Rhythmic Brain Activity Research Articles

The posterior hypothalamic area as an independent generator of rhythmic theta oscillatory activity

Theta rhythm is one of the most prominent examples of rhythmic oscillatory activity in mammalian brain and it is generated mainly in structures of the limbic cortex, including the hippocampal formation. In the 1970s it was shown that theta rhythm may be also recorded in diencephalic region including the posterior hypothalamic nuclei and supramammillary nucleus, together considered as the posterior hypothalamic area (PHa). For decades it was stated that local posterior hypothalamic oscillatory activity is controlled by the descending inputs going to the PHa from the septohippocampal system. However, the latest studies indicated that theta rhythm can be recorded in deafferented PHa in vitro preparations which indicates that the posterior hypothalamic area should be considered as an independent of the other brain structures theta generator. In subsequent research the neurochemical and cellular basis of PHa theta were examined in both in vivo and in vitro conditions. In the light of multiple evidence obtained in these studies, it is the author’s intent to summarize the data concerning the role of the posterior hypothalamic area in hippocampal theta rhythm generation as well as the ability of that brain structure to independently generate theta rhythmicity.

Weak signal detection capacity of type-II Morris–Lecar neuron system under presynaptic bombardments

The information encoding mechanism of the neuronal system is quite complex and is sensitive to environmental conditions. Neuronal noise, especially synaptic random inputs, is a natural part of the brain. Theoretical and experimental studies have revealed that noise plays a vital role in signal frequency selectivity and weak sensory input perception of the neuronal system. There is a consensus that sufficiently intense noise can trigger rhythmic brain activity, and these noise-induced oscillations could improve signal processing of the neuronal system, particularly when the external signal frequency aligns with the frequency of the noise-induced rhythm. Such behavior in response to noise in the signal-processing mechanism of biological systems is elucidated by stochastic resonance. In this regard, this paper systematically analyzes the stochastic resonance in a Type-II Morris–Lecar neuron under excitatory and inhibitory background spike bombardments. Our results indicate that Morris–Lecar Type II neurons enhance their signal coding capacity by exploiting background synaptic activity. In addition, it has been revealed that the biological properties of the background synaptic connections of neurons that oscillate at different frequencies, such as delta, theta, alpha, beta, and gamma bands, are different. On the other hand, it has been found that neurons adapt to the properties of pre-synaptic neurons to encode weak signals. This study ensures novel insights into the functional role of background synaptic input in neuronal coding mechanisms by demonstrating a biophysical factor of stochastic resonance via numerical analyses. Furthermore, our results show that the properties of the background synaptic inputs significantly determine what kind of signal to encode or not. These results are an important indicator of the signal frequency selectivity of neurons, such as auditory cells.

Loneliness and brain rhythmic activity in resting state: an exploratory report.

Recent studies using resting-state functional magnetic resonance imaging have shown that loneliness is associated with altered blood oxygenation in several brain regions. However, the relationship between loneliness and changes in neuronal rhythm activity in the brain remains unclear. To evaluate brain rhythm, we conducted an exploratory resting-state electroencephalogram (EEG) study of loneliness. We recorded resting-state EEG signals from 139 participants (94 women; mean age = 19.96 years) and analyzed power spectrum density (PSD) and functional connectivity (FC) in both the electrode and source spaces. The PSD analysis revealed significant correlations between loneliness scores and decreased beta-band powers, which may indicate negative emotion, attention, reward, and/or sensorimotor processing. The FC analysis revealed a trend of alpha-band FC associated with individuals' loneliness scores. These findings provide new insights into the neural basis of loneliness, which will facilitate the development of neurobiologically informed interventions for loneliness.

Modulation of large rhythmic depolarizations in human large basket cells by norepinephrine and acetylcholine

Rhythmic brain activity is critical to many brain functions and is sensitive to neuromodulation, but so far very few studies have investigated this activity on the cellular level in vitro in human brain tissue samples. This study reveals and characterizes a novel rhythmic network activity in the human neocortex. Using intracellular patch-clamp recordings of human cortical neurons, we identify large rhythmic depolarizations (LRDs) driven by glutamate release but not by GABA. These LRDs are intricate events made up of multiple depolarizing phases, occurring at ~0.3 Hz, have large amplitudes and long decay times. Unlike human tissue, rat neocortex layers 2/3 exhibit no such activity under identical conditions. LRDs are mainly observed in a subset of L2/3 interneurons that receive substantial excitatory inputs and are likely large basket cells based on their morphology. LRDs are highly sensitive to norepinephrine (NE) and acetylcholine (ACh), two neuromodulators that affect network dynamics. NE increases LRD frequency through β-adrenergic receptor activity while ACh decreases it via M4 muscarinic receptor activation. Multi-electrode array recordings show that NE enhances and synchronizes oscillatory network activity, whereas ACh causes desynchronization. Thus, NE and ACh distinctly modulate LRDs, exerting specific control over human neocortical activity.

