Low-frequency Activity Research Articles

A randomized study on the effect of a wearable device using 0.75 Hz transcranial electrical stimulation on sleep onset insomnia

IntroductionThe normal transition to sleep is characterized by a reduction in higher frequency activity and an increase in lower frequency activity in frontal brain regions. In sleep onset insomnia these changes in activity are weaker and may prolong the transition to sleep.MethodsUsing a wearable device, we compared 30min of short duration repetitive transcranial electric stimulation (SDR-tES) at 0.75Hz, prior to going to bed, with an active control at 25Hz in the same individuals.ResultsTreatment with 0.75Hz significantly reduced sleep onset latency (SOL) by 53% when compared with pre-treatment baselines and was also significantly more effective than stimulation with 25Hz which reduced SOL by 30%. Reductions in SOL with 25Hz stimulation displayed order effects suggesting the possibility of placebo. No order effects were observed with 0.75Hz stimulation. The decrease in SOL with 0.75Hz treatment was proportional to an individual’s baseline wherein those suffering from the longest pre-treated SOLs realized the greatest benefits. Changes in SOL were correlated with left/right frontal EEG signal coherence around the stimulation frequency, providing a possible mechanism and target for more focused treatment. Stimulation at both frequencies also decreased perceptions of insomnia symptoms measured with the Insomnia Severity Index, and comorbid anxiety measured with the State Trait Anxiety Index.DiscussionOur study identifies a new potential treatment for sleep onset insomnia that is comparably effective to current state-of-practice options including pharmacotherapy and cognitive behavioral therapy and is safe, effective, and can be delivered in the home.

Basal ganglia theta power indexes trait anxiety in people with Parkinson's disease.

Neuropsychiatric symptoms are common and disabling in Parkinson's disease (PD), with troublesome anxiety occurring in one-third of patients. Management of anxiety in PD is challenging, hampered by insufficient insight into underlying mechanisms, lack of objective anxiety measurements, and largely ineffective treatments. In this study, we assessed the intracranial neurophysiological correlates of anxiety in PD patients treated with deep brain stimulation (DBS) in the laboratory and at home. We hypothesized that low-frequency (theta-alpha) activity would be associated with anxiety. We recorded local field potentials (LFP) from the subthalamic nucleus (STN) or the globus pallidus pars interna (GPi) DBS implants in three PD cohorts: 1) patients with recordings (STN) performed in hospital at rest via perioperatively externalized leads, without active stimulation, both ON or OFF dopaminergic medication; 2) patients with recordings (STN or GPi) performed at home while resting, via a chronically implanted commercially available sensing-enabled neurostimulator (Medtronic PerceptTM device), ON dopaminergic medication, with stimulation both on or off; 3) patients with recordings performed at home while engaging in a behavioral task via STN and GPi leads and electrocorticography paddles over premotor cortex connected to an investigational sensing-enabled neurostimulator, ON dopaminergic medication, with stimulation both on or off. Trait anxiety was measured with validated clinical scales in all participants, and state anxiety was measured with momentary assessment scales at multiple time points in the two at-home cohorts. Power in theta (4-8 Hz) and alpha (8-12 Hz) ranges were extracted from the LFP recordings, and their relation with anxiety ratings was assessed using linear mixed-effects models. In total, 33 PD patients (59 hemispheres) were included. Across three independent cohorts, with stimulation off, basal ganglia theta power was positively related to trait anxiety (all p<0.05). Also in a naturalistic setting, with individuals at home at rest with stimulation and medication ON, basal ganglia theta power was positively related to trait anxiety (p<0.05). This relationship held regardless of the hemisphere and DBS target. There was no correlation between trait anxiety and premotor cortical theta-alpha power. There was no within-patient association between basal ganglia theta-alpha power and state anxiety. We showed that basal ganglia theta activity indexes trait anxiety in PD. Our data suggest that theta could be a possible physiomarker of neuropsychiatric symptoms and specifically of anxiety in PD, potentially suitable for guiding advanced DBS treatment tailored to the individual patient's needs, including non-motor symptoms.

