Low-frequency Brain Oscillations Research Articles

Potentiation of the depressant effect of alcohol by flunitrazepam in rats: an electrocorticographic, respiratory and electrocardiographic study.

Alcohol, a widely commercialized psychotropic drug, and the benzodiazepine Flunitrazepam, an anxiolytic widely prescribed for patients with anxiety and insomnia problems, are well known drugs and both act on the central nervous system. The misuse and the association of these two drugs are public health concerns in several countries and could cause momentary, long-lasting and even lethal neurophysiological problems due to the potentiation of their adverse effects in synergy. The present study observed the result of the association of these drugs on electrophysiological responses in the brain, heart, and respiratory rate in Wistar rats. 8 experimental groups were determined: control, one alcohol group (20% at a dose of 1ml/100g VO), three Flunitrazepam groups (doses 0.1; 0.2 and 0.3mg/kg) and three alcohol-Flunitrazepam groups (20% at a dose of 1ml/100g VO of alcohol, combined with 0.1; 0.2 and 0.3mg/kg of Flunitrazepam, respectively). The results showed that there was a more pronounced reduction in alpha and theta wave power in the alcohol-Flunitrazepam groups, a decrease in the power of beta oscillations and greater sedation. There was a progressive decrease in respiratory rate linked to the increase of Flunitrazepam dose in the alcohol-Flunitrazepam associated administration. It was observed alteration in heart rate and Q-T interval in high doses of Flunitrazepam. Therefore, we conclude that the association alcohol-Flunitrazepam presented deepening of depressant synergistic effects according to the increase in the dose of the benzodiazepine, and this could cause alterations in low frequency brain oscillations, breathing, and hemodynamics of the patient.

Decline in white matter volume and EEG delta oscillations in mild cognitive impairment

AbstractBackgroundChanges in white matter (WM) may be associated with progression and risk of Alzheimer’s disease (AD) (Nasrabady et. al, 2018) along with conversion to Mild Cognitive Impairment (MCI) (Smith et. al, 2008). Total WM volume and its relation with EROs in MCI remain unclear. As a general notion, greater delta EROs occurring in the post‐stimulus time‐period indicate better cognitive responses in contrary to dynamics of resting state EEG. Surgical WM disruptions are associated with alterations more prominently in low frequency brain oscillations (EROs) (Hawasli et al, 2016). The current study aims to investigate WM volumes and EROs in cognitively unimpaired individuals (CU) and MCI.MethodSixteen individuals with MCI were compared with demographically matched 16 CU using EROs elicited by a visual classical‐oddball paradigm along with WM volumes obtained 3D T1‐weighted TFE‐sequence. WM volumes analyzed with univariate ANOVA. Repeated measures ANOVAs conducted for delta(0.5‐3.5Hz), theta(4‐7Hz), alpha(8‐13Hz), beta(15‐30Hz), and gamma(30‐48Hz) amplitudes. Binary logistic regression analyses conducted for significant WM volume variables and EROs. Correlations between WM and EROs were analyzed with Person correlation coefficient.ResultDelta ERO amplitudes were diminished [F(5,145) = 3.373,p = .035] in MCI at frontal (p = .011), central (p = .014) and parietal (p = .006) electrode locations. Furthermore, WM in right middle orbitofrontal [F(1,29) = 4.599,p = .041], left inferior temporal [F(1,29) = 4.198,p = .049] and left parahippocampal gyrus [F(51,29) = 5.182,p = .030] demonstrated less volume in MCI compared to CU. Binary logistic regression indicated that [X2(9) = 26.615,p = .002] combined WM volumes and delta EROs can classify MCI and CU with 87.1% accuracy. There were positive correlations between occipital delta and left (r = .501, p = .003) and right gyrus rectus (r = .374, p = .003) WM volumes.ConclusionThis study showed WM volumes and delta EROs were reduced in MCI. Decreased amplitudes of delta EROs seem to reflect volume loss of WM in MCI, possibly indicating an underlying demyelination or axonal loss. Delta EROs and WM changes may be helpful tools to monitor MCI focusing on axons and myelination/oligodendrocytes. Furthermore, their combined measurements can classify MCI from healthy individuals sufficiently.

