Effect of normal aging upon interhemispheric EEG coherence: analysis during rest and photic stimulation

Prognostic interictal electroencephalographic biomarkers and models to assess antiseizure medication efficacy for clinical practice: A scoping review

Antiseizure medication (ASM) is the primary treatment for epilepsy. In clinical practice, methods to assess ASM efficacy (predict seizure freedom or seizure reduction), during any phase of the drug treatment lifecycle, are limited. This scoping review identifies and appraises prognostic electroencephalographic (EEG) biomarkers and prognostic models that use EEG features, which are associated with seizure outcomes following ASM initiation, dose adjustment, or withdrawal. We also aim to summarize the population and context in which these biomarkers and models were identified and described, to understand how they could be used in clinical practice. Between January 2021 and October 2022, four databases, references, and citations were systematically searched for ASM studies investigating changes to interictal EEG or prognostic models using EEG features and seizure outcomes. Study bias was appraised using modified Quality in Prognosis Studies criteria. Results were synthesized into a qualitative review. Of 875 studies identified, 93 were included. Biomarkers identified were classed as qualitative (visually identified by wave morphology) or quantitative. Qualitative biomarkers include identifying hypsarrhythmia, centrotemporal spikes, interictal epileptiform discharges (IED), classifying the EEG as normal/abnormal/epileptiform, and photoparoxysmal response. Quantitative biomarkers were statistics applied to IED, high-frequency activity, frequency band power, current source density estimates, pairwise statistical interdependence between EEG channels, and measures of complexity. Prognostic models using EEG features were Cox proportional hazards models and machine learning models. There is promise that some quantitative EEG biomarkers could be used to assess ASM efficacy, but further research is required. There is insufficient evidence to conclude any specific biomarker can be used for a particular population or context to prognosticate ASM efficacy. We identified a potential battery of prognostic EEG biomarkers, which could be combined with prognostic models to assess ASM efficacy. However, many confounders need to be addressed for translation into clinical practice.

Functional brain changes using electroencephalography after a 24-week multidomain intervention program to prevent dementia

Quantitative electroencephalography (QEEG) has proven useful in predicting the response to various treatments, but, until now, no study has investigated changes in functional connectivity using QEEG following a lifestyle intervention program. We aimed to investigate neurophysiological changes in QEEG after a 24-week multidomain lifestyle intervention program in the SoUth Korean study to PrEvent cognitive impaiRment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN). Participants without dementia and with at least one modifiable dementia risk factor, aged 60–79 years, were randomly assigned to the facility-based multidomain intervention (FMI) (n = 51), the home-based multidomain intervention (HMI) (n = 51), and the control group (n = 50). The analysis of this study included data from 44, 49, and 34 participants who underwent EEG at baseline and at the end of the study in the FMI, HMI, and control groups, respectively. The spectrum power and power ratio of EEG were calculated. Source cortical current density and functional connectivity were estimated by standardized low-resolution brain electromagnetic tomography. Participants who received the intervention showed increases in the power of the beta1 and beta3 bands and in the imaginary part of coherence of the alpha1 band compared to the control group. Decreases in the characteristic path lengths of the alpha1 band in the right supramarginal gyrus and right rostral middle frontal cortex were observed in those who received the intervention. This study showed positive biological changes, including increased functional connectivity and higher global efficiency in QEEG after a multidomain lifestyle intervention.

Clinical trial registration

[https://clinicaltrials.gov/ct2/show/NCT03980392] identifier [NCT03980392].

Schizophrenia induces abnormal frequency-dependent patterns of dynamic brain network reconfiguration during an auditory oddball task

OBJECTIVE

Schizophrenia is a psychiatric disorder that has been shown to disturb the dynamic top-down processing of sensory information. Various imaging techniques have revealed abnormalities in brain activity associated with this disorder, both locally and between cerebral regions. However, there is increasing interest in investigating dynamic network response to novel and relevant events at the network level during an attention-demanding task with high-temporal-resolution techniques. The aim of the work was: (i) to test the capacity of a novel algorithm to detect recurrent brain meta-states from auditory oddball task recordings; and (ii) to evaluate how the dynamic activation and behavior of the aforementioned meta-states were altered in schizophrenia, since it has been shown to impair top-down processing of sensory information.

