Interhemispheric differences of electroencephalography signal characteristics in different sleep stages.

OBJECTIVE: The current electroencephalography (EEG) measurement setup is complex, laborious to set up, and uncomfortable for patients. We hypothesize that differences in EEG signal characteristics for sleep staging between the left and right hemispheres are negligible; therefore, there is potential to simplify the current measurement setup. We aimed to investigate the technical hemispheric differences in EEG signal characteristics along with electrooculography (EOG) signals during different sleep stages. METHODS: Type II portable polysomnography (PSG) recordings of 50 patients were studied. Amplitudes and power spectral densities (PSDs) of the EEG and EOG signals were compared between the left (C3-M2, F3-M2, O1-M2, and E1-M2) and the right (C4-M1, F4-M1, O2-M1, and E2-M2) hemispheres. Regression analysis was performed to investigate the potential influence of sleep stages on the hemispheric differences in PSDs. Wilcoxon signed-rank tests were also employed to calculate the effect size of hemispheres across different frequency bands and sleep stages. RESULTS: The results showed statistically significant differences in signal characteristics between hemispheres, but the absolute differences were minor. The median hemispheric differences in amplitudes were smaller than 3 µv with large interquartile ranges during all sleep stages. The absolute and relative PSD characteristics were highly similar between hemispheres in different sleep stages. Additionally, there were negligible differences in the effect size between hemispheres across all sleep stages. CONCLUSIONS: Technical signal differences between hemispheres were minor across all sleep stages, indicating that both hemispheres contain similar information needed for sleep staging. A reduced measurement setup could be suitable for sleep staging without the loss of relevant information.

EEG and fNIRS datasets based on Stroop task during two weeks of high-altitude exposure in new immigrants.

Maintaining sufficient cerebral oxygen metabolism is crucial for human survival, especially in challenging conditions such as high-altitudes. Human cognitive neural activity is sensitive to fluctuations in oxygen levels. However, there is a lack of publicly available datasets on human behavioural responses and cerebral dynamics assessments during the execution of conflicting tasks in natural hypoxic environments. We recruited 80 healthy new immigrant volunteers (males, aged 20 ± 2 years) and employed the Stroop cognitive conflict paradigm. After a two-week exposure to both high and low-altitudes, the behavioural performance, prefrontal oxygen levels, and electroencephalography (EEG) signals were recorded. Comparative analyses were conducted on the behavioural reaction times and accuracy during Stroop tasks, and statistical analyses of participants' prefrontal oxygen levels and EEG signals were performed. We anticipate that our open-access dataset will contribute to the development of monitoring devices and algorithms, designed specifically for measuring cerebral oxygen and EEG dynamics in populations exposed to extreme environments, particularly among individuals suffering from oxygen deficiency.

Prediction error in implicit adaptation during visually- and memory-guided reaching tasks.

Human movements are adjusted by motor adaptation in order to maintain their accuracy. There are two systems in motor adaptation, referred to as explicit or implicit adaptation. It has been suggested that the implicit adaptation is based on the prediction error and has been used in a number of motor adaptation studies. This study aimed to examine the effect of visual memory on prediction error in implicit visuomotor adaptation by comparing visually- and memory-guided reaching tasks. The visually-guided task is thought to be implicit learning based on prediction error, whereas the memory-guided task requires more cognitive processes. We observed the adaptation to visuomotor rotation feedback that is gradually rotated. We found that the adaptation and retention rates were higher in the visually-guided task than in the memory-guided task. Furthermore, the delta-band power obtained by electroencephalography (EEG) in the visually-guided task was increased immediately following the visual feedback, which indicates that the prediction error was larger in the visually-guided task. Our results show that the visuomotor adaptation is enhanced in the visually-guided task because the prediction error, which contributes update of the internal model, was more reliable than in the memory-guided task. Therefore, we suggest that the processing of the prediction error is affected by the task-type, which in turn affects the rate of the visuomotor adaptation.

Open access EEG dataset of repeated measurements from a single subject for microstate analysis.