Striato-pallidal oscillatory connectivity correlates with symptom severity in dystonia patients

Dystonia is a hyperkinetic movement disorder that has been associated with an imbalance towards the direct pathway between striatum and internal pallidum, but the neuronal underpinnings of this abnormal basal ganglia pathway activity remain unknown. Here, we report invasive recordings from ten dystonia patients via deep brain stimulation electrodes that allow for parallel recordings of several basal ganglia nuclei, namely the striatum, external and internal pallidum, that all displayed activity in the low frequency band (3–12 Hz). In addition to a correlation with low-frequency activity in the internal pallidum (R = 0.88, P = 0.001), we demonstrate that dystonic symptoms correlate specifically with low-frequency coupling between striatum and internal pallidum (R = 0.75, P = 0.009). This points towards a pathophysiological role of the direct striato-pallidal pathway in dystonia that is conveyed via coupling in the enhanced low-frequency band. Our study provides a mechanistic insight into the pathophysiology of dystonia by revealing a link between symptom severity and frequency-specific coupling of distinct basal ganglia pathways.

Cortical encoding of hierarchical linguistic information when syllabic rhythms are obscured by echoes

In speech perception, low-frequency cortical activity tracks hierarchical linguistic units (e.g., syllables, phrases, and sentences) on top of acoustic features (e.g., speech envelope). Since the fluctuation of speech envelope typically corresponds to the syllabic boundaries, one common interpretation is that the acoustic envelope underlies the extraction of discrete syllables from continuous speech for subsequent linguistic processing. However, it remains unclear whether and how cortical activity encodes linguistic information when the speech envelope does not provide acoustic correlates of syllables. To address the issue, we introduced a frequency-tagging speech stream where the syllabic rhythm was obscured by echoic envelopes and investigated neural encoding of hierarchical linguistic information using electroencephalography (EEG). When listeners attended to the echoic speech, cortical activity showed reliable tracking of syllable, phrase, and sentence levels, among which the higher-level linguistic units elicited more robust neural responses. When attention was diverted from the echoic speech, reliable neural tracking of the syllable level was also observed in contrast to deteriorated neural tracking of the phrase and sentence levels. Further analyses revealed that the envelope aligned with the syllabic rhythm could be recovered from the echoic speech through a neural adaptation model, and the reconstructed envelope yielded higher predictive power for the neural tracking responses than either the original echoic envelope or anechoic envelope. Taken together, these results suggest that neural adaptation and attentional modulation jointly contribute to neural encoding of linguistic information in distorted speech where the syllabic rhythm is obscured by echoes.

A study comparing brain wave patterns of fentanyl and ketamine in adult patients undergoing minimally invasive surgery.

This study aimed to investigate and compare the neurophysiological impacts of two widely used anesthetic agents, Fentanyl and Ketamine, on EEG power spectra during different stages of anesthesia in adult patients undergoing minimally invasive surgery. EEG data were collected from patients undergoing anesthesia with either Fentanyl or Ketamine. The data were analyzed for relative power spectrum and fast-to-slow wave power ratios, alongside Spectral Edge Frequency 95% (SEF95), at 3 key stages: pre-anesthesia, during stable anesthesia, and post-anesthesia. EEG Relative Power Spectrum: Initially, both groups exhibited similar EEG spectral profiles, establishing a uniform baseline (P > .05). Upon anesthesia induction, the Fentanyl group showed a substantial increase in delta band power (P < .05), suggesting deeper anesthesia, while the Ketamine group maintained higher alpha and beta band activity (P < .05), indicative of a lighter sedative effect. Fast and Slow Wave Power Ratios: The Fentanyl group exhibited a marked reduction in the fast-to-slow wave power ratio during anesthesia (P < .05), persisting post-anesthesia (P < .05) and indicating a lingering effect on brain activity. Conversely, the Ketamine group demonstrated a more stable ratio (P > .05), conducive to settings requiring rapid cognitive recovery. Spectral Edge Frequency 95% (SEF95): Analysis showed a significant decrease in SEF95 values for the Fentanyl group during anesthesia (P < .05), reflecting a shift towards lower frequency power. The Ketamine group experienced a less pronounced decrease (P > .05), maintaining a higher SEF95 value that suggested a lighter level of sedation. The study highlighted the distinct impacts of Fentanyl and Ketamine on EEG power spectra, with Fentanyl inducing deeper anesthesia as evidenced by shifts towards lower frequency activity and a significant decrease in SEF95 values. In contrast, Ketamine's preservation of higher frequency activity and more stable SEF95 values suggests a lighter, more dissociative anesthetic state. These findings emphasize the importance of EEG monitoring in anesthesia for tailoring anesthetic protocols to individual patient needs and optimizing postoperative outcomes.

