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Aging is often associated with cognitive and neural decline, but how these factors interact is still not fully understood. Recently, functional connectivity, or the degree to which brain regions are concurrently active, has provided insight into age-related differences. However, functional connectivities during task and rest differ and few studies have examined how these relate to a broad range of cognitive functions. The present study investigated the effect of age on cognition, whole-brain functional connectivity during resting-state and task, and their relationships across the adult lifespan. Cognition was broadly assessed using a battery of cognitive assessments and mean network characteristics were calculated across the whole brain. Behaviorally, increased age was associated with worse recall, executive function, and verbal working memory abilities but better language performance. Neurally, increased age was associated with lower overall within- and between-network functional connectivities during both rest and task, and these age-connectivity relationships were stronger during task performance. Connectivity was also related to cognition, and for all participants, these relationships were strongest during rest. Specifically, higher resting-state between-network functional connectivity was associated with poorer cognition for all adults and poorer language ability among older adults. Collectively, these findings demonstrate that while age effects were strongest during the task, resting-state functional connectivity was most closely tied to cognition. Moreover, these results are theoretically consistent with dedifferentiation accounts of cognition and aging and show that less differentiated functional connectivities are associated with cognitive costs for both older and younger adults. • Increased age related to worse recall, working memory, executive function. • Increased age related to lower within- and between-network connectivities. • Higher between-network connectivity at rest related to worse cognition at all ages. • Older adults with higher between-network at rest connectivity had worse language. [ABSTRACT FROM AUTHOR]

Abstract Older adults typically show decline in a variety of cognitive functions including inhibitory control and language production, with corresponding age-related increases in fMRI activation. However, it remains unclear whether such increases are compensatory or whether they reflect neural decline. One factor that may influence these brain-behavior relationships is difficulty. The current study investigated the effect of difficulty on age-related differences in the behavioral and neural bases of language production and inhibitory control using a phonological Go/No-Go picture naming task. Task demands were manipulated by varying the proportion of naming trials (Go trials) and inhibition trials (No-Go trials) across runs. All participants showed task-difficulty related declines in behavioral performance and increases in fMRI activation. Behaviorally, older adults were more sensitive to task difficulty, and elicited more fMRI activation than younger adults. Older adults were less neurally responsive to additional task demands (i.e., picture naming alone vs. Go/No-Go picture naming), but interestingly showed similar within-task increases as younger adults (e.g., Go Bias vs. No-Go Bias). Moreover, the relationships between fMRI activation and behavioral performance in older adults were multifaceted and the strength of these relations changed as a function of task difficulty. Specifically, activation in pre- and post- central gyri, right supramarginal and angular gyri was negatively correlated with naming reaction times, suggesting that activation in these regions may help mitigate age-related declines in language production. These findings are partially consistent with the CRUNCH model, highlighting the important influence of task difficulty on older adults' behavioral performance and their patterns of fMRI activation during language production. Highlights • All adults were slower and had more fMRI activation as task difficulty increased. • Behaviorally, older adults were more sensitive to task difficulty. • Compensation was found in bilateral motor and right parietal regions. • Reduced fMRI activation-behavior correlations were found with increased difficulty. • The findings partially support the CRUNCH model. [ABSTRACT FROM AUTHOR]

As we age, language reflects patterns of both stability and change. On the one hand, vocabulary and semantic abilities are largely stable across the adult lifespan, yet lexical retrieval is often slower and less successful (i.e., slower picture naming times, increased tip of the tongue incidents). Although the behavioral bases of these effects have been well established, less is known about the brain regions that support these age-related differences. We used functional Magnetic Resonance Imaging (fMRI) to examine the neural basis of picture naming. Specifically, we were interested in whether older adults would be equally sensitive to semantic characteristics, specifically the number of semantic near neighbors. Near neighbors, defined here as items with a high degree of semantic feature overlap, were of interest as these are thought to elicit competition among potential candidates and increase naming difficulty. Consistent with prior reports, pictures with more semantic near neighbors were named more slowly and less accurately for all adults. Additionally, this interference for naming times was larger as age increased, starting around 30 years old. In contrast to the age-related behavioral slowing, the neural basis of these effects was stable across adulthood. Across all adults, a number of language-relevant regions including left posterior middle temporal gyrus and left inferior frontal gyrus, pars triangularis were sensitive to the number of near neighbors. Our results suggest that although middle-aged and older adults' picture naming is more slowed by increased semantic competition, the brain regions supporting semantic processes remain stable across the adult lifespan. [ABSTRACT FROM AUTHOR]

Neuroimaging studies often either look at functional activation in response to an explicit task, or functional connectivity (i.e., interregional correlations) during resting-state. Few studies have looked at the intensity of brain activity or its relationship with age, behavior, and language. The current study investigated both intensity (i.e., the Amplitude of Low-Frequency Fluctuations, ALFF) and the functional connectivity of spontaneous brain activity during rest and their relationship with age and language. A life-span sample of individuals (N = 152) completed a battery of neuropsychological tests to assess basic cognitive functions and resting-state functional MRI data to assess spontaneous brain activity. Focusing on an extend language network, the mean ALFF and total degree were calculated for this network. We found that increased age was associated with more intense activity (i.e., higher ALFF) but lower within-network connectivity. Additionally, these increases in activity within the language network during resting-state were related to worse language ability, particularly in younger adults, supporting a dedifferentiation account of cognition. Our results support the utility of using resting-state data as an indicator of cognition and support the role of ALFF as a potential biomarker in characterizing the relationships between resting-state brain activity, age, and cognition. • Increased age was associated with higher ALFF but lower connectivity. • Increased ALFF in the language network related to worse language ability. • These results support a dedifferentiation account of cognition. • Resting-state ALFF can link brain activity, age, and cognition. [ABSTRACT FROM AUTHOR]