Electroencephalography (EEG) microstate analysis is a neuroimaging analytical method that has received considerable attention in recent years and is widely used for analysing EEG signals. EEG is easily influenced by internal and external factors, which can affect the repeatability and stability of EEG microstate analysis. However, there have been few reports and publicly available datasets on the repeatability of EEG microstate analysis. In the current study, a 39-year-old healthy male underwent a total of 60 simultaneous electroencephalography and electrocardiogram measurements over a period of three months. After the EEG recording was completed, magnetic resonance imaging (MRI) was also conducted. To date, this EEG dataset has the highest number of repeated measurements for one individual. The dataset can be used to assess the stability and repeatability of EEG microstates and other analytical methods, to decode resting EEG states among subjects with open eyes, and to explore the stability and repeatability of cortical spatiotemporal dynamics through source analysis with individual MRI.

Association of Localizing 18F-FDG-PET Hypometabolism and Outcome Following Epilepsy Surgery: Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Although commonly used in the evaluation of patients for epilepsy surgery, the association between the detection of localizing 18fluorine fluorodeoxyglucose PET (18F-FDG-PET) hypometabolism and epilepsy surgery outcome is uncertain. We conducted a systematic review and meta-analysis to determine whether localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery. METHODS: A systematic literature search was undertaken. Eligible publications included evaluation with 18F-FDG-PET before epilepsy surgery, with ≥10 participants, and those that reported surgical outcome at ≥12 months. Random-effects meta-analysis was used to calculate the odds of achieving a favorable outcome, defined as Engel class I, International League Against Epilepsy class 1-2, or seizure-free, with localizing 18F-FDG-PET hypometabolism, defined as concordant with the epilepsy surgery resection zone. Meta-regression was used to characterize sources of heterogeneity. RESULTS: The database search identified 8,916 studies, of which 98 were included (total patients n = 4,104). Localizing 18F-FDG-PET hypometabolism was associated with favorable outcome after epilepsy surgery for all patients with odds ratio (OR) 2.68 (95% CI 2.08-3.45). Subgroup analysis yielded similar findings for those with (OR 2.64, 95% CI 1.54-4.52) and without epileptogenic lesion detected on MRI (OR 2.49, 95% CI 1.80-3.44). Concordance with EEG (OR 2.34, 95% CI 1.43-3.83), MRI (OR 1.69, 95% CI 1.19-2.40), and triple concordance with both (OR 2.20, 95% CI 1.32-3.64) was associated with higher odds of favorable outcome. By contrast, diffuse 18F-FDG-PET hypometabolism was associated with worse outcomes compared with focal hypometabolism (OR 0.34, 95% CI 0.22-0.54). DISCUSSION: Localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery, irrespective of the presence of an epileptogenic lesion on MRI. The extent of 18F-FDG-PET hypometabolism provides additional information, with diffuse hypometabolism associated with worse surgical outcome than focal 18F-FDG-PET hypometabolism. These findings support the incorporation of 18F-FDG-PET into routine noninvasive investigations for patients being evaluated for epilepsy surgery to improve epileptogenic zone localization and to aid patient selection for surgery.

Prefrontal intra-individual ERP variability and its asymmetry: exploring its biomarker potential in mild cognitive impairment.

BACKGROUND: The worldwide trend of demographic aging highlights the progress made in healthcare, albeit with health challenges like Alzheimer's Disease (AD), prevalent in individuals aged 65 and above. Its early detection at the mild cognitive impairment (MCI) stage is crucial. Event-related potentials (ERPs) obtained by averaging EEG segments responded to repeated events are vital for cognitive impairment research. Consequently, examining intra-trial ERP variability is vital for comprehending fluctuations within psychophysiological processes of interest. This study aimed to investigate cognitive deficiencies and instability in MCI using ERP variability and its asymmetry from a prefrontal two-channel EEG device. METHODS: In this study, ERP variability for both target and non-target responses was examined using the response variance curve (RVC) in a sample comprising 481 participants with MCI and 1,043 age-matched healthy individuals. The participants engaged in auditory selective attention tasks. Cognitive decline was assessed using the Seoul Neuropsychological Screening Battery (SNSB) and the Mini-Mental State Examination (MMSE). The research employed various statistical methods, including independent t-tests, and univariate and multiple logistic regression analyses. These analyses were conducted to investigate group differences and explore the relationships between neuropsychological test results, ERP variability and its asymmetry measures, and the prevalence of MCI. RESULTS: Our results showed that patients with MCI exhibited unstable cognitive processing, characterized by increased ERP variability compared to cognitively normal (CN) adults. Multiple logistic regression analyses confirmed the association between ERP variability in the target and non-target responses with MCI prevalence, independent of demographic and neuropsychological factors. DISCUSSION: The unstable cognitive processing in the MCI group compared to the CN individuals implies abnormal neurological changes and reduced and (or) unstable attentional maintenance during cognitive processing. Consequently, utilizing ERP variability measures from a portable EEG device could serve as a valuable addition to the conventional ERP measures of latency and amplitude. This approach holds significant promise for identifying mild cognitive deficits and neural alterations in individuals with MCI.