Low-Frequency Oscillations for Nonlocal Neuronal Coupling in Shared Intentionality Before and After Birth: Toward the Origin of Perception

The theoretical study observes literature to understand whether or not low-frequency oscillations can simultaneously alter the excitability of neurons from peripheral nervous subsystems in different individuals to provide Shared Intentionality in recipients (e.g., fetuses and newborns) and what are the attributes of ecological context for Shared Intentionality. To grasp the perception of objects during environmental learning at the onset of cognition, a fetus needs exogenous factors that could stimulate her nervous system to choose the relevant sensory stimulus. Low-frequency brain oscillations can cause the nonlocal coupling of neurons in peripheral and central nervous subsystems that provide subliminal perception. An external low-frequency oscillator and the proximity of individuals can stimulate the coordination of their heart rates and modulate neuronal excitability. External low-frequency oscillations can increase the cognitive performance of the subjects. The characteristics of this pulsed low-frequency field are oscillations with 400 and 700 nm wavelengths alternately with the pulsed frequency ranging from 1 to 1.6 Hz. This theoretical work contributes to knowledge about nonlocal neuronal coupling in different organisms that can appear due to low-frequency oscillations. The significance of the article is that it explains the neurophysiological processes occurring during Shared Intentionality - one of the central issues in understanding the cognitive development of young children, as the conventional view in cognitive sciences argues. The article's impact is a proposal of the universal mechanism of nonlocal neuronal coupling in shaping the embryonal nervous system in animals of all species, which opens new directions for research on the origin of perception of objects.

Shared Intentionality Modulation at the Cell Level: Low-Frequency Oscillations for Temporal Coordination in Bioengineering Systems

The theoretical article aims to develop knowledge about the modulation of shared intentionality at the cellular level. A hypothesis about the neurobiological processes during shared intentionality argues that this pre-perceptual communication occurs through nonlocal neuronal coupling in an ecosystem that can be described as the mother-fetus communication model. The current theoretical study analyses literature to discuss recent findings on the effect of oscillations on neuronal temporal coordination to verify whether external low-frequency oscillations can only synchronize specific local neuronal networks from peripheral and central nervous subsystems for modulating shared intentionality. The review discusses 4 findings. First, gamma oscillations are associated with the temporal coordination of local ensembles of cells. Second, there is a relationship between low-frequency brain oscillations and the temporal coordination of peripheral and central nervous subsystems. Third, delta oscillations influence neuronal activity by modulating gamma activity. Fourth, external delta and gamma oscillations increase cortical excitability. The article concludes that delta oscillations can modulate gamma oscillations in the different subsystems of the nervous system, providing temporal network coordination. An external low-frequency oscillator can coordinate only relevant local neuronal networks in various subsystems already exhibiting gamma activity.

P-18 Low-frequency brain oscillations in human motor control

P-18 Low-frequency brain oscillations in human motor control

Low Frequency Brain Oscillations during the execution and imagination of simple hand movements for Brain-Computer Interface applications.

Low Frequency Brain Oscillations (LFOs) are brief periods of oscillatory activity in delta and lower theta band that appear at motor cortical areas before and around movement onset. It has been shown that LFO power decreases in post-stroke patients and re-emerges with motor functional recovery. To date, LFOs have not yet been explored during the motor execution (ME) and imagination (MI) of simple hand movements, often used in BCI-supported motor rehabilitation protocols post-stroke. This study aims at analyzing the LFOs during the ME and MI of the finger extension task in a sample of 10 healthy subjects and 2 stroke patients in subacute phase. The results showed that LFO power peaks occur in the preparatory phase of both ME and MI tasks on the sensorimotor channels in healthy subjects and their alterations in stroke patients. Clinical Relevance- Results suggest that LFOs could be explored as biomarker of the motor function recovery in rehabilitative protocols based on the movement imagination.

