BACKGROUND:Engagement in social, physical, and cognitive activities is beneficial for maintaining cognitive health in later life by providing cognitive reserves against cognitive and neurodegenerative decline. OBJECTIVE:Insight is needed to understand how different activities combine to provide cognitive protection before and after the beginning of decline. METHODS:The current work used a cross-sectional data set of older adults who were cognitively unimpaired (CU), live with subjective cognitive impairment (SCI), live with mild cognitive impairment (MCI), or live with Alzheimer's disease. Beneficial behaviors included easily modifiable risk factors for dementia in late life: engagement in social, creative, and physical activities. The study explored individual and combined effects on the relationships between hippocampal volume and memory. FINDINGS:Greater engagement in beneficial behaviors minimized the neural-cognitive relationship in the SCI group. Once disease progression continued to MCI, risk factors no longer modified the brain-cognition relationship. DISCUSSION:Understanding how individual behaviors combine provides guidance when developing intervention trials or public policy procedures.

Despite facing the same task demands, every individual experiences different levels of perceived difficulty. This complicates the interpretation of cognitively induced brain activity due to the confounding of task demands and difficulty. Within the context of aging, differences in brain activity may reflect variations in perceived difficulty or age-related divergence in the recruitment of neural resources. The current work used titrated cognitive demands during a verbal delayed match to sample task within the fMRI. Between-group comparisons of 40 younger and 39 older healthy adults identified brain regions significantly related to behavioral performance. Brain regions were identified using the "Reserve and Resilience Framework," supporting the theories of upregulation or reorganization. The two age groups in this study did not significantly differ in their titrated cognitive capacity scores. Despite all participants performing a task they found equally challenging, moderated-mediation analysis of the fMRI data showed brain activity that differed between the two age groups. Furthermore, the relationships between brain activity and cognitive capacity differed between the age groups. Results supported upregulation, reorganization, and suppression of brain activity related to both increases and decreases in cognitive capacity. Therefore, brain activity increases and decreases appear to be balanced against each other to maintain high cognitive capacity. Furthermore, current findings show a beneficial effect of suppressed brain activity. These results support the need to expand the current cognitive reserve and resilience framework to include neural suppression as a potential mechanism of healthy cognitive aging.

BACKGROUND:Cognitive training is recognized as an efficient approach to improve cognition in older adults at risk for dementia. Real-world interventions that are more globally stimulating could have a greater impact on cognition than typical cognitive training programs - particularly for individuals with lower levels of education, a key risk factor for dementia. Team 10 of the Canadian Consortium on Neurodegeneration in Aging developed ENGAGE. ENGAGE is a 4-month multifaceted program combining memory and attentional training with stimulating leisure activities. This study aimed to assess its efficacy in older adults with subjective cognitive decline or mild cognitive impairment. METHOD:This was a randomized controlled preference trial (trial #alz104957). One hundred and twenty-eight participants were enrolled in two sites, CRIUGM (Montreal) and Baycrest (Toronto). There were two consecutive randomizations: a) randomization to ENGAGE-MUSIC/SPANISH intervention vs. an active control intervention (ENGAGE-DISCOVERY); b) randomization to SPANISH vs. MUSIC. The MUSIC and SPANISH conditions combined Music or Spanish learning with formal cognitive training. This was a preference trial, so patients could exclude Spanish or Music prior to randomization. A mixed linear model assessed PRE vs. POST changes on composite scores of memory and attention, cognition in everyday life, and use of memory strategies. Secondary analyses examined whether there were different intervention effects when comparing the MUSIC and SPANISH groups to the control intervention separately. RESULT:The composite score of attention and the use of memory strategies in daily life showed larger pre-post-training effects in the ENGAGE-MUSIC/SPANISH intervention group than in the active control intervention, yielding a significant Intervention x Time interaction. The composite score of memory and the test of cognition in everyday life improved with time, but there was no significant interaction with intervention. Secondary analyses of the two leisure groups only identified differences in the attention composite, where SPANISH participants had a greater beneficial effect than the MUSIC participants. CONCLUSION:The ENGAGE program significantly improved attention and everyday memory strategy use, with differential effects of Spanish and Music. This indicates that interventions combining leisure activities with formal cognitive training have the potential for mitigating cognitive decline and reducing dementia risk.