Effects of transcranial direct current stimulation on brain activity and cortical functional connectivity in children with autism spectrum disorders.

Transcranial direct current stimulation (tDCS) has emerged as a therapeutic option to mitigate symptoms in individuals with autism spectrum disorder (ASD). Our study investigated the effects of a two-week regimen of tDCS targeting the left dorsolateral prefrontal cortex (DLPFC) in children with ASD, examining changes in rhythmic brain activity and alterations in functional connectivity within key neural networks: the default mode network (DMN), sensorimotor network (SMN), and dorsal attention network (DAN). We enrolled twenty-six children with ASD and assigned them randomly to either an active stimulation group (n=13) or a sham stimulation group (n=13). The active group received tDCS at an intensity of 1mA to the left DLPFC for a combined duration of 10 days. Differences in electrical brain activity were pinpointed using standardized low-resolution brain electromagnetic tomography (sLORETA), while functional connectivity was assessed via lagged phase synchronization. Compared to the typically developing children, children with ASD exhibited lower current source density across all frequency bands. Post-treatment, the active stimulation group demonstrated a significant increase in both current source density and resting state network connectivity. Such changes were not observed in the sham stimulation group. tDCS targeting the DLPFC may bolster brain functional connectivity in patients with ASD, offering a substantive groundwork for potential clinical applications.

Loss of mGlu5 receptors in somatostatin-expressing neurons alters negative emotional states.

Subtype 5 metabotropic glutamate receptors (mGlu5) are known to play an important role in regulating cognitive, social and valence systems. However, it remains largely unknown at which circuits and neuronal types mGlu5 act to influence these behavioral domains. Altered tissue- or cell-specific expression or function of mGlu5 has been proposed to contribute to the exacerbation of neuropsychiatric disorders. Here, we examined how these receptors regulate the activity of somatostatin-expressing (SST+) neurons, as well as their influence on behavior and brain rhythmic activity. Loss of mGlu5 in SST+ neurons elicited excitatory synaptic dysfunction in a region and sex-specific manner together with a range of emotional imbalances including diminished social novelty preference, reduced anxiety-like behavior and decreased freezing during retrieval of fear memories. In addition, the absence of mGlu5 in SST+ neurons during fear processing impaired theta frequency oscillatory activity in the medial prefrontal cortex and ventral hippocampus. These findings reveal a critical role of mGlu5 in controlling SST+ neurons excitability necessary for regulating negative emotional states.

Stochastic resonance in a single autapse–coupled neuron

The signal detection ability of nervous system is highly associated with nonlinear and collective behaviors in neuronal medium. Neuronal noise, which occurs as natural endogenous fluctuations in brain activity, is the most salient factor influencing this ability. Experimental and theoretical research suggests that noise is beneficial, not detrimental, for regular functioning of nervous system. In this regard, there is a general agreement that noise at an adequate intensity can engage rhythmic activity in brain and noise-induced oscillations enhances performance of the weak signal processing, especially when frequency of the signal is around that of the noise-induced rhythmic oscillation. This behavior in biological neural systems is explained by the notion of “stochastic resonance”. Another factor that plays a key role in regulating neuronal behaviors, including motor and cognitive tasks by maintaining signaling between cells, is characteristics of synapses different in structure and functioning. Here, we study stochastic resonance in Hodgkin–Huxley neuron that has a peculiar synaptic connection called autapse, known as a biophysical feedback mechanism, under presynaptic noise originating from superposition of inhibitory and excitatory Poisson bombardment. Our results show that, under certain conditions, autapse dynamics are able to improve the weak signal detection performance of Hodgkin–Huxley neuron via stochastic resonance. This study provides novel insights into functional role of autapse in neural information processing by revealing a biophysical aspect of stochastic resonance with numerical computations.

Spontaneous α Brain Dynamics Track the Episodic "When".