APPROACH

A novel unsupervised method for the detection of brain meta-states based on recurrence plots and community detection algorithms, previously tested on resting-state data, was used on auditory oddball task recordings. Brain meta-states and several properties related to their activation during target trials in the task were extracted from electroencephalography (EEG) data from patients with schizophrenia and cognitively healthy controls.

MAIN RESULTS

The methodology successfully detected meta-states during an auditory oddball task, and they appeared to show both frequency-dependent time-locked and non-time-locked activity with respect to the stimulus onset. Moreover, patients with schizophrenia displayed higher network diversity, and showed more sluggish meta-state transitions, reflected in increased dwell times, less complex meta-state sequences, decreased meta-state space speed, and abnormal ratio of negative meta-state correlations.

SIGNIFICANCE

Abnormal cognition in schizophrenia is also reflected in decreased brain flexibility at the dynamic network level, which may hamper top-down processing, possibly indicating impaired decision-making linked to dysfunctional predictive coding. Moreover, the results showed the ability of the methodology to find meaningful and task-relevant changes in dynamic connectivity and pathology-related group differences.

Default mode network and neural phase synchronization in healthy aging: A resting state EEG study

Aging is associated with altered brain connectivity within the default mode network (DMN). Although research using functional magnetic resonance imaging has quantified age-related alterations in functional connectivity within this network during resting state, it is less clear how this may be reflected in electrophysiological measures, and how this relates to cognitive performance in older adults. The aim of this study was to quantify age differences in phase synchrony of the DMN during resting state, with particular focus on connectivity between the anterior node (i.e., medial prefrontal cortex, or mPFC) and other associated regions in this network. Electroencephalography was recorded from 55 younger adults (18-30 years, 28 females) and 34 older adults (64-88 years, 16 females) in two resting state conditions (eyes-open and -closed). Source-level functional connectivity was quantified using phase-locking value (PLV) with a spatial filter of six sources of interest, and were subjected to data-driven permutation testing between groups from 1 to 50 Hz. Older adults also completed tests of memory, language, executive functioning, and processing speed. Findings indicated decreased connectivity in the alpha2 range for older than younger adults between the mPFC and other DMN regions including the left angular gyrus and bilateral lateral temporal cortices, the latter of which were associated with lower performance in semantic fluency and executive functioning in older adults. Furthermore, greater PLV in theta and beta bands between the mPFC and posterior cingulate regions was found in older than younger adults. These results suggest age-related changes in DMN functional connectivity are non-uniform and frequency-dependent, and may reflect poorer performance in cognitive domains thought to decline with aging.

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.

Music Training, Working Memory, and Neural Oscillations: A Review

This review focuses on reports that link music training to working memory and neural oscillations. Music training is increasingly associated with improvement in working memory, which is strongly related to both localized and distributed patterns of neural oscillations. Importantly, there is a small but growing number of reports of relationships between music training, working memory, and neural oscillations in adults. Taken together, these studies make important contributions to our understanding of the neural mechanisms that support effects of music training on behavioral measures of executive functions. In addition, they reveal gaps in our knowledge that hold promise for further investigation. The current review is divided into the main sections that follow: (1) discussion of behavioral measures of working memory, and effects of music training on working memory in adults; (2) relationships between music training and neural oscillations during temporal stages of working memory; (3) relationships between music training and working memory in children; (4) relationships between music training and working memory in older adults; and (5) effects of entrainment of neural oscillations on cognitive processing. We conclude that the study of neural oscillations is proving useful in elucidating the neural mechanisms of relationships between music training and the temporal stages of working memory. Moreover, a lifespan approach to these studies will likely reveal strategies to improve and maintain executive function during development and aging.