Tracking the habituation of the event-related EEG potential in automatic change detection using an auditory two-tone oddball paradigm.

The mismatch negativity and the P3a of the event-related EEG potential reflect the electrocortical response to a deviant stimulus in a series of stimuli. Although both components have been investigated in various paradigms, these paradigms usually incorporate many repetitions of the same deviant, thus leaving open whether both components vary as a function of the deviant's position in a series of deviant stimuli-i.e. whether they are subject to qualitative/quantitative habituation from one instantiation of a deviant to the next. This is so because the detection of mismatch negativity/P3a in the event-related EEG potential requires an averaging over dozens or hundreds of stimuli, i.e. over many instantiations of the deviant per participant. The present study addresses this research gap. We used a two-tone oddball paradigm implementing only a small number of (deviant) stimuli per participant, but applying it to a large number of participants (n > 230). Our data show that the mismatch negativity amplitude exhibits no decrease as a function of the deviant's position in a series of (standard and) deviant stimuli. Importantly, only after the very first deviant stimulus, a distinct P3a could be detected, indicative of an orienting reaction and an attention shift, and thus documenting a dissociation of mismatch negativity and P3a.

[Development of Wireless Wearable Sleep Monitoring System Based on EEG Signal].

A wireless wearable sleep monitoring system based on EEG signals is developed. The collected EEG signals are wirelessly sent to the PC or mobile phone Bluetooth APP for real-time display. The system is small in size, low in power consumption, and light in weight. It can be worn on the patient's forehead and is comfortable. It can be applied to home sleep monitoring scenarios and has good application value. The key performance indicators of the system are compared with the industry-related medical device measurement standards, and the measurement results are better than the special standards.

The effects of multi-colour light filtering glasses on human brain wave activity.

The prevalence of electronic screens in modern society has significantly increased our exposure to high-energy blue and violet light wavelengths. Accumulating evidence links this exposure to adverse visual and cognitive effects and sleep disturbances. To mitigate these effects, the optical industry has introduced a variety of filtering glasses. However, the scientific validation of these glasses has often been based on subjective reports and a narrow range of objective measures, casting doubt on their true efficacy. In this study, we used electroencephalography (EEG) to record brain wave activity to evaluate the effects of glasses that filter multiple wavelengths (blue, violet, indigo, and green) on human brain activity. Our results demonstrate that wearing these multi-colour light filtering glasses significantly reduces beta wave power (13-30 Hz) compared to control or no glasses. Prior research has associated a reduction in beta power with the calming of heightened mental states, such as anxiety. As such, our results suggest that wearing glasses such as the ones used in this study may also positively change mental states, for instance, by promoting relaxation. This investigation is innovative in applying neuroimaging techniques to confirm that light-filtering glasses can induce measurable changes in brain activity.

A Multivariate analysis on evoked components of Chinese semantic congruity: an OP-MEG study with EEG.

