Loss of cognitive function is a significant challenge in aging, and developing models to understand and target cognitive decline is crucial for the development of Geroscience-based interventions. Aged mice offer a valuable model as they share features of cognitive decline with humans. Despite numerous studies, knowledge of longitudinal age-related cognitive changes and cognitive frailty in naturally aging mice is limited, particularly in cohorts exceeding 30 months of age, where cognitive decline is more pronounced. Moreover, the impaired physical function of aged mice is known to affect latency-based strategies to measure cognitive performances. Here, we show a comprehensive longitudinal assessment using the Barnes Maze test in a large cohort of 424 aged (≥ 21 months) C57BL/6J mice. We introduced a new metric, the Cognitive Frailty Index (CoFI), which summarizes different age-associated Barnes Maze parameters into a unique function. CoFI strongly associates with advancing age and mortality, offering a reliable ability to discriminate long- and short-lived mice. We also established a CoFI cut-off and a physically adjusted CoFI, both of which can distinguish between physical and cognitive frailty. This is further supported by the enhanced predictive power when physical and cognitive frailty are combined to assess short-term mortality. Moreover, the computation method for CoFI is adaptable to various cognitive assessment tests, leveraging procedures akin to those used for calculating other frailty indices. In conclusion, through robust longitudinal tracking, CoFI has the potential to become an important ally in assessing the effectiveness of Geroscience-based interventions to counteract age-related cognitive impairment.

Neurodegenerative diseases like Parkinson's (PD) and Alzheimer's (AD) exhibit considerable heterogeneity of functional brain features within patients, complicating diagnosis and treatment. Here, we use electroencephalography (EEG) and normative modeling to investigate neurophysiological mechanisms underpinning this heterogeneity. Resting-state EEG data from 14 clinical units included healthy adults (n = 499) and patients with PD (n = 237) and AD (n = 197), aged over 40. Spectral and source connectivity analyses provided features for normative modeling, revealing significant, frequency-dependent EEG deviations with high heterogeneity in PD and AD. Around 30% of patients exhibited spectral deviations, while ~80% showed functional source connectivity deviations. Notably, the spatial overlap of deviant features did not exceed 60% for spectral and 25% for connectivity analysis. Furthermore, patient-specific deviations correlated with clinical measures, with greater deviations linked to worse UPDRS for PD (⍴ = 0.24, p = 0.025) and MMSE for AD (⍴ = -0.26, p = 0.01). These results suggest that EEG deviations could enrich individualized clinical assessment in Precision Neurology.

It is well-established that skilled, young-adult readers rely on predictive processing during online language comprehension; however, fewer studies have investigated whether this extends to healthy, older adults (60 + years). The aim of the present research was to assess whether older readers make use of lexical prediction by investigating whether they demonstrate processing costs for incorrect predictions in a controlled experimental design. The eye movements of a sample of older adults (60-86 years) were recorded as they read strongly and weakly constraining sentences containing a predictable word or an unpredictable alternative that was either semantically related or unrelated. To determine whether predictive processing depends on the stimuli presentation format, a second experiment presented the same materials in a self-paced reading task in which each word of a sentence appears one at a time at the readers' own pace. Older adults showed processing benefits for expected input on eye-movement measures of reading. They also showed processing costs for unexpected input across both methodologies, but only when semantically unrelated to the best completion. Taken together, the results suggest that the use of predictive processes remains relatively preserved with age. The implications of these findings for understanding whether prediction is a fundamental component of online language comprehension are discussed.

Mounting evidence suggests that transcranial alternating current stimulation can enhance response inhibition, a cognitive process crucial for sustained effort and decision-making. However, most studies have focused on within-session effects, with limited investigation into the effects of repeated applications, which are crucial for clinical applications. We examined the effects of repeated bifocal transcranial alternating current stimulation targeting the right inferior frontal gyrus and pre-supplementary motor area on response inhibition, functional connectivity, and simulated driving performance. Thirty young adults (18-35 yr) received either a sham or transcranial alternating current stimulation (20 Hz, 20 min) across 5 sessions over 2 wk. Resting-state electroencephalography assessed functional connectivity between the pre-supplementary motor area and right inferior frontal gyrus at baseline, the final transcranial alternating current stimulation session, and the 7-d follow-up. Response inhibition was measured using a stop-signal task, and driving performance was assessed before and after the intervention. The results showed significant improvements in functional connectivity in the transcranial alternating current stimulation group between sessions, though response inhibition and driving braking performance remained unchanged. However, while not the targeted behavior, general driving performance potentially improved following bifocal transcranial alternating current stimulation, with participants maintaining stable driving behavior alongside increased spare attentional capacity. These findings suggest that repeated bifocal transcranial alternating current stimulation may enhance cortical connectivity and related cognitive-motor processes, supporting its potential for clinical applications.

There are concerns whether (repeated) exposure to general anaesthesia is associated with long-term cognitive decline.

We investigated the potential, negative relationship between total exposure to surgery under general anaesthesia and its impact on long-term cognitive development.

A prospective longitudinal cohort study.

The Netherlands.