Age-Dependent Effect of Transcranial Alternating Current Stimulation on Motor Skill Consolidation

Transcranial alternating current stimulation (tACS) is the application of subthreshold, sinusoidal current to modulate ongoing brain rhythms related to sensory, motor and cognitive processes. Electrophysiological studies suggested that the effect of tACS applied at an alpha frequency (8–12 Hz) was state-dependent. The effects of tACS, that is, an increase in parieto-occipital electroencephalography (EEG) alpha power and magnetoencephalography (MEG) phase coherence, was only observed when the eyes were open (low alpha power) and not when the eyes were closed (high alpha power). This state-dependency of the effects of alpha tACS might extend to the aging brain characterized by general slowing and decrease in spectral power of the alpha rhythm. We additionally hypothesized that tACS will influence the motor cortex, which is involved in motor skill learning and consolidation. A group of young and old healthy adults performed a serial reaction time task (SRTT) with their right hand before and after the tACS stimulation. Each participant underwent three sessions of stimulation: sham, stimulation applied at the individual participant’s alpha peak frequency or individual alpha peak frequency (iAPF; α-tACS) and stimulation with iAPF plus 2 Hz (α2-tACS) to the left motor cortex for 10 min (1.5 mA). We measured the effect of stimulation on general motor skill (GMS) and sequence-specific skill (SS) consolidation. We found that α-tACS and α2-tACS improved GMS and SS consolidation in the old group. In contrast, α-tACS minimally improved GMS consolidation but impaired SS consolidation in the young group. On the other hand, α2-tACS was detrimental to the consolidation of both skills in the young group. Our results suggest that individuals with aberrant alpha rhythm such as the elderly could benefit more from tACS stimulation, whereas for young healthy individuals with intact alpha rhythm the stimulation could be detrimental.

Predicting Age From Brain EEG Signals-A Machine Learning Approach

Objective: The brain age gap estimate (BrainAGE) is the difference between the estimated age and the individual chronological age. BrainAGE was studied primarily using MRI techniques. EEG signals in combination with machine learning (ML) approaches were not commonly used for the human age prediction, and BrainAGE. We investigated whether age-related changes are affecting brain EEG signals, and whether we can predict the chronological age and obtain BrainAGE estimates using a rigorous ML framework with a novel and extensive EEG features extraction. Methods: EEG data were obtained from 468 healthy, mood/anxiety, eating and substance use disorder participants (297 females) from the Tulsa-1000, a naturalistic longitudinal study based on Research Domain Criteria framework. Five sets of preprocessed EEG features across channels and frequency bands were used with different ML methods to predict age. Using a nested-cross-validation (NCV) approach and stack-ensemble learning from EEG features, the predicted age was estimated. The important features and their spatial distributions were deduced. Results: The stack-ensemble age prediction model achieved R2 = 0.37 (0.06), Mean Absolute Error (MAE) = 6.87(0.69) and RMSE = 8.46(0.59) in years. The age and predicted age correlation was r = 0.6. The feature importance revealed that age predictors are spread out across different feature types. The NCV approach produced a reliable age estimation, with features consistent behavior across different folds. Conclusion: Our rigorous ML framework and extensive EEG signal features allow a reliable estimation of chronological age, and BrainAGE. This general framework can be extended to test EEG association with and to predict/study other physiological relevant responses.