Across species, neurons track time over the course of seconds to minutes, which may feed the sense of time passing. Here, we asked whether neural signatures of time-tracking could be found in humans. Participants stayed quietly awake for a few minutes while being recorded with magnetoencephalography (MEG). They were unaware they would be asked how long the recording lasted (retrospective time) or instructed beforehand to estimate how long it will last (prospective timing). At rest, rhythmic brain activity is nonstationary and displays bursts of activity in the alpha range (α: 7-14 Hz). When participants were not instructed to attend to time, the relative duration of α bursts linearly predicted individuals' retrospective estimates of how long their quiet wakefulness lasted. The relative duration of α bursts was a better predictor than α power or burst amplitude. No other rhythmic or arrhythmic activity predicted retrospective duration. However, when participants timed prospectively, the relative duration of α bursts failed to predict their duration estimates. Consistent with this, the amount of α bursts was discriminant between prospective and retrospective timing. Last, with a control experiment, we demonstrate that the relation between α bursts and retrospective time is preserved even when participants are engaged in a visual counting task. Thus, at the time scale of minutes, we report that the relative time of spontaneous α burstiness predicts conscious retrospective time. We conclude that in the absence of overt attention to time, α bursts embody discrete states of awareness constitutive of episodic timing.SIGNIFICANCE STATEMENT The feeling that time passes is a core component of consciousness and episodic memory. A century ago, brain rhythms called "α" were hypothesized to embody an internal clock. However, rhythmic brain activity is nonstationary and displays on-and-off oscillatory bursts, which would serve irregular ticks to the hypothetical clock. Here, we discovered that in a given lapse of time, the relative bursting time of α rhythms is a good indicator of how much time an individual will report to have elapsed. Remarkably, this relation only holds true when the individual does not attend to time and vanishes when attending to it. Our observations suggest that at the scale of minutes, α brain activity tracks episodic time.

Magnetoencephalography(MEG) spectral signature of cognitive impairment ‐ A perspective on pathophysiological changes with blood pressure

AbstractBackgroundSpectral ratios (e.g., resting‐state EEG alpha/theta power ratio), which index rhythmic brain activity, have been shown to distinguish early‐onset AD from healthy controls. Magnetoencephalographic (MEG) brain imaging offers advantages over EEG through its unique combination of excellent temporal as well as spatial precision for detecting brain activity. The purpose of this study is to compare MEG spectral activity in cognitively impaired and healthy controls with changes in systolic blood pressure (sbp), specifically focused in the frontal lobe as this region is known to be susceptible to hypertension related white matter degradation.MethodsSixteen cognitively impaired, including 13 possible and 3 probable mild cognitive impairment (MCI), (mean age 65.6 years, males/females: 5/11, Whites/Blacks: 11/5) and sixteen age, sex, and race matched healthy controls (mean age 62.4 years, males/females: 4/12, Whites/Blacks: 11/5) were recruited from an ongoing multiethnic community‐based study to complete six minutes of resting‐state MEG along with a T1w brain MRI. All MEG data underwent standard preprocessing. Resultant whole‐brain maps of spectral activity were filtered into six canonical frequency bands, including delta (2‐4 Hz), theta (5‐7 Hz), alpha (8‐12 Hz), beta (15‐29 Hz), gamma (30‐59 Hz) and high gamma (60‐90 Hz). Relative mean power of each frequency band, and spectral ratios of alpha/theta, beta/delta as well as a spectral slowing index [(alpha+beta+gamma)/(delta+theta)] were computed.ResultMean sbp was 135 mm Hg for both groups. Generalized linear regression models showed cognitive impairment was negatively associated with spectral ratios beta/delta and spectral slowing index. We also found a significant positive association between spectral ratios (beta/delta β = ‐0.0115, p = 0.0015; spectral slowing index β = ‐0.0125, p = 0.0144) and interaction of systolic blood pressure with cognitive impairment. Results are summarized in tables 1‐2.ConclusionLower spectral ratios have previously been demonstrated in individuals with AD. Somewhat surprisingly, our findings indicate that lower blood pressure is associated with lower values on these MEG metrics in cognitively impaired individuals. Interestingly, overtreatment of hypertension in elderly with MCI has been associated with greater cognitive decline. Thus, these results will be examined in a larger cohort and the analysis will be expanded to include anti‐hypertensive medication data to potentially explain the above findings.

Fast and Slow Rhythms of Naturalistic Reading Revealed by Combined Eye-Tracking and Electroencephalography.

