Hub structure in functional network of EEG signals supporting high cognitive functions in older individuals.

Introduction: Maintaining high cognitive functions is desirable for "wellbeing" in old age and is particularly relevant to a super-aging society. According to their individual cognitive functions, optimal intervention for older individuals facilitates the maintenance of cognitive functions. Cognitive function is a result of whole-brain interactions. These interactions are reflected in several measures in graph theory analysis for the topological characteristics of functional connectivity. Betweenness centrality (BC), which can identify the "hub" node, i.e., the most important node affecting whole-brain network activity, may be appropriate for capturing whole-brain interactions. During the past decade, BC has been applied to capture changes in brain networks related to cognitive deficits arising from pathological conditions. In this study, we hypothesized that the hub structure of functional networks would reflect cognitive function, even in healthy elderly individuals. Method: To test this hypothesis, based on the BC value of the functional connectivity obtained using the phase lag index from the electroencephalogram under the eyes closed resting state, we examined the relationship between the BC value and cognitive function measured using the Five Cognitive Functions test total score. Results: We found a significant positive correlation of BC with cognitive functioning and a significant enhancement in the BC value of individuals with high cognitive functioning, particularly in the frontal theta network. Discussion: The hub structure may reflect the sophisticated integration and transmission of information in whole-brain networks to support high-level cognitive function. Our findings may contribute to the development of biomarkers for assessing cognitive function, enabling optimal interventions for maintaining cognitive function in older individuals.

Enhanced temporal complexity of EEG signals in older individuals with high cognitive functions.

Recent studies suggest that the maintenance of cognitive function in the later life of older people is an essential factor contributing to mental wellbeing and physical health. Particularly, the risk of depression, sleep disorders, and Alzheimer's disease significantly increases in patients with mild cognitive impairment. To develop early treatment and prevention strategies for cognitive decline, it is necessary to individually identify the current state of cognitive function since the progression of cognitive decline varies among individuals. Therefore, the development of biomarkers that allow easier measurement of cognitive function in older individuals is relevant for hyperaged societies. One of the methods used to estimate cognitive function focuses on the temporal complexity of electroencephalography (EEG) signals. The characteristics of temporal complexity depend on the time scale, which reflects the range of neuron functional interactions. To capture the dynamics, composed of multiple time scales, multiscale entropy (MSE) analysis is effective for comprehensively assessing the neural activity underlying cognitive function in the brain. Thus, we hypothesized that EEG complexity analysis could serve to assess a wide range of cognitive functions in older adults. To validate our hypothesis, we divided older participants into two groups based on their cognitive function test scores: a high cognitive function group and a low cognitive function group, and applied MSE analysis to the measured EEG data of all participants. The results of the repeated-measures analysis of covariance using age and sex as a covariate in the MSE profile showed a significant difference between the high and low cognitive function groups (F = 10.18, p = 0.003) and the interaction of the group × electrodes (F = 3.93, p = 0.002). Subsequently, the results of the post-hoc t-test showed high complexity on a slower time scale in the frontal, parietal, and temporal lobes in the high cognitive function group. This high complexity on a slow time scale reflects the activation of long-distance neural interactions among various brain regions to achieve high cognitive functions. This finding could facilitate the development of a tool for diagnosis of cognitive decline in older individuals.

Smaller insula and inferior frontal volumes in young adults with pervasive developmental disorders.