Cognitive training is recognized as an efficient approach to improve cognition in older adults at risk for dementia. Real-world interventions that are more globally stimulating could have a greater impact on cognition than typical cognitive training programs — particularly for individuals with lower levels of education, a key risk factor for dementia. Team 10 of the Canadian Consortium on Neurodegeneration in Aging developed ENGAGE. ENGAGE is a 4-month multifaceted program combining memory and attentional training with stimulating leisure activities. This study aimed to assess its efficacy in older adults with subjective cognitive decline or mild cognitive impairment. This was a randomized controlled preference trial (trial #alz104957). One hundred and twenty-eight participants were enrolled in two sites, CRIUGM (Montreal) and Baycrest (Toronto). There were two consecutive randomizations: a) randomization to ENGAGE-MUSIC/SPANISH intervention vs. an active control intervention (ENGAGE-DISCOVERY); b) randomization to SPANISH vs. MUSIC. The MUSIC and SPANISH conditions combined Music or Spanish learning with formal cognitive training. This was a preference trial, so patients could exclude Spanish or Music prior to randomization. A mixed linear model assessed PRE vs. POST changes on composite scores of memory and attention, cognition in everyday life, and use of memory strategies. Secondary analyses examined whether there were different intervention effects when comparing the MUSIC and SPANISH groups to the control intervention separately. The composite score of attention and the use of memory strategies in daily life showed larger pre-post-training effects in the ENGAGE-MUSIC/SPANISH intervention group than in the active control intervention, yielding a significant Intervention x Time interaction. The composite score of memory and the test of cognition in everyday life improved with time, but there was no significant interaction with intervention. Secondary analyses of the two leisure groups only identified differences in the attention composite, where SPANISH participants had a greater beneficial effect than the MUSIC participants. The ENGAGE program significantly improved attention and everyday memory strategy use, with differential effects of Spanish and Music. This indicates that interventions combining leisure activities with formal cognitive training have the potential for mitigating cognitive decline and reducing dementia risk.

Females have a higher risk of developing Alzheimer’s disease (AD) and report poorer sleep quality with age compared to males. Because poor sleep quality is also a risk factor for AD, it may contribute to sex-specific differences in AD risk. Females differ in the prevalence, presentation, and severity of sleep disorders, and tend to show greater mismatch between objective and subjective sleep metrics. To better understand these factors, this study investigated sex differences in self-reported sleep quality metrics across varying levels of cognitive impairment. Cross-sectional self-report data from COMPASS-ND/CIMA-Q were analyzed across three groups [cognitively unimpaired (CU, n=104), subjective cognitive impairment (SCI, n=108), amnestic mild cognitive impairment (MCI, n=290)], including components of the Pittsburgh Sleep Quality Index, metrics of daytime fatigue/dysfunction, sleep medication use, sleep apnea, rapid eye movement (REM) sleep behaviour disorder, and restless leg syndrome. Principal component analyses including these sleep variables were run separately for males ( n =246) and females ( n =256). Linear models assessed whether principal component scores differed by sex and group (CU, SCI, MCI). In both sexes, the first principal component (PC1) reflected overall sleep quality and daytime fatigue/dysfunction, with higher scores indicating better sleep and lower fatigue/dysfunction. The second component (PC2) captured discordance between sleep quality and fatigue, with higher scores indicating poor sleep but low fatigue. Linear models showed that both PC1 and PC2 scores were significantly lower in MCI compared to CU. Thus, MCI was associated with both poor sleep and high fatigue (low PC1), as well as good sleep but high fatigue (low PC2), suggesting a mismatch between perceived sleep quality and daytime functioning for some participants. While no significant sex-by-group interactions were found, subtle sex differences were noted: Compared to males, females with low PC2 scores reported more symptoms of REM sleep behaviour disorder and restless leg syndrome. Findings highlight distinct sleep and cognitive impairment patterns, with potential sex-specific sleep symptom profiles. Understanding these profiles could improve early identification of cognitive decline and support targeted sleep interventions. Tailoring approaches to these differences may enhance both sleep quality and cognitive outcomes in aging populations.

Introduction: Post-stroke dysphagia and communication impairments occur in two-thirds of acute stroke survivors. Identifying the shared neuroanatomical substrate for related impairments could facilitate the development of cross-system therapies. Our purpose was to elucidate discrete brain regions predictive of the combined presence of dysphagia alongside dysarthria and/or aphasia post-stroke. Methods: We included 40 right hemisphere stroke (RHS) and 67 left hemisphere stroke (LHS) patients from an acute ischemic stroke cohort with lesions demarcated on diffusion-weighted imaging. We undertook binary non-parametric voxel-lesion symptom mapping with a false discovery rate of p < 0.05 for co-occurring dysphagia, dysarthria, and aphasia (LHS only). If no voxels survived the threshold, a cluster analysis of >20 voxels involving an uncorrected p < 0.01 was applied to identify brain regions associated with the co-occurring impairments. Results: Cluster analyses revealed that dysphagia and dysarthria were associated with insular and superior temporal gyrus (STG) involvement after RHS and with basal ganglia (BG), internal capsule, and thalamic involvement after LHS. Co-occurring dysphagia, dysarthria, and aphasia were associated with BG, STG, and insular cortex involvement. Discussion: Our findings highlight the role of the insula and structures of the BG in co-occurrence patterns involving dysphagia, dysarthria, and aphasia. These newly identified biomarkers may inform new rehabilitation therapeutic targets for treating cross-system functions.

Working memory (WM) describes the dynamic process of maintenance and manipulation of information over a certain time delay. Neuronally, WM recruits a distributed network of cortical regions like the visual and dorsolateral prefrontal cortex as well as the subcortical hippocampus. How the input dynamics and subsequent neural dynamics impact WM remains unclear though. To answer this question, we combined the analysis of behavioral WM capacity with measuring neural dynamics through task-related power spectrum changes, e.g., median frequency (MF) in functional magnetic resonance imaging (fMRI). We show that the processing of the input dynamics, e.g., the task structure's specific timescale, leads to changes in the unimodal visual cortex's corresponding timescale which also relates to working memory capacity. While the more transmodal hippocampus relates to working memory capacity through its balance across multiple timescales or frequencies. In conclusion, we here show the relevance of both input dynamics and different neural timescales for WM capacity in uni – and transmodal regions like visual cortex and hippocampus for the subject's WM performance.

This study tested the hypothesis that within older Barbadian adults, sex, education, and occupation type lessen age-related cognitive decline. The analyses used a cross-sectional data set from 1325 people collected in the 2006 SABE Study (Health, Well-being, and Aging). Cognition was assessed as scores in each subdomain of the Mini-Mental State Exam. The loss of a single point in each subdomain was predicted by sex, years of education, job type, and their interactions with age. Results demonstrated that age and protective factors affect each cognitive domain differently. High education combined with mentally complex employment helped maintain cognitive performance in later life. Beneficial lifetime exposures are additive, providing combined benefits. Findings provide insight into public policy aiming to minimize the number of adults with cognitive decline and dementia in Barbados and the Caribbean.

This study characterized the effects of aging on individual cognitive domains and how sex, job type, and years of education alter the age effect on older adults from Barbados. This was an analysis of the cross-sectional data collected as part of the SABE Study (Health, Well-being and Ageing) in 2006. The loss of a single point in each of the individual cognitive domains assessed using the mini-mental state exam served as dependent variables. Independent variables included age, sex, years of education, job type, and the interactions with age in a series of logistic regression analyses. The study aimed to identify which factors altered the effect of age on cognitive performance and which directly affected performance. Results demonstrated that the effect of age differed across the cognitive domains. In addition, sex, education, and job type all differentially affected cognitive performance in an additive, formative manner. The most consistent finding was that high years of education coupled with employment requiring mostly mental effort was the best combination for maintaining high levels of cognitive performance in late life. The results demonstrate that adverse age effects on cognitive performance may be minimized or delayed through modifiable lifetime exposures in the people of Barbados.

