta activity at fronto-central scalp and brain regions, respectively. In contrast, the epilepsy-related activity elevations were predominantly in the alpha band at parieto-occipital electrodes and brain regions, respectively. We conclude that lower frequency activity can be a sign of normal brain immaturity or brain pathology depending on the specific topography and frequency of the oscillating neuronal network.

Baroreflexes of the rat. VI. Sleep and responses to aortic nerve stimulation in the dmNTS

The sensitivity of the baroreflex determines its stability and effectiveness in controlling blood pressure (BP). Sleep and arousal are reported to affect baroreflex sensitivity, but the findings are not consistent across studies. After statistically correcting the effect of sleep on the baselines in chronically neuromuscular-blocked (NMB) rats, we found that sleep affects BP and heart period (HP) baroreflex gain similarly. This finding is consistent with baroreflex modulation of HP and BP before divergence of the sympathetic and parasympathetic pathways. Therefore, we hypothesized that the gain modulation occurs in the dorsal medial nucleus of the solitary tract (dmNTS). The present study used long-term dmNTS recordings in NMB rats and single-pulse aortic depressor nerve stimulation. Under these conditions, the magnitude of A-fiber evoked responses (ERs), recorded from second- or higher-order dmNTS baroreflex neurons, was reliably augmented during high-amplitude low-frequency EEG activity (slow-wave sleep) and reduced during low-amplitude high-frequency EEG activity (arousal; DeltaER = 11%, t = 9.49, P < 0.001, degrees of freedom = 1,016). This result has methodological implications for techniques that use changes in HP to estimate baroreflex BP gain and general implications for understanding the relationship between sleep and cardiovascular control.

Reduced event‐related low frequency EEG activity in schizophrenia during an auditory oddball task

This study examines EEG low frequency characteristics which have been linked to specific cognitive functions such as stimulus encoding and attention during an auditory oddball task in schizophrenia patients and healthy controls. EEG data was recorded from 17 young schizophrenia patients in a stable phase of their illness and 17 healthy controls performing an auditory oddball task. Evoked and induced delta and theta activity, N100, P300 amplitude were computed. Between 200-500 ms after a stimulus was presented, patients displayed significantly reduced P300, less evoked and induced delta and theta activity than controls. We conclude that the well known finding of P300 reduction in schizophrenia can be linked to reductions in delta and theta activity, which are a manifestation of impaired stimulus evaluation, memory retrieval, and a lack of sustained attention.

EEG Spectral Analysis in Primary Insomnia: NREM Period Effects and Sex Differences

To compare NREM EEG power in primary insomnia (PI) and good sleeper controls (GSC), examining both sex and NREM period effects; to examine relationships between EEG power, clinical characteristics, and self-reports of sleep. Overnight polysomnographic study. Sleep laboratory. PI (n=48; 29 women) and GSC (n=25; 15 women). None. EEG power from 1-50 Hz was computed for artifact-free sleep epochs across four NREM periods. Repeated measures mixed effect models contrasted differences between groups, EEG frequency bands, and NREM periods. EEG power-frequency curves were modeled using regressions with fixed knot splines. Mixed models showed no significant group (PI vs. GSC) differences; marginal sex differences (delta and theta bands); significant differences across NREM periods; and group*sex and group*NREM period interactions, particularly in beta and gamma bands. Modeled power-frequency curves showed no group difference in whole-night NREM, but PI had higher power than GSC from 18-40 Hz in the first NREM period. Among women, PI had higher 16 to 44-Hz power than GSC in the first 3 NREM periods, and higher 3 to 5-Hz power across all NREM periods. PI and GSC men showed no consistent differences in EEG power. High-frequency EEG power was not related to clinical or subjective sleep ratings in PI. Women with PI, but not men, showed increased high-frequency and low-frequency EEG activity during NREM sleep compared to GSC, particularly in early NREM periods. Sex and NREM period may moderate quantitative EEG differences between PI and GSC.

Genetic and Disorder-Specific Aspects of Resting State EEG Abnormalities in Schizophrenia

We evaluated whether abnormal frequency composition of the resting state electroencephalogram (EEG) in schizophrenia was associated with genetic liability for the disorder by studying first-degree biological relatives of schizophrenia patients. The study included a data-driven method for defining EEG frequency components and determined the specificity of resting state EEG frequency abnormalities by assessing schizophrenia patients, bipolar disorder patients, and relatives of both patient groups. Schizophrenia patients and their relatives, but not bipolar patients or their relatives, exhibited increased high-frequency activity (beta) providing evidence for disturbances in resting state brain activity being specific to genetic liability for schizophrenia. Schizophrenia patients exhibited augmented low-frequency EEG activity (delta, theta), while bipolar disorder patients and the 2 groups of relatives generally failed to manifest similar low-frequency EEG abnormalities. The Val(158)Met polymorphism for the catechol-O-methyl transferase (COMT) gene was most strongly associated with delta and theta activity in schizophrenia patients. Met homozygote schizophrenia patients exhibited augmented activity for the 2 low-frequency bands compared with control subjects. Excessive high-frequency EEG activity over frontal brain regions may serve as an endophenotype that reflects cortical expression of genetic vulnerability for schizophrenia. Low-frequency resting state EEG anomalies in schizophrenia may relate to disorder-specific pathophysiology in schizophrenia and the influence of the COMT gene on tonic dopamanergic function.