scholarly journals Bidirectional Association Between Sleep and Brain Atrophy in Aging

2021 ◽  
Vol 13 ◽  
Author(s):  
Viktória Kokošová ◽  
Pavel Filip ◽  
David Kec ◽  
Marek Baláž
Keyword(s):  
Human Brain ◽  
Brain Atrophy ◽  
Brain Aging ◽  
Brain Activity ◽  
Brain Regions ◽  
Electrical Brain Activity ◽  
Age Related ◽  
Bidirectional Association ◽  
Quality Sleep ◽  
Brain Functional Connectivity

Human brain aging is characterized by the gradual deterioration of its function and structure, affected by the interplay of a multitude of causal factors. The sleep, a periodically repeating state of reversible unconsciousness characterized by distinct electrical brain activity, is crucial for maintaining brain homeostasis. Indeed, insufficient sleep was associated with accelerated brain atrophy and impaired brain functional connectivity. Concurrently, alteration of sleep-related transient electrical events in senescence was correlated with structural and functional deterioration of brain regions responsible for their generation, implying the interconnectedness of sleep and brain structure. This review discusses currently available data on the link between human brain aging and sleep derived from various neuroimaging and neurophysiological methods. We advocate the notion of a mutual relationship between the sleep structure and age-related alterations of functional and structural brain integrity, pointing out the position of high-quality sleep as a potent preventive factor of early brain aging and neurodegeneration. However, further studies are needed to reveal the causality of the relationship between sleep and brain aging.

Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Semantic Retrieval ◽  
Age Related ◽  
The Face ◽  
Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

scholarly journals Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

2021 ◽  
Author(s):  
Adeline Jabès ◽  
Giuliana Klencklen ◽  
Paolo Ruggeri ◽  
Christoph M. Michel ◽  
Pamela Banta Lavenex ◽  
...  
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Resting State ◽  
Cognitive Aging ◽  
Temporal Dynamics ◽  
Spatial Working Memory ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Age Related

AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

Is Artistic Composition in Abstract Art Detected Automatically?

2021 ◽  
pp. 102-106
Author(s):  
Claudia Menzel ◽  
Gyula Kovács ◽  
Gregor U. Hayn-Leichsenring ◽  
Christoph Redies
Keyword(s):  
Human Brain ◽  
Significant Role ◽  
Mismatch Negativity ◽  
Brain Activity ◽  
Perceptual Processing ◽  
Abstract Art ◽  
Electrical Brain Activity ◽  
Image Set ◽  
The Brain

Most artists who create abstract paintings place the pictorial elements not at random, but arrange them intentionally in a specific artistic composition. This arrangement results in a pattern of image properties that differs from image versions in which the same pictorial elements are randomly shuffled. In the article under discussion, the original abstract paintings of the author’s image set were rated as more ordered and harmonious but less interesting than their shuffled counterparts. The authors tested whether the human brain distinguishes between these original and shuffled images by recording electrical brain activity in a particular paradigm that evokes a so-called visual mismatch negativity. The results revealed that the brain detects the differences between the two types of images fast and automatically. These findings are in line with models that postulate a significant role of early (low-level) perceptual processing of formal image properties in aesthetic evaluations.

Neurocognitive Aging and Functional Connectivity Using Functional Magnetic Resonance Imaging

2018 ◽  
Author(s):  
Hana Burianová
Keyword(s):  
Functional Connectivity ◽  
Cognitive Processes ◽  
Large Scale ◽  
Healthy Aging ◽  
Brain Activity ◽  
Brain Regions ◽  
Effective Strategies ◽  
Cognitive Improvement ◽  
Age Related ◽  
Neurocognitive Aging

Determining the mechanisms that underlie neurocognitive aging, such as compensation or dedifferentiation, and facilitating the development of effective strategies for cognitive improvement is essential due to the steadily rising aging population. One approach to study the characteristics of healthy aging comprises the assessment of functional connectivity, delineating markers of age-related neurocognitive plasticity. Functional connectivity paradigms characterize complex one-to-many (or many-to-many) structure–function relations, as higher-level cognitive processes are mediated by the interaction among a number of functionally related neural areas rather than localized to discrete brain regions. Task-related or resting-state interregional correlations of brain activity have been used as reliable indices of functional connectivity, delineating age-related alterations in a number of large-scale brain networks, which subserve attention, working memory, episodic retrieval, and task-switching. Together with behavioral and regional activation studies, connectivity studies and modeling approaches have contributed to our understanding of the mechanisms of age-related reorganization of distributed functional networks; specifically, reduced neural specificity (dedifferentiation) and associated impairment in inhibitory control and compensatory neural recruitment.

scholarly journals Metabolomics of Human Brain Aging and Age-Related Neurodegenerative Diseases

2014 ◽  
Vol 73 (7) ◽  
pp. 640-657 ◽  
Author(s):  
Mariona Jové ◽  
Manuel Portero-Otín ◽  
Alba Naudí ◽  
Isidre Ferrer ◽  
Reinald Pamplona
Keyword(s):  
Human Brain ◽  
Neurodegenerative Diseases ◽  
Brain Aging ◽  
Age Related

scholarly journals Conservative and disruptive modes of adolescent change in brain functional connectivity

2019 ◽  
Author(s):  
František Váša ◽  
Rafael Romero-Garcia ◽  
Manfred G. Kitzbichler ◽  
Jakob Seidlitz ◽  
Kirstie J. Whitaker ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Developmental Change ◽  
Aerobic Glycolysis ◽  
Brain Regions ◽  
Association Cortex ◽  
Brain Organization ◽  
Healthy Human ◽  
Age Related ◽  
Strongly Connected

AbstractAdolescent changes in human brain function are not entirely understood. Here we used multi-echo functional magnetic resonance imaging (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in N=298 healthy adolescents. Participants were aged 14-26 years and were scanned on two or more occasions at least 6 months apart. We found two distinct modes of age-related change in FC: “conservative” and “disruptive”. Conservative development was characteristic of primary cortex, which was strongly connected at 14 years and became even more connected in the period 14-26 years. Disruptive development was characteristic of association cortex, hippocampus and amygdala, which were not strongly connected at 14 years but became more strongly connected during adolescence. We defined the maturational index (MI) as the signed coefficient of the linear relationship between baseline FC (at 14 years,FC14) and adolescent change in FC (∆FC14−26). Disruptive systems (with negative MI) were functionally specialised for social cognition and autobiographical memory and were significantly co-located with prior maps of aerobic glycolysis (AG), AG-related gene expression, post-natal expansion of cortical surface area, and adolescent shrinkage of cortical depth. We conclude that human brain organization is disrupted during adolescence by the emergence of strong functional connectivity of subcortical nuclei and association cortical areas, representing metabolically expensive re-modelling of synaptic connectivity between brain regions that were not strongly connected in childhood. We suggest that this re-modelling process may support emergence of social skills and self-awareness during healthy human adolescence.

scholarly journals Metabolism modulates network synchrony in the aging brain

2020 ◽  
Author(s):  
Corey Weistuch ◽  
Lilianne R Mujica-Parodi ◽  
Anar Amgalan ◽  
Ken A Dill
Keyword(s):  
Statistical Physics ◽  
Quantitative Methods ◽  
Brain Aging ◽  
Brain Activity ◽  
High Sensitivity ◽  
Brain Regions ◽  
Aging Brain ◽  
Global Changes ◽  
Abrupt Changes ◽  
Network Synchrony

AbstractBrain aging is associated with hypometabolism and associated global changes in functional connectivity. Using fMRI, we show that network synchrony, a collective property of brain activity, decreases with age. Applying quantitative methods from statistical physics, we provide a generative (Ising) model for these changes as a function of the average communication strength between brain regions. In particular, we find healthy brains to be poised at a critical point of this communication strength, enabling a balance between segregated (to functional domains) and integrated (between domains) patterns of synchrony. However, one characteristic of criticality is a high sensitivity to small changes. Thus, minute weakening of pairwise communication between regions, as seen in the aging brain, gives rise to qualitatively abrupt changes in synchrony. Finally, by experimentally modulating metabolic activity in younger adults, we show how metabolism alone–independent of other changes associated with aging–can provide a mechanism for global changes in synchrony.

scholarly journals Neuroscience Research on Human Visual Path Integration: Empirical Overview and Strategic Considerations

2021 ◽  
Author(s):  
Jimmy Y. Zhong
Keyword(s):  
Path Integration ◽  
Hippocampal Formation ◽  
Brain Activity ◽  
Brain Regions ◽  
Neural Basis ◽  
Age Related ◽  
Neuroscience Research ◽  
Integration Strategies ◽  
The Impact ◽  
The Brain

Over the past two decades, many neuroimaging studies have attempted uncover the brain regions and networks involved in path integration and identify the underlying neurocognitive mechanisms. Although these studies made inroads into the neural basis of path integration, they have yet to offer a full disclosure of the functional specialization of the brain regions supporting path integration. In this paper, I reviewed notable neuroscientific studies on visual path integration in humans, identified the commonalities and discrepancies in their findings, and incorporated fresh insights from recent path integration studies. Specifically, this paper presented neuroscientific studies performed with virtual renditions of the triangle/path completion task and addressed whether or not the hippocampus is necessary for human path integration. Based on studies that showed evidence supporting and negating the involvement of the hippocampal formation in path integration, this paper introduces the proposal that the use of different path integration strategies may determine the extent to which the hippocampus and entorhinal cortex are engaged during path integration. To this end, recent studies that investigated the impact of different path integration strategies on behavioral performance and functional brain activity were discussed. Methodological concerns were raised with feasible recommendations for improving the experimental design of future strategy-related path integration studies, which can cover cognitive neuroscience research on age-related differences in the role of the hippocampal formation in path integration and Bayesian modelling of the interaction between landmark and self-motion cues. The practical value of investigating different path integration strategies was also discussed briefly from a biomedical perspective.

scholarly journals Estimation and Validation of Individualized Dynamic Brain Models with Resting State fMRI

2019 ◽  
Author(s):  
Matthew F. Singh ◽  
Todd S. Braver ◽  
Michael W. Cole ◽  
ShiNung Ching
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Nonlinear Dynamical Systems ◽  
Brain Activity ◽  
Network Models ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Data Driven ◽  
Imaging Data ◽  
Individual Level

AbstractA key challenge for neuroscience is to develop generative, causal models of the human nervous system in an individualized, data-driven manner. Previous initiatives have either constructed biologically-plausible models that are not constrained by individual-level human brain activity or used data-driven statistical characterizations of individuals that are not mechanistic. We aim to bridge this gap through the development of a new modeling approach termed Mesoscale Individualized Neurodynamic (MINDy) modeling, wherein we fit nonlinear dynamical systems models directly to human brain imaging data. The MINDy framework is able to produce these data-driven network models for hundreds to thousands of interacting brain regions in just 1-3 minutes per subject. We demonstrate that the models are valid, reliable, and robust. We show that MINDy models are predictive of individualized patterns of resting-state brain dynamical activity. Furthermore, MINDy is better able to uncover the mechanisms underlying individual differences in resting state activity than functional connectivity methods.

scholarly journals Neural Advantages of Older Musicians Involve the Cerebellum: Implications for Healthy Aging Through Lifelong Musical Instrument Training

2022 ◽  
Vol 15 ◽  
Author(s):  
Masatoshi Yamashita ◽  
Chie Ohsawa ◽  
Maki Suzuki ◽  
Xia Guo ◽  
Makiko Sadakata ◽  
...  
Keyword(s):  
Old Age ◽  
Healthy Aging ◽  
Brain Activity ◽  
Gray Matter Volume ◽  
Music Performance ◽  
Musical Instrument ◽  
Brain Regions ◽  
Musical Experience ◽  
Instrumental Training ◽  
Age Related

This study compared 30 older musicians and 30 age-matched non-musicians to investigate the association between lifelong musical instrument training and age-related cognitive decline and brain atrophy (musicians: mean age 70.8 years, musical experience 52.7 years; non-musicians: mean age 71.4 years, no or less than 3 years of musical experience). Although previous research has demonstrated that young musicians have larger gray matter volume (GMV) in the auditory-motor cortices and cerebellum than non-musicians, little is known about older musicians. Music imagery in young musicians is also known to share a neural underpinning [the supramarginal gyrus (SMG) and cerebellum] with music performance. Thus, we hypothesized that older musicians would show superiority to non-musicians in some of the abovementioned brain regions. Behavioral performance, GMV, and brain activity, including functional connectivity (FC) during melodic working memory (MWM) tasks, were evaluated in both groups. Behaviorally, musicians exhibited a much higher tapping speed than non-musicians, and tapping speed was correlated with executive function in musicians. Structural analyses revealed larger GMVs in both sides of the cerebellum of musicians, and importantly, this was maintained until very old age. Task-related FC analyses revealed that musicians possessed greater cerebellar-hippocampal FC, which was correlated with tapping speed. Furthermore, musicians showed higher activation in the SMG during MWM tasks; this was correlated with earlier commencement of instrumental training. These results indicate advantages or heightened coupling in brain regions associated with music performance and imagery in musicians. We suggest that lifelong instrumental training highly predicts the structural maintenance of the cerebellum and related cognitive maintenance in old age.

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