Research has suggested that using two or more languages on a daily basis helps older adults maintain a heightened functional state and improves neurocomputational efficiency. In this review, we discuss studies that have examined the effect of life-long bilingualism on age-related cognitive and neural decline, with a focus on discrepancies between different sources of evidence. We intend to outline and characterize factors which might explain inconsistencies between studies claiming that bilingualism has neurocognitive benefits and those that failed to find such evidence. We argue that individual variation in language proficiency and exposure, especially language switching frequency and daily frequency of use of the two languages, likely account for a significant chunk of the inconsistencies found in the literature and constrain the effectiveness of bilingualism as a cognitive and brain reserve factor. Finally, we briefly review studies of cognitive intervention and speculate on the potential of developing language training protocols to increase cognitive and neural resilience in older adults. [ABSTRACT FROM AUTHOR]

In this paper, three different configurations of composite materials models of TiB 2 /Cu homogeneous structure, single TiB 2 /Cu network structure and hybrid reinforced (TiB 2p +TiB w)/Cu network structure are established based on their actual microstructure. The models take into account the ductile fracture of the matrix, the brittle fracture of the reinforcing phase and the traction separation behavior of the interface. Influence of mesh size and mass scaling factor on the simulation results are discussed. The validity of the simulation results is verified by the agreement of the experimental tensile stress-strain curve. The effects of TiB 2 particle size, volume fraction and hybrid effects of TiB 2p +TiB w on plastic deformation and mechanical properties of composites are assessed from the three aspects: interface damage, load-bearing capacity of reinforcement and matrix damage. Compared with the TiB 2 /Cu homogeneous composites and the single TiB 2 /Cu network composites, the hybrid reinforced (TiB 2p +TiB w)/Cu network composites has better comprehensive mechanical properties, and its tensile strength and elongation are 349 MPa and 10.6 %, respectively. The addition of whiskers can effectively improve the bearing capacity of the hybrid reinforced (TiB 2p +TiB w)/Cu network composites, but reduce the elongation of composites. [Display omitted] • Models of homogeneous composites, single TiB 2 network composites and hybrid TiB 2p +TiB w network composites are established. • The particle size, volume fraction and the hybrid effects of TiB 2p +TiB w on the deformation of composites are studied. • The composites are assessed from the three aspects: interface damage, load-bearing capacity of and matrix damage. [ABSTRACT FROM AUTHOR]

Infrared small target detection is a challenging task due to the small target size and complex background clusters. The matrix factorization-based algorithms can work well in addressing this issue. In this paper, to address the residual over-optimized issue in matrix factorization, a novel Pareto frontier optimization-based algorithm is proposed to obtain the best trade-off between a given noise level and the optimal objective value. To suppress background outliers, a robust Huber penalty and non-negative constraints are introduced in matrix factorization. To solve the nuclear norm regularization faster, a randomized SVD algorithm is adopted. Finally, the proposed algorithm is compared with 11 representative detectors on 6 proposed test sequences, which have more than 1500 frames. The experimental results demonstrate the effectiveness of the proposed algorithm in improving speed and suppressing outliers. The source codes and data are available on https://github.com/wahahamyt/ISTD. [ABSTRACT FROM AUTHOR]

Abstract: Iron-induced oxidative stress is thought to play a crucial role in the pathogenesis of Parkinson''s disease. Our previous studies demonstrated that decreased expression of ferroportin 1 contributes to 6-hydroxydopamine induced intracellular iron accumulation and that decreased ferroportin 1 expression is caused by increased expression of iron regulatory protein 1. Iron regulatory protein 1 is a central regulator of iron homeostasis and is a likely target of extracellular agents to program changes in cellular iron metabolism. Therefore, the mechanism of iron regulatory protein 1 upregulation induced by 6-hydroxydopamine has become a significant focus of research. Iron regulatory protein 1 is regulated by protein kinase C, although this regulation is tissue specific. Therefore, in the present study, we aimed to determine whether alteration of protein kinase C activity modified iron regulatory protein 1 expression in the dopaminergic MES23.5 cell line, Furthermore, we investigated whether 6-hydroxydopamine induced iron regulatory protein 1 upregulation is mediated by protein kinase C, thus achieving regulation of cellular iron levels. The results showed that iron regulatory protein 1 was upregulated by phorbol 12-myristate-13-acetate, the PKC activator in dopaminergic MES23.5 cells, and ferroportin 1 expression and iron efflux were decreased as a result of iron regulatory protein 1 upregulation. The protein kinase C inhibitor bisindolylmaleimide I hydrochloride abolished the effect of phorbol 12-myristate-13-acetate. Protein kinase C-δ and protein kinase C-ζ, but not protein kinase C-ɛ were activated by 6-hydroxydopamine. The protein kinase C-δ inhibitor rottlerin inhibited protein kinase C-δ phosphorylation and abolished iron regulatory protein 1 upregulation induced by 6-hydroxydopamine. The protein kinase C-ζ pseudo-substrate inhibitor inhibited protein kinase C-ζ phosphorylation and abolished iron regulatory protein 1 upregulation induced by 6-hydroxydopamine. These data indicate that iron regulatory protein 1 is regulated by protein kinase C in dopaminergic MES23.5 cells and that protein kinase C activated by 6-hydroxydopamine regulates iron regulatory protein 1 expression, thus achieving regulation of cellular iron levels. [Copyright &y& Elsevier]