BackgroundPsychological resilience may play an important role in protecting multiple sclerosis care-partners from the negative effects of their support role. However, predictors of resilience in this population have yet to be identified. ObjectivesTo identify characteristics predictive of psychological resilience in multiple sclerosis care-partners as informed by the Ecological Model of Resilience. MethodsInformal multiple sclerosis care-partners (n = 540) completed an online survey. Psychological resilience was measured using the 25-item Connor-Davidson Resilience Scale. Sociodemographic and care-context predictors of resilience were analyzed using hierarchical regression. ResultsThe mean resilience score was 59.0 (SD = 7.6) out of a possible 100. Sociodemographic variables accounted for 31% of the variance in resilience scores in multiple sclerosis care-partners. When care-context variables were incorporated into the model, 55% of variance was explained (F[7,320] = 26.824, p < 0.001). Each group of variables remained significant in both low disability and high disability models. Social support was the only individual variable that remained significant across all models (p < 0.05). ConclusionsMultiple sclerosis care-partners differ strikingly from other caregiving populations. Both sociodemographic and care-context variables were found to promote or hinder resilience in multiple sclerosis care-partners. Social support, in particular, may be an important target for promoting resilience in multiple sclerosis care-partners and could be leveraged in future initiatives.

The vast majority of fMRI studies of task-related brain activity utilize common levels of task demands and analyses that rely on the central tendencies of the data. This approach does not take into account perceived difficulty nor regional variations in brain activity between people. The results are findings of brain-behavior relationships that weaken as sample sizes increase. Participants of the current study included twenty-six healthy young adults evenly split between the sexes. The current work utilizes five parametrically modulated levels of memory load centered around each individual's predetermined working memory cognitive capacity. Principal components analyses (PCA) identified the group-level central tendency of the data. After removing the group effect from the data, PCA identified individual-level patterns of brain activity across the five levels of task demands. Expression of the group effect significantly differed between the sexes across all load levels. Expression of the individual level patterns demonstrated a significant load by sex interaction. Furthermore, expressions of the individual maps make better predictors of response time behavior than group-derived maps. We demonstrated that utilization of an individual's unique pattern of brain activity in response to increasing a task's perceived difficulty is a better predictor of brain-behavior relationships than study designs and analyses focused on identification of group effects. Furthermore, these methods facilitate exploration into how individual differences in patterns of brain activity relate to individual differences in behavior and cognition.

This study investigated whether relationships between age and measures of gray matter in the brain differed across the lifespan and by years of education. The hypothesis is that year to year differences in brain measures vary across the lifespan and are affected by the years of education someone has. Cortical thickness and subcortical volume were measured from 391 healthy adults (age range: 19-80 years). Brain measures were predicted using a quadratic age effect and moderating effects of education using linear regression. Results demonstrate that 12 brain regions had significant moderating effects of age and education on brain measures. These are brain regions where the effect of age on gray matter varied across the lifespan and across levels of education. The results highlighted that when the moderating effects of education are absent from the model, age and brain measures were linearly related. The moderating effects reveal complex age-brain dynamics and support theories of brain maintenance, suggesting that lifestyle factors limit the negative effects of advancing age. Greater education was related to maintained gray matter until later ages. This protection came at a cost, which indicated that year to year decline in gray matter was larger in late life in those with greater levels of education. Improving our understanding of how age and individual differences affect gray matter measures is an important step toward improving the clinical utility of cortical thickness and volume. This article is part of the Virtual Special Issue titled "COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING". The full issue can be found on ScienceDirect at https://www.sciencedirect.com/ journal/neurobiology-of-aging/special-issue/105379XPWJP. (c) 2020 Elsevier Inc. All rights reserved.

People often discount future rewards, embracing smaller rewards that are delivered sooner rather than waiting for larger rewards delivered later. Previous behavioral research has demonstrated that people are more patient when options are presented as decisions to accelerate rather than delay consumption. This behavioral effect is well-established in the literature, but the underlying neural mechanisms have not been identified. We examined the neural correlates of delay and acceleration framing in intertemporal choice. We find greater activation in the hippocampus, amygdala, and anterior insula when options were framed as decisions to delay rather than accelerate consumption. These findings are consistent with theoretical accounts that posit that preferences are constructed. Specifically, the heightened activation observed in medial temporal regions may reflect more vivid representations of sooner outcomes in delay versus acceleration framing. These results provide insight into contextual effects in intertemporal choice specifically and preference construction more broadly.

Semantic memory representations are generally well maintained in aging, whereas semantic control is thought to be more affected. To explain this phenomenon, this study tested the predictions of the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), focusing on task demands in aging as a possible framework. The CRUNCH effect would manifest itself in semantic tasks through a compensatory increase in neural activation in semantic control network regions but only up to a certain threshold of task demands. This study compares 39 younger (20-35 years old) with 39 older participants (60-75 years old) in a triad-based semantic judgment task performed in an fMRI scanner while manipulating task demand levels (low versus high) through semantic distance. In line with the CRUNCH predictions, differences in neurofunctional activation and behavioral performance (accuracy and response times) were expected in younger versus older participants in the low- versus high-demand conditions, which should be manifested in semantic control Regions of Interest (ROIs). Our older participants had intact behavioral performance, as proposed in the literature for semantic memory tasks (maintained accuracy and slower response times (RTs)). Age-invariant behavioral performance in the older group compared to the younger one is necessary to test the CRUNCH predictions. The older adults were also characterized by high cognitive reserve, as our neuropsychological tests showed. Our behavioral results confirmed that our task successfully manipulated task demands: error rates, RTs and perceived difficulty increased with increasing task demands in both age groups. We did not find an interaction between age group and task demand, or a statistically significant difference in activation between the low- and high-demand conditions for either RTs or accuracy. As for brain activation, we did not find the expected age group by task demand interaction, or a significant main effect of task demand. Overall, our results are compatible with some neural activation in the semantic network and the semantic control network, largely in frontotemporoparietal regions. ROI analyses demonstrated significant effects (but no interactions) of task demand in the left and right inferior frontal gyrus, the left posterior middle temporal gyrus, the posterior inferior temporal gyrus and the prefrontal gyrus. Overall, our test did not confirm the CRUNCH predictions.

In this study, Artificial Intelligence was used to analyze a dataset containing the cortical thickness from 1,100 healthy individuals. This dataset had the cortical thickness from 31 regions in the left hemisphere of the brain as well as from 31 regions in the right hemisphere. Then, 62 artificial neural networks were trained and validated to estimate the number of neurons in the hidden layer. These neural networks were used to create a model for the cortical thickness through age for each region in the brain. Using the artificial neural networks and kernels with seven points, numerical differentiation was used to compute the derivative of the cortical thickness with respect to age. The derivative was computed to estimate the cortical thickness speed. Finally, color bands were created for each region in the brain to identify a positive derivative, that is, a part of life with an increase in cortical thickness. Likewise, the color bands were used to identify a negative derivative, that is, a lifetime period with a cortical thickness reduction. Regions of the brain with similar derivatives were organized and displayed in clusters. Computer simulations showed that some regions exhibit abrupt changes in cortical thickness at specific periods of life. The simulations also illustrated that some regions in the left hemisphere do not follow the pattern of the same region in the right hemisphere. Finally, it was concluded that each region in the brain must be dynamically modeled. One advantage of using artificial neural networks is that they can learn and model non-linear and complex relationships. Also, artificial neural networks are immune to noise in the samples and can handle unseen data. That is, the models based on artificial neural networks can predict the behavior of samples that were not used for training. Furthermore, several studies have shown that artificial neural networks are capable of deriving information from imprecise data. Because of these advantages, the results obtained in this study by the artificial neural networks provide valuable information to analyze and model the cortical thickness.

Olfactory dysfunction consistently occurs in patients with Alzheimer's disease (AD), beyond the mild and gradual decline in olfactory ability found in normal aging. This dysfunction begins early in the disease course, typically before clinical diagnosis, and progresses with disease severity. While odor identification and detection deficits clearly differentiate AD from controls, there remains uncertainty as to whether these are determined by olfactory threshold. The purpose of the current preliminary fMRI study was to examine the neural correlates of olfactory processing in healthy young and old adults and compare them with AD patients. We also explored the interplay between age and disease-related psychophysical olfactory declines and odorant-induced brain activation. Results indicated AD patients had decreased odor detection task-related signal in all regions of the primary olfactory cortex, with activity in the entorhinal cortex best differentiating the groups. Moderated-mediation analyses on neuro-psychophysical relationships found that increased brain activation in the entorhinal cortex moderated the negative effect of disease-related threshold changes on olfactory detection. Therefore, even in the face of higher (worse) olfactory thresholds, older adults and AD patients compensated for this effect with increased brain activation in a primary olfactory brain region. This was the case for odor detection but not odor identification. fMRI activation induced by an olfactory detection task may eventually be useful in improving early discovery of AD and may, eventually, facilitate early treatment interventions in subjects at risk for AD.

Task-based functional magnetic resonance imaging (MRI) neuroimaging for the study of cognitive neuroscience provides insight into how the brain responds to increasing cognitive demands. Theoretical models of neural-cognitive relationships define neural efficiency and neural capacity as two parameters to describe the rate of gain of brain activity and the upper limits of the increases, respectively. Although qualitatively well described, there are limited discussions and demonstrations of estimating these parameters from data. The current work presents a method using a quadratic equation model of cognitive demands. The methods were applied to 21 healthy young adults while engaging in four levels of the verbal n-back working memory task (0, 1, 2 and 3-back). Measures of the area under the curve captured both linear and curvilinear responses to quantify the locations and amounts of task-related increases in brain activity. In addition, we calculated voxel-wise maps of neural efficiency and neural capacity. Results showed increases in brain activation in regions typically involved in working memory. The relationships between increasing cognitive demands and brain activity also differed across the brain within and between individuals, as indicated by differential neural efficiency and neural capacity values. This approach provides tools for evaluating current theories about the relationships between brain activity and cognition. Neural efficiency and neural capacity provide physiological measures of brain activity, which will help evaluate how age, disease and intervention processes affect brain activity. Finally, all presented methods are readily applicable using standard current software packages for neuroimaging.

Mediation analyses are a statistical tool for testing the hypothesis about how the relationship between two variables may be direct or indirect via a third variable. Assessing statistical significance has been an area of active research; however, assessment of statistical power has been hampered by the lack of closed form calculations and the need for substantial amounts of computational simulations. The current work provides a detailed explanation of implementing large scale simulation procedures within a shared computing cluster environment. In addition, all results and code for implementing these procedures is publicly available. The resulting power analyses compare the effects of sample size and strength and direction of the relationships between the three variables. Comparisons of three confidence interval calculation methods demonstrated that the bias-corrected method is optimal and requires approximately ten less participants than the percentile method to achieve equivalent power. Differing strengths of distal and proximal effects were compared and did not differentially affect the power to detect mediation effects. Suppression effects were explored and demonstrate that in the presence of no observed relationship between two variables, entrance of the mediating variable into the model can reveal a suppressed relationship. The power to detect suppression effects is similar to unsuppressed mediation. These results and their methods provide important information about the power of mediation models for study planning. Of greater importance is that the methods lay the groundwork for assessment of statistical power of more complicated models involving multiple mediators and moderators.

Introduction The trigeminal system is a chemosensory system, next to smell and taste, allowing intranasal sensations such as freshness, spiciness, etc. The lateralization task is used to measure trigeminal sensitivity and consists in identifying the nostril stimulated by an odorous substance in a two-alternative forced-choice procedure. However, when performed in the standard method, this task takes almost 25 to 30 min to administer and only gives access to few information. Methods The aim of this pilot study was to compare two alternative methods of administering the lateralization task with the standard method in a group of 53 participants (41.6 years; 32 women). Specifically, we compared (1) the standard method of 40 constant stimuli with a duration of 500 ms, (2) a short version of 20 variable stimuli ranging from 200 to 600 ms (different duration method—DD), and (3) an automatic adaptive staircase method where the test adjusts the duration of stimulation according to the participant’s responses (adaptive duration method—AD). Results Based on the number of correct answers and the thresholds obtained with the automatic staircase method, the average scores for the two alternative methods correlate with the score at the standard method. In addition, both alternative methods are able to discriminate between participants with a high sensitivity and those with a lower sensitivity. Finally, the DD method is significantly shorter in terms of administration time than the other two methods. Conclusion This pilot study presents two novel methods to evaluate trigeminal sensitivity which each have a specific superiority over the established technique. Implications The DD method cuts testing time in half whereas the AD method provides threshold estimates for individual nostrils.