Coherence and phase synchrony analyses of EEG signals in Mild Cognitive Impairment (MCI): A study of functional brain connectivity

This paper presents an EEG study for coherence and phase synchrony in mild cognitive impairment (MCI) subjects. MCI is characterized by cognitive decline, which is an early stage of Alzheimer’s disease (AD). AD is a neurodegenerative disorder with symptoms such as memory loss and cognitive impairment. EEG coherence is a statistical measure of correlation between signals from electrodes spatially separated on the scalp. The magnitude of phase synchrony is expressed in the phase locking value (PLV), a statistical measure of neuronal connectivity in the human brain. Brain signals were recorded using an Emotiv Epoc 14-channel wireless EEG at a sampling frequency of 128 Hz. In this study, we used 22 elderly subjects consisted of 10 MCI subjects and 12 healthy subjects as control group. The coherence between each electrode pair was measured for all frequency bands (delta, theta, alpha and beta). In the MCI subjects, the value of coherence and phase synchrony was generally lower than in the healthy subjects especially in the beta frequency. A decline of intrahemisphere coherence in the MCI subjects occurred in the left temporo-parietal-occipital region. The pattern of decline in MCI coherence is associated with decreased cholinergic connectivity along the path that connects the temporal, occipital, and parietal areas of the brain to the frontal area of the brain. EEG coherence and phase synchrony are able to distinguish persons who suffer AD in the early stages from healthy elderly subjects.

Melatonin Effects on EEG Activity During Sleep Onset in Mild-to-Moderate Alzheimer's Disease: A Pilot Study

There is evidence demonstrating that 5-mg of fast-release melatonin significantly reduces nocturnal sleep onset in patients with mild-to-moderate Alzheimer's disease (AD). However, the physiological mechanism that could promote sleep installation by melatonin in patients with AD is still poorly understood. The present pilot study was designed to analyze the effects of melatonin on cortical activity during the sleep onset period (SOP) in eight mild-to-moderate AD patients treated with 5-mg of fast-release melatonin. Electroencephalographic recordings were obtained from C3-A1, C4-A2, F7-T3, F8-T4, F3-F4, and O1-O2. The relative power (RP), interhemispheric, intrahemispheric, and fronto-posterior correlations of six electroencephalographic bands were calculated and compared between two conditions: placebo and melatonin. Results show that at F7-T3, F3-F4, and C3-A1, melatonin induced an increase of the RP of the delta band. Likewise, in F7-T3, melatonin induced a decrease of the RP in the alpha1 band. Similarly, results show a lower interhemispheric correlation between the F7-T3 and F8-T4 derivations in the alpha1 band compared to the placebo condition. We conclude that the short sleep onset related to melatonin intake in AD patients was associated with a lower RP of the alpha1, a higher RP of the delta band (mainly in the left hemisphere) and a decreased interhemispheric EEG coupling in the alpha1 band. The possible role of the GABAergic neurotransmission as well as of the cascade of neurochemical events that melatonin triggers on sleep onset are discussed.

Detection of time-, frequency- and direction-resolved communication within brain networks

Electroencephalography (EEG) records fast-changing neuronal signalling and communication and thus can offer a deep understanding of cognitive processes. However, traditional data analyses which employ the Fast-Fourier Transform (FFT) have been of limited use as they do not allow time- and frequency-resolved tracking of brain activity and detection of directional connectivity. Here, we applied advanced qEEG tools using autoregressive (AR) modelling, alongside traditional approaches, to murine data sets from common research scenarios: (a) the effect of age on resting EEG; (b) drug actions on non-rapid eye movement (NREM) sleep EEG (pharmaco-EEG); and (c) dynamic EEG profiles during correct vs incorrect spontaneous alternation responses in the Y-maze. AR analyses of short data strips reliably detected age- and drug-induced spectral EEG changes, while renormalized partial directed coherence (rPDC) reported direction- and time-resolved connectivity dynamics in mice. Our approach allows for the first time inference of behaviour- and stage-dependent data in a time- and frequency-resolved manner, and offers insights into brain networks that underlie working memory processing beyond what can be achieved with traditional methods.