Comparative Study of E-beam and Optical Probing Approaches in Attacking the ICs

AbstractOptical probing methods through the chip backside have been demonstrated to be powerful attack techniques in the field of electronic security. However, these attacks typically require specific circuit conditions, such as enforcing gate or register switching at certain frequencies or repeating measurements over multiple executions to achieve an acceptable signal-to-noise ratio (SNR). Meeting these requirements can pose challenges, such as low-frequency switching or inaccessibility of the control signals. This study evaluates these requirements for contactless electron- and photon-based probing attacks by performing extensive experiments and discussing the advantages and drawbacks of each approach. Our findings demonstrate that E-beam probing has the potential to outperform optical methods in scenarios involving static or low-frequency circuit activities. Nevertheless, E-beam probing requires the assistance of optical techniques for area localization and requires aggressive thinning and trenching to the STI level.

In vivo optogenetics using a Utah Optrode Array with enhanced light output and spatial selectivity

Objective.Optogenetics allows the manipulation of neural circuitsin vivowith high spatial and temporal precision. However, combining this precision with control over a significant portion of the brain is technologically challenging (especially in larger animal models).Approach.Here, we have developed, optimised, and testedin vivo, the Utah Optrode Array (UOA), an electrically addressable array of optical needles and interstitial sites illuminated by 181μLEDs and used to optogenetically stimulate the brain. The device is specifically designed for non-human primate studies.Main results.Thinning the combinedμLED and needle backplane of the device from 300μm to 230μm improved the efficiency of light delivery to tissue by 80%, allowing lowerμLED drive currents, which improved power management and thermal performance. The spatial selectivity of each site was also improved by integrating an optical interposer to reduce stray light emission. These improvements were achieved using an innovative fabrication method to create an anodically bonded glass/silicon substrate with through-silicon vias etched, forming an optical interposer. Optical modelling was used to demonstrate that the tip structure of the device had a major influence on the illumination pattern. The thermal performance was evaluated through a combination of modelling and experiment, in order to ensure that cortical tissue temperatures did not rise by more than 1 °C. The device was testedin vivoin the visual cortex of macaque expressing ChR2-tdTomato in cortical neurons.Significance.It was shown that the UOA produced the strongest optogenetic response in the region surrounding the needle tips, and that the extent of the optogenetic response matched the predicted illumination profile based on optical modelling-demonstrating the improved spatial selectivity resulting from the optical interposer approach. Furthermore, different needle illumination sites generated different patterns of low-frequency potential activity.

Cross-regional coordination of activity in the human brain during autobiographical self-referential processing

For the human brain to operate, populations of neurons across anatomical structures must coordinate their activity within milliseconds. To date, our understanding of such interactions has remained limited. We recorded directly from the hippocampus (HPC), posteromedial cortex (PMC), ventromedial/orbital prefrontal cortex (OFC), and the anterior nuclei of the thalamus (ANT) during two experiments of autobiographical memory processing that are known from decades of neuroimaging work to coactivate these regions. In 31 patients implanted with intracranial electrodes, we found that the presentation of memory retrieval cues elicited a significant increase of low frequency (LF < 6 Hz) activity followed by cross-regional phase coherence of this LF activity before select populations of neurons within each of the four regions increased high-frequency (HF > 70 Hz) activity. The power of HF activity was modulated by memory content, and its onset followed a specific temporal order of ANT→HPC/PMC→OFC. Further, we probed cross-regional causal effective interactions with repeated electrical pulses and found that HPC stimulations cause the greatest increase in LF-phase coherence across all regions, whereas the stimulation of any region caused the greatest LF-phase coherence between that particular region and ANT. These observations support the role of the ANT in gating, and the HPC in synchronizing, the activity of cortical midline structures when humans retrieve self-relevant memories of their past. Our findings offer a fresh perspective, with high temporal fidelity, about the dynamic signaling and underlying causal connections among distant regions when the brain is actively involved in retrieving self-referential memories from the past.

