Magnetoencephalography Brain Signatures Relate to Cognition and Cognitive Reserve in the Oldest-Old: The EMIF-AD 90 + Study

SuperAgers and centenarians, dynamics of healthy ageing with cognitive resilience

Graceful healthy ageing and extended longevity is the most desired goal for human race. The process of ageing is inevitable and has a profound impact on the gradual deterioration of our physiology and health since it triggers the onset of many chronic conditions like dementia, osteoporosis, diabetes, arthritis, cancer, and cardiovascular disease. However, some people who lived/live more than 100 years called 'Centenarians" and how do they achieve their extended lifespans are not completely understood. Studying these unknown factors of longevity is important not only to establish a longer human lifespan but also to manage and treat people with shortened lifespans suffering from age-related morbidities. Furthermore, older adults who maintain strong cognitive function are referred to as "SuperAgers" and may be resistant to risk factors linked to cognitive decline. Investigating the mechanisms underlying their cognitive resilience may contribute to the development of therapeutic strategies that support the preservation of cognitive function as people age. The key to a long, physically, and cognitively healthy life has been a mystery to scientists for ages. Developments in the medical sciences helps us to a better understanding of human physiological function and greater access to medical care has led us to an increase in life expectancy. Moreover, inheriting favorable genetic traits and adopting a healthy lifestyle play pivotal roles in promoting longer and healthier lives. Engaging in regular physical activity, maintaining a balanced diet, and avoiding harmful habits such as smoking contribute to overall well-being. The synergy between positive lifestyle choices, access to education, socio-economic factors, environmental determinants and genetic supremacy enhances the potential for a longer and healthier life. Our article aims to examine the factors associated with healthy ageing, particularly focusing on cognitive health in centenarians. We will also be discussing different aspects of ageing including genomic instability, metabolic burden, oxidative stress and inflammation, mitochondrial dysfunction, cellular senescence, immunosenescence, and sarcopenia.

Cognitive resilience/reserve: Myth or reality? A review of definitions and measurement methods

INTRODUCTION

This review examines the concept of cognitive reserve (CR) in relation to brain aging, particularly in the context of dementia and its early stages. CR refers to an individual's ability to maintain or regain cognitive function despite brain aging, damage, or disease. Various factors, including education, occupation complexity, leisure activities, and genetics are believed to influence CR.

METHODS

We revised the literature in the context of CR. A total of 842 articles were identified, then we rigorously assessed the relevance of articles based on titles and abstracts, employing a systematic approach to eliminate studies that did not align with our research objectives.

RESULTS

We evaluate-also in a critical way-the methods commonly used to define and measure CR, including sociobehavioral proxies, neuroimaging, and electrophysiological and genetic measures. The challenges and limitations of these measures are discussed, emphasizing the need for more targeted research to improve the understanding, definition, and measurement of CR.

CONCLUSIONS

The review underscores the significance of comprehending CR in the context of both normal and pathological brain aging and emphasizes the importance of further research to identify and enhance this protective factor for cognitive preservation in both healthy and neurologically impaired older individuals.

HIGHLIGHTS

This review examines the concept of cognitive reserve in brain aging, in the context of dementia and its early stages. We have evaluated the methods commonly used to define and measure cognitive reserve. Sociobehavioral proxies, neuroimaging, and electrophysiological and genetic measures are discussed. The review emphasizes the importance of further research to identify and enhance this protective factor for cognitive preservation.

Synchronization in fractional-order neural networks by the energy balance strategy

Considering the individual differences between neurons, the fractional-order framework is introduced, and the neurons with various orders denote the individual differences during the cell differentiation. In this paper, the fractional-order FithzHugh-Nagumo (FHN) neural circuit is used to reproduce the firing patterns. In addition, an energy balance strategy is applied to determine the inter-neuronal communication. The neurons with energy imbalance exchange the information whereas the synaptic channels are blocked when energy balance is achieved. Two neurons coupled by this strategy achieve the phase synchronization and phase lock, and it indicates the two neurons generate spiking at the same time or with an interval. Similarly, the synchronization results are also obtained in the chain neuronal network, and the neurons exhibit the same firing patterns since the synchronization factor is closed to 1. Particularly, the neurons with order diversities lead to the heterogeneity and gradient field in the regular network, and the target wave is developed over time. With the wave spreading in the network, the silent states and exciting states appear in the whole network. The formation and diffusion of the target wave reveals the information transmission in neuronal network, and it indicates the individual differences paly an essential role in the collective behavior of neurons.