Alpha band EEG coherence in healthy nonagenarians

ABSTRACT Electroencephalographic (EEG) coherence is a parameter that enables evaluation of cerebral connectivity. It may be related to the functional state of the brain. In the elderly, it may reflect the neuronal loss caused by aging. Objective To describe characteristics of coherence in nonagenarians. Methods We evaluated interhemispheric coherence for the alpha band in 42 cognitively normal individuals aged 90 to 101 years. Coherence values in the occipital electrode (O1O2), in the resting state with closed eyes, were calculated by means of spectral analysis using digital EEG EMSA 32 channels, 12 bits and a frequency of 200 Hz. Results The mean coherence value for the alpha band at O1O2 was 0.65 (SD 0.13). No significant differences were found between men and women. Conclusions The findings from this study did not show any decrease in interhemispheric coherence for the alpha band in cognitively normal nonagenarians. This may be useful as a standard value for this age group.

Exercise-Related Changes of Networks in Aging and Mild Cognitive Impairment Brain

Aging and mild cognitive impairment (MCI) are accompanied by decline of cognitive functions. Meanwhile, the most common form of dementia is Alzheimer's disease (AD), which is characterized by loss of memory and other intellectual abilities serious to make difficulties for patients in their daily life. MCI is a transition period between normal aging and dementia, which has been used for early detection of emerging dementia. It converts to dementia with an annual rate of 5-15% as compared to normal aging with 1% rate. Small decreases in the conversion rate of MCI to AD might significantly reduce the prevalence of dementia. Thus, it is important to intervene at the preclinical stage. Since there are still no effective drugs to treat AD, non-drug intervention is crucial for the prevention and treatment of cognitive decline in aging and MCI populations. Previous studies have found some cognitive brain networks disrupted in aging and MCI population, and physical exercise (PE) could effectively remediate the function of these brain networks. Understanding the exercise-related mechanisms is crucial to design efficient and effective PE programs for treatment/intervention of cognitive decline. In this review, we provide an overview of the neuroimaging studies on physical training in normal aging and MCI to identify the potential mechanisms underlying current physical training procedures. Studies of functional magnetic resonance imaging, electroencephalography, magnetoencephalography and positron emission tomography on brain networks were all included. Based on our review, the default mode network, fronto-parietal network and fronto-executive network are probably the three most valuable targets for efficiency evaluation of interventions.

Interactive effects of age and gender on EEG power and coherence during a short-term memory task in middle-aged adults

The effects of age and gender on electroencephalographic (EEG) activity during a short-term memory task were assessed in a group of 40 healthy participants aged 22-63 years. Multi-channel EEG was recorded in 20 younger (mean = 24.65-year-old, 10 male) and 20 middle-aged participants (mean = 46.40-year-old, 10 male) during performance of a Sternberg task. EEG power and coherence measures were analyzed in different frequency bands. Significant interactions emerged between age and gender in memory performance and concomitant EEG parameters, suggesting that the aging process differentially influences men and women. Middle-aged women showed a lower short-term memory performance compared to young women, which was accompanied by decreasing delta and theta power and increasing brain connectivity with age in women. In contrast, men showed no age-related decline in short-term memory performance and no changes in EEG parameters. These results provide first evidence of age-related alterations in EEG activity underlying memory processes, which were already evident in the middle years of life in women but not in men.

Alteration of consciousness via diverse photo-acoustic stimulatory patterns. Phenomenology and effect on salivary flow rate, alpha-amylase and total protein levels

Long-term photo-acoustic stimulation is used for the induction of altered states of consciousness for both therapeutic and experimental purposes. Long-term photo-acoustic stimulation also leads to changes in the composition of saliva which have a key contribution to the efficiency of this technique in easing mucosal symptoms of oral psychosomatic patients. The aim of this study is to find out whether there is any cumulative effect of repeated stimulation and whether there are any detectable differences between diverse stimulatory patterns of long lasting photo-acoustic stimulation on the phenomenology of the appearing trance state and on salivary secretion. There was significant cumulative effect in relation with the appearance of day dreaming as phenomenological parameter, and in relation with protein output and amylase/protein ratio as salivary parameter. Pattern specific effect was detectable in relation with salivary flow rate only. Although our results clearly indicate the existence of certain cumulative and stimulation-pattern specific effects of repeated photo-acoustic stimulation, the absolute values of all these effects were relatively small in this study. Therefore, in spite of their theoretical importance there are no direct clinical consequences of these findings. However, our data do not exclude at all the possibility that repeated stimulation with other stimulatory parameters may lead to more pronounced effects. Further studies are needed to make clear conclusion in this respect.