Dissociating prosodic from syntactic delta activity during natural speech comprehension

Decoding human speech requires the brain to segment the incoming acoustic signal into meaningful linguistic units, ranging from syllables and words to phrases. Integrating these linguistic constituents into a coherent percept sets the root of compositional meaning and hence understanding. One important cue for segmentation in natural speech is prosodic cues, such as pauses, but their interplay with higher-level linguistic processing is still unknown. Here, we dissociate the neural tracking of prosodic pauses from the segmentation of multi-word chunks using magnetoencephalography (MEG). We find that manipulating the regularity of pauses disrupts slow speech-brain tracking bilaterally in auditory areas (below 2Hz) and in turn increases left-lateralized coherence of higher-frequency auditory activity at speech onsets (around 25-45Hz). Critically, we also find that multi-word chunks-defined as short, coherent bundles of inter-word dependencies-are processed through the rhythmic fluctuations of low-frequency activity (below 2Hz) bilaterally and independently of prosodic cues. Importantly, low-frequency alignment at chunk onsets increases the accuracy of an encoding model in bilateral auditory and frontal areas while controlling for the effect of acoustics. Our findings provide novel insights into the neural basis of speech perception, demonstrating that both acoustic features (prosodic cues) and abstract linguistic processing at the multi-word timescale are underpinned independently by low-frequency electrophysiological brain activity in the delta frequency range.

EEG signatures of cognitive decline after mild SARS-CoV-2 infection: an age-dependent study

BackgroundCurrent research on the neurological impact of SARS-CoV-2 primarily focuses on the elderly or severely ill individuals. This study aims to explore the diverse neurological consequences of SARS-CoV-2 infection, with a particular focus on mildly affected children and adolescents.MethodsA cohort study was conducted to collect pre- and post-infection resting-state electroencephalogram (EEG) data from 185 participants and 181 structured questionnaires of long-term symptoms across four distinct age groups. The goal was to comprehensively evaluate the impact of SARS-CoV-2 infection on these different age demographics. The study analyzed EEG changes of SARS-CoV-2 by potential biomarkers across age groups using both spatial and temporal approaches.ResultsSpatial analysis indicated that children and adolescents exhibit smaller changes in brain network and microstate patterns post-infection, implying a milder cognitive impact. Sequential linear analyses showed that SARS-CoV-2 infection is associated with a marked rise in low-complexity, synchronized neural activity within low-frequency EEG bands. This is evidenced by a significant increase in Hjorth activity within the theta band and Hjorth mobility in the delta band. Sequential nonlinear analysis indicated a significant reduction in the Hurst exponent across all age groups, pointing to increased chaos and complexity within the cognitive system following infection. Furthermore, linear regression analysis based on questionnaires established a significant positive relationship between the magnitude of changes in these neural indicators and the persistence of long-term symptoms post-infection.ConclusionsThe findings underscore the enduring neurological impacts of SARS-CoV-2 infection, marked by cognitive decline and increased EEG disarray. Although children and adolescents experienced milder effects, cognitive decline and heightened low-frequency electrical activity were evident. These observations might contribute to understanding potential anxiety, insomnia, and neurodevelopmental implications.

When Maturation is Not Linear: Brain Oscillatory Activity in the Process of Aging as Measured by Electrophysiology.