The application of wearable magnetoencephalography using optically-pumped magnetometers has drawn extensive attention in the field of neuroscience. Electroencephalogram system can cover the whole head and reflect the overall activity of a large number of neurons. The efficacy of optically-pumped magnetometer in detecting event-related components can be validated through electroencephalogram results. Multivariate pattern analysis is capable of tracking the evolution of neurocognitive processes over time. In this paper, we adopted a classical Chinese semantic congruity paradigm and separately collected electroencephalogram and optically-pumped magnetometer signals. Then, we verified the consistency of optically-pumped magnetometer and electroencephalogram in detecting N400 using mutual information index. Multivariate pattern analysis revealed the difference in decoding performance of these two modalities, which can be further validated by dynamic/stable coding analysis on the temporal generalization matrix. The results from searchlight analysis provided a neural basis for this dissimilarity at the magnetoencephalography source level and the electroencephalogram sensor level. This study opens a new avenue for investigating the brain's coding patterns using wearable magnetoencephalography and reveals the differences in sensitivity between the two modalities in reflecting neuron representation patterns.

The EEG-Based Fusion Entropy-Featured Identification of Isometric Contraction Forces under the Same Action.

This study explores the important role of assessing force levels in accurately controlling upper limb movements in human-computer interfaces. It uses a new method that combines entropy to improve the recognition of force levels. This research aims to differentiate between different levels of isometric contraction forces using electroencephalogram (EEG) signal analysis. It integrates eight different entropy measures: power spectrum entropy (PSE), singular spectrum entropy (SSE), logarithmic energy entropy (LEE), approximation entropy (AE), sample entropy (SE), fuzzy entropy (FE), alignment entropy (PE), and envelope entropy (EE). The findings emphasize two important advances: first, including a wide range of entropy features significantly improves classification efficiency; second, the fusion entropy method shows exceptional accuracy in classifying isometric contraction forces. It achieves an accuracy rate of 91.73% in distinguishing between 15% and 60% maximum voluntary contraction (MVC) forces, along with 69.59% accuracy in identifying variations across 15%, 30%, 45%, and 60% MVC. These results illuminate the efficacy of employing fusion entropy in EEG signal analysis for isometric contraction detection, heralding new opportunities for advancing motor control and facilitating fine motor movements through sophisticated human-computer interface technologies.

Towards ASSR-based hearing assessment using natural sounds.

Objective. The auditory steady-state response (ASSR) allows estimation of hearing thresholds. The ASSR can be estimated from electroencephalography (EEG) recordings from electrodes positioned on both the scalp and within the ear (ear-EEG). Ear-EEG can potentially be integrated into hearing aids, which would enable automatic fitting of the hearing device in daily life. The conventional stimuli for ASSR-based hearing assessment, such as pure tones and chirps, are monotonous and tiresome, making them inconvenient for repeated use in everyday situations. In this study we investigate the use of natural speech sounds for ASSR estimation.Approach.EEG was recorded from 22 normal hearing subjects from both scalp and ear electrodes. Subjects were stimulated monaurally with 180 min of speech stimulus modified by applying a 40 Hz amplitude modulation (AM) to an octave frequency sub-band centered at 1 kHz. Each 50 ms sub-interval in the AM sub-band was scaled to match one of 10 pre-defined levels (0-45 dB sensation level, 5 dB steps). The apparent latency for the ASSR was estimated as the maximum average cross-correlation between the envelope of the AM sub-band and the recorded EEG and was used to align the EEG signal with the audio signal. The EEG was then split up into sub-epochs of 50 ms length and sorted according to the stimulation level. ASSR was estimated for each level for both scalp- and ear-EEG.Main results. Significant ASSRs with increasing amplitude as a function of presentation level were recorded from both scalp and ear electrode configurations.Significance. Utilizing natural sounds in ASSR estimation offers the potential for electrophysiological hearing assessment that are more comfortable and less fatiguing compared to existing ASSR methods. Combined with ear-EEG, this approach may allow convenient hearing threshold estimation in everyday life, utilizing ambient sounds. Additionally, it may facilitate both initial fitting and subsequent adjustments of hearing aids outside of clinical settings.

Exploring the possible relationship between skin microbiome and brain cognitive functions: a pilot EEG study.