Temporo-frontal functional connectivity during auditory change detection is altered in Alzheimer's disease

Cortico-cortical connections might be disturbed in patients with Alzheimer's disease (AD). This study aimed to investigate the alterations of functional connectivity in AD during auditory change detection processing by measuring the local neuronal activation and functional connectivity between cortical regions. Magnetoencephalographic responses to deviant and standard sounds were recorded in 16 AD patients, 18 young controls and 16 elderly controls. Larger source amplitudes and shorter peak latencies were found in the right temporal magnetic mismatch responses of young controls compared with elderly controls and AD patients. During deviant stimuli, the right theta temporal-frontal phase synchrony was significantly smaller in AD than in young controls and elderly controls. Moreover, the left temporal-frontal synchronization at theta and alpha bands was reduced in AD and elderly controls compared with young controls. In conclusion, the loss in temporo-frontal theta synchronization might be an electrophysiological hallmark of AD.

Age-related changes in EEG coherence

BACKGROUND AND PURPOSE

Coherence changes can reflect the pathophysiological processes involved in human ageing. We conducted a retrospective population study that sought to analyze the age-related changes in EEG coherence in a group of 17,722 healthy professional drivers.

MATERIALS AND METHODS

The EEGs were obtained using a standard 10-20 electrode configuration on the scalp. The recordings from 19 scalp electrodes were taken while the participants' eyes were closed. The linear correlations between the age and coherence were estimated by linear regression analysis.

RESULTS

Our results showed a significant decrease in coherence with age in the theta and alpha bands, and there was an increasing coherence with the beta bands. The most prominent changes occurred in the alpha bands. The delta bands contained movement artefacts, which most likely do not change with age.

CONCLUSIONS

The age-related EEG desynchrony can be partly explained by the age-related reduction of cortical connectivity. Higher frequencies of oscillations require less cortical area of high coherence. These findings explain why the lowest average coherence values were observed in the beta and sigma bands, as well as why the beta bands show borderline statistical significance and the sigma bands show non-significance. The age-dependent decrease in coherence may influence the estimation of age-related changes in EEG energy due to phase cancellation.

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.

Impact of visual repetition rate on intrinsic properties of low frequency fluctuations in the visual network

BACKGROUND

Visual processing network is one of the functional networks which have been reliably identified to consistently exist in human resting brains. In our work, we focused on this network and investigated the intrinsic properties of low frequency (0.01-0.08 Hz) fluctuations (LFFs) during changes of visual stimuli. There were two main questions to be discussed in this study: intrinsic properties of LFFs regarding (1) interactions between visual stimuli and resting-state; (2) impact of repetition rate of visual stimuli.

METHODOLOGY/PRINCIPAL FINDINGS

We analyzed scanning sessions that contained rest and visual stimuli in various repetition rates with a novel method. The method included three numerical approaches involving ICA (Independent Component Analyses), fALFF (fractional Amplitude of Low Frequency Fluctuation), and Coherence, to respectively investigate the modulations of visual network pattern, low frequency fluctuation power, and interregional functional connectivity during changes of visual stimuli. We discovered when resting-state was replaced by visual stimuli, more areas were involved in visual processing, and both stronger low frequency fluctuations and higher interregional functional connectivity occurred in visual network. With changes of visual repetition rate, the number of areas which were involved in visual processing, low frequency fluctuation power, and interregional functional connectivity in this network were also modulated.

CONCLUSIONS/SIGNIFICANCE

To combine the results of prior literatures and our discoveries, intrinsic properties of LFFs in visual network are altered not only by modulations of endogenous factors (eye-open or eye-closed condition; alcohol administration) and disordered behaviors (early blind), but also exogenous sensory stimuli (visual stimuli with various repetition rates). It demonstrates that the intrinsic properties of LFFs are valuable to represent physiological states of human brains.