Changes in brain oscillatory activity are commonly used as biomarkers both in cognitive neuroscience and in neuropsychiatric conditions. However, little is known about how its profile changes across maturation. Here we use regression models to characterize magnetoencephalography power changes within classical frequency bands in a sample of 792 healthy participants, covering the range 13 to 80 years old. Our findings unveil complex, non-linear power trajectories that defy the traditional linear paradigm, with notable cortical region variations. Interestingly, slow wave activity increases correlate with improved cognitive performance throughout life and larger gray matter volume in the elderly. Conversely, fast wave activity diminishes in adulthood. Elevated low-frequency activity during aging, traditionally seen as compensatory, may also signify neural deterioration. This dual interpretation, highlighted by our study, reveals the intricate dynamics between brain oscillations, cognitive performance, and aging. It advances our understanding of neurodevelopment and aging by emphasizing the regional specificity and complexity of brain rhythm changes, with implications for cognitive and structural integrity.

Basal ganglia theta power indexes trait anxiety in people with Parkinson's disease.

Neuropsychiatric symptoms are common and disabling in Parkinson's disease (PD), with troublesome anxiety occurring in one-third of patients. Management of anxiety in PD is challenging, hampered by insufficient insight into underlying mechanisms, lack of objective anxiety measurements, and largely ineffective treatments.In this study, we assessed the intracranial neurophysiological correlates of anxiety in PD patients treated with deep brain stimulation (DBS) in the laboratory and at home. We hypothesized that low-frequency (theta-alpha) activity would be associated with anxiety. We recorded local field potentials (LFP) from the subthalamic nucleus (STN) or the globus pallidus pars interna (GPi) DBS implants in three PD cohorts: 1) patients with recordings (STN) performed in hospital at rest via perioperatively externalized leads, without active stimulation, both ON or OFF dopaminergic medication; 2) patients with recordings (STN or GPi) performed at home while resting, via a chronically implanted commercially available sensing-enabled neurostimulator (Medtronic Percept™ device), ON dopaminergic medication, with stimulation both ON or OFF; 3) patients with recordings performed at home while engaging in a behavioral task via STN and GPi leads and electrocorticography paddles (ECoG) over premotor cortex connected to an investigational sensing-enabled neurostimulator, ON dopaminergic medication, with stimulation both ON or OFF.Trait anxiety was measured with validated clinical scales in all participants, and state anxiety was measured with momentary assessment scales at multiple time points in the two at-home cohorts. Power in theta (4-8 Hz) and alpha (8-12 Hz) ranges were extracted from the LFP recordings, and their relation with anxiety ratings was assessed using linear mixed-effects models. In total, 33 PD patients (59 hemispheres) were included. Across three independent cohorts, with stimulation OFF, basal ganglia theta power was positively related to trait anxiety (all p<0.05). Also in a naturalistic setting, with individuals at home at rest with stimulation and medication ON, basal ganglia theta power was positively related to trait anxiety (p<0.05). This relationship held regardless of the hemisphere and DBS target. There was no correlation between trait anxiety and premotor cortical theta-alpha power. There was no within-patient association between basal ganglia theta-alpha power and state anxiety. We showed that basal ganglia theta activity indexes trait anxiety in PD. Our data suggest that theta could be a possible physiomarker of neuropsychiatric symptoms and specifically of anxiety in PD, potentially suitable for guiding advanced DBS treatment tailored to the individual patient's needs, including non-motor symptoms.

Binocularly suppressed stimuli induce brain activities related to aesthetic emotions

IntroductionAesthetic emotions are a class of emotions aroused by evaluating aesthetically appealing objects or events. While evolutionary aesthetics suggests the adaptive roles of these emotions, empirical assessments are lacking. Previous neuroscientific studies have demonstrated that visual stimuli carrying evolutionarily important information induce neural responses even when presented non-consciously. To examine the evolutionary importance of aesthetic emotions, we conducted a neuroscientific study using magnetoencephalography (MEG) to measure induced neural responses to non-consciously presented portrait paintings categorised as biological and non-biological and examined associations between the induced responses and aesthetic ratings.MethodsMEG and pre-rating data were collected from 23 participants. The pre-rating included visual analogue scales for object saliency, facial saliency, liking, and beauty scores, in addition to ‘biologi-ness,’ which was used for subcategorising stimuli into biological and non-biological. The stimuli were presented non-consciously using a continuous flash suppression paradigm or consciously using binocular presentation without flashing masks, while dichotomic behavioural responses were obtained (beauty or non-beauty). Time-frequency decomposed MEG data were used for correlation analysis with pre-rating scores for each category.ResultsBehavioural data revealed that saliency scores of non-consciously presented stimuli influenced dichotomic responses (beauty or non-beauty). MEG data showed that non-consciously presented portrait paintings induced spatiotemporally distributed low-frequency brain activities associated with aesthetic ratings, which were distinct between the biological and non-biological categories and conscious and non-conscious conditions.ConclusionAesthetic emotion holds evolutionary significance for humans. Neural pathways are sensitive to visual images that arouse aesthetic emotion in distinct ways for biological and non-biological categories, which are further influenced by consciousness. These differences likely reflect the diversity in mechanisms of aesthetic processing, such as processing fluency, active elaboration, and predictive processing. The aesthetic processing of non-conscious stimuli appears to be characterised by fluency-driven affective processing, while top-down regulatory processes are suppressed. This study provides the first empirical evidence supporting the evolutionary significance of aesthetic processing.