Multivariate analysis of speech envelope tracking reveals coupling beyond auditory cortex

The systematic alignment of low-frequency brain oscillations with the acoustic speech envelope signal is well established and has been proposed to be crucial for actively perceiving speech. Previous studies investigating speech-brain coupling in source space are restricted to univariate pairwise approaches between brain and speech signals, and therefore speech tracking information in frequency-specific communication channels might be lacking. To address this, we propose a novel multivariate framework for estimating speech-brain coupling where neural variability from source-derived activity is taken into account along with the rate of envelope's amplitude change (derivative). We applied it in magnetoencephalographic (MEG) recordings while human participants (male and female) listened to one hour of continuous naturalistic speech, showing that a multivariate approach outperforms the corresponding univariate method in low- and high frequencies across frontal, motor, and temporal areas. Systematic comparisons revealed that the gain in low frequencies (0.6 - 0.8 Hz) was related to the envelope's rate of change whereas in higher frequencies (from 0.8 to 10 Hz) it was mostly related to the increased neural variability from source-derived cortical areas. Furthermore, following a non-negative matrix factorization approach we found distinct speech-brain components across time and cortical space related to speech processing. We confirm that speech envelope tracking operates mainly in two timescales (δ and θ frequency bands) and we extend those findings showing shorter coupling delays in auditory-related components and longer delays in higher-association frontal and motor components, indicating temporal differences of speech tracking and providing implications for hierarchical stimulus-driven speech processing.

Spontaneous alpha-band amplitude predicts subjective visibility but not discrimination accuracy during high-level perception

Near-threshold perception is a paradigm case of awareness diverging from reality – the perception of an unchanging stimulus can vacillate from undetected to clearly perceived. The amplitude of low-frequency brain oscillations - particularly in the alpha-band (8–13 Hz) - has emerged as a reliable predictor of trial-to-trial variability in perceptual decisions based on simple, low-level stimuli. Here, we addressed the question of how spontaneous oscillatory amplitude impacts subjective and objective aspects of perception using high-level visual stimuli. Human observers completed a near-threshold face/house discrimination task with subjective visibility ratings while electroencephalograms (EEG) were recorded. Using single-trial multiple regression analysis, we found that spontaneous fluctuations in prestimulus alpha-band amplitude were negatively related to visibility judgments but did not predict trial-by-trial accuracy. These results extend previous findings that indicate that strong prestimulus alpha diminishes subjective perception without affecting the accuracy or sensitivity (d’) of perceptual decisions into the domain of high-level perception.

Lack of an association between anticipatory alpha oscillations and attentional selection in children with attention-deficit/hyperactivity disorder

ObjectiveAttention-deficit/hyperactivity disorder (ADHD) is characterized by attention problems. The current study investigated whether and how anticipatory alpha oscillations, the subsequent target-elicited N2 posterior-contralateral component (N2pc) and their relationship contributed to attention problems in children with ADHD. MethodsElectroencephalograms (EEGs) were recorded from 8−13-year-old children with ADHD and typically developing children during a cued visuospatial covert attention task. ResultsChildren with ADHD could not sustain hemispheric alpha lateralization during the late stage of the cued period. Similar to the pattern of adults, high-accuracy typically developing children showed a strong positive correlation between the degree of cue-induced anticipatory alpha lateralization and the subsequent target-evoked N2pc amplitude, the latter of which further predicted behavioral performance. However, only the aberrant “cue alpha-target N2pc” temporal relationship was related to symptom severity and behavioral performance in children with ADHD. ConclusionsWe showed that the temporal association of “cue alpha-target N2pc” was already present in some typically developing children. However, children with ADHD might need more time to develop this temporal association. SignificanceOur results provide neurophysiological evidence that the developmental origin of covert spatial attention is related to the temporal association between low-frequency brain oscillations and event-related potentials (ERPs).