Human microbiota mainly resides on the skin and in the gut. Human gut microbiota can produce a variety of short chain fatty acids (SCFAs) that affect many physiological functions and most importantly modulate brain functions through the bidirectional gut-brain axis. Similarly, skin microorganisms also have identical metabolites of SCFAs reported to be involved in maintaining skin homeostasis. However, it remains unclear whether these SCFAs produced by skin bacteria can affect brain cognitive functions. In this study, we hypothesize that the brain's functional activities are associated with the skin bacterial population and examine the influence of local skin-bacterial growth on event-related potentials (ERPs) during an oddball task using EEG. Additionally, five machine learning (ML) methods were employed to discern the relationship between skin microbiota and cognitive functions. Twenty healthy subjects underwent three rounds of tests under different conditions-alcohol, glycerol, and water. Statistical tests confirmed a significant increase in bacterial population under water and glycerol conditions when compared to the alcohol condition. The metabolites of bacteria can turn phenol red from red-orange to yellow, confirming an increase in acidity. P3 amplitudes were significantly enhanced in response to only oddball stimulus at four channels (Fz, FCz, and Cz) and were observed after the removal of bacteria when compared with that under the water and glycerol manipulations. By using machine learning methods, we demonstrated that EEG features could be separated with a good accuracy (> 88%) after experimental manipulations. Our results suggest a relationship between skin microbiota and brain functions. We hope our findings motivate further study into the underlying mechanism. Ultimately, an understanding of the relationship between skin microbiota and brain functions can contribute to the treatment and intervention of diseases that link with this pathway.

Favoritism or bias? Cooperation and competition under different intergroup relationships: evidence from EEG hyperscanning.

Cooperation and competition are the most common forms of social interaction in various social relationships. Intergroup relationships have been posited to influence individuals' interpersonal interactions significantly. Using electroencephalography hyperscanning, this study aimed to establish whether intergroup relationships influence interpersonal cooperation and competition and the underlying neural mechanisms. According to the results, the in-group Coop-index is better than the out-group, whereas the out-group Comp-index is stronger than the in-group. The in-group functional connectivity between the frontal-central region and the right temporoparietal junction in the ß band was stronger in competition than cooperation. The out-group functional connectivity between the frontal-central region and the left temporoparietal junction in the α band was stronger in cooperation than competition. In both cooperation and competition, the in-group exhibited higher interbrain synchronization between the prefrontal cortex and parietal region in the θ band, as well as between the frontal-central region and frontal-central region in the α band, compared to the out-group. The intrabrain phase-locking value in both the α and ß bands can effectively predict performance in competition tasks. Interbrain phase-locking value in both the α and θ bands can be effectively predicted in a performance cooperation task. This study offers neuroscientific evidence for in-group favoritism and out-group bias at an interpersonal level.

Dynamical modulation of hypersynchronous seizure onset with transcranial magneto-acoustic stimulation in a hippocampal computational model.

Hypersynchronous (HYP) seizure onset is one of the frequently observed seizure-onset patterns in temporal lobe epileptic animals and patients, often accompanied by hippocampal sclerosis. However, the exact mechanisms and ion dynamics of the transition to HYP seizures remain unclear. Transcranial magneto-acoustic stimulation (TMAS) has recently been proposed as a novel non-invasive brain therapy method to modulate neurological disorders. Therefore, we propose a biophysical computational hippocampal network model to explore the evolution of HYP seizure caused by changes in crucial physiological parameters and design an effective TMAS strategy to modulate HYP seizure onset. We find that the cooperative effects of abnormal glial uptake strength of potassium and excessive bath potassium concentration could produce multiple discharge patterns and result in transitions from the normal state to the HYP seizure state and ultimately to the depolarization block state. Moreover, we find that the pyramidal neuron and the PV+ interneuron in HYP seizure-onset state exhibit saddle-node-on-invariant-circle/saddle homoclinic (SH) and saddle-node/SH at onset/offset bifurcation pairs, respectively. Furthermore, the response of neuronal activities to TMAS of different ultrasonic waveforms revealed that lower sine wave stimulation can increase the latency of HYP seizures and even completely suppress seizures. More importantly, we propose an ultrasonic parameter area that not only effectively regulates epileptic rhythms but also is within the safety limits of ultrasound neuromodulation therapy. Our results may offer a more comprehensive understanding of the mechanisms of HYP seizure and provide a theoretical basis for the application of TMAS in treating specific types of seizures.