Using Activity Measures and GNSS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle.

There has been an increased focus on new technologies to monitor habitat use and behaviour of cattle to develop a more sustainable livestock grazing system without compromising animal welfare. One of the currently used methods for monitoring cattle behaviour is tri-axial accelerometer data from systems such as virtual fencing technology or bespoke monitoring technology. Collection and transmission of high-frequency accelerometer and GNSS data is a major energy cost, and quickly drains the battery in contemporary virtual fencing systems, making it unsuitable for long-term monitoring. In this paper, we explore the possibility of determining habitat preference and habitat utilisation patterns in cattle using low-frequency activity and location data. We achieve this by (1) calculating habitat selection ratios, (2) determining daily activity patterns, and (3) based on those, inferring grazing and resting sites in a group of cattle wearing virtual fencing collars in a coastal setting with grey, wooded, and decalcified dunes, humid dune slacks, and salt meadows. We found that GNSS data, and a measure of activity, combined with accurate mapping of habitats can be an effective tool in assessing habitat preference. The animals preferred salt meadows over the other habitats, with wooded dunes and humid dune slacks being the least preferred. We were able to identify daily patterns in activity. By comparing general trends in activity levels to the existing literature, and using a Gaussian mixture model, it was possible to infer resting and grazing behaviour in the different habitats. According to our inference of behaviour the herd predominantly used the salt meadows for resting and ruminating. The approach used in this study allowed us to use GNSS location data and activity data and combine it with accurate habitat mapping to assess habitat preference and habitat utilisation patterns, which can be an important tool for guiding management decisions.

Electroencephalographic Correlates of Clinical Severity in the Natural history study of RTT and Related Disorders.

This study was undertaken to characterize quantitative electroencephalographic (EEG) features in participants from the Natural history study of RTT and Related Disorders and to assess the potential for these features to act as objective measures of cortical function for Rett syndrome (RTT). EEG amplitude and power features were derived from the resting EEG of 60 females with RTT (median age = 10.7 years) and 26 neurotypical females (median age = 10.6 years). Analyses focus on group differences and within the RTT group, associations between the EEG parameters and clinical severity. For a subset of participants (n = 20), follow-up data were available for assessing the reproducibility of the results and the stability in the parameters over 1 year. Compared to neurotypical participants, participants with RTT had greater amplitude variability and greater low-frequency activity as reflected by greater delta power, more negative 1/f slope, and lower theta/delta, alpha/delta, beta/delta, alpha/theta, and beta/theta ratios. Greater delta power, more negative 1/f slope, and lower power ratios were associated with greater severity. Analyses of year 1 data replicated the associations between 1/f slope and power ratios and clinical severity and demonstrated good within-subject consistency in these measures. Overall, group comparisons reflected a greater predominance of lower versus higher frequency activity in participants with RTT, which is consistent with prior clinical interpretations of resting EEG in this population. The observed associations between the EEG power measures and clinical assessments and the repeatability of these measures underscore the potential for EEG to provide an objective measure of cortical function and clinical severity for RTT. ANN NEUROL 2024;96:175-186.

Asymmetries of the subthalamic activity in Parkinson's disease: phase-amplitude coupling among local field potentials.