The frequency-dependent effect of electrical fields on the mobility of intracellular vesicles in astrocytes

Slow-wave sleep, defined by low frequency (<4 Hz) electrical brain activity, is a basic brain function affecting metabolite clearance and memory consolidation. The origin of low-frequency activity is related to cortical up and down states, but the underlying cellular mechanism of how low-frequency activities affect metabolite clearance and memory consolidation has remained elusive. We applied electrical stimulation with voltages comparable to in vivo sleep recordings over a range of frequencies to cultured glial astrocytes while monitored the trafficking of GFP-tagged intracellular vesicles using total internal reflection fluorescence microscopy (TIRFM). We found that during low frequency (2 Hz) electrical stimulation the mobility of intracellular vesicle increased more than 20%, but remained unchanged under intermediate (20 Hz) or higher (200 Hz) frequency stimulation. We demonstrated a frequency-dependent effect of electrical stimulation on the mobility of astrocytic intracellular vesicles. We suggest a novel mechanism of brain modulation that electrical signals in the lower range frequencies embedded in brainwaves modulate the functionality of astrocytes for brain homeostasis and memory consolidation. The finding suggests a physiological mechanism whereby endogenous low-frequency brain oscillations enhance astrocytic function that may underlie some of the benefits of slow-wave sleep and highlights possible medical device approach for treating neurological diseases.

Low-Frequency Brain Oscillations Track Motor Recovery in Human Stroke.

The majority of patients with stroke survive the acute episode and live with enduring disability. Effective therapies to support recovery of motor function after stroke are yet to be developed. Key to this development is the identification of neurophysiologic signals that mark recovery and are suitable and susceptible to interventional therapies. Movement preparatory low-frequency oscillations (LFOs) play a key role in cortical control of movement. Recent animal data point to a mechanistic role of motor cortical LFOs in stroke motor deficits and demonstrate neuromodulation intervention with therapeutic benefit. Their relevance in human stroke pathophysiology is unknown. We studied the relationship between movement-preparatory LFOs during the performance of a visuomotor grip task and motor function in a longitudinal (<5 days, 1 and 3 months) cohort study of 33 patients with motor stroke and in 19 healthy volunteers. Acute stroke-lesioned brains fail to generate the LFO signal. Whereas in healthy humans, a transient occurrence of LFOs preceded movement onset at predominantly contralateral frontoparietal motor regions, recordings in patients revealed that movement-preparatory LFOs were substantially diminished to a level of 38% after acute stroke. LFOs progressively increased at 1 and 3 months. This re-emergence closely tracked the recovery of motor function across several movement qualities including grip strength, fine motor skills, and synergies and was frequency band specific. Our results provide the first human evidence for a link between movement-preparatory LFOs and functional recovery after stroke, promoting their relevance for movement control. These results suggest that it may be interesting to explore targeted, LFOs-restorative brain stimulation therapy in human stroke patients. ANN NEUROL 2019;86:853-865.

Plasticity in the dynamic pain connectome associated with ketamine-induced neuropathic pain relief.

Therapeutic interventions for neuropathic pain, such as the N-methyl-D-aspartate (NMDA) antagonist ketamine, can vary widely in effectiveness. In this study, we conducted a longitudinal functional MRI study to test the hypothesis that the pain-relieving effect of ketamine is the result of reversal of abnormalities in regional low-frequency brain oscillations (LFOs) and abnormal cross-network functional connectivity (FC) of the dynamic pain connectome. We found that (1) ketamine decreased regional LFOs in the posterior cingulate cortex of the default mode network, (2) a machine-learning algorithm demonstrated that treatment-induced brain changes could be used to make generalizable inferences about pain relief, (3) treatment responders exhibited a significant decrease in cross-network static FC between the posterior cingulate cortex and regions of the sensorimotor and salience networks following treatment, (4) the degree of reduced cross-network FC correlated with the amount of pain relief, and (5) ketamine treatment did not produce significant differences in static or dynamic FC within the ascending nociceptive or descending antinociceptive pathway. These findings support the proposition that regional LFOs contribute to cross-network connectivity that underlie the effectiveness of ketamine to produce significant relief from neuropathic pain. Together with our recent findings that pretreatment dynamic FC of the descending antinociceptive pathway can predict ketamine treatment outcomes, these new findings indicate that pain relief from ketamine arises from a combination of flexible pretreatment FC of the descending antinocieptive pathway together with plasticity (reduction) of cross-network connectivity of the default mode network with sensorimotor and salience networks.