Enlarged head circumference and increased brain weight have been reported in infants with pervasive developmental disorders (PDD), and volumetric studies suggest that children with PDD have abnormally enlarged brain volumes. However, little is known about brain volume abnormalities in young adults with PDD. We explored gray matter (GM) volume in young adults with PDD. T1-weighted volumetric images were acquired with a 3-T magnetic resonance scanner from 32 males with high-functioning PDD (23.8+/-4.2 years; Full Scale Intelligence Quotient [FSIQ]=101.6+/-15.6) and 40 age-matched normal male control subjects (22.5+/-4.3 years; FSIQ=109.7+/-7.9). Regional GM volumes were compared between the two groups using voxel-based morphometry (VBM) with the Diffeomorphic Anatomical Registration using Exponentiated Lie algebra (DARTEL). Compared with the control group, the high-functioning PDD group showed significantly less GM in the right insula, the right inferior frontal gyrus, and the right inferior parietal lobule. A conservative threshold confirmed considerably smaller volumes in the right insula and inferior frontal gyrus. In these areas, negative correlations were found between Autism Spectrum Quotient scores and GM volume, although no significant correlations were found between each subject's FSIQ and GM volume. No regions showed greater GM volumes in the high-functioning PDD group. The insular cortex, which works as a relay area for multiple neurocognitive systems, may be one of the key regions underlying the complex clinical features of PDD. These smaller GM volumes in high-functioning PDD subjects may reflect the clinical features of PDD itself, rather than FSIQ.

High Phase Synchronization in Alpha Band Activity in Older Subjects With High Creativity.

Despite growing evidence that high creativity leads to mental well-being in older individuals, the neurophysiological bases of creativity remain elusive. Creativity reportedly involves multiple brain areas and their functional interconnections. In particular, functional magnetic resonance imaging (fMRI) is used to investigate the role of patterns of functional connectivity between the default network and other networks in creative activity. These interactions among networks play the role of integrating various neural processes to support creative activity and involve attention, cognitive control, and memory. The electroencephalogram (EEG) enables researchers to capture a pattern of band-specific functional connectivity, as well as moment-to-moment dynamics of brain activity; this can be accomplished even in the resting-state by exploiting the excellent temporal resolution of the EEG. Furthermore, the recent advent of functional connectivity analysis in EEG studies has focused on the phase-difference variable because of its fine spatio-temporal resolution. Therefore, we hypothesized that the combining method of EEG signals having high-temporal resolution and the phase synchronization analysis having high-spatio-temporal resolutions brings a new insight of functional connectivity regarding high creative activity of older participants. In this study, we examined the resting-state EEG signal in 20 healthy older participants and estimated functional connectivities using the phase lag index (PLI), which evaluates the phase synchronization of EEG signals. Individual creativity was assessed using the S-A creativity test in a separate session before the EEG recording. In the analysis of associations of EEG measures with the S-A test scores, the covariate effect of the intelligence quotient was evaluated. As a result, higher individual S-A scores were significantly associated with higher node degrees, defined as the average PLI of a node (electrode) across all links with the remaining nodes, across all nodes at the alpha band. A conventional power spectrum analysis revealed no significant association with S-A scores in any frequency band. Older participants with high creativity exhibited high functional connectivity even in the resting-state, irrespective of intelligence quotient, which supports the theory that creativity entails widespread brain connectivity. Thus, PLIs derived from EEG data may provide new insights into the relationship between functional connectivity and creativity in healthy older people.

Associations between trait anxiety, insulin resistance, and atherosclerosis in the elderly: a pilot cross-sectional study.

Anxiety has been shown to be associated with cardiovascular disease. Atherosclerosis is responsible for the vast majority of cardiovascular events. Recent evidence is accumulating to show that insulin resistance (IR) plays a central role in determining the clinical manifestations of established atherosclerotic lesions. The current preliminary study aimed to investigate the associations between trait anxiety, IR, and atherosclerotic progression in healthy elderly subjects with normal fasting glucose and without metabolic syndrome. Thirty-five healthy elderly subjects (19 males and 16 females, mean age 64.5+/-4.7 years) were enrolled in this study. Trait anxiety was measured using a questionnaire corresponding to the trait anxiety scale taken from the State and Trait Anxiety Inventory. The homeostasis model assessment (HOMA-R) and plasma leptin-to-adiponectin ratio (L/A ratio), which are convenient IR indexes calculated from fasting blood sampling, were examined. As measurements of atherosclerotic progression, we performed two ultrasound methods, namely brachial artery flow-mediated dilation (FMD), an endothelial function assessment quantitatively reflecting the endothelium-dependent vasodilation responses following hyperemia, and measurement of carotid intima-media thickness (IMT). The severity of trait anxiety was positively associated with HOMA-R and L/A ratio, and negatively associated with the percent change of brachial artery FMD (%FMD). HOMA-R and L/A ratio were positively associated with carotid IMT, and L/A ratio was negatively associated with %FMD. These data showed the associations between trait anxiety, IR indexes and endothelial dysfunction or atherosclerotic progression. This pilot study, with a cross-sectional design, supports the promising role of IR for clarifying the pathophysiological mechanism by which anxiety contributes to an increasing risk of atherosclerosis.

Adiponectin multimer distribution, not absolute amount of plasma, correlates with depression severity in healthy elderly subjects.

Adiponectin is an adipocyte-specific secretory protein that circulates in serum as three oligomeric complexes known as the high, medium and low molecular weight form (HMW, MMW and LMW). HMW adiponectin has been suggested to be a better predictor of metabolic variables, and it was recently reported that the ratio of HMW to total adiponectin or to LMW, not the absolute amount of plasma adiponectin, might be crucial in determining insulin sensitivity. Insulin resistance (IR) is considered to be a primary component of vascular risk factors. Although the association of depression with atherosclerotic vascular diseases has been well documented, the contribution of IR to the evolution and progression of depression-associated vascular morbidity and mortality remains unknown. The current preliminary study showed that the ratio of HMW to total adiponectin or to LMW, not the absolute amount of plasma adiponectin, was negatively associated with depression severity in healthy elderly subjects without metabolic syndrome. This pilot study supports a promising role of adiponectin multimer distribution for clarifying the pathophysiological mechanism by which depression is associated with increased risk for IR, leading to cardiovascular disease, metabolic syndrome or type 2 diabetes.

Neurophysiological basis of creativity in healthy elderly people: a multiscale entropy approach.

OBJECTIVES: Creativity, which presumably involves various connections within and across different neural networks, reportedly underpins the mental well-being of older adults. Multiscale entropy (MSE) can characterize the complexity inherent in EEG dynamics with multiple temporal scales. It can therefore provide useful insight into neural networks. Given that background, we sought to clarify the neurophysiological bases of creativity in healthy elderly subjects by assessing EEG complexity with MSE, with emphasis on assessment of neural networks. METHODS: We recorded resting state EEG of 20 healthy elderly subjects. MSE was calculated for each subject for continuous 20-s epochs. Their relevance to individual creativity was examined concurrently with intellectual function. RESULTS: Higher individual creativity was linked closely to increased EEG complexity across higher temporal scales, but no significant relation was found with intellectual function (IQ score). CONCLUSIONS: Considering the general "loss of complexity" theory of aging, our finding of increased EEG complexity in elderly people with heightened creativity supports the idea that creativity is associated with activated neural networks. SIGNIFICANCE: Results reported here underscore the potential usefulness of MSE analysis for characterizing the neurophysiological bases of elderly people with heightened creativity.

Age-related variation in EEG complexity to photic stimulation: a multiscale entropy analysis.

OBJECTIVE: This study was intended to examine variations in electroencephalographic (EEG) complexity in response to photic stimulation (PS) during aging to test the hypothesis that the aging process reduces physiologic complexity and functional responsiveness. METHODS: Multiscale entropy (MSE), an estimate of time-series signal complexity associated with long-range temporal correlation, is used as a recently proposed method for quantifying EEG complexity with multiple coarse-grained sequences. We recorded EEG in 13 healthy elderly subjects and 12 healthy young subjects during pre-PS and post-PS conditions and estimated their respective MSE values. RESULTS: For the pre-PS condition, no significant complexity difference was found between the groups. However, a significant MSE change (complexity increase) was found post-PS only in young subjects, thereby revealing a power-law scaling property, which means long-range temporal correlation. CONCLUSIONS: Enhancement of long-range temporal correlation in young subjects after PS might reflect a cortical response to stimuli, which was absent in elderly subjects. These results are consistent with the general "loss of complexity/diminished functional response to stimuli" theory of aging. SIGNIFICANCE: Our findings demonstrate that application of MSE analysis to EEG is a powerful approach for studying age-related changes in brain function.