The role of brain asymmetries of dopaminergic neurons in motor symptoms of Parkinson's disease is still undefined. Local field recordings from the subthalamic nucleus revealed some neurophysiological biomarkers of the disease: increased beta activity, increased low-frequency activity and high-frequency oscillations. Phase-amplitude coupling coordinates the timing of neuronal activity and allows determining the mechanism for communication within distinct regions of the brain. In this study, we discuss the use of phase-amplitude coupling to assess the differences between the two hemispheres in a cohort of 24 patients with Parkinson's disease before and after levodopa administration. Subthalamic low- (12-20 Hz) and high-beta (20-30 Hz) oscillations were compared with low- (30-45 Hz), medium- (70-100 Hz) and high-frequency (260-360 Hz) bands. We found a significant beta-phase-amplitude coupling asymmetry between left and right and an opposite-side-dependent effect of the pharmacological treatment, which is associated with the reduction of motor symptoms. In particular, high coupling between high frequencies and high-beta oscillations was found during the OFF condition (P < 0.01) and a low coupling during the ON state (P < 0.0001) when the right subthalamus was assessed; exactly the opposite happened when the left subthalamus was considered in the analysis, showing a lower coupling between high frequencies and high-beta oscillations during the OFF condition (P < 0.01), followed by a higher one during the ON state (P < 0.01). Interestingly, these asymmetries are independent of the motor onset side, either left or right. These findings have important implications for neural signals that may be used to trigger adaptive deep brain stimulation in Parkinson's and could provide more exhaustive insights into subthalamic dynamics.

TMS provokes target-dependent intracranial rhythms across human cortical and subcortical sites

BackgroundTranscranial magnetic stimulation (TMS) is believed to alter ongoing neural activity and cause circuit-level changes in brain function. While the electrophysiological effects of TMS have been extensively studied with scalp electroencephalography (EEG), this approach generally evaluates low-frequency neural activity at the cortical surface. However, TMS can be safely used in patients with intracranial electrodes (iEEG), allowing for direct assessment of deeper and more localized oscillatory responses across the frequency spectrum. Objective/HypothesisOur study used iEEG to understand the effects of TMS on human neural activity in the spectral domain. We asked (1) which brain regions respond to cortically-targeted TMS, and in what frequency bands, (2) whether deeper brain structures exhibit oscillatory responses, and (3) whether the neural responses to TMS reflect evoked versus induced oscillations. MethodsWe recruited 17 neurosurgical patients with indwelling electrodes and recorded neural activity while patients underwent repeated trials of single-pulse TMS at either the dorsolateral prefrontal cortex (DLPFC) or parietal cortex. iEEG signals were analyzed using spectral methods to understand the oscillatory responses to TMS. ResultsStimulation to DLPFC drove widespread low-frequency increases (3–8 Hz) in frontolimbic cortices and high-frequency decreases (30–110 Hz) in frontotemporal areas, including the hippocampus. Stimulation to parietal cortex specifically provoked low-frequency responses in the medial temporal lobe. While most low-frequency activity was consistent with phase-locked evoked responses, anterior frontal regions exhibited induced theta oscillations following DLPFC stimulation. ConclusionsBy combining TMS with intracranial EEG recordings, our results suggest that TMS is an effective means to perturb oscillatory neural activity in brain-wide networks, including deeper structures not directly accessed by stimulation itself.