Neural oscillations are thought to support speech and language processing. They may not only inherit acoustic rhythms, but might also impose endogenous rhythms onto processing. In support of this, we here report that human (both, male and female) eye movements during naturalistic reading exhibit rhythmic patterns that show frequency-selective coherence with the electroencephalogram (EEG)-in the absence of any stimulation rhythm. Periodicity was observed in two distinct frequency bands: First, word-locked saccades at 4-5 Hertz display coherence with whole-head theta-band activity. Second, fixation durations fluctuate rhythmically at ∼1 Hertz, in coherence with occipital delta-band activity. This latter effect was additionally phase-locked to sentence endings, suggesting a relationship with the formation of multi-word chunks. Taken together, eye movements during reading contain rhythmic patterns that occur in synchrony with oscillatory brain activity. This suggests that linguistic processing imposes preferred processing time scales onto reading, largely independent of actual physical rhythms in the stimulus.SIGNIFICANCE STATEMENT:The sampling, grouping, and transmission of information is supported by rhythmic brain activity, so-called neural oscillations. In addition to sampling external stimuli, such rhythms may also be endogenous, affecting processing from the inside out. In particular, endogenous rhythms may impose their pace onto language processing. Studying this is challenging because speech contains physical rhythms that mask endogenous activity. To overcome this challenge, we turned to naturalistic reading, where text does not require the reader to sample in a specific rhythm. We observed rhythmic patterns of eye movements that are synchronized to brain activity as recorded with EEG. This rhythmicity is not imposed by the external stimulus, which indicates that rhythmic brain activity may serve as a pacemaker for language processing.

Neurophysiological isolation of individual rhythmic brain activity arising from auditory-speech load

Knowledge about the rhythmic activity of neural networks associated with the implementation of a particular brain function can be used to construct diagnostic systems for objective analyses of cognitive dysfunctions. The aim of this study was to identify specific frequency-based electroencephalogram phenomena associated with speech processing. The study included data from 40 clinically healthy volunteers aged 30 to 50 years (median 32.5 years), including 23 men and 17 women. While listening to a speech stimulus, changes in bioelectrical activity over the speech centers were recorded in 23 subjects (58%). During active speech production, similar changes were recorded in 12 subjects (30%). A pairwise comparison of electroencephalogram frequencies recorded during background recording and listening to the stimuli revealed statistically significant differences in changes in rhythmic activity over Broca’s area during listening and over Wernicke's area during active speech production, while changes in rhythmic activity over Broca’s area during active speech production and over Wernicke's area during listening were less significant. The most characteristic changes in the bioelectrical activity over the speech centers during listening and speaking were fluctuations with a frequency (on average) of 17.5–17.7 Hz. This may reflect a specific electroencephalogram rhythm associated with activity in the speech areas of the brain, which could allow these regions to be more accurately identified during auditory-verbal processing.

The fate of interneurons, GABAA receptor sub-types and perineuronal nets in Alzheimer's disease.

Alzheimer's disease (AD) is the most common neurological disease, which is associated with gradual memory loss and correlated with synaptic hyperactivity and abnormal oscillatory rhythmic brain activity that precedes phenotypic alterations and is partly responsible for the spread of the disease pathology. Synaptic hyperactivity is thought to be because of alteration in the homeostasis of phasic and tonic synaptic inhibition, which is orchestrated by the GABAA inhibitory system, encompassing subclasses of interneurons and GABAA receptors, which play a vital role in cognitive functions, including learning and memory. Furthermore, the extracellular matrix, the perineuronal nets (PNNs) which often go unnoticed in considerations of AD pathology, encapsulate the inhibitory cells and neurites in critical brain regions and have recently come under the light for their crucial role in synaptic stabilisation and excitatory-inhibitory balance and when disrupted, serve as a potential trigger for AD-associated synaptic imbalance. Therefore, in this review, we summarise the current understanding of the selective vulnerability of distinct interneuron subtypes, their synaptic and extrasynaptic GABAA R subtypes as well as the changes in PNNs in AD, detailing their contribution to the mechanisms of disease development. We aim to highlight how seemingly unique malfunction in each component of the interneuronal GABA inhibitory system can be tied together to result in critical circuit dysfunction, leading to the irreversible symptomatic damage observed in AD.

Spectral brain signatures of aesthetic natural perception in the α and β frequency bands.