Cross-Frequency Coupling Based Neuromodulation for Treating Neurological Disorders.

Synchronous, rhythmic changes in the membrane polarization of neurons form oscillations in local field potentials. It is hypothesized that high-frequency brain oscillations reflect local cortical information processing, and low-frequency brain oscillations project information flow across larger cortical networks. This provides complex forms of information transmission due to interactions between oscillations at different frequency bands, which can be rendered with cross-frequency coupling (CFC) metrics. Phase-amplitude coupling (PAC) is one of the most common representations of the CFC. PAC reflects the coupling of the phase of oscillations in a specific frequency band to the amplitude of oscillations in another frequency band. In a normal brain, PAC accompanies multi-item working memory in the hippocampus, and changes in PAC have been associated with diseases such as schizophrenia, obsessive-compulsive disorder (OCD), Alzheimer disease (AD), epilepsy, and Parkinson’s disease (PD). The purpose of this article is to explore CFC across the central nervous system and demonstrate its correlation to neurological disorders. Results from previously published studies are reviewed to explore the significant role of CFC in large neuronal network communication and its abnormal behavior in neurological disease. Specifically, the association of effective treatment in PD such as dopaminergic medication and deep brain stimulation with PAC changes is described. Lastly, CFC analysis of the electrocorticographic (ECoG) signals recorded from the motor cortex of a Parkinson’s disease patient and the parahippocampal gyrus of an epilepsy patient are demonstrated. This information taken together illuminates possible roles of CFC in the nervous system and its potential as a therapeutic target in disease states. This will require new neural interface technologies such as phase-dependent stimulation triggered by PAC changes, for the accurate recording, monitoring, and modulation of the CFC signal.

Lip movements entrain the observers' low-frequency brain oscillations to facilitate speech intelligibility.

During continuous speech, lip movements provide visual temporal signals that facilitate speech processing. Here, using MEG we directly investigated how these visual signals interact with rhythmic brain activity in participants listening to and seeing the speaker. First, we investigated coherence between oscillatory brain activity and speaker's lip movements and demonstrated significant entrainment in visual cortex. We then used partial coherence to remove contributions of the coherent auditory speech signal from the lip-brain coherence. Comparing this synchronization between different attention conditions revealed that attending visual speech enhances the coherence between activity in visual cortex and the speaker's lips. Further, we identified a significant partial coherence between left motor cortex and lip movements and this partial coherence directly predicted comprehension accuracy. Our results emphasize the importance of visually entrained and attention-modulated rhythmic brain activity for the enhancement of audiovisual speech processing.

Reduced Amplitude of Low-Frequency Brain Oscillations in the Psychosis Risk Syndrome and Early Illness Schizophrenia.

Low-frequency oscillations (LFOs) of the blood oxygen level-dependent (BOLD) signal are gaining interest as potential biomarkers sensitive to neuropsychiatric pathology. Schizophrenia has been associated with alterations in intrinsic LFOs that covary with cognitive deficits and symptoms. However, the extent to which LFO dysfunction is present before schizophrenia illness onset remains unknown. Resting-state FMRI data were collected from clinical high-risk (CHR; n=45) youth, early illness schizophrenia (ESZ; n=74) patients, and healthy controls (HCs; n=85) aged 12-35 years. Age-adjusted voxelwise fractional amplitude of low-frequency fluctuations (fALFF; 0.01-0.08 Hz) of the BOLD signal was compared among the three groups. Main effects of Group (p<0.005 height threshold, familywise error cluster-level corrected p<0.05) were followed up via Tukey-corrected pairwise comparisons. Significant main effects of Group (p<0.05) revealed decreased fALFF in ESZ and CHR groups relative to HCs, with values in the CHR group falling between those of ESZ and HC groups. These differences were identified primarily in posterior cortex, including temporoparietal regions, extending into occipital and cerebellar lobes. Less LFO activity was related to greater symptom severity in both CHR and ESZ groups in several of these posterior cortical regions. These data support an intermediate phenotype of reduced posterior cortical LFO amplitude in CHR individuals, with resting fALFF values smaller than in HCs but higher than in ESZ patients. Findings indicate that LFO magnitude alterations relate to clinical symptoms and predate psychosis onset but are more pronounced in the early stages of schizophrenia.