Directionality of EEG synchronization in Alzheimer's disease subjects

Is directionality of electroencephalographic (EEG) synchronization abnormal in amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD)? EEG data were recorded in 64 normal elderly (Nold), 69 amnesic MCI, and 73 mild AD subjects at rest condition (closed eyes). Direction of information flux within EEG functional coupling at electrode pairs was performed by directed transfer function (DTF) at delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz). Parietal to frontal direction of the information flux within EEG functional coupling was stronger in Nold than in MCI and/or AD subjects, namely for alpha and beta rhythms. In contrast, the directional flow within inter-hemispheric EEG functional coupling did not discriminate among the three groups. These results suggest that directionality of parieto-to-frontal EEG synchronization is abnormal not only in AD but also in amnesic MCI.

Aging and brain activation with working memory tasks: an fMRI study of connectivity

BACKGROUND

White matter changes in aging and neuropsychiatric disorders may produce disconnection of neural circuits. Temporal correlations in regional blood oxygen level dependent (BOLD) signals may be used to assess effective functional connectivity in specific circuits, such as prefrontal cortex (PFC) circuits supporting working memory (WM) tasks. We hypothesized healthy older subjects would show lower connectivity than younger subjects.

METHODS

Healthy younger (n = 9, 25.9 (SD 6.0) years) and older adults (n = 11, 68.3 (4.9) years) performed WM tasks during functional MRI. Subjects viewed images and were instructed to label them, either simultaneously or after a delay; BOLD responses with and without delay were contrasted to assess differential WM activation and connectivity. Two tasks were used: a semantic task, with line drawings categorized as 'alive' or 'not living', and an emotional task, with emotive faces as stimuli and subjects selecting the better emotional description.

RESULTS

In both tasks, older subjects activated larger regions and had greater inter-individual variability in extent of activation. In the semantic task, connectivity was lower in the older subjects for the amygdala/orbital PFC circuit (p = 0.04). Contrary to our predictions, older subjects exhibited higher connectivity than younger subjects in the circuit linking orbital and dorsolateral PFC in both semantic (p = 0.04) and emotional (p = 0.02) tasks.

CONCLUSIONS

Healthy subjects exhibited age-dependent differences in connectivity in working memory circuits, but this may reflect effects of aging on white matter, compensatory mechanisms, and other factors. Volumetric determination of white matter hyperintensities in future studies may clarify the functional importance of structural damage.

EEG coherence obtained from an auditory oddball task increases with age

Changes in coherence with aging during cognitive tasks have, until now, not been investigated. However, several fMRI and positron emission tomography studies of cognitive tasks have found increased bilateral activity in elderly subjects. Changes in coherence with aging during a cognitive task were investigated to see if EEG coherence was present in older adults. An auditory oddball task, which is a widely used test for cognitive function, was used. Eleven young adults (27.8 +/- 4.8 years, six females) and 10 older adults (61.3 +/- 4.6 years, six females) were studied, and both interhemispheric and long- and short-range intrahemispheric coherence were considered. Higher interhemispheric coherence was found in the older subjects in the delta band. Short intrahemispheric coherence was also increased in the theta, delta, and alpha bands. Higher coherence, although not significantly different, was also found for all other coherence types and bands, except for long intrahemispheric coherence in the low gamma band. The results presented here provide the first evidence that aging is associated with increased EEG coherence during a relatively easy cognitive task.