During our everyday lives, visual beauty is often conveyed by sustained and dynamic visual stimulation, such as when we walk through an enchanting forest or watch our pets playing. Here, I devised an MEG experiment that mimics such situations: participants viewed 8 s videos of everyday situations and rated their beauty. Using multivariate analysis, I linked aesthetic ratings to 1) sustained MEG broadband responses and 2) spectral MEG responses in the α and β frequency bands. These effects were not accounted for by a set of high- and low-level visual descriptors of the videos, suggesting that they are genuinely related to aesthetic perception. My findings provide the first characterization of spectral brain signatures linked to aesthetic experiences in the real world.NEW & NOTEWORTHY In the real world, aesthetic experiences arise from complex and dynamic inputs. This study shows that such aesthetic experiences are represented in a spectral neural code: cortical α and β activity track our judgments of the aesthetic appearance of natural videos, providing a new starting point for studying the neural correlates of beauty through rhythmic brain activity.

Electroencephalography based emotion detection using ensemble classification and asymmetric brain activity

Over the past decade, emotion detection using rhythmic brain activity has become a critical area of research. The asymmetrical brain activity has garnered the most significant level of research attention due to its implications for the study of emotions, including hemispheric asymmetry or, more generally, asymmetrical brain activity. This study aimed at enhancing the accuracy of emotion detection using Electroencephalography (EEG) brain signals. This happens by identifying electrodes where relevant brain activity changes occur during the emotions and by defining pairs of relevant electrodes having asymmetric brain activities during emotions. Experimental results showed that the proposed method is highly competitive compared with existing studies of multi-class emotion recognition. These results were improved by processing not the whole EEG signals but by focusing on fragments of the signals, called epochs, which represent the instants where the excitation is maximum during emotions. The epochs were extracted using the zero-time windowing method and the numerator group-delay function.

Effect of Rhythmic and Nonrhythmic Brain Activity on Power Spectral Analysis in Children With Attention Deficit Hyperactivity Disorder

Power spectral analysis is one of the most important analysis tools for resting-state electroencephalography (EEG) in attention deficit hyperactivity disorder (ADHD) children. However, some conclusions of power spectral analysis are different or even contradictory in ADHD studies. Little is known about the reasons. We suspect that the conventional methods do not clearly differentiate rhythmic activity from nonrhythmic activity. We propose a modified better oscillation detection method (MBOSC) to identify the rhythmic brain activity. The performance of the MBOSC method is estimated using the simulated data. Then, the relative power and the MBOSC method are, respectively, used to analyze the EEG signals recorded in 30 ADHD children and 28 typically developing children at the resting state. The results show that the frequency range detected by MBOSC is more concentrated than two other counterparts, and indicate that the change of relative power in the alpha band is caused by rhythmic brain activity, while the change of relative power in the delta band is caused by nonrhythmic brain activity. These findings provide a new perspective to investigate the inconsistency in power spectral analysis of ADHD children.

The rubber hand illusion is accompanied by a distributed reduction of alpha and beta power in the EEG.

Previous studies have reported correlates of bodily self-illusions such as the rubber hand in signatures of rhythmic brain activity. However, individual studies focused on specific variations of the rubber hand paradigm, used different experimental setups to induce this, or used different control conditions to isolate the neurophysiological signatures related to the illusory state, leaving the specificity of the reported illusion-signatures unclear. We here quantified correlates of the rubber hand illusion in EEG-derived oscillatory brain activity and asked two questions: which of the observed correlates are robust to the precise nature of the control conditions used as contrast for the illusory state, and whether such correlates emerge directly around the subjective illusion onset. To address these questions, we relied on two experimental configurations to induce the illusion, on different non-illusion conditions to isolate neurophysiological signatures of the illusory state, and we implemented an analysis directly focusing on the immediate moment of the illusion onset. Our results reveal a widespread suppression of alpha and beta-band activity associated with the illusory state in general, whereby the reduction of beta power prevailed around the immediate illusion onset. These results confirm previous reports of a suppression of alpha and beta rhythms during body illusions, but also highlight the difficulties to directly pinpoint the precise neurophysiological correlates of the illusory state.

Phase Coherence of Rhythmic Brain Activity as an Indicator of Differences in Sound Stimuli in the Oddball Paradigm

Phase Coherence of Rhythmic Brain Activity as an Indicator of Differences in Sound Stimuli in the Oddball Paradigm

A Waveform-Independent Measure of Recurrent Neural Activity.