Low-Frequency Brain Oscillations in Schizophrenia.

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Recurrent networks expect

How the brain anticipates future events is one of the most intriguing questions in neural information processing. The brain does not simply respond to the external world but in predictably structured environments like natural language, birdsong and somatosensory flow in fluids predicts it [1]. Reactions are improved by predictive encoding of what sensory stimuli may occur as well as when they may occur. Quantitative studies of implicit timing in streaming perceptual discrimination tasks show that performance is enhanced if stimuli occur at expected times according to an established rhythm. The neural basis for implicit timing is not fully understood but oscillatory entrainment mechanisms have been suggested [2]. Recent studies confirm that low-frequency brain oscillations do become phase entrained in such tasks. Phase entrainment increases with the temporal regularity of the sensory stream and correlates with enhanced discrimination performance [3]. It is not limited to sensory cortices; larger scale cortical networks, as well as subcortical networks like the basal ganglia [4], may also be coherently modulated by the predictability of stimuli streams. The presence of large scale oscillatory entrainment suggests that network mediated neuronal ensemble dynamics may be involved. Recurrent neural networks generate complex but reproducible temporally extended dynamical activity patterns in response to input stimuli [5,6]. Such transient activity patterns have been suggested to provide a natural substrate for working memory and a representation of elapsed time. Here we add to the understanding of how random recurrent neural networks support neural information processing by demonstrating that temporal expectation also naturally emerges from their dynamics. We show that the weakly chaotic oscillations generated by recurrent networks can be phase synchronized [7] by temporally regular stimulus sequences. We show network responses are maximally discriminative when stimuli fall at their preferred phase in phase entrained networks (Figure ​(Figure1).1). Discriminability increases continuously with both temporal regularity and stimulus type predictability which also interact. Our results do not depend on specific network characteristics, are resilient to the presence of network noise and random distractor stimuli and are consistent with multiple streaming perceptual discrimination studies. Figure 1 Excess correct classification probability of on-time target stimuli compared to mistimed target stimuli (100 ms early, black ; 100 ms late, red) in a temporally regular streaming task with inter-trial-interval 800 ms. Results are plotted versus the Lyapunov ...

Frontal Top-Down Signals Increase Coupling of Auditory Low-Frequency Oscillations to Continuous Speech in Human Listeners

SummaryHumans show a remarkable ability to understand continuous speech even under adverse listening conditions. This ability critically relies on dynamically updated predictions of incoming sensory information, but exactly how top-down predictions improve speech processing is still unclear. Brain oscillations are a likely mechanism for these top-down predictions [1, 2]. Quasi-rhythmic components in speech are known to entrain low-frequency oscillations in auditory areas [3, 4], and this entrainment increases with intelligibility [5]. We hypothesize that top-down signals from frontal brain areas causally modulate the phase of brain oscillations in auditory cortex. We use magnetoencephalography (MEG) to monitor brain oscillations in 22 participants during continuous speech perception. We characterize prominent spectral components of speech-brain coupling in auditory cortex and use causal connectivity analysis (transfer entropy) to identify the top-down signals driving this coupling more strongly during intelligible speech than during unintelligible speech. We report three main findings. First, frontal and motor cortices significantly modulate the phase of speech-coupled low-frequency oscillations in auditory cortex, and this effect depends on intelligibility of speech. Second, top-down signals are significantly stronger for left auditory cortex than for right auditory cortex. Third, speech-auditory cortex coupling is enhanced as a function of stronger top-down signals. Together, our results suggest that low-frequency brain oscillations play a role in implementing predictive top-down control during continuous speech perception and that top-down control is largely directed at left auditory cortex. This suggests a close relationship between (left-lateralized) speech production areas and the implementation of top-down control in continuous speech perception.

The Attenuation of Very Low Frequency Brain Oscillations in Transitions from a Rest State to Active Attention

Background: The default mode interference hypothesis ( Sonuga-Barke &amp; Castellanos, 2007 ) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008 ). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals.