EEG and event-related potentials in normal aging

Aperiodic component of EEG power spectrum and cognitive performance are modulated by education in aging

Recent studies have shown a growing interest in the so-called "aperiodic" component of the EEG power spectrum, which describes the overall trend of the whole spectrum with a linear or exponential function. In the field of brain aging, this aperiodic component is associated both with age-related changes and performance on cognitive tasks. This study aims to elucidate the potential role of education in moderating the relationship between resting-state EEG features (including aperiodic component) and cognitive performance in aging. N = 179 healthy participants of the "Leipzig Study for Mind-Body-Emotion Interactions" (LEMON) dataset were divided into three groups based on age and education. Older adults exhibited lower exponent, offset (i.e. measures of aperiodic component), and Individual Alpha Peak Frequency (IAPF) as compared to younger adults. Moreover, visual attention and working memory were differently associated with the aperiodic component depending on education: in older adults with high education, higher exponent predicted slower processing speed and less working memory capacity, while an opposite trend was found in those with low education. While further investigation is needed, this study shows the potential modulatory role of education in the relationship between the aperiodic component of the EEG power spectrum and aging cognition.

Studying the Alzheimer's disease continuum using EEG and fMRI in single-modality and multi-modality settings

Alzheimer's disease (AD) is a biological, clinical continuum that covers the preclinical, prodromal, and clinical phases of the disease. Early diagnosis and identification of the stages of Alzheimer's disease (AD) are crucial in clinical practice. Ideally, biomarkers should reflect the underlying process (pathological or otherwise), be reproducible and non-invasive, and allow repeated measurements over time. However, the currently known biomarkers for AD are not suitable for differentiating the stages and predicting the trajectory of disease progression. Some objective parameters extracted using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are widely applied to diagnose the stages of the AD continuum. While electroencephalography (EEG) has a high temporal resolution, fMRI has a high spatial resolution. Combined EEG and fMRI (EEG-fMRI) can overcome single-modality drawbacks and obtain multi-dimensional information simultaneously, and it can help explore the hemodynamic changes associated with the neural oscillations that occur during information processing. This technique has been used in the cognitive field in recent years. This review focuses on the different techniques available for studying the AD continuum, including EEG and fMRI in single-modality and multi-modality settings, and the possible future directions of AD diagnosis using EEG-fMRI.

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.

[Formula: see text]-[Formula: see text]: A Nonparametric Model for Neural Power Spectra Decomposition

The power spectra estimated from the brain recordings are the mixed representation of aperiodic transient activity and periodic oscillations, i.e., aperiodic component (AC) and periodic component (PC). Quantitative neurophysiology requires precise decomposition preceding parameterizing each component. However, the shape, statistical distribution, scale, and mixing mechanism of AC and PCs are unclear, challenging the effectiveness of current popular parametric models such as FOOOF, IRASA, BOSC, etc. Here, ξ- π was proposed to decompose the neural spectra by embedding the nonparametric spectra estimation with penalized Whittle likelihood and the shape language modeling into the expectation maximization framework. ξ- π was validated on the synthesized spectra with loss statistics and on the sleep EEG and the large sample iEEG with evaluation metrics and neurophysiological evidence. Compared to FOOOF, both the simulation presenting shape irregularities and the batch simulation with multiple isolated peaks indicated that ξ- π improved the fit of AC and PCs with less loss and higher F1-score in recognizing the centering frequencies and the number of peaks; the sleep EEG revealed that ξ- π produced more distinguishable AC exponents and improved the sleep state classification accuracy; the iEEG showed that ξ- π approached the clinical findings in peak discovery. Overall, ξ- π offered good performance in the spectra decomposition, which allows flexible parameterization using descriptive statistics or kernel functions. ξ- π is a seminal tool for brain signal decoding in fields such as cognitive neuroscience, brain-computer interface, neurofeedback, and brain diseases.

Lower individual alpha frequency in individuals with chronic low back pain and fear of movement

ABSTRACT

Significant progress has been made in linking measures of individual alpha frequency (IAF) and pain. A lower IAF has been associated with chronic neuropathic pain and with an increased sensitivity to pain in healthy young adults. However, the translation of these findings to chronic low back pain (cLBP) are sparse and inconsistent. To address this limitation, we assessed IAFs in a cohort of 70 individuals with cLBP, implemented 3 different IAF calculations, and separated cLBP subjects based on psychological variables. We hypothesized that a higher fear movement in cLBP is associated with a lower IAF at rest. A total of 10 minutes of resting data were collected from 128 electroencephalography channels. Our results offer 3 novel contributions to the literature. First, the high fear group had a significantly lower peak alpha frequency. The high fear group also reported higher pain and higher disability. Second, we calculated individual alpha frequency using 3 different but established methods; the effect of fear on individual alpha frequency was robust across all methods. Third, fear of movement, pain intensity, and disability highly correlated with each other and together significantly predicted IAF. Our findings are the first to show that individuals with cLBP and high fear have a lower peak alpha frequency.

Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review

The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures and functions that lead to age-related pathological disorders. Electroencephalographic (EEG) signals recorded during resting-state conditions have been widely used because of the significant advantage of non-invasive signal acquisition with higher temporal resolution. These advantages include the capability of a variety of linear and nonlinear signal analyses and state-of-the-art machine-learning and deep-learning techniques. Advances in artificial intelligence (AI) can not only reveal the neural mechanisms underlying aging but also enable the assessment of brain age reliably by means of the age-related characteristics of EEG signals. This paper reviews the literature on the age-related features, available analytic methods, large-scale resting-state EEG databases, interpretations of the resulting findings, and recent advances in age-related AI models.

Functionally annotated electrophysiological neuromarkers of healthy ageing and memory function

The unprecedented increase in life expectancy presents a unique opportunity and the necessity to explore both healthy and pathological aspects of ageing. Electroencephalography (EEG) has been widely used to identify neuromarkers of cognitive ageing due to its affordability and richness in information. However, despite the growing volume of data and methodological advancements, the abundance of contradictory and non-reproducible findings has hindered clinical translation. To address these challenges, our study introduces a comprehensive workflow expanding on previous EEG studies and investigates various static and dynamic power and connectivity estimates as potential neuromarkers of cognitive ageing in a large dataset. We also assess the robustness of our findings by testing their susceptibility to band specification. Finally, we characterise our findings using functionally annotated brain networks to improve their interpretability and multi-modal integration. Our analysis demonstrates the effect of methodological choices on findings and that dynamic rather than static neuromarkers are not only more sensitive but also more robust. Consequently, they emerge as strong candidates for cognitive ageing neuromarkers. Moreover, we were able to replicate the most established EEG findings in cognitive ageing, such as alpha oscillation slowing, increased beta power, reduced reactivity across multiple bands, and decreased delta connectivity. Additionally, when considering individual variations in the alpha band, we clarified that alpha power is characteristic of memory performance rather than ageing, highlighting its potential as a neuromarker for cognitive ageing. Finally, our approach using functionally annotated source reconstruction allowed us to provide insights into domain-specific electrophysiological mechanisms underlying memory performance and ageing. HIGHLIGHTS: We provide an open and reproducible pipeline with a comprehensive workflow to investigate static and dynamic EEG neuromarkers. Neuromarkers related to neural dynamics are sensitive and robust. Individualised alpha power characterises cognitive performance rather than ageing. Functional annotation allows cross-modal interpretation of EEG findings.

Preoperative characterization of baseline EEG recordings for risk stratification of post-anesthesia care unit delirium

STUDY OBJECTIVE

Delirium in the post-anesthesia care unit (PACU-D) presents a serious condition with a high medical and socioeconomic impact. In particular, PACU-D is among common postoperative complications of elderly patients. As PACU-D may be associated with postoperative delirium, early detection of at-risk patients and strategies to prevent PACU-D are important. We characterized EEG baseline signatures of patients who developed PACU-D following surgery and general anesthesia and patients who did not.

DESIGN AND SETTING

We conducted a post-hoc analysis of preoperative EEG recordings between patients with and without PACU-D, as indicated by positive bCAM scores post general anesthesia and surgery.

PATIENTS AND MEASUREMENTS

Preoperative baseline EEG recordings from 89 patients were recorded at controlled eyes-open (focused wakefulness) and eyes-closed (relaxed wakefulness) conditions. We computed power spectral densities, permutation entropy, spectral entropy and spectral edge frequency to see if these parameters can reflect potential baseline EEG differences between PACU-D (31.5%) and noPACU-D (68.5%) patients. Wilcoxon's Rank Sum Test as well as AUC values were used to determine statistical significance.

MAIN RESULTS

Baseline EEG recordings showed significant differences between PACU-D and noPACU-D patients preoperatively. Compared to the noPACU-D group, PACU-D patients presented with lower power in higher frequencies during relaxed and focused wakefulness alike. These differences in power led to AUC values of 0.73 [0.59;0.85] (permutation entropy) and 0.72 [0.61;0.83] (spectral edge frequency) indicative of a "fair" performance to separate patients with and without PACU-D.

CONCLUSIONS

The baseline EEG of relaxed wakefulness as well as focused wakefulness may be used to assess the risk of developing PACU-D following surgery under general anesthesia. Moreover, routinely used monitoring parameters capture these differences as well, potentially allowing an easy transfer to clinical settings.

CLINICAL TRIAL NUMBER

NCT03775356.

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 previously been associated with older age, findings concerning functional properties of neuronal networks, as reflected in their electrophysiological signatures, remain rather controversial. These discrepancies might arise due to several reasons, including diverse factors determining general spectral slowing in the alpha frequency range as well as amplitude mixing between the rhythmic and non-rhythmic parameters. We used a large dataset (N = 1703, mean age 70) to comprehensively investigate age-related alterations in multiple EEG biomarkers taking into account rhythmic and non-rhythmic activity and their individual contributions to cognitive performance. While we found strong evidence for an individual alpha peak frequency (IAF) decline in older age, we did not observe a significant relationship between theta power and age while controlling for IAF. Not only did IAF decline with age, but it was also positively associated with interference resolution in a working memory task primarily in the right and left temporal lobes suggesting its functional role in information sampling. Critically, we did not detect a significant relationship between alpha power and age when controlling for the 1/f spectral slope, while the latter one showed age-related alterations. These findings thus suggest that the entanglement of IAF slowing and power in the theta frequency range, as well as 1/f slope and alpha power measures, might explain inconsistencies reported previously in the literature. Finally, despite the absence of age-related alterations, alpha power was negatively associated with the speed of processing in the right frontal lobe while 1/f slope showed no consistent relationship to cognitive performance. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered for the comprehensive assessment of association between age, neuronal activity, and cognitive performance.

The effect of different types of physical activity on cognitive reaction time in older adults in China

Introduction

Aging is not only reflected in the degeneration of physiological functions but is also embodied in the decline of psychological and cognitive functions. The decline of cognitive function can reduce the quality of life in older adults, and even potentially cause Alzheimer's disease, which may lead to a heavy burden on patients, families, and society. The purpose of this study was to investigate the effects of physical activity (PA) on cognitive reaction time in older adults.

Methods

A cross-sectional survey design was used in this study. A total of 839 elderly subjects were recruited from Beijing and Shanghai. In total, 792 subjects met the inclusion criteria (age > 60 years, without disability, speech, and hearing impairment), including 384 men (age:67.7 ± 5.7 years) and 408 women (age: 68.2 ± 5.8 years). The PA was assessed by the Physical Activity Scale for the Elderly (PASE). All kinds of PA were divided into three levels: "Low" (< 50% average score), "Moderate" (50-150% average score), and "High" (>150% average score). The reaction time of subjects was measured by the selective reaction tester (Model: CSTF-XF, TFHT, Beijing, China).

Results

For leisure-time PA, the results showed that the cognitive reaction time of older adults in the "Low" group (1.11 ± 0.32 s) was significantly longer than that in the "Moderate" group (1.05 ± 0.30 s, p < 0.01) and the "High" group (0.99 ± 0.28 s, p < 0.01). For housework PA, there was no significant difference in the cognitive reaction time among the three groups ("Low": 1.09 ± 0.31 s; "Moderate": 1.07 ± 0.31 s; "High": 1.05 ± 0.28 s, p > 0.05). For work-related PA, the results showed that the cognitive reaction time of older adults in the "Low" group (1.09 ± 0.30 s) was significantly longer than that in the "High" group (0.99 ± 0.28 s) and the "Moderate" group (1.03 ± 0.32 s, p < 0.01).

Conclusion

The PA has a positive effect on reducing cognitive reaction time in older adults. It is recommended that older adults maintain a moderate level of leisure PA and work-related PA to delay the decline in cognitive reaction time.

Effects of Tai Chi and Walking Exercise on Emotional Face Recognition in Elderly People: An ERP Study

Both tai chi and walking can improve the physical health of the elderly, but the effect on the emotional cognitive function of the elderly is unclear. To investigate the effect of long-term walking and tai chi exercise on the emotional cognitive function of the elderly, 63 subjects were recruited in this study according to age and exercise habits, including 16 in the youth control group, 15 in the elderly non-exercise control group, 17 in the elderly walking group, and 18 in the elderly tai chi group. The “learning–test paradigm” of emotional faces was used to measure the subjects’ ability to recognize and remember emotional (negative and neutral) faces. Behavioral and EEG data were recorded during the learning and testing phases. The results showed that there is aging in emotional cognition in older adults compared with younger adults. Long-term walking and tai chi exercise can delay the deterioration of emotional cognitive function in older adults to some extent. Both walking and tai chi exercise can delay the decline in aging-related emotional face recognition function to some extent. Walking exercise can delay the decline in aging-related emotional face memory function to some extent.

Altered event-related potentials and theta oscillations index auditory working memory deficits in healthy aging

Speech comprehension deficits constitute a major issue for an increasingly aged population, as they may lead older individuals to social isolation. Since conversation requires constant monitoring, updating and selecting information, auditory working memory decline, rather than impoverished hearing acuity, has been suggested a core factor. However, in stark contrast to the visual domain, the neurophysiological mechanisms underlying auditory working memory deficits in healthy aging remain poorly understood, especially those related to on-the-fly information processing under increasing load. Therefore, we investigated the behavioral costs and electrophysiological differences associated with healthy aging and working memory load during continuous auditory processing. We recorded EEG activity from 27 younger (∼25 years) and 29 older (∼70 years) participants during their performance on an auditory version of the n-back task with speech syllables and 2 workload levels (1-back; 2-back). Behavioral measures were analyzed as indices of function; event-related potentials as proxies for sensory and cognitive processes; and theta oscillatory power as a reflection of memory and central executive function. Our results show age-related differences in auditory information processing within a latency range that is consistent with a series of impaired functions, from sensory gating to cognitive resource allocation during constant information updating, especially under high load.

The Menstrual Cycle Alters Resting-State Cortical Activity: A Magnetoencephalography Study

Resting-state neural oscillations are used as biomarkers for functional diseases such as dementia, epilepsy, and stroke. However, accurate interpretation of clinical outcomes requires the identification and minimisation of potential confounding factors. While several studies have indicated that the menstrual cycle also alters brain activity, most of these studies were based on visual inspection rather than objective quantitative measures. In the present study, we aimed to clarify the effect of the menstrual cycle on spontaneous neural oscillations based on quantitative magnetoencephalography (MEG) parameters. Resting-state MEG activity was recorded from 25 healthy women with normal menstrual cycles. For each woman, resting-state brain activity was acquired twice using MEG: once during their menstrual period (MP) and once outside of this period (OP). Our results indicated that the median frequency and peak alpha frequency of the power spectrum were low, whereas Shannon spectral entropy was high, during the MP. Theta intensity within the right temporal cortex and right limbic system was significantly lower during the MP than during the OP. High gamma intensity in the left parietal cortex was also significantly lower during the MP than during the OP. Similar differences were also observed in the parietal and occipital regions between the proliferative (the late part of the follicular phase) and secretory phases (luteal phase). Our findings suggest that the menstrual cycle should be considered to ensure accurate interpretation of functional neuroimaging in clinical practice.

Normobaric oxygen may correct chronic cerebral ischemia-mediated EEG anomalies

AIMS

To explore the safety and efficacy of normobaric oxygen (NBO) on correcting chronic cerebral ischemia (CCI) and related EEG anomalies.

METHODS

This prospective randomized trial (NCT03745092) enrolled 50 cases of CCI patients, which were divided into NBO (8 L/min of oxygen supplement) group and control group (room air) randomly, and also enrolled 21 healthy volunteers. Two times of 30-min EEG recordings with the interval of 45min of NBO or room air were analyzed quantitatively.

RESULTS

The CCI-mediated EEG presented with two patterns of electrical activities: high-power oscillations (high-power EEG, n = 26) and paroxysmal slow activities under the normal-power background (normal-power EEG, n = 24). The fronto-central absolute power (AP) of the beta, alpha, theta, and delta in the high-power EEG was higher than that in healthy EEG (p < 0.05). The fronto-central theta/alpha, delta/alpha and (delta + theta)/(alpha + beta) ratios in the normal-power EEG were higher than those in healthy EEG (p < 0.05). The high-power EEG in NBO group had higher fronto-central AP reduction rates than those in control group (p < 0.05). NBO remarkably reduced the fronto-central theta/alpha, delta/alpha, and (delta + theta)/(alpha + beta) ratios in the normal-power EEG (p < 0.05).

CONCLUSIONS

NBO rapidly ameliorates CCI-mediated EEG anomalies, including attenuation of the abnormal high-power oscillations and the paroxysmal slow activities associated with CCI.

Diversity of the gut-microbiome related to cognitive behavioral outcomes in healthy older adults

With the aging of the United States population, age-related cognitive disorders will be more prevalent and will negatively impact society. Differences in factors within and among individuals that influence cognitive decline complicate studies on the topic. One difference among individuals - gut microbiome diversity and composition - changes within the person across their lifespan and varies among individuals. An individual's gut microflora can significantly influence gut-brain communication, brain function, and behavior. Little research has been done to evaluate the gut-brain relation in non-clinical populations, with no previous studies, to our knowledge, in healthy older adults. In the present study, we investigated the relation between microbiome diversity and cognitive decline. The researchers invited sixty-three healthy older adults between 67-83 years of age to provide a fecal sample and complete an electrophysiological assessment of brain potentials (Event-Related Potentials; ERP) and the Cambridge Neuropsychological Test Automated Battery (CANTAB). Electrophysiological and behavioral data were related to alpha diversity, a measure of the variety of species in the gut-microbiome, supporting the hypothesis that a relation exists between gut microbial diversity and cognitive performance in healthy older adults as measured by CANTAB and ERP. To our knowledge, this study is the first to demonstrate the association between ERP outcomes and the gut-microbiome. Our results begin to bridge the gap in our understanding of the connection between behavior and the composition of the gut-microbiome, commonly referred to as the gut-brain connection.

Resting-state EEG alpha/theta power ratio discriminates early-onset Alzheimer's disease from healthy controls

OBJECTIVES

The present study aims to compare early-onset Alzheimer's disease (EOAD) patients with healthy controls (HC), and late-onset Alzheimer's disease (LOAD) patients using resting-state delta, theta, alpha, and beta oscillations and provide a cut-off score of alpha/theta ratio to discriminate individuals with EOAD and young HC.

METHODS

Forty-seven individuals with EOAD, 51 individuals with LOAD, and demographically-matched 49 young and 51 older controls were included in the study. Spectral-power analysis using Fast-Fourier Transformation (FFT) is performed on resting-state electroencephalography (EEG) data. Delta, theta, alpha, and beta oscillations compared between groups and Receiver Operating Characteristic (ROC) curve analysis was conducted.

RESULTS

Compared to healthy controls individuals with EOAD showed an increase in slow frequency bands and a decrease in fast frequency bands. Frontal alpha/theta power ratio is the best discriminating value between EOAD and young HC with the sensitivity and specificity greater than 80% with area under the curve (AUC) 0.881.

CONCLUSIONS

EOAD display more widespread and severe electrophysiological abnormalities than LOAD and HC which may reflect more pronounced pathological burden and cholinergic deficits in EOAD. Additionally, the alpha/theta ratio can discriminate EOAD and young HC successfully.

SIGNIFICANCE

This study is the first to report that resting-state EEG power can be a promising marker for diagnostic accuracy between EOAD and healthy controls.

When the time is right: Temporal dynamics of brain activity in healthy aging and dementia

Brain activity and communications are complex phenomena that dynamically unfold over time. However, in contrast with the large number of studies reporting neuroanatomical differences in activation relative to young adults, changes of temporal dynamics of neural activity during normal and pathological aging have been grossly understudied and are still poorly known. Here, we synthesize the current state of knowledge from MEG and EEG studies that aimed at specifying the effects of healthy and pathological aging on local and network dynamics, and discuss the clinical and theoretical implications of these findings. We argue that considering the temporal dynamics of brain activations and networks could provide a better understanding of changes associated with healthy aging, and the progression of neurodegenerative disease. Recent research has also begun to shed light on the association of these dynamics with other imaging modalities and with individual differences in cognitive performance. These insights hold great potential for driving new theoretical frameworks and development of biomarkers to aid in identifying and treating age-related cognitive changes.

Age differences in resting state EEG and their relation to eye movements and cognitive performance

Prior research has focused on EEG differences across age or EEG differences across cognitive tasks/eye tracking. There are few studies linking age differences in EEG to age differences in behavioural performance which is necessary to establish how neuroactivity corresponds to successful and impaired ageing. Eighty-six healthy participants completed a battery of cognitive tests and eye-tracking measures. Resting state EEG (n = 75, 31 young, 44 older adults) was measured for delta, theta, alpha and beta power as well as for alpha peak frequency. Age deficits in cognition were aligned with the literature, showing working memory and inhibitory deficits along with an older adult advantage in vocabulary. Older adults showed poorer eye movement accuracy and response times, but we did not replicate literature showing a greater age deficit for antisaccades than for prosaccades. We replicated EEG literature showing lower alpha peak frequency in older adults but not literature showing lower alpha power. Older adults also showed higher beta power and less parietal alpha power asymmetry than young adults. Interaction effects showed that better prosaccade performance was related to lower beta power in young adults but not in older adults. Performance at the trail making test part B (measuring task switching and inhibition) was improved for older adults with higher resting state delta power but did not depend on delta power for young adults. It is argued that individuals with higher slow-wave resting EEG may be more resilient to age deficits in tasks that utilise cross-cortical processing.

Age-related modulation of EEG time-frequency responses in prospective memory retrieval

BACKGROUND

Prospective memory involves remembering to execute an intention at the appropriate moment (prospective component) as well as retrieving the intended action (retrospective component). Several electrophysiological studies showed that neural activity associated with the prospective and the retrospective component differed between older and younger adults. However, these studies mainly reported event-related potentials (ERP), without considering other oscillatory parameters of age-related neural modulations that might be associated with the two components.

OBJECTIVE

In the present study, we analysed electrophysiological data to describe the age-related patterns of brain oscillations associated with the prospective and the retrospective components of prospective memory.

METHODS

The prospective and the retrospective components were manipulated in two experiments. In experiment 1, the prospective component was manipulated by varying the cue distinctiveness (i.e., how easy it was to detect the cue based on colour). In experiment 2, the retrospective component was manipulated by varying the number of intentions to be remembered (i.e., one or two intentions). We used time-frequency analysis to characterise the EEG oscillatory activity in younger and older adults.

RESULTS

The prospective component was associated with age differences in alpha and beta frequency bands. Compared to younger adults, older adults showed a decrease of parietal alpha activity when they detected distinct prospective memory cues, and a decrease of parietal beta when they detected less distinct cues. Moreover, older adults showed less beta activity compared to the younger adults across experimental manipulations. No age differences emerged with respect to the retrospective component.

CONCLUSIONS

The specific pattern of oscillatory activity associated with the prospective component in older adults could underlie the dynamic deployment of different attentional resources supporting cue detection. Moreover, beta activity in both experiments might support an attempt exerted by older adults to enhance task coordination processes. Overall, cluster-based permutation analyses provided a first description of the changes of the EEG time-frequency responses related to intention retrieval in older adults.

Time in Brain: How Biological Rhythms Impact on EEG Signals and on EEG-Derived Brain Networks

Electroencephalography (EEG) is a widely employed tool for exploring brain dynamics and is used extensively in various domains, ranging from clinical diagnosis via neuroscience, cognitive science, cognitive psychology, psychophysiology, neuromarketing, neurolinguistics, and pharmacology to research on brain computer interfaces. EEG is the only technique that enables the continuous recording of brain dynamics over periods of time that range from a few seconds to hours and days and beyond. When taking long-term recordings, various endogenous and exogenous biological rhythms may impinge on characteristics of EEG signals. While the impact of the circadian rhythm and of ultradian rhythms on spectral characteristics of EEG signals has been investigated for more than half a century, only little is known on how biological rhythms influence characteristics of brain dynamics assessed with modern EEG analysis techniques. At the example of multiday, multichannel non-invasive and invasive EEG recordings, we here discuss the impact of biological rhythms on temporal changes of various characteristics of human brain dynamics: higher-order statistical moments and interaction properties of multichannel EEG signals as well as local and global characteristics of EEG-derived evolving functional brain networks. Our findings emphasize the need to take into account the impact of biological rhythms in order to avoid erroneous statements about brain dynamics and about evolving functional brain networks.

Parameterizing neural power spectra into periodic and aperiodic components

Electrophysiological signals exhibit both periodic and aperiodic properties. Periodic oscillations have been linked to numerous physiological, cognitive, behavioral and disease states. Emerging evidence demonstrates that the aperiodic component has putative physiological interpretations and that it dynamically changes with age, task demands and cognitive states. Electrophysiological neural activity is typically analyzed using canonically defined frequency bands, without consideration of the aperiodic (1/f-like) component. We show that standard analytic approaches can conflate periodic parameters (center frequency, power, bandwidth) with aperiodic ones (offset, exponent), compromising physiological interpretations. To overcome these limitations, we introduce an algorithm to parameterize neural power spectra as a combination of an aperiodic component and putative periodic oscillatory peaks. This algorithm requires no a priori specification of frequency bands. We validate this algorithm on simulated data, and demonstrate how it can be used in applications ranging from analyzing age-related changes in working memory to large-scale data exploration and analysis.

Age- and gender-specific characteristics of the resting-state brain activity: a magnetoencephalography study

Aging and gender influence regional brain activities. Although these biases should be considered during the clinical examinations using magnetoencephalography, they have yet to be standardized. In the present study, resting-state magnetoencephalography data were recorded from 54 healthy females and 48 males aged 22 to 75 years, who were controlled for cognitive performance. The regional oscillatory power was estimated for each frequency band (delta, theta, alpha, beta, low-gamma, and high-gamma) using the sLORETA-like algorithm and the biases of age and gender were evaluated, respectively. The results showed that faster oscillatory powers increased with age in the rostral regions and decreased in the caudal regions, while few slower oscillatory powers changed with age. Gender differences in oscillatory powers were found in a broad frequency range, mostly in the caudal brain regions. The present study characterized the effects of healthy aging and gender asymmetricity on the regional resting-state brain activity, with the aim to facilitate the accurate and efficient use of magnetoencephalography in clinical practice.

Multifaceted aspects of charge transfer

Charge transfer and charge transport are by far among the most important processes for sustaining life on Earth and for making our modern ways of living possible. Involving multiple electron-transfer steps, photosynthesis and cellular respiration have been principally responsible for managing the energy flow in the biosphere of our planet since the Great Oxygen Event. It is impossible to imagine living organisms without charge transport mediated by ion channels, or electron and proton transfer mediated by redox enzymes. Concurrently, transfer and transport of electrons and holes drive the functionalities of electronic and photonic devices that are intricate for our lives. While fueling advances in engineering, charge-transfer science has established itself as an important independent field, originating from physical chemistry and chemical physics, focusing on paradigms from biology, and gaining momentum from solar-energy research. Here, we review the fundamental concepts of charge transfer, and outline its core role in a broad range of unrelated fields, such as medicine, environmental science, catalysis, electronics and photonics. The ubiquitous nature of dipoles, for example, sets demands on deepening the understanding of how localized electric fields affect charge transfer. Charge-transfer electrets, thus, prove important for advancing the field and for interfacing fundamental science with engineering. Synergy between the vastly different aspects of charge-transfer science sets the stage for the broad global impacts that the advances in this field have.

Entropy and the Brain: An Overview

Entropy is a powerful tool for quantification of the brain function and its information processing capacity. This is evident in its broad domain of applications that range from functional interactivity between the brain regions to quantification of the state of consciousness. A number of previous reviews summarized the use of entropic measures in neuroscience. However, these studies either focused on the overall use of nonlinear analytical methodologies for quantification of the brain activity or their contents pertained to a particular area of neuroscientific research. The present study aims at complementing these previous reviews in two ways. First, by covering the literature that specifically makes use of entropy for studying the brain function. Second, by highlighting the three fields of research in which the use of entropy has yielded highly promising results: the (altered) state of consciousness, the ageing brain, and the quantification of the brain networks' information processing. In so doing, the present overview identifies that the use of entropic measures for the study of consciousness and its (altered) states led the field to substantially advance the previous findings. Moreover, it realizes that the use of these measures for the study of the ageing brain resulted in significant insights on various ways that the process of ageing may affect the dynamics and information processing capacity of the brain. It further reveals that their utilization for analysis of the brain regional interactivity formed a bridge between the previous two research areas, thereby providing further evidence in support of their results. It concludes by highlighting some potential considerations that may help future research to refine the use of entropic measures for the study of brain complexity and its function. The present study helps realize that (despite their seemingly differing lines of inquiry) the study of consciousness, the ageing brain, and the brain networks' information processing are highly interrelated. Specifically, it identifies that the complexity, as quantified by entropy, is a fundamental property of conscious experience, which also plays a vital role in the brain's capacity for adaptation and therefore whose loss by ageing constitutes a basis for diseases and disorders. Interestingly, these two perspectives neatly come together through the association of entropy and the brain capacity for information processing.

Orientation-dependency of perceptual surround suppression and orientation decoding of centre-surround stimuli are preserved with healthy ageing

A key visual neuronal property that is mirrored in human behaviour is centre-surround contrast suppression, which is orientation-dependent. When a target is embedded in a high-contrast surround, the centre appears reduced in contrast, the magnitude of which depends on the relative orientation between centre and surround. Previous reports demonstrate changes in perceptual surround suppression with ageing; however, whether the orientation-dependency of surround suppression is impacted by ageing has not been explored. Here, we tested 18 younger (aged 19-33) and 18 older (aged 60-77) adults. Perceptual surround suppression was stronger for parallel than orthogonal stimuli; however contrary to previous work, here we found no difference in perceptual suppression strength between age-groups. In the same participants, we measured event-related potentials (ERPs) and conducted multivariate pattern analysis to confirm that parallel and orthogonal centre-surround stimuli elicit distinguishable brain activity, predominantly over occipital areas. Despite a delay in the first prominent ERP component (P1) in response to each pattern, older adults showed similar decoding of orientation information (i.e. distinguish between parallel and orthogonal centre-surround stimuli from 70 ms post-stimulus onset) as younger adults. This suggests that sufficient information to distinguish orientation in centre-surround stimuli becomes available to the older human brain as early as in younger adults.

BOLD and EEG signal variability at rest differently relate to aging in the human brain

Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability - identified with either hemodynamic or electrophysiological methods - reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25 ​± ​3 years, N ​= ​135) and older (67 ​± ​4 years, N ​= ​54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1-12 ​Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15-25 ​Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex.

Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging

The individual alpha peak frequency (IAPF) of the human electroencephalography (EEG) typically experiences slowing with increasing age. Despite this hallmark change, studies that investigate modulations of conventional EEG alpha power and connectivity by aging and age-related neuropathology neglect to account for intergroup differences in IAPF. To investigate the relationship of age-related IAPF slowing with EEG power and connectivity, we recorded eyes-closed resting-state EEG in 37 young adults and 32 older adults. We replicated the finding of a slowed IAPF in older adults. IAPF values were significantly correlated with the frequency of maximum global connectivity and the means of their distributions did not differ, suggesting that connectivity was highest at the IAPF. Older adults expressed reduced global EEG power and connectivity at the conventional upper alpha band (10-12 Hz) compared with young adults. By contrast, groups had equivalent power and connectivity at the IAPF. The results suggest that conventional spectral boundaries may be biased against older adults or any group with a slowed IAPF. We conclude that investigations of alpha activity in aging and age-related neuropathology should be adapted to the IAPF of the individual and that previous findings should be interpreted with caution. EEG in the dominant alpha range may be unsuitable for examining cortico-cortical connectivity due to its subcortical origins.

Inhibitory Control Impairment on Somatosensory Gating Due to Aging: An Event-Related Potential Study

The capacity to suppress irrelevant incoming input, termed sensory gating, is one of the most investigated inhibitory processes associated with cognitive impairments due to aging. The aim of this study was to examine the influence of aging on sensory gating by using somatosensory event-related potentials (ERPs) elicited by repetitive non-painful tactile stimulation (paired-pulsed task). Somatosensory ERPs were recorded in 20 healthy young adults and 20 healthy older adults while they received two identical pneumatic stimuli (S1 and S2) of 100 ms duration with an inter-stimulus interval of 550 ± 50 ms on both forefingers. The difference between the somatosensory ERPs amplitude elicited by S1 and S2 was computed as a sensory gating measure. The amplitude and the latency of P50, N100 and late positive complex (LPC) were analyzed as well as the source generators of the gating effect. Reduced sensory gating was found in older individuals for N100 at frontal and centro-parietal electrodes and for LPC at fronto-central electrodes. Source localization analyses also revealed a reduced current density during gating effect in the older group in frontal areas in N100 and LPC. Moreover, older individuals showed delayed latencies in N100. No significant gating effect differences were found between groups in P50. These findings suggest an age-related slowing of processing speed and a reduced efficiency of inhibitory mechanisms in response to repetitive somatosensory information during stimulus evaluation, and a preservation of processing speed and inhibitory control during early stimulus coding in aging.

EEG Frequency Characteristics in Healthy Advanced Elderly

Abstract. Changes in electroencephalographic (EEG) activity over the course of the normal aging process demonstrate that elderly individuals exhibit an increase in slow wave activity. In this study, we reexamined findings that EEG activity in healthy elderly individuals aged over 85 years (range 85–94) was the same or different compared to individuals younger than 84 years (range 65–84). We performed EEG frequency analysis to investigate the characteristics of resting state frequency components in a cross-sectional study. In individuals aged 85 and older, the dominant frequency component demonstrated a significant shift toward the slower alpha frequency in the left temporal and occipital regions. However, among the oldest individuals, a spectral peak appeared at 9.0–10.0 Hz, and power curves at peak frequency exhibited a sharp rise. Interestingly, healthy individuals older than 85 did not exhibit an appreciable change in EEG, suggesting that “slowing” is not a characteristic sign of aging.

Characterizing Population EEG Dynamics throughout Adulthood

For decades, electroencephalography (EEG) has been a useful tool for investigating the neural mechanisms underlying human psychological processes. However, the amount of time needed to gather EEG data means that most laboratory studies use relatively small sample sizes. Using the Muse, a portable and wireless four-channel EEG headband, we obtained EEG recordings from 6029 subjects 18–88 years in age while they completed a category exemplar task followed by a meditation exercise. Here, we report age-related changes in EEG power at a fine chronological scale for δ, θ, α, and β bands, as well as peak α frequency and α asymmetry measures for both frontal and temporoparietal sites. We found that EEG power changed as a function of age, and that the age-related changes depended on sex and frequency band. We found an overall age-related shift in band power from lower to higher frequencies, especially for females. We also found a gradual, year-by-year slowing of the peak α frequency with increasing age. Finally, our analysis of α asymmetry revealed greater relative right frontal activity. Our results replicate several previous age- and sex-related findings and show how some previously observed changes during childhood extend throughout the lifespan. Unlike previous age-related EEG studies that were limited by sample size and restricted age ranges, our work highlights the advantage of using large, representative samples to address questions about developmental brain changes. We discuss our findings in terms of their relevance to attentional processes and brain-based models of emotional well-being and aging.

Transcranial Alternating Current Stimulation (tACS) differentially modulates speech perception in young and older adults

BACKGROUND

Normal aging is accompanied by a functional decline in processing temporal features of spoken language, such as voice onset time (VOT). On an electrophysiological level, this finding is paralleled by altered patterns of gamma oscillations.

OBJECTIVE

Using 40 Hz transcranial alternating current stimulation (tACS) over the bilateral auditory cortex, this study aims to compare the effect of tACS to modulate VOT-processing in samples of healthy young and older adults.

METHODS

Twenty-five healthy young (age 20-35 years) and 20 older adults (age 60-75 years) participated in this study. Presented with an auditory phoneme categorization task participants received 40 Hz and 6 Hz tACS on two consecutive sessions.

RESULTS

While 40 Hz tACS diminished task accuracy in young adults, older adults benefitted from this stimulation resulting in a more precise phonetic categorization.

CONCLUSION

The results of the study are discussed with respect to the non-linear relationship between gamma oscillations in the vicinity of the auditory cortex and VOT-processing. The present findings are promising in the context of an intervention for subjects with impaired ability to process temporal acoustic features in the speech signal.

Brain Dynamics of Aging: Multiscale Variability of EEG Signals at Rest and during an Auditory Oddball Task

Recently, the study of brain signal fluctuations is widely put forward as a promising entry point to characterize brain dynamics in health and disease. Although interesting results have been reported regarding how variability of brain activations can serve as an indicator of performance and adaptability in elderly, many uncertainties and controversies remain with regard to the comparability, reproducibility, and generality of the described findings, as well as the ensuing interpretations.

The present work focused on the study of fluctuations of cortical activity across time scales in young and older healthy adults. The main objective was to offer a comprehensive characterization of the changes of brain (cortical) signal variability during aging, and to make the link with known underlying structural, neurophysiological, and functional modifications, as well as aging theories. We analyzed electroencephalogram (EEG) data of young and elderly adults, which were collected at resting state and during an auditory oddball task. We used a wide battery of metrics that typically are separately applied in the literature, and we compared them with more specific ones that address their limits. Our procedure aimed to overcome some of the methodological limitations of earlier studies and verify whether previous findings can be reproduced and extended to different experimental conditions. In both rest and task conditions, our results mainly revealed that EEG signals presented systematic age-related changes that were time-scale-dependent with regard to the structure of fluctuations (complexity) but not with regard to their magnitude. Namely, compared with young adults, the cortical fluctuations of the elderly were more complex at shorter time scales, but less complex at longer scales, although always showing a lower variance. Additionally, the elderly showed signs of spatial, as well as between, experimental conditions dedifferentiation. By integrating these so far isolated findings across time scales, metrics, and conditions, the present study offers an overview of age-related changes in the fluctuation electrocortical activity while making the link with underlying brain dynamics.

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults

In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood‐oxygenation level‐dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting‐state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath‐hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age‐related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population‐based Cambridge Centre for Ageing and Neuroscience cohort (Cam‐CAN; http://www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task‐based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects of age on task‐based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing. The results from the mediation analysis demonstrate that RSFA is modulated by measures of vascular function and is not driven solely by changes in the variance of neural activity. Based on these findings we propose that the RSFA scaling method is articularly useful in large scale and longitudinal neuroimaging studies of ageing, or with frail participants, where alternative measures of vascular reactivity are impractical. Hum Brain Mapp 36:2248–2269, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Age-Related Effects on ERP and Oscillatory EEG-Dynamics in a 2-Back Task

It is well known that working memory is one of the most vulnerable cognitive functions in elderly. However, little is known about the neuronal underpinnings and temporal dynamics of working memory mechanisms in healthy aging which are necessary to understand the age-related changes. To this end, 36 young and 36 old healthy individuals performed a 2-back task and a 0-back control task, while the electroencephalogram (EEG) was recorded. Participants were instructed to press a response key whenever a target appeared and not to respond in case of nontargets. Expectedly, older participants showed considerably slower RTs and significantly higher rates of omitted targets and false alarms than young participants in the 2-back task, whereas no age-group difference in detection rate was found in the 0-back task. From the EEG event-related potentials as well as time-frequency plots were computed. The ERPs showed a general delay of the frontocentral N2, and an attenuation and delay of both the P3a and P3b in older versus younger adults. Importantly, the frontal P3a was reduced in older adults in the 2-back task. Time-frequency decomposition revealed consistently lower power in frontal theta (6 Hz) and parietal alpha (9–11 Hz) frequency range in older versus younger adults whereas no age-related differences were found in the delta frequency range. Task unspecific reduction of posterior alpha in elderly was paralleled by a reduction of the P3b. In contrast, the older adults had a strongly reduced frontal theta power in the 2-back task, which parallels the P3a reduction in the ERPs. The widespread reduction of alpha may indicate that older adults needed to recruit more attentional resources for successful task performance, whereas reduced frontal theta may indicate that older adults are less able to recruit frontal resources related to top-down control with increasing task demands. This suggests a less efficient fronto-parietal network synchronicity in older individuals that leads to deficits in identification and maintenance of task relevant stimuli.

Hypothesis-driven methods to augment human cognition by optimizing cortical oscillations

Cortical oscillations have been shown to represent fundamental functions of a working brain, e.g., communication, stimulus binding, error monitoring, and inhibition, and are directly linked to behavior. Recent studies intervening with these oscillations have demonstrated effective modulation of both the oscillations and behavior. In this review, we collect evidence in favor of how hypothesis-driven methods can be used to augment cognition by optimizing cortical oscillations. We elaborate their potential usefulness for three target groups: healthy elderly, patients with attention deficit/hyperactivity disorder, and healthy young adults. We discuss the relevance of neuronal oscillations in each group and show how each of them can benefit from the manipulation of functionally-related oscillations. Further, we describe methods for manipulation of neuronal oscillations including direct brain stimulation as well as indirect task alterations. We also discuss practical considerations about the proposed techniques. In conclusion, we propose that insights from neuroscience should guide techniques to augment human cognition, which in turn can provide a better understanding of how the human brain works.

Aging and motor inhibition: a converging perspective provided by brain stimulation and imaging approaches

The ability to inhibit actions, one of the hallmarks of human motor control, appears to decline with advancing age. Evidence for a link between changes in inhibitory functions and poor motor performance in healthy older adults has recently become available with transcranial magnetic stimulation (TMS). Overall, these studies indicate that the capacity to modulate intracortical (ICI) and interhemispheric (IHI) inhibition is preserved in high-performing older individuals. In contrast, older individuals exhibiting motor slowing and a declined ability to coordinate movement appear to show a reduced capability to modulate GABA-mediated inhibitory processes. As a decline in the integrity of the GABA-ergic inhibitory processes may emerge due to age-related loss of white and gray matter, a promising direction for future research would be to correlate individual differences in structural and/or functional integrity of principal brain networks with observed changes in inhibitory processes within cortico-cortical, interhemispheric, and/or corticospinal pathways. Finally, we underscore the possible links between reduced inhibitory functions and age-related changes in brain activation patterns.

Brain-wide slowing of spontaneous alpha rhythms in mild cognitive impairment

The neurophysiological changes associated with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) include an increase in low frequency activity, as measured with electroencephalography or magnetoencephalography (MEG). A relevant property of spectral measures is the alpha peak, which corresponds to the dominant alpha rhythm. Here we studied the spatial distribution of MEG resting state alpha peak frequency and amplitude values in a sample of 27 MCI patients and 24 age-matched healthy controls. Power spectra were reconstructed in source space with linearly constrained minimum variance beamformer. Then, 88 Regions of Interest (ROIs) were defined and an alpha peak per ROI and subject was identified. Statistical analyses were performed at every ROI, accounting for age, sex and educational level. Peak frequency was significantly decreased (p < 0.05) in MCIs in many posterior ROIs. The average peak frequency over all ROIs was 9.68 ± 0.71 Hz for controls and 9.05 ± 0.90 Hz for MCIs and the average normalized amplitude was (2.57 ± 0.59)·10⁻² for controls and (2.70 ± 0.49)·10⁻² for MCIs. Age and gender were also found to play a role in the alpha peak, since its frequency was higher in females than in males in posterior ROIs and correlated negatively with age in frontal ROIs. Furthermore, we examined the dependence of peak parameters with hippocampal volume, which is a commonly used marker of early structural AD-related damage. Peak frequency was positively correlated with hippocampal volume in many posterior ROIs. Overall, these findings indicate a pathological alpha slowing in MCI.

Developmental differences in EEG and sleep responses to acute ethanol administration and its withdrawal (hangover) in adolescent and adult Wistar rats

Age-related differences in sensitivity to the acute effects of alcohol may play an important role in the increased risk for the development of alcoholism seen in teens that begin drinking at an early age. The present study evaluated the acute and protracted (hangover) effects of ethanol in adolescent (P33-P40) and adult (P100-P107) Wistar rats, using the cortical electroencephalogram (EEG). Six minutes of EEG was recorded during waking, 15 min after administration of 0, 1.5, or 3.0 g/kg ethanol, and for 3 h at 20 h post ethanol, during the rats' next sleep cycle. Significantly higher overall frontal and parietal cortical power was seen in a wide range of EEG frequencies in adolescent rats as compared to adult rats in their waking EEG. Acute administration of ethanol did not produce differences between adolescents and adults on behavioral measures of acute intoxication. However, it did produce a significantly less intense acute EEG response to ethanol in the theta frequencies in parietal cortex in the adolescents as compared to the adults. At 20 h following acute ethanol administration, during the rats' next sleep cycle, a decrease in slow-wave frequencies (1-4 Hz) was seen and the adolescent rats were found to display more reduction in the slow-wave frequencies than the adults did. The present study found that adolescent rats, as compared to adults, demonstrate low sensitivity to acute ethanol administration in the theta frequencies and more susceptibility to disruption of slow-wave sleep during hangover. These studies may lend support to the idea that these traits may contribute to increased risk for alcohol use disorders seen in adults who begin drinking in their early teenage years.

Spatiotemporal dependency of age-related changes in brain signal variability

Recent theoretical and empirical work has focused on the variability of network dynamics in maturation. Such variability seems to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into healthy aging. Two different data sets, one EEG (total n = 48, ages 18–72) and one magnetoencephalography (n = 31, ages 20–75) were analyzed for such spatiotemporal dependency using multiscale entropy (MSE) from regional brain sources. In both data sets, the changes in MSE were timescale dependent, with higher entropy at fine scales and lower at more coarse scales with greater age. The signals were parsed further into local entropy, related to information processed within a regional source, and distributed entropy (information shared between two sources, i.e., functional connectivity). Local entropy increased for most regions, whereas the dominant change in distributed entropy was age-related reductions across hemispheres. These data further the understanding of changes in brain signal variability across the lifespan, suggesting an inverted U-shaped curve, but with an important qualifier. Unlike earlier in maturation, where the changes are more widespread, changes in adulthood show strong spatiotemporal dependence.

Lifespan age differences in working memory: a two-component framework

We suggest that working memory (WM) performance can be conceptualized as the interplay of low-level feature binding processes and top-down control, relating to posterior and frontal brain regions and their interaction in a distributed neural network. We propose that due to age-differential trajectories of posterior and frontal brain regions top-down control processes are not fully mature until young adulthood and show marked decline with advancing age, whereas binding processes are relatively mature in children, but show senescent decline in older adults. A review of the literature spanning from middle childhood to old age shows that binding and top-down control processes undergo profound changes across the lifespan. We illustrate commonalities and dissimilarities between children, younger adults, and older adults reflecting the change in the two components' relative contribution to visual WM performance across the lifespan using results from our own lab. We conclude that an integrated account of visual WM lifespan changes combining research from behavioral neuroscience and cognitive psychology of child development as well as aging research opens avenues to advance our understanding of cognition in general.

Age-related changes in visually evoked electrical brain activity

Whereas much is known about the degenerative effects of aging on cortical tissue, less is known about how aging affects visually evoked electrical activity, and at what latencies. We compared visual processing in elderly and young controls using a visual masking paradigm, which is particularly sensitive to detect temporal processing deficits, while recording EEG. The results show that, on average, elderly have weaker visual evoked potentials than controls, and that elderly show a distinct scalp potential topography (microstate) at around 150 ms after stimulus onset. This microstate occurred irrespective of the visual stimulus presented. Electrical source imaging showed that the changes in the scalp potential resulted from decreased activity in lateral occipital cortex and increases in fronto-parietal areas. We saw, however, no evidence that increased fronto-parietal activity enhanced performance on the discrimination task, and no evidence that it compensated for decreased posterior activity. Our results show qualitatively different patterns of visual evoked potentials (VEPs) in the elderly, and demonstrate that increased fronto-parietal activity arises during visual processing in the elderly already between 150 and 200 ms after stimulus onset. The microstate associated with these changes is a potential diagnostic tool to detect age-related cortical changes.

Age-related differences in corticospinal excitability during a Go/NoGo task

Age-related slowing of reaction times (RTs) is well documented but whether the phenomenon reflects deficits in movement preparation and/or response generation processes is unclear. To gain further insight into this issue, transcranial magnetic stimulation (TMS) was used to investigate motor cortex (M1) excitability and short-interval intracortical inhibitory (SICI) processes during a Go/NoGo RT task in younger and older adults. Single- and paired-pulse TMS was delivered over the left M1 during preparation and response generation periods in a right-hand muscle. Younger adults had shorter RTs and a larger increase in corticospinal excitability at response generation period than older adults. SICI modulation for both groups showed a large reduction in inhibition immediately prior to EMG onset. These findings indicate age-related differences in corticospinal excitability during the response generation stage of sensorimotor information processing.

Aging, Smoking and Hemispheric EEG Asymmetry

As previous research has shown central nicotinic receptors to (a) be asymmetrical, (b) decline with age, and (c) be more abundant in smokers, quantified EEG indices of hemispheric asymmetry were employed to assess whether smoker/non-smoker status affected the aging brain and whether the aging brain demonstrated an altered response to acute smoking/nicotine. Forty healthy volunteers participated, including 20 young (18–39 years) and 20 elderly (64–81 years) adults. Half of the subjects in each age category were lifelong non-smokers and half were cigarette smokers with average smoking histories of 9.3 and 52.0 years for young and elderly respectively. Inter-hemispheric theta and alpha asymmetry indices illustrated greater left hemisphere power (relative to right) in elderly adults, while the reverse trend was seen in young adults. Smokers and non-smokers both showed similar aging trends but differed with respect to their presence in frontal and posterior regions. Intra-hemispheric asymmetry indices, particularly with alpha activity, illustrated a reduced anterior-posterior gradient of power distribution in the elderly. Acute smoking increased slow (delta) and fast (beta) inter-hemispheric indices but only in elderly smokers. Smoking also altered the intra-hemispheric balance of slow wave activity in both age groups of smokers. The results are discussed in relation to normal and pathological aging.

Effect of acute moderate exercise on cognitive event-related potentials n100, p200, n200, and interpeak latencies

BACKGROUND

Effect of acute moderate exercise on cognition has been studied recently, although there are controversial reports in this context. This is the reason we performed this study, to observe the effect of acute moderate exercise on the cognitive functions of persons having a sedentary lifestyle, by measuring the latencies of event-related potentials N100, P200, N200, and the inter-peak latencies N100-P200, P200-N200, and N200-P300.

MATERIALS AND METHODS

Sixty right-handed participants (34 males, 26 females) of age group 15 - 30 years, having a sedentary lifestyle, were recruited for the study. A baseline recording of event-related potentials was conducted and then they were subjected to acute moderate exercise (60 - 80% of the maximum load of effort during exercise, where 100%=200 - Age), again the recording was carried out using the paired student's 't' test, to compare the present values with the initial values.

RESULTS

After performing the exercise there was a significant decrease in the latency of wave N1 and P2 of females for both frequent and rare stimuli. A significant decrease in the latency was seen in wave N2 with rare stimulus in both females and males. While, for frequent stimulus a significant decrease was seen only in females. Also the N2-P3 interpeak latency significantly decreased in males, while there was no significant decrease in females.

CONCLUSION

There was a definite role of exercise in enhancing the cognitive functions as evidenced by its effect on the latencies of event-related potentials N100, P200, N200, and interpeak latencies.

Neuropathic pain in spinal cord injury: significance of clinical and electrophysiological measures

A large percentage of spinal cord-injured subjects suffer from neuropathic pain below the level of the lesion (bNP). The neural mechanisms underlying this condition are not clear. The aim of this study was to elucidate the general effects of spinal deafferentiation and of bNP on electroencephalographic (EEG) activity. In addition, the relationship between the presence of bNP and impaired function of the spinothalamic tract was studied. Measurements were performed in complete and incomplete spinal cord-injured subjects with and without bNP as well as in a healthy control group. Spinothalamic tract function, assessed by contact heat evoked potentials, did not differ between subjects with and without bNP; nevertheless, it was impaired in 94% of subjects suffering from bNP. In the EEG recordings, the degree of deafferentiation was reflected in a slowing of EEG peak frequency in the 6-12-Hz band. Taking into account this unspecific effect, spinal cord-injured subjects with bNP showed significantly slower EEG activity than subjects without bNP. A discrimination analysis in the subjects with spinothalamic tract dysfunction correctly classified 84% of subjects as belonging to either the group with bNP or the group without bNP, according to their EEG peak frequency. These findings could be helpful for both the development of an objective diagnosis of bNP and for testing the effectiveness of new therapeutic agents.

Differential effects of acute alcohol on EEG and sedative responses in adolescent and adult Wistar rats

Age-related developmental differences in sensitivity to the acute effects of alcohol may play an important role in the development of alcoholism. The present study was designed to evaluate the acute effects of alcohol on cortical electroencephalogram (EEG) in adolescent (P36) and adult (P78) Wistar rats. Five minutes of EEG was recorded after administration of 0, 0.75 or 1.5 g/kg alcohol. The righting reflex was performed to measure the sedative effects of alcohol (3.5 g/kg) and total sleeping time for each rat. Our results showed that alcohol (1.5 g/kg) increased power in the 1-2 Hz band and decreased the power in the 32-50 Hz band in the parietal cortical region of adolescent rats. Alcohol (1.5 g/kg) also increased stability of the EEG power in the slow-wave frequency bands (2-4 Hz, 4-6 Hz, and 6-8 Hz) of adolescent rats. In the frontal cortex of adult rats, but not in adolescent rats, alcohol (1.5 or 0.75 g/kg) decreased the power in the 16-32 Hz frequency band. Alcohol (1.5 g/kg) differentially increased power in a multiple of slow-wave frequency bands (2-4 Hz and 4-6 Hz) in the parietal cortex of adult rats as compared to adolescent rats. Adolescent rats were shown significantly shorter sleeping time and higher blood alcohol levels after regaining reflex than adult rats. Our results provide additional evidence of age-related differences in the effects of acute alcohol on cortical EEG, sedation and tolerance.