Fronto-parietal coupling of brain rhythms in mild cognitive impairment: a multicentric EEG study

Electroencephalographic (EEG) data were recorded in 69 normal elderly (Nold), 88 mild cognitive impairment (MCI), and 109 mild Alzheimer's disease (AD) subjects at rest condition, to test whether the fronto-parietal coupling of EEG rhythms is in line with the hypothesis that MCI can be considered as a pre-clinical stage of the disease at group level. Functional coupling was estimated by synchronization likelihood of Laplacian-transformed EEG data at electrode pairs, which accounts for linear and non-linear components of that coupling. Cortical rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), beta 2 (20-30Hz), and gamma (30-40Hz). Compared to the Nold subjects, the AD patients presented a marked reduction of the synchronization likelihood (delta to gamma) at both fronto-parietal and inter-hemispherical (delta to beta 2) electrodes. As a main result, alpha 1 synchronization likelihood progressively decreased across Nold, MCI, and mild AD subjects at midline (Fz-Pz) and right (F4-P4) fronto-parietal electrodes. The same was true for the delta synchronization likelihood at right fronto-parietal electrodes (F4-P4). For these EEG bands, the synchronization likelihood correlated with global cognitive status as measured by the Mini Mental State Evaluation. The present results suggest that at group level, fronto-parietal coupling of the delta and alpha rhythms progressively becomes abnormal though MCI and mild AD. Future longitudinal research should evaluate whether the present EEG approach is able to predict the cognitive decline in individual MCI subjects.

Memory-related EEG power and coherence reductions in mild Alzheimer's disease

OBJECTIVES

To examine memory-related EEG power and coherence over temporal and central recording sites in patients with early Alzheimer's disease (AD) and normal controls.

METHOD

EEG was recorded from central (Fz, Cz and Pz) and temporal (T3 and T4) electrodes while ten very mild AD patients and ten controls performed a Sternberg-type memory scanning task with three levels of working memory load. Spectral power in delta (0-3 Hz), theta (3-5 Hz), lower alpha1 (5-7 Hz), lower alpha2 (7-9 Hz), upper alpha (9-11 Hz) and beta (15-30 Hz) was averaged for temporal and central electrodes. Coherence was averaged between central electrodes, between central and right temporal electrodes and between central and left temporal electrodes.

RESULTS

While behavioral performance of very mild AD patients did not differ significantly from that of normal controls, findings suggest that normal controls but not AD patients respond to memory demands by increasing upper alpha power over temporal cortex. When compared with normal controls, AD patients had reduced upper alpha coherence between central and right temporal cortex.

DISCUSSION

Results are consistent with previous research on the role of upper alpha in semantic memory and suggest that very mild AD may inhibit selective synchronization of upper alpha in temporal lobes. Reduced coherence between central and temporal cortex is discussed in light of a neurological model of AD that hypothesizes reduced electrocortical efficiency and a breakdown of neural network communication to temporal lobes possibly resulting from temporal lobe atrophy.

Age effects on visual EEG responses reveal distinct frontal alpha networks

OBJECTIVES

The present study aimed to describe the effect of aging on single-trial visual alpha responses.

METHODS

Visual evoked potentials were recorded at F3, Cz, P3, and O1 in 12 young (20-30-year-olds) and in 10 middle-aged adults (50-55-year-olds). Slow (7-10 Hz) and fast (10-15 Hz) alpha frequency bands were analyzed. Three parameters of single alpha responses were assessed for the 0-300 ms period after stimulus: (i) maximal single-sweep amplitude; (ii) phase-locking with stimulus, and (iii) enhancement of post-stimulus relative to pre-stimulus alpha activity.

RESULTS

Ongoing alpha activity at anterior sites was larger in middle-aged subjects. Age differences in response amplitude depended on the anterior shift of ongoing alpha activity. Over fronto-central areas, the phase-locking of fast alpha responses was significantly increased, whereas the phase-locking of slow alpha responses was decreased in middle-aged compared to young adults, independently of amplitude. In contrast to slow alpha responses, frontal and occipital fast alpha responses were interrelated.

CONCLUSIONS

These observations are in accordance with previous findings from the auditory modality implying that the age-related changes in frontal alpha oscillations are modality-independent. Slow and fast frontal alpha responses were affected differentially by the age, which might reflect the activations of functionally distinct alpha networks.