Prognostic Value of Complete Resection of the High-Frequency Oscillation Area in Intracranial EEG: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: High-frequency oscillations (HFOs; ripples 80-250 Hz; fast ripples [FRs] 250-500 Hz) recorded with intracranial electrodes generated excitement and debate about their potential to localize epileptogenic foci. We performed a systematic review and meta-analysis on the prognostic value of complete resection of the HFOs-area (crHFOs-area) for epilepsy surgical outcome in intracranial EEG (iEEG) accessing multiple subgroups. METHODS: We searched PubMed, Embase, and Web of Science for original research from inception to October 27, 2022. We defined favorable surgical outcome (FSO) as Engel class I, International League Against Epilepsy class 1, or seizure-free status. The prognostic value of crHFOs-area for FSO was assessed by (1) the pooled FSO proportion after crHFOs-area; (2) FSO for crHFOs-area vs without crHFOs-area; and (3) the predictive performance. We defined high combined prognostic value as FSO proportion >80% + FSO crHFOs-area >without crHFOs-area + area under the curve (AUC) >0.75 and examined this for the clinical subgroups (study design, age, diagnostic type, HFOs-identification method, HFOs-rate thresholding, and iEEG state). Temporal lobe epilepsy (TLE) was compared with extra-TLE through dichotomous variable analysis. Individual patient analysis was performed for sex, affected hemisphere, MRI findings, surgery location, and pathology. RESULTS: Of 1,387 studies screened, 31 studies (703 patients) met our eligibility criteria. Twenty-seven studies (602 patients) analyzed FRs and 20 studies (424 patients) ripples. Pooled FSO proportion after crHFOs-area was 81% (95% CI 76%-86%) for FRs and 82% (73%-89%) for ripples. Patients with crHFOs-area achieved more often FSO than those without crHFOs-area (FRs odds ratio [OR] 6.38, 4.03-10.09, p < 0.001; ripples 4.04, 2.32-7.04, p < 0.001). The pooled AUCs were 0.81 (0.77-0.84) for FRs and 0.76 (0.72-0.79) for ripples. Combined prognostic value was high in 10 subgroups: retrospective, children, long-term iEEG, threshold (FRs and ripples) and automated detection and interictal (FRs). FSO after complete resection of FRs-area (crFRs-area) was achieved less often in people with TLE than extra-TLE (OR 0.37, 0.15-0.89, p = 0.006). Individual patient analyses showed that crFRs-area was seen more in patients with FSO with than without MRI lesions (p = 0.02 after multiple correction). DISCUSSION: Complete resection of the brain area with HFOs is associated with good postsurgical outcome. Its prognostic value holds, especially for FRs, for various subgroups. The use of HFOs for extra-TLE patients requires further evidence.

[Effects of antenatal corticosteroid therapy in pregnant women on the brain development of preterm infants as assessed by amplitude-integrated electroencephalography]. / æŒ¯å¹ æ•´åˆè„‘ç”µå›¾è¯„ä¼°å­•å¦‡äº§å‰ç³–çš®è´¨æ¿€ç´ æ²»ç–—å¯¹æ—©äº§å„¿è„‘å‘è‚²çš„å½±å“.

OBJECTIVES: To investigate the effects of antenatal corticosteroid (ACS) therapy in pregnant women on the brain development of preterm infants using amplitude-integrated electroencephalography (aEEG). METHODS: A retrospective analysis was conducted on 211 preterm infants with a gestational age of 28 to 34+6 weeks. The infants were divided into an ACS group (131 cases) and a control group (80 cases) based on whether antenatal dexamethasone was given for promoting fetal lung maturity. The first aEEG monitoring (referred to as aEEG1) was performed within 24 hours after birth, and the second aEEG monitoring (referred to as aEEG2) was performed between 5 to 7 days after birth. The aEEG results were compared between the two groups. RESULTS: In preterm infants with a gestational age of 28 to 31+6 weeks, the ACS group showed a more mature periodic pattern and higher lower amplitude boundary in aEEG1 compared to the control group (P<0.05). In preterm infants with a gestational age of 32 to 33+6 weeks and 34 to 34+6 weeks, the ACS group showed a higher proportion of continuous patterns, more mature periodic patterns and higher Burdjalov scores in aEEG1 (P<0.05). And the ACS group exhibited a higher proportion of continuous patterns, more mature periodic patterns, higher lower amplitude boundaries, narrower bandwidths, and higher Burdjalov scores in aEEG2 (P<0.05). CONCLUSIONS: ACS-treated preterm infants have more mature aEEG patterns compared to those not treated with ACS, suggesting a beneficial effect of ACS on the brain development of preterm infants.

Subjective effects of broadband water sounds with inaudible high-frequency components.

This study aimed to investigate the effects of reproducing an ultrasonic sound above 20 kHz on the subjective impressions of water sounds using psychological and physiological information obtained by the semantic differential method and electroencephalography (EEG), respectively. The results indicated that the ultrasonic component affected the subjective impression of the water sounds. In addition, regarding the relationship between psychological and physiological aspects, a moderate correlation was confirmed between the EEG change rate and subjective impressions. However, no differences in characteristics were found between with and without the ultrasound component, suggesting that ultrasound does not directly affect the relationship between subjective impressions and EEG energy at the current stage. Furthermore, the correlations calculated for the left and right channels in the occipital region differed significantly, which suggests functional asymmetry for sound perception between the right and left hemispheres.

Timing along the cardiac cycle modulates neural signals of reward-based learning.

Natural fluctuations in cardiac activity modulate brain activity associated with sensory stimuli, as well as perceptual decisions about low magnitude, near-threshold stimuli. However, little is known about the relationship between fluctuations in heart activity and other internal representations. Here we investigate whether the cardiac cycle relates to learning-related internal representations - absolute and signed prediction errors. We combined machine learning techniques with electroencephalography with both simple, direct indices of task performance and computational model-derived indices of learning. Our results demonstrate that just as people are more sensitive to low magnitude, near-threshold sensory stimuli in certain cardiac phases, so are they more sensitive to low magnitude absolute prediction errors in the same cycles. However, this occurs even when the low magnitude prediction errors are associated with clearly suprathreshold sensory events. In addition, participants exhibiting stronger differences in their prediction error representations between cardiac cycles exhibited higher learning rates and greater task accuracy.

Alterations of the alpha rhythm in visual snow syndrome: a case-control study.

BACKGROUND: Visual snow syndrome is a disorder characterized by the combination of typical perceptual disturbances. The clinical picture suggests an impairment of visual filtering mechanisms and might involve primary and secondary visual brain areas, as well as higher-order attentional networks. On the level of cortical oscillations, the alpha rhythm is a prominent EEG pattern that is involved in the prioritisation of visual information. It can be regarded as a correlate of inhibitory modulation within the visual network. METHODS: Twenty-one patients with visual snow syndrome were compared to 21 controls matched for age, sex, and migraine. We analysed the resting-state alpha rhythm by identifying the individual alpha peak frequency using a Fast Fourier Transform and then calculating the power spectral density around the individual alpha peak (+/- 1 Hz). We anticipated a reduced power spectral density in the alpha band over the primary visual cortex in participants with visual snow syndrome. RESULTS: There were no significant differences in the power spectral density in the alpha band over the occipital electrodes (O1 and O2), leading to the rejection of our primary hypothesis. However, the power spectral density in the alpha band was significantly reduced over temporal and parietal electrodes. There was also a trend towards increased individual alpha peak frequency in the subgroup of participants without comorbid migraine. CONCLUSIONS: Our main finding was a decreased power spectral density in the alpha band over parietal and temporal brain regions corresponding to areas of the secondary visual cortex. These findings complement previous functional and structural imaging data at a electrophysiological level. They underscore the involvement of higher-order visual brain areas, and potentially reflect a disturbance in inhibitory top-down modulation. The alpha rhythm alterations might represent a novel target for specific neuromodulation. TRIAL REGISTRATION: we preregistered the study before preprocessing and data analysis on the platform osf.org (DOI: https://doi.org/10.17605/OSF.IO/XPQHF , date of registration: November 19th 2022).