1823 Adults, aged 25-84 with normal cognitive functioning on inclusion with three serial cognitive assessments between 1995 and 2008, with comprehensive documentation on demographic, lifestyle, and health factors.

The primary outcomes were test scores in the cognitive domains of learning and memory, executive function, selective attention, mental speed, and information processing speed. Linear mixed models were used to analyse the effects of the estimated total time under general anaesthesia at baseline on cognitive development during a 12-year follow-up period.

When adjusting for demographic and systemic health-related factors, prolonged exposure to surgery under general anaesthesia (measured in total baseline minutes) negatively affected three cognitive domains. These included the CST (executive functioning, P  < 0.05), Stroop (selective attention and mental speed, P  < 0.001) and LDST (information processing speed, P  < 0.005). Age and education were the primary factors impacting lifetime cognitive decline. Hypertension, diabetes, and smoking negatively affected various cognitive domains.

Increased exposure to surgery under general anaesthesia independently contributes to long-term cognitive decline. Demographic variables and health-related factors are key contributors to accelerated cognitive decline over an individual's lifetime.

Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer's disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer's Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70-77% accuracy and 61-83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Although the potential benefits of calorie restriction on human lifespan remain uncertain, it is currently one of the most extensively researched non-genetic approaches to extending both lifespan and healthspan in animals. Calorie restriction offers numerous health benefits, including a reduced incidence of age-related diseases. However, calorie restriction also produces a range of negative effects, which are not fully documented and require further investigation, particularly in humans. As the viability of calorie restriction in humans will depend on the balance of benefits and detrimental effects, it is crucial to understand the nature of these negative effects and what drives them. In this Review, we summarize the effects of calorie restriction on wound healing, hunger, cold sensitivity, bone health, brain size, cognition, reproductive performance and infection, primarily based on studies of rodents with some data from other species and from humans. Overall, the detrimental effects of calorie restriction seem to stem directly from prioritization of vital functions and downregulation or suppression of energy-demanding processes, which helps preserve survival but can also lead to impaired physiological performance and increased vulnerability to stressors. The exact mechanisms underlying these effects remain unclear. Whether it might be possible to engage in calorie restriction but avoid these negative effects remains uncertain.

Efforts to understand the effects of physical activity on cognitive health have long relied on employing objective measures that assess the efficacy of the mechanics of cognition. However, this perspective overlooks complementary dimensions of cognitive functioning, namely one's subjective appraisal of the efficacy of their cognitive mechanics. In a set of four investigations (N =  2965), we sought to discern whether physical activity (PA), and other health and demographic factors, contribute to subjective experiences of cognitive mechanics (SCF) and to map for future investigations domains of function that are sensitive to health factors. We employed linear multiple regression analyses to examine survey data collected online from four large samples of young adults who responded to measures of health behaviours and SCF. PA contributed to subjective experiences of attentional control and spatial navigation but not memory, executive function, or general cognitive functioning. Further, sleep, diet, and stress were each consistently associated with selective measures of subjective experiences of cognition. Taken together, these studies indicate the importance of PA, as well as additional health behaviours, as significant contributors to SCF.

Switching between tasks is slower and more error-prone than performing a single task. While studies have compared task-switching and associated neural processing between younger and older adults, knowledge of age-related differences in components of task-switching across adulthood, and associated neural mechanisms, remains elusive. In this study, these age differences were investigated using functional near-infrared spectroscopy (fNIRS). A sample of 132 adults aged 18-79 undertook a variant of the Trail Making Test and a task-switching paradigm. Hemodynamic changes in the bilateral frontal cortex during the task-switching paradigm were measured using a 48-channel fNIRS device. Behavioral results showed that age showed a negative linear relationship with time taken to task-switch and a negative quadratic relationship with success in task-switching. In addition, fNIRS results showed that age had a positive linear relationship with activation in the left posterolateral frontal cortex across trial conditions. Among older adults, who had slower and less accurate switch performance than younger adults, greater left posterolateral frontal activation was associated with faster and more accurate switch performance. Therefore, different aspects of task-switching performance exhibit varying patterns of age-related differences across adulthood. Increased engagement of the left posterolateral frontal cortex, which plays a specific role in reconfiguring and implementing relevant task rules, may help older adults compensate for declined switch performance.