Propagation of nonlinear ion-acoustic fluctuations in the mantle of Venus

Motivated by the observations of ion-acoustic fluctuations with the Parker Solar Probe (PSP) and earlier by the Pioneer Venus Orbiter (PVO) in the Venusian magnetosheath, we investigate the nature of ion-acoustic solitary and double-layer (DL) structures in the mantle. We employed a hydrodynamic description along with reductive perturbation theory to derive the nonlinear Zakharov—Kuznetsov equation that elucidates the dynamics of three-dimensional ion-acoustic wave packets. Using the spacecraft measurements of the plasma configuration at Venus, we carried out a parametric analysis of these structures, including the influence of the magnetic field strength and the relative densities and temperatures, considering two cases: quasi-parallel and oblique propagation. Moreover, we determined the structural characteristics of these waves, where oblique (quasi-parallel) solitary waves have a potential of 0.4 V (0.4 V) and a maximum electric field amplitude Em ~ 0.024 mV m−1 (8 m V m−1) across spatial and temporal widths of ~40–80 km (~140–200 m) and 0.4 s (1.6 ms). These waves produce low-frequency electrostatic activity in the frequency range of 1.6–10 Hz (630–3160 Hz). Quasi-parallel DLs have potential drops of (6.5–13) V and Em ~ (0.16–0.35) mV m−1 with a width and duration of (100–120) m and ~1 ms, and a frequency range of ~630–3980 Hz. These outcomes can explain the detected electrostatic fluctuations above the ionosphere via PVO in the frequency channels of 730 Hz and 5.4 kHz. Furthermore, the DL features estimated in this work are in line with the recent PSP measurements of the DLs propagating in the magnetosheath of Venus.

Comparison of statistical low-frequency earthquake activity models

Slow earthquakes are slow fault slip events. Quantifying and monitoring slow earthquake activity characteristics are important, because they may change before large earthquakes occur. Statistical seismicity models are useful for quantifying seismicity characteristics. However, no standard statistical model exists for slow earthquake activity. This study used a high-quality catalog of low-frequency earthquakes (LFEs), a type of slow earthquake, in the Nankai subduction zone from April 2004 to August 2015 and conducted the first comparison of existing statistical LFE activity models to determine which model better describes LFE activity. Based on this comparison, this study proposes a new hybrid model that incorporates existing model features. The new model considers the LFE activity history in a manner similar to the epidemic-type aftershock sequence (ETAS) model and represents the LFE aftershock rate (subsequent LFE occurrence rate) with a small number of model parameters, as in the Omori–Utsu aftershock law for regular earthquakes. The results show that the proposed model outperforms other existing models. However, the new model cannot reproduce a feature of LFE activity: the sudden cessation of intense LFE bursts. This is because the new model superimposes multiple aftershock activities and predicts extremely high seismicity rates during and after the LFE bursts. I suggest that reproducing and successfully predicting the sudden cessation of intense LFE bursts is critical for the further improvement of statistical LFE activity models. In addition, the empirical equations formulated in this study for the LFE aftershock rates may be useful for future statistical and physical modeling of LFE activity.Graphical

French coastal network for carbonate system monitoring: the CocoriCO2 dataset

Abstract. Since the beginning of the industrial revolution, atmospheric carbon dioxide (CO2) concentrations have risen steadily and have induced a decrease of the averaged surface ocean pH by 0.1 units, corresponding to an increase in ocean acidity of about 30 %. In addition to ocean warming, ocean acidification poses a tremendous challenge to some marine organisms, especially calcifiers. The need for long-term oceanic observations of pH and temperature is a key element to assess the vulnerability of marine communities and ecosystems to these pressures. Nearshore productive environments, where a large majority of shellfish farming activities are conducted, are known to present pH levels as well as amplitudes of daily and seasonal variations that are much larger than those observed in the open ocean. Yet, to date, there are very few coastal observation sites where these parameters are measured simultaneously and at high frequency. To bridge this gap, an observation network was initiated in 2021 in the framework of the CocoriCO2 project. Six sites were selected along the French Atlantic and Mediterranean coastlines based on their importance in terms of shellfish production and the presence of high- and low-frequency monitoring activities. At each site, autonomous pH sensors were deployed, both inside and outside shellfish production areas, next to high-frequency CTD (conductivity–temperature–depth) probes operated through two operating monitoring networks. pH sensors were set to an acquisition rate of 15 min, and discrete seawater samples were collected biweekly in order to control the quality of pH data (laboratory spectrophotometric measurements) as well as to measure total alkalinity and dissolved inorganic carbon concentrations for full characterization of the carbonate system. While this network has been up and running for more than 2 years, the acquired dataset has already revealed important differences in terms of pH variations between monitored sites related to the influence of diverse processes (freshwater inputs, tides, temperature, biological processes). Data are available at https://doi.org/10.17882/96982 (Petton et al., 2023a).