Urbach-Wiethe disease in a young patient without apparent amygdala calcification

Urbach-Wiethe disease is an extremely rare genetically-based syndrome which usually leads to dermatological and neurological changes. Neurologically, the amygdaloid region is primarily bilaterally affected. Therefore, several functions modulated by the amygdala are changed in patients with Urbach-Wiethe disease. As the neurological alterations evolve only gradually, it is particularly important to determine the cognitive and brain status of a juvenile. The patient described here was seen briefly at age 9 and tested neuropsychologically at age 19; furthermore, computer tomography and magnetic resonance imaging of his head was done. There were no important abnormalities in the brain, which is unusual in the light of previous data from other patients. On the cognitive level, the patient was generally within normal limits. However, he had mild problems in attention and concentration, and more prominent problems in emotional processing domain, and in personality dimensions. It is concluded that amygdala calcifications in Urbach-Wiethe disease take place progressively-possibly underpinned by genetic and gender variables; this can subsequently allow psychosocial-social factors (such a proper education and socialization) and biological factors (compensatory neuroplasticity) to retard and diminish the development of socio-emotional and cognitive deteriorations, though the outcome of questionnaires indicates that such patients may develop substantial concerns as to their future life and well-being.

Resting-state electroencephalographic correlates of cognitive reserve: Moderating the age-related worsening in cognitive function

This exploratory study aimed to investigate the resting-state electroencephalographic (rsEEG) correlates of the cognitive reserve from a life span perspective. Current source density (CSD) and lagged-linear connectivity (LLC) measures were assessed to this aim. We firstly explored the relationship between rsEEG measures for the different frequency bands and a socio-behavioral proxy of cognitive reserve, the Cognitive Reserve Index (CRI). Secondly, we applied moderation analyses to assess whether any of the correlated rsEEG measures showed a moderating role in the relationship between age and cognitive function. Moderate negative correlations were found between the CRI and occipital CSD of delta and beta 2. Moreover, inter- and intrahemispheric LLC measures were correlated with the CRI, showing a negative association with delta and positive associations with alpha 1, beta 1, and beta 2. Among those correlated measures, just two rsEEG variables were significant moderators of the relationship between age and cognition: occipital delta CSD and right hemispheric beta 2 LLC between occipital and limbic regions. The effect of age on cognitive performance was stronger for higher values of both measures. Therefore, lower values of occipital delta CSD and lower beta 2 LLC between right occipital and limbic regions might protect or compensate for the effects of age on cognition. Results of this exploratory study might be helpful to allocate more preventive efforts to curb the progression of cognitive decline in adults with less CR, possibly characterized by these rsEEG parameters at a neural level. However, given the exploratory nature of this study, more conclusive work on these rsEEG measures is needed to firmly establish their role in the cognition-age relationship, for example, verifying if these measures moderate the relationship between brain structure and cognition.

Development and validation of a nomogram for predicting mild cognitive impairment in middle-aged and elderly people

BACKGROUND

Mild cognitive impairment (MCI) is a clinical cognitive impairment state between dementia and normal aging. Early identification of MCI is beneficial, and it can delay the development of dementia. We aimed to develop and validate a prediction model to predict MCI of middle-aged and elderly people (aged 45 years and over).

METHODS

According to 478 middle-aged and elderly people (48-85 years old) from a cross-sectional study, we developed and validated a predictive nomogram. The least absolute shrinkage and selection operator (LASSO) regression model and multivariate logistic regression analysis were used to select variables and develop a prediction model. The performance of the nomogram was evaluated in terms of its discriminative power, calibration, and decision curve analysis (DCA).

RESULTS

The predictive nomogram was composed of the following: age, gender, education level, residence, and reading. The model showed good discrimination power (area under receiver-operating characteristic (ROC) curve was 0.8704) and good calibration. Similar results were seen in 10-fold cross-validation. The nomogram showed clinically useful in DCA analysis.

CONCLUSION

This predictive nomogram provides researchers with a practical tool for predicting MCI. The variables included in this nomogram were readily available. The population used for this nomogram was middle-aged and elderly people.