Whether and how traumatic brain injury (TBI) impacts ageing in the decades post-injury remains a matter of debate, partly due to a lack of controlled studies. This study examined the long-term impact of TBI on cognition and wellbeing in middle-aged and older adults and explored the relationship between age, cognition, and wellbeing, compared with a non-TBI control group. Cross-sectional data from 143 participants aged ≥40 with moderate-severe TBI (6-33 years post-injury; mean age 59.64) were compared with 71 non-TBI controls (mean age 62.10) group matched on age, gender, and premorbid IQ. Individuals with significant confounding comorbidities were excluded. A battery of neuropsychological tests and wellbeing measures (emotional distress, sleep, health-related quality of life [HRQoL]) was administered. Older age and TBI were each independently associated with poorer cognition across multiple domains (p < 0.05). The relationship between verbal learning and memory impairment post-TBI differed between age groups: individuals with TBI in their 40s-60s performed significantly worse than same-aged controls on verbal story acquisition (B = 0.09, p = 0.040, 95% confidence interval [CI] [0.004, 0.17]) and recall (B = 0.12, p = 0.009, 95% CI [0.03, 0.21]), and verbal wordlist recall (B = 0.11, p = 0.007, 95% CI [0.03, 0.19]). In comparison, no significant group differences in verbal memory emerged for ages 70-90. The TBI group reported greater emotional distress (B = 3.55, p < 0.001, 95% CI [1.73, 5.37]), poorer sleep quality (B = 1.07, p = 0.016, 95% CI [0.20, 1.94]), and poorer physical HRQoL (B = -4.26, p = 0.003, 95% CI [-7.08, -1.43]) than controls at all ages. Poorer physical HRQoL was related to poorer cognition post-TBI (p < 0.05). Our results challenge the notion that TBI exacerbates ageing. Moderate-severe TBI resulted in significant long-term impairments in cognition and wellbeing, with verbal learning and memory more impaired during middle-adulthood but not older adulthood compared to controls. TBI was not associated with changes to wellbeing with ageing. Intervention for verbal memory deficits in middle-aged adults with TBI is important, along with wider long-term supports for cognition, wellbeing, and activity participation in all individuals with TBI.

Despite advancements in understanding Huntington's disease (HD) over the past two decades, absence of disease-modifying treatments remains a challenge. Accurately characterizing progression states is crucial for developing effective therapeutic interventions. Various factors contribute to this challenge, including the need for precise methods that can account for the complex nature of HD progression.

This study aims to address this gap by leveraging the concept of the brain's biological age as a foundation for a data-driven clustering method to delineate various states of progression. Brain-predicted age, influenced by somatic expansion and its impact on brain volumes, offers a promising avenue for stratification by stratifying subgroups and determining the optimal timing for interventions.

To achieve this, data from 953 participants across diverse cohorts, including PREDICT-HD, TRACK-HD, and IMAGE-HD, were meticulously analyzed. Brain-predicted age was computed using sophisticated algorithms, and participants were categorized into four groups based on CAG and age product score. Unsupervised k-means clustering with brain-predicted age difference (brain-PAD) was then employed to identify distinct progression states.

The analysis revealed significant disparities in brain-predicted age between HD participants and controls, with these differences becoming more pronounced as the disease progressed. Brain-PAD demonstrated a correlation with disease severity, effectively identifying five distinct progression states characterized by significant longitudinal disparities.

These findings highlight the potential of brain-PAD in capturing HD progression states, thereby enhancing prognostic methodologies and providing valuable insights for future clinical trial designs and interventions. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Compared to nonverbal cognition such as executive or memory functions, language-related cognition generally appears to remain more stable until later in life. Nevertheless, different language-related processes, for example, verbal fluency versus vocabulary knowledge, appear to show different trajectories across the life span. One potential explanation for differences in verbal functions may be alterations in the functional and structural network architecture of different large-scale brain networks. For example, differences in verbal abilities have been linked to the communication within and between the frontoparietal (FPN) and default mode network (DMN). It, however, remains open whether brain connectivity within these networks may be informative for language performance at the individual level across the life span. Further information in this regard may be highly desirable as verbal abilities allow us to participate in daily activities, are associated with quality of life, and may be considered in preventive and interventional setups to foster cognitive health across the life span. So far, mixed prediction results based on resting-state functional connectivity (FC) and structural connectivity (SC) data have been reported for language abilities across different samples, age groups, and machine-learning (ML) approaches. Therefore, the current study set out to investigate the predictability of verbal fluency and vocabulary knowledge based on brain connectivity data in the DMN, FPN, and the whole brain using an ML approach in a lifespan sample (N = 717; age range: 18-85) from the 1000BRAINS study. Prediction performance was, thereby, systematically compared across (i) verbal [verbal fluency and vocabulary knowledge] and nonverbal abilities [processing speed and visual working memory], (ii) modalities [FC and SC data], (iii) feature sets [DMN, FPN, DMN-FPN, and whole brain], and (iv) samples [total, younger, and older aged group]. Results from the current study showed that verbal abilities could not be reliably predicted from FC and SC data across feature sets and samples. Thereby, no predictability differences emerged between verbal fluency and vocabulary knowledge across input modalities, feature sets, and samples. In contrast to verbal functions, nonverbal abilities could be moderately predicted from connectivity data, particularly SC, in the total and younger age group. Satisfactory prediction performance for nonverbal cognitive functions based on currently chosen connectivity data was, however, not encountered in the older age group. Current results, hence, emphasized that verbal functions may be more difficult to predict from brain connectivity data in domain-general cognitive networks and the whole brain compared to nonverbal abilities, particularly executive functions, across the life span. Thus, it appears warranted to more closely investigate differences in predictability between different cognitive functions and age groups.

Spatial navigation is essential for wellbeing and independence and shows significant declines as part of age-related neurodegenerative disorders, such as Alzheimer's disease. Navigation is also one of the earliest behaviors impacted by this devastating disease. Neurobiological models of aging and spatial navigation have focused primarily on the cognitive factors that account for impaired navigation abilities during the course of healthy aