Oscillatory EEG activity during REM sleep in elderly people predicts subsequent dream recall after awakenings

Several findings underlined that the electrophysiological (EEG) background of the last segment of sleep before awakenings may predict the presence/absence of dream recall (DR) in young subjects. However, little is known about the EEG correlates of DR in elderly people. Only an investigation found differences between recall and non-recall conditions during NREM sleep EEG in older adults, while—surprisingly—no EEG predictor of DR was found for what concerns REMsleep. Considering REMsleep as a privileged scenario to produce mental sleep activity related to cognitive processes, our study aimed to investigate whether specific EEG topography and frequency changes during REM sleep in elderly people may predict a subsequent recall of mental sleep activity. Twenty-one healthy older volunteers (mean age 69.2 ± 6.07 SD) and 20 young adults (mean age 23.4 ± 2.76 SD) were recorded for one night from19 scalp derivations. Dreams were collected upon morning awakenings from REM sleep. EEG signals of the last 5min were analyzed by the Better OSCillation algorithm to detect the peaks of oscillatory activity in both groups. Statistical comparisons revealed that older as well as young individuals recall their dream experience when the last segment of REM sleep is characterized by frontal theta oscillations. No Recall (Recall vs. Non-Recall) × Age (Young vs. Older) interaction was found. This result replicated the previous evidence in healthy young subjects, as shown in within- and between-subjects design. The findings are completely original for older individuals, demonstrating that theta oscillations are crucial for the retrieval of dreaming also in this population. Furthermore, our results did not confirm a greater presence of the theta activity in healthy aging. Conversely, we found a greater amount of rhythmic theta and alpha activity in young than older participants. It is worth noting that the theta oscillations detected are related to cognitive functioning. We emphasize the notion that the oscillatory theta activity should be distinguished from the non-rhythmic theta activity identified in relation to other phenomena such as (a) sleepiness and hypoarousal conditions during the waking state and (b) cortical slowing, considered as an EEG alteration in clinical samples

Alterations in rhythmic and non-rhythmic resting-state EEG activity and their link to cognition in older age

While many structural and biochemical changes in the brain have been previously associated with aging, the findings concerning electrophysiological signatures, reflecting functional properties of neuronal networks, remain rather controversial. To try resolve this issue, we took advantage of a large population study (N=1703) and comprehensively investigated the association of multiple EEG biomarkers (power of alpha and theta oscillations, individual alpha peak frequency (IAF), the slope of 1/f power spectral decay), aging, and aging and cognitive performance. Cognitive performance was captured with three factors representing processing speed, episodic memory, and interference resolution. Our results show that not only did IAF decline with age but it was also associated with interference resolution over multiple cortical areas. To a weaker extent, 1/f slope of the PSD showed age-related reductions, mostly in frontal brain regions. Finally, alpha power was negatively associated with the speed of processing in the right frontal lobe, despite the absence of age-related alterations. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered when investigating the association between age, neuronal activity, and cognitive performance

Cortical electrical activity changes in healthy aging using EEG-eLORETA analysis

Brain aging causes loss of synaptic spines, neuronal apoptosis, and a reduction in neurotransmitter levels. These aging phenomena disturb cortical electrical activity and its synchronization with connected regions. Previous electroencephalography (EEG) studies reported an age-related decrease in electrical activity in the alpha frequency band at occipital, parietal, and temporal areas as well as a decrease in occipital delta activity. However, there is an ongoing debate about whether there is an increase or decrease of the activity in other frequency bands with aging due to inconsistent study findings. In this study, we aimed to detect age-related changes of cortical electrical activities in all five frequency bands (delta, theta, alpha, beta, and gamma) in a large sample of healthy subjects for the first time. Using eLORETA (exact low-resolution brain electromagnetic tomography) analysis, we applied an eLORETA source estimation method to resting-state EEG data in 147 healthy subjects (median age 55, IQR 26.5–67.0) to obtain cortical electrical activity and assessed age-related changes in this activity using correlation analysis with multiple comparison correction. The combination of the eLORETA source estimation method and correlation analysis implemented in eLORETA software detected age-related changes in specific cortical regions for each frequency band: (1) delta and theta cortical electrical activities decreased at the occipital area with age, (2) alpha cortical electrical activity decreased at the occipitoparietotemporal areas with age, (3) beta cortical electrical activity increased at the insula, sensorimotor area, supplementary motor area, premotor area, and right temporal areas with age (most significant correlation at the right insula), (4) gamma cortical electrical activity increased at the frontoparietal and left temporal areas with age. These findings extend previous EEG study findings and provide valuable information related to mechanisms of healthy aging. Overall, our findings revealed that even healthy aging greatly affects cortical electrical activities in a region-specific way

The effect of aging and rhythmic temporal structure during encoding on recognition memory: an EEG Study

Aging deficits in memory have long been established in the literature, however, little has been done to investigate how environmental factors can be used to ameliorate age related declines in memory functioning. Recent research in recognition memory suggests that increased temporal expectancy during encoding can benefit recognition memory at retrieval in a younger adult sample. The current study aimed to investigate whether the benefit to recognition memory, and associated neural processes, observed in young adults is also evident in normal aging. Unfortunately, due to national restrictions affecting data collection, no older participants were able to be tested. As such, the current project resolved to provide a proof of concept to inform an investigation of the originally intended scope. Ten young participants (M age = 23.5; SD = 2.22) were exposed to pictures of everyday objects in 3 rhythmic and 3 arrhythmic encoding blocks, after which they performed a recognition memory test containing previously studied and new objects. A clear trend suggesting better memory following rhythmic encoding was observed, but no significant difference between conditions emerged. Furthermore, analysis of relevant ERP components uncovered no old/new effect in relation to the LPC or the LFE. Conversely, the FN400 displayed an old/new effect. Thus, the temporal manipulation did not result in significant differences in recognition, but it should be noted that the study is underpowered. However, participants did display a good ability to discriminate stimuli, and in addition RT differences between correct and incorrect recognition judgements and an FN400 old/new effect suggest that the paradigm is effective and sensitive to processing differences between conditions. Recognition could be detected by the FN400 in the present experiment. However, trends in recognition ability between temporal structures suggest that an insufficient sample size is likely to have caused the lacking significant temporal effects. As such, the paradigm is appropriate for extension including a larger sample size and the planned comparison of age groups

Small-World Network Analysis of Cortical Connectivity in Chronic Fatigue Syndrome using EEG

The primary aim of this thesis was to explore the relationship between electroencephalography (qEEG) and brain system dysregulation in people with Chronic Fatigue Syndrome (CFS). EEG recordings were taken from an archival dataset of 30 subjects, 15 people with CFS and 15 healthy controls (HCs), evaluated during an eye-closed resting state condition. Exact low resolution electromagnetic tomography (eLORETA) was applied to the qEEG data to estimate cortical sources and perform functional connectivity analysis assessing the strength of time-varying signals between all pairwise cortical regions of interest. To obtain a comprehensive view of local and global processing, eLORETA lagged coherence was computed on 84 regions of interest representing 42 Brodmann areas for the left and right hemispheres of the cortex, for the delta (1-3 Hz) and alpha-1 (8-10 Hz) and alpha-2 (10-12 Hz) frequency bands. Graph theory analysis of eLORETA coherence matrices for each participant was conducted to derive the “small-worldness” index, a measure of the optimal balance between the functional integration (global) and segregation (local) properties known to be present in brain networks. The data were also associated with the cognitive impairment composite score on the DePaul Symptom Questionnaire (DSQ), a patient-reported symptom outcome measure of frequency and severity of cognitive symptoms. Results showed that small-worldness for the delta band was significantly lower for patients with CFS compared to HCs. Small-worldness for delta, alpha-1, and alpha-2 were associated with higher cognitive composite scores on the DSQ. Finally, small-worldness in all 3 frequency bands correctly distinguished those with CFS from HCS with a classification rate of nearly 87 percent. These preliminary findings suggest disease processes in CFS may be functionally disruptive to small-world characteristics, especially in the delta frequency band, resulting in cognitive impairments. In turn, these findings may help to confirm a biological basis for cognitive symptoms, providing clinically relevant diagnostic indicators, and characterizing the neurophysiological status of people with CFS

Brain rhythmic abnormalities in convalescent patients with anti-NMDA receptor encephalitis: a resting-state EEG study

ObjectiveAnti-N-methyl-D-aspartate receptor encephalitis (anti-NMDARE) is autoimmune encephalitis with a characteristic neuropsychiatric syndrome and persistent cognition deficits even after clinical remission. The objective of this study was to uncover the potential noninvasive and quantified biomarkers related to residual brain distortions in convalescent anti-NMDARE patients.MethodsBased on resting-state electroencephalograms (EEG), both power spectral density (PSD) and brain network analysis were performed to disclose the persistent distortions of brain rhythms in these patients. Potential biomarkers were then established to distinguish convalescent patients from healthy controls.ResultsOppositely configured spatial patterns in PSD and network architecture within specific rhythms were identified, as the hyperactivated PSD spanning the middle and posterior regions obstructs the inter-regional information interactions in patients and thereby leads to attenuated frontoparietal and frontotemporal connectivity. Additionally, the EEG indexes within delta and theta rhythms were further clarified to be objective biomarkers that facilitated the noninvasive recognition of convalescent anti-NMDARE patients from healthy populations.ConclusionCurrent findings contributed to understanding the persistent and residual pathological states in convalescent anti-NMDARE patients, as well as informing clinical decisions of prognosis evaluation

Brain networks under attack : robustness properties and the impact of lesions

A growing number of studies approach the brain as a complex network, the so-called ‘connectome’. Adopting this framework, we examine what types or extent of damage the brain can withstand—referred to as network ‘robustness’—and conversely, which kind of distortions can be expected after brain lesions. To this end, we review computational lesion studies and empirical studies investigating network alterations in brain tumour, stroke and traumatic brain injury patients. Common to these three types of focal injury is that there is no unequivocal relationship between the anatomical lesion site and its topological characteristics within the brain network. Furthermore, large-scale network effects of these focal lesions are compared to those of a widely studied multifocal neurodegenerative disorder, Alzheimer’s disease, in which central parts of the connectome are preferentially affected. Results indicate that human brain networks are remarkably resilient to different types of lesions, compared to other types of complex networks such as random or scale-free networks. However, lesion effects have been found to depend critically on the topological position of the lesion. In particular, damage to network hub regions—and especially those connecting different subnetworks—was found to cause the largest disturbances in network organization. Regardless of lesion location, evidence from empirical and computational lesion studies shows that lesions cause significant alterations in global network topology. The direction of these changes though remains to be elucidated. Encouragingly, both empirical and modelling studies have indicated that after focal damage, the connectome carries the potential to recover at least to some extent, with normalization of graph metrics being related to improved behavioural and cognitive functioning. To conclude, we highlight possible clinical implications of these findings, point out several methodological limitations that pertain to the study of brain diseases adopting a network approach, and provide suggestions for future research

Trouble comportemental en sommeil paradoxal idiopathique et synucleinopathies : rythmes spectraux et connectivité fonctionnelle à l’EEG au repos

Le trouble comportemental en sommeil paradoxal idiopathique (TCSPi) précède de plusieurs années le diagnostic d’une maladie synucléinopathique. Dans cette étude, nous cherchions à déterminer si la puissance spectrale relative, les composantes rythmiques et arythmiques des spectres de puissance, ainsi que la connectivité fonctionnelle permettaient d’identifier à un temps de base les patients ayant un TCSPi qui développerait une synucléinopathie lors des suivis cliniques annuels. Un enregistrement EEG au repos et une évaluation neuropsychologique ont été conduits auprès de quatre-vingt-un participants atteints d’un TCSPi (66.89 ± 6.91 ans, 20 femmes) et des évaluations neurologiques annuelles étaient menées afin de définir si les patients montraient des symptômes d’une maladie synucléinopathique. La puissance spectrale standard ainsi qu’une estimation spectrale des composantes rythmiques et arythmiques ont été calculées. Ensuite, la connectivité fonctionnelle globale et entre chaque paire d’électrodes ont été estimée par le weighted Phase Lag Index. Après une durée de suivi de 5.01 ± 2.76 ans, 34 participants ont été diagnostiqués avec une synucléinopathie et 47 sont restés exempts de maladie. Comparativement aux participants avec un TCSPi n’ayant pas converti, ceux ayant converti montraient, lors de l’évaluation de base, une puissance spectrale relative plus élevée dans la bande thêta, une pente de la composante arythmique plus abrupte ainsi qu'une puissance rythmique plus élevée en thêta dans les régions occipitales et temporales ainsi qu’en en bêta1 dans les régions frontales. De plus, les patients TCSPi ayant converti présentaient une hyperconnectivité globale dans la bande bêta, mais une hypoconnectivité dans la bande alpha entre les régions temporo-occipitales gauches lors de l’évaluation de base comparativement à ceux n’ayant pas converti. Les altérations mesurables en EEG au repos lors de l’évaluation de base chez les participants avec TCSPi ayant converti vers une maladie synucléinopathique suggèrent une perturbation des réseaux à grande échelle affectés par la neurodégénérescence précoce des structures sous-corticales.Idiopathic REM sleep behavior disorder (iRBD) precedes the diagnosis of synucleinopathies by several years. In this study, we aimed to determine whether relative spectral power, rhythmic and arrhythmic components of power spectra, and functional connectivity at baseline could identify patients with iRBD who will develop a synucleinopathy at follow-up. Resting-state EEG recordings and neuropsychological evaluations were conducted on eighty-one participants with iRBD (66.89 ± 6.91 years; 20 women), and annual neurological assessments were performed to define the emergence of synucleinopathy symptoms. Standard spectral power and spectral estimates of rhythmic and arrhythmic components were calculated. Additionally, global and pairwise functional connectivity were estimated using the weighted Phase Lag Index. After a follow-up period of 5.01 ± 2.76 years, 34 participants were diagnosed with a synucleinopathic disorder, while 47 remained disease-free. Compared to patients who did not convert, patients who converted at follow-up exhibited higher relative spectral power in the theta band, steeper slopes of the arrhythmic component, and increased rhythmic power in theta in posterior regions and beta1 in frontal regions at baseline evaluation. Furthermore, participants who converted showed hyperconnectivity in the beta band and hypoconnectivity in the alpha band between left temporo-occipital regions at baseline compared to participants who did not convert. The measurable alterations in resting-state EEG at baseline in participants with iRBD who phenoconverted towards a synucleinopathy suggest disruption of large-scale networks affected by early neurodegeneration of subcortical structures

Brain Function and Health, Sports, and Exercise

This reprint represents the articles published in the Special Issue “Brain Function and Health, Sports, and Exercise”. Fifteen articles were published, with topics covering the relationship between acute effects of exercise on cognitive function, as well as the influence of exercise on positive medium-term adaptations in populations as children, youth, adults and older. We think that the different approaches used in the different articles will help the readers to have a greater overview of the current research in brain and exercise