Rhythmic neural activity, so-called oscillations, plays a key role in neural information transmission, processing, and storage. Neural oscillations in distinct frequency bands are central to physiological brain function, and alterations thereof have been associated with several neurological and psychiatric disorders. The most common methods to analyze neural oscillations, e.g., short-time Fourier transform or wavelet analysis, assume that measured neural activity is composed of a series of symmetric prototypical waveforms, e.g., sinusoids. However, usually, the models generating the signal, including waveform shapes of experimentally measured neural activity are unknown. Decomposing asymmetric waveforms of nonlinear origin using these classic methods may result in spurious harmonics visible in the estimated frequency spectra. Here, we introduce a new method for capturing rhythmic brain activity based on recurrences of similar states in phase-space. This method allows for a time-resolved estimation of amplitude fluctuations of recurrent activity irrespective of or specific to waveform shapes. The algorithm is derived from the well-established field of recurrence analysis, which, in comparison to Fourier-based analysis, is still very uncommon in neuroscience. In this paper, we show its advantages and limitations in comparison to short-time Fourier transform and wavelet convolution using periodic signals of different waveform shapes. Furthermore, we demonstrate its application using experimental data, i.e., intracranial and noninvasive electrophysiological recordings from the human motor cortex of one epilepsy patient and one healthy adult, respectively.

Endogenous modulation of delta phase by expectation–A replication of Stefanics et al., 2010

The human brain efficiently extracts the temporal statistics of sensory environments and automatically generates expectations about future events. An influential Hypothesis holds that these expectations can find their implementation in neural oscillations, notably in the delta band (.5–3 Hz). Rhythmic fluctuations of cortical excitement are thought to align and match up in phase to the temporal structure of the sensory environment. This alignment is thought to result in the more excitable phase range of neural oscillations to overlap with the predicted onset of sensory events which in turn results in more efficient processing of sensory input, especially so in audition. An unresolved issue concerns whether such phase-aligned rhythmic brain activity is driven exclusively by the exogenous temporal structure of the input, or whether it also reflects phase re-alignment due to endogenous expectations based on stimulus probability and task relevance. In a seminal study, Stefanics et al. (2010) presented stimuli in a rhythmic stream and observed that delta phase consistency across trials was modulated by endogenous target onset expectations: delta phase consistency was higher prior to more probable (strongly expected) compared to less probable (weakly expected) target onsets. The present study replicates Experiment II of the original study, most importantly the modulation of delta phase consistency by endogenous expectations, and underlines a direct relationship between phase locking and behaviour. Our additional analyses locate the sources of the delta phase-alignment to motor, pre-motor, parietal, and temporal areas, and provide evidence for an ongoing delta oscillation, in line with the interpretation of oscillatory phase alignment rather than a transient evoked response. Importantly, this work shows that the phase of delta oscillations can be modulated by top-down control, and hence qualifies as a potential mechanism for the neural implementation of (rhythmic) temporal predictions.

Cortical oscillatory dysrhythmias in visual snow syndrome: a magnetoencephalography study.

Visual snow refers to the persistent visual experience of static in the whole visual field of both eyes. It is often reported by patients with migraine and co-occurs with conditions such as tinnitus and tremor. The underlying pathophysiology of the condition is poorly understood. Previously, we hypothesized that visual snow syndrome may be characterized by disruptions to rhythmical activity within the visual system. To test this, data from 18 patients diagnosed with visual snow syndrome, and 16 matched controls, were acquired using magnetoencephalography. Participants were presented with visual grating stimuli, known to elicit decreases in alpha-band (8–13 Hz) power and increases in gamma-band power (40–70 Hz). Data were mapped to source-space using a beamformer. Across both groups, decreased alpha power and increased gamma power localized to early visual cortex. Data from the primary visual cortex were compared between groups. No differences were found in either alpha or gamma peak frequency or the magnitude of alpha power, p > 0.05. However, compared with controls, our visual snow syndrome cohort displayed significantly increased primary visual cortex gamma power, p = 0.035. This new electromagnetic finding concurs with previous functional MRI and PET findings, suggesting that in visual snow syndrome, the visual cortex is hyperexcitable. The coupling of alpha-phase to gamma amplitude within the primary visual cortex was also quantified. Compared with controls, the visual snow syndrome group had significantly reduced alpha–gamma phase–amplitude coupling, p < 0.05, indicating a potential excitation–inhibition imbalance in visual snow syndrome, as well as a potential disruption to top-down ‘noise-cancellation’ mechanisms. Overall, these results suggest that rhythmical brain activity in the primary visual cortex is both hyperexcitable and disorganized in visual snow syndrome, consistent with this being a condition of thalamocortical dysrhythmia.