Brain Dynamics Altered by Photic Stimulation in Patients with Alzheimer’s Disease and Mild Cognitive Impairment

Individuals with mild cognitive impairment (MCI) are at high risk of developing Alzheimer’s disease (AD). Repetitive photic stimulation (PS) is commonly used in routine electroencephalogram (EEG) examinations for rapid assessment of perceptual functioning. This study aimed to evaluate neural oscillatory responses and nonlinear brain dynamics under the effects of PS in patients with mild AD, moderate AD, severe AD, and MCI, as well as healthy elderly controls (HC). EEG power ratios during PS were estimated as an index of oscillatory responses. Multiscale sample entropy (MSE) was estimated as an index of brain dynamics before, during, and after PS. During PS, EEG harmonic responses were lower and MSE values were higher in the AD subgroups than in HC and MCI groups. PS-induced changes in EEG complexity were less pronounced in the AD subgroups than in HC and MCI groups. Brain dynamics revealed a “transitional change” between MCI and Mild AD. Our findings suggest a deficiency in brain adaptability in AD patients, which hinders their ability to adapt to repetitive perceptual stimulation. This study highlights the importance of combining spectral and nonlinear dynamical analysis when seeking to unravel perceptual functioning and brain adaptability in the various stages of neurodegenerative diseases.     

Noise and sleep at home,a field study on primary and after-effects

The sleep of 20 healthy subjects (10 male, 10 female, 25–63 years) who lived more than one year in streets with high traffic load were recorded during 12 consecutive nights each. Throughout every night EEG, EOG, and sound pressure levels were recorded. In the morning and in the evening as well the subjects completed a short questionnaire and executed a reaction time test. During the experimental phase (five nights) noise level was attenuated by earplugs in 10 subjects, and the other 10 subjects who usually slept with closed windows slept with open windows. Compared to the control nights the 1%-noise level changed by 9 dB(A). In comparison with other variables (age, sex, personality) noise influenced the course of sleep slightly. Small negative effects were found for some physiological, for subjective, and for performance data indicating that there is no (complete) habituation to the usual acoustical environment.     

Topography-specific spindle frequency changes in Obstructive Sleep Apnea

Background

Sleep spindles, as detected on scalp electroencephalography (EEG), are considered to be markers of thalamo-cortical network integrity. Since obstructive sleep apnea (OSA) is a known cause of brain dysfunction, the aim of this study was to investigate sleep spindle frequency distribution in OSA. Seven non-OSA subjects and 21 patients with OSA (11 mild and 10 moderate) were studied. A matching pursuit procedure was used for automatic detection of fast (≥13Hz) and slow (<13Hz) spindles obtained from 30min samples of NREM sleep stage 2 taken from initial, middle and final night thirds (sections I, II and III) of frontal, central and parietal scalp regions.

Results

Compared to non-OSA subjects, Moderate OSA patients had higher central and parietal slow spindle percentage (SSP) in all night sections studied, and higher frontal SSP in sections II and III. As the night progressed, there was a reduction in central and parietal SSP, while frontal SSP remained high. Frontal slow spindle percentage in night section III predicted OSA with good accuracy, with OSA likelihood increased by 12.1%for every SSP unit increase (OR 1.121, 95% CI 1.013 - 1.239, p=0.027).

Conclusions

These results are consistent with diffuse, predominantly frontal thalamo-cortical dysfunction during sleep in OSA, as more posterior brain regions appear to maintain some physiological spindle frequency modulation across the night. Displaying changes in an opposite direction to what is expected from the aging process itself, spindle frequency appears to be informative in OSA even with small sample sizes, and to represent a sensitive electrophysiological marker of brain dysfunction in OSA.

     

Cortisol response and subjective sleep disturbance after low-frequency noise exposure

A previous experimental study showed that the cortisol response upon awakening was reduced following nights with low-frequency noise exposure. This study comprised a larger number of subjects and an extended period of acclimatisation nights. In total, 26 male subjects slept during five consecutive nights in a sleep laboratory. Half of the subjects were exposed to low-frequency noise (40 dBA) on the 4th night and had their reference night (24 dBA) on the 5th night, while the reverse conditions were present for the other half of the group. Subjective sleep disturbances were recorded by questionnaires and cortisol response upon awakening was measured in saliva. The results showed that subjects were more tired and felt less socially orientated in the morning after nights with low-frequency noise. Mood was negatively affected in the evening after nights with low-frequency noise. No effect of noise condition was found on the cortisol secretion. There was a significant effect of group and weekday, indicating that further methodological developments are necessary before saliva cortisol secretion can be reliably used as an indicator of noise-disturbed sleep.     

A field study of effects of road traffic and railway noise on polysomnographic sleep parameters

The aim of this study was to explore and compare the effect of noise from railway and road traffic on sleep in subjects habitually exposed to nocturnal noise. Forty young and middle aged healthy subjects were studied with polysomnography (PSG) during two consecutive nights in their own bedroom. Noise measurements and recordings were conducted concurrently outside of the bedroom fac?ade as well as inside the bedroom of each participant. Different noise exposure parameters were calculated (L(p,A,eq,night), L(p,A,Fmax,night), and L(AF5,night)) and analyzed in relation to whole-night sleep parameters. The group exposed to railway noise had significantly less Rapid eye movement, (REM) sleep than the group exposed to road traffic noise. A significant association was found between the maximum level (L(p,A,Fmax,night)) of railway noise and time spent in REM sleep. REM sleep was significantly shorter in the group exposed to at least a single railway noise event above 50 dB inside the bedroom. These results, obtained in an ecological valid setting, support previous laboratory findings that railway noise has a stronger impact than road traffic noise on physiological parameters during sleep, and that the maximum noise level is an important predictor of noise effects on sleep assessed by PSG, at least for railway noise.     

Working Memory Decline in Alzheimer’s Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS

Alzheimer’s disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey–Osterrieth complex figure and Raven’s progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.     

Approximate Entropy of Brain Network in the Study of Hemispheric Differences

Human brain, a dynamic complex system, can be studied with different approaches, including linear and nonlinear ones. One of the nonlinear approaches widely used in electroencephalographic (EEG) analyses is the entropy, the measurement of disorder in a system. The present study investigates brain networks applying approximate entropy (ApEn) measure for assessing the hemispheric EEG differences; reproducibility and stability of ApEn data across separate recording sessions were evaluated. Twenty healthy adult volunteers were submitted to eyes-closed resting EEG recordings, for 80 recordings. Significant differences in the occipital region, with higher values of entropy in the left hemisphere than in the right one, show that the hemispheres become active with different intensities according to the performed function. Besides, the present methodology proved to be reproducible and stable, when carried out on relatively brief EEG epochs but also at a 1-week distance in a group of 36 subjects. Nonlinear approaches represent an interesting probe to study the dynamics of brain networks. ApEn technique might provide more insight into the pathophysiological processes underlying age-related brain disconnection as well as for monitoring the impact of pharmacological and rehabilitation treatments.     

A comparative study of magnetic resonance venography techniques for the evaluation of the internal jugular veins in multiple sclerosis patients

Background and Purpose

The use of magnetic resonance imaging (MRI) to assess the vascular nature of diseases such as multiple sclerosis (MS) is a growing field of research. This work reports on the application of MR angiographic (MRA) and venographic (MRV) techniques in assessing the extracranial vasculature in MS patients.

Materials and Methods

A standardized MRI protocol containing 2D TOF-MRV and dynamic 3D contrast-enhanced (CE) MRAV was run for 170 MS patients and 40 healthy controls (HC). The cross-sectional area (CSA) of the internal jugular veins (IJVs) was measured at three neck levels in all subjects for both MRV techniques to determine the presence of venous stenoses. All data were analyzed retrospectively.

Results

For the values where both methods showed signal, the 3D method showed larger CSA measurement values compared to 2D methods in both IJVs, in both MS and HC subjects which was confirmed with student paired t-tests. Of the 170 MS patients, 93 (55%) in CE-MRAV and 103 (61%) in TOF-MRV showed stenosis in at least one IJV. The corresponding numbers for the 40 HC subjects were 2 (5%) and 4 (10%), respectively. Carotid ectasias with IJV stenosis were seen in 26 cases (15%) with 3D CE-MRAV and were not observable with 2D TOF-MRV. Carotid ectasias were not seen in the HC group. In the 2D TOF-MRV data, banding of the IJVs related to slow flow was seen in 58 (34%) MS cases and in no HC cases. MS patients showed lower average CSAs than the HC subjects.

Conclusion

The 3D CE MRAV depicted the vascular anatomy more completely than the 2D TOF-MRV. However, the 3D CE MRAV does not provide any information about the flow characteristics which are indirectly available in the 2D TOF-MRV in those cases where there is slow flow.     

Assessing severity of obstructive sleep apnea by fractal dimension sequence analysis of sleep EEG

Different sleep stages are associated with distinct dynamical patterns in EEG signals. In this article, we explored the relationship between the sleep architecture and fractal dimension (FD) of sleep EEG. In particular, we applied the FD analysis to the sleep EEG of patients with obstructive sleep apnea-hypopnea syndrome (OSAHS), which is characterized by recurrent oxyhemoglobin desaturation and arousals from sleep, a disease which received increasing public attention due to its significant potential impact on health. We showed that the variation of FD reflects the macrostructure of sleep. Furthermore, the fast fluctuation of FD, as measured by the zero-crossing rate of detrended FD (zDFD), is a useful indicator of sleep disturbance, and therefore, correlates with apnea-hypopnea index (AHI), and hourly number of blood oxygen saturation (SpO₂) decreases greater than 4%, as obstructive apnea/hypopnea disturbs sleep architecture. For practical purpose, a modified index combining zDFD of EEG and body mass index (BMI) may be useful for evaluating the severity of OSAHS symptoms.     

Neurofeedback Training Based on Motor Imagery Strategies Increases EEG Complexity in Elderly Population

Neurofeedback training (NFT) has shown promising results in recent years as a tool to address the effects of age-related cognitive decline in the elderly. Since previous studies have linked reduced complexity of electroencephalography (EEG) signal to the process of cognitive decline, we propose the use of non-linear methods to characterise changes in EEG complexity induced by NFT. In this study, we analyse the pre- and post-training EEG from 11 elderly subjects who performed an NFT based on motor imagery (MI–NFT). Spectral changes were studied using relative power (RP) from classical frequency bands (delta, theta, alpha, and beta), whilst multiscale entropy (MSE) was applied to assess EEG-induced complexity changes. Furthermore, we analysed the subject’s scores from Luria tests performed before and after MI–NFT. We found that MI–NFT induced a power shift towards rapid frequencies, as well as an increase of EEG complexity in all channels, except for C3. These improvements were most evident in frontal channels. Moreover, results from cognitive tests showed significant enhancement in intellectual and memory functions. Therefore, our findings suggest the usefulness of MI–NFT to improve cognitive functions in the elderly and encourage future studies to use MSE as a metric to characterise EEG changes induced by MI–NFT.     

The relationship between traffic noise and insomnia among adult Japanese women

To clarify the relationship between traffic noise and insomnia, the authors conducted a survey and measured the actual sound level of noise in an urban area. Questionnaires were distributed to adult women who lived within 150 m from two major roads and were completed by 648 of the 1286 subjects (50.4%). The area was divided into three zones according to distance from the road (more than 50, 20-50 and 0-19.9 m). Fifty-seven subjects (8.8%) were classified as having insomnia. Average values of sound level at distances of 20, 50, and 100 m from the major road were L_eq 64.7, 57.1, and 51.8 dBA, respectively. Overall, there were no significant differences among the three zones in the prevalence of insomnia and no association between distance from the road and insomnia. However, the result from a sub-data set of the subjects who lived in the areas that showed decreasing noise level as the distance from the main road increased showed that distance from the road was associated with insomnia. This study suggests that researchers should consider the actual traffic situation and its sound level in epidemiological studies about the effects of traffic noise on insomnia.     

Ensemble Approach for Detection of Depression Using EEG Features

Depression is a public health issue that severely affects one’s well being and can cause negative social and economic effects to society. To raise awareness of these problems, this research aims at determining whether the long-lasting effects of depression can be determined from electroencephalographic (EEG) signals. The article contains an accuracy comparison for SVM, LDA, NB, kNN, and D3 binary classifiers, which were trained using linear (relative band power, alpha power variability, spectral asymmetry index) and nonlinear (Higuchi fractal dimension, Lempel–Ziv complexity, detrended fluctuation analysis) EEG features. The age- and gender-matched dataset consisted of 10 healthy subjects and 10 subjects diagnosed with depression at some point in their lifetime. Most of the proposed feature selection and classifier combinations achieved accuracy in the range of 80% to 95%, and all the models were evaluated using a 10-fold cross-validation. The results showed that the motioned EEG features used in classifying ongoing depression also work for classifying the long-lasting effects of depression.     

The effect of traffic noise on sleep of young adults in their homes

The disturbance of sleep by traffic noise is a major problem area in noise pollution. Extensive laboratory tests using multichannel electroencephalograms (EEG) have been carried out by many workers to determine the general response of people when exposed to noise during sleep. An experimental technique for obtaining results in people's homes has been developed using a simplified one-channel EEG. The responses of six people in the age range 19-24 were measured. A significant correlation was found between sleep disturbance and traffic noise when the noise is expressed in EPNdB. In the home experiments the subjects appeared to be approximately 10 dB less sensitive to noises than laboratory subjects for similar noise exposure. There also appeared to be some adaptation to the noise exposure; however, only one subject was tested for a period of 20 days and was insufficient to give definite results on adaptation.     

HABITUATION OF SLEEP TO A SHIP'S NOISE AS DETERMINED BY ACTIGRAPHY AND A SLEEP QUESTIONNAIRE

Habituation of sleep to a ship's noise was assessed by actigraphy and a sleep questionnaire. Four male students aged 21-24 years were studied for 15 consecutive nights in an experimental bedroom. During the first four nights, the subjects slept in a quiet environment. For the next eight consecutive nights, the subjects were exposed to the noise of a ship's engine with a sound level of 60dB(A) (the International Maritime Organization Standard) previously tape-recorded in a room of a diesel engine ship. On the last three experimental nights, the subjects again slept in a quiet environment. The subjects went to bed in the experimental room at about 0:00 and were woken at 8:00 a.m. the next morning by an alarm clock. Sleep was monitored by a wrist-worn actigraphy. On the morning following each experimental night, the subjects were instructed to answer the OSA questionnaire, a structured self-rating sleep scale developed in Japan. Habituation of sleep to the noise of a ship with a sound level of 60dB(A) was observed to some extent in the subjective sleep parameters but not in the sleep parameters measured by actigraphy.     

A comparison of steady-state evoked potentials to modulated tones in awake and sleeping humans.

Steady-state evoked potential responses were measured to binaural amplitude-modulated (AM) and combined amplitude- and frequency-modulated (AM/FM) tones. For awake subjects, AM/FM tones produced larger amplitude responses than did AM tones. Awake and sleeping responses to 30-dB HL AM/FM tones were compared. Response amplitudes were lower during sleep and the extent to which they differed from awake amplitudes was dependent on both carrier and modulation frequencies. Background EEG noise at the stimulus modulation frequency was also reduced during sleep and varied with modulation frequency. A detection efficiency function was used to indicate the modulation frequencies likely to be most suitable for electrical estimation of behavioral threshold. In awake subjects, for all carrier frequencies tested, detection efficiency was highest at a modulation frequency of 45 Hz. In sleeping subjects, the modulation frequency regions of highest efficiency varied with carrier frequency. For carrier frequencies of 250 Hz, 500 Hz, and 1 kHz, the highest efficiencies were found in two modulation frequency regions centered on 45 and 90 Hz. For 2 and 4 kHz, the highest efficiencies were at modulation frequencies above 70 Hz. Sleep stage affected both response amplitude and background EEG noise in a manner that depended on modulation frequency. The results of this study suggest that, for sleeping subjects, modulation frequencies above 70 Hz may be best when using steady-state potentials for hearing threshold estimation.     

Sleep disturbance effects of traffic noise—A laboratory study on after effects

Body movements during sleep and subjective sleep quality, as well as mood and performance were investigated after exposure to intermittent and continuous traffic noise during the night. In a first experiment, six young subjects slept in the laboratory for five nights; in a second experiment 12 subjects slept six consecutive nights in the laboratory. A good dose-response relationship was obtained between intermittent noise and subjective sleep quality: i.e., the higher the noise level, the poorer the sleep quality. A similar dose-response relationship was found for body movements immediately following noise peaks during nights with intermittent noise. Performance and mood tended to be worse after intermittent noise. However, these effects did not increase with an increase in noise levels. Compared with intermittent noise, continuous noise had a significantly smaller effect on sleep quality. Mood and performance were not worse after continuous noise. The results suggest that increased attention should be paid to peak noise levels when standards for nocturnal noise are set.     

脑电信号的标度分析及其在睡眠状态区分中的应用

脑电信号具有长程幂律相关性及多重分形的标度特性,并随生理病理状态改变.本文首次针对睡眠脑电信号应用单重分形去趋势波动分析(detrended fluctuation analysis,简记为DFA)方法与多重分形奇异谱对睡眠脑电信号的标度特征进行系统的对比研究.发现DFA标度指数α对于不同导联和样本组间的差异较为敏感,随睡眠状态的变化不规律;而多重分形奇异强度区间Δα随睡眠状态的变化更为规律,睡眠Ⅰ期至Ⅳ期不断增大,并且导联间差异和样本组间差异均较小.多重分形Δα参数更适合作为判定睡眠状态的定量参数.     

The Refined Composite Downsampling Permutation Entropy Is a Relevant Tool in the Muscle Fatigue Study Using sEMG Signals

Surface electromyography (sEMG) is a valuable technique that helps provide functional and structural information about the electric activity of muscles. As sEMG measures output of complex living systems characterized by multiscale and nonlinear behaviors, Multiscale Permutation Entropy (MPE) is a suitable tool for capturing useful information from the ordinal patterns of sEMG time series. In a previous work, a theoretical comparison in terms of bias and variance of two MPE variants—namely, the refined composite MPE (rcMPE) and the refined composite downsampling (rcDPE), was addressed. In the current paper, we assess the superiority of rcDPE over MPE and rcMPE, when applied to real sEMG signals. Moreover, we demonstrate the capacity of rcDPE in quantifying fatigue levels by using sEMG data recorded during a fatiguing exercise. The processing of four consecutive temporal segments, during biceps brachii exercise maintained at 70% of maximal voluntary contraction until exhaustion, shows that the 10th-scale of rcDPE was capable of better differentiation of the fatigue segments. This scale actually brings the raw sEMG data, initially sampled at 10 kHz, to the specific 0–500 Hz sEMG spectral band of interest, which finally reveals the inner complexity of the data. This study promotes good practices in the use of MPE complexity measures on real data.     

Sleep disturbances in highly stress reactive mice: Modeling endophenotypes of major depression

Background  

Neuronal mechanisms underlying affective disorders such as major depression (MD) are still poorly understood. By selectively breeding mice for high (HR), intermediate (IR), or low (LR) reactivity of the hypothalamic-pituitary-adrenocortical (HPA) axis, we recently established a new genetic animal model of extremes in stress reactivity (SR). Studies characterizing this SR mouse model on the behavioral, endocrine, and neurobiological levels revealed several similarities with key endophenotypes observed in MD patients. HR mice were shown to have changes in rhythmicity and sleep measures such as rapid eye movement sleep (REMS) and non-REM sleep (NREMS) as well as in slow wave activity, indicative of reduced sleep efficacy and increased REMS. In the present study we were interested in how far a detailed spectral analysis of several electroencephalogram (EEG) parameters, including relevant frequency bands, could reveal further alterations of sleep architecture in this animal model. Eight adult males of each of the three breeding lines were equipped with epidural EEG and intramuscular electromyogram (EMG) electrodes. After recovery, EEG and EMG recordings were performed for two days.     

Exploring Neurofeedback Training for BMI Power Augmentation of Upper Limbs: A Pilot Study

Electroencephalography neurofeedback (EEG-NFB) training can induce changes in the power of targeted EEG bands. The objective of this study is to enhance and evaluate the specific changes of EEG power spectral density that the brain-machine interface (BMI) users can reliably generate for power augmentation through EEG-NFB training. First, we constructed an EEG-NFB training system for power augmentation. Then, three subjects were assigned to three NFB training stages, based on a 6-day consecutive training session as one stage. The subjects received real-time feedback from their EEG signals by a robotic arm while conducting flexion and extension movement with their elbow and shoulder joints, respectively. EEG signals were compared with each NFB training stage. The training results showed that EEG beta (12–40 Hz) power increased after the NFB training for both the elbow and the shoulder joints’ movements. EEG beta power showed sustained improvements during the 3-stage training, which revealed that even the short-term training could improve EEG signals significantly. Moreover, the training effect of the shoulder joints was more obvious than that of the elbow joints. These results suggest that NFB training can improve EEG signals and clarify the specific EEG changes during the movement. Our results may even provide insights into how the neural effects of NFB can be better applied to the BMI power augmentation system and improve the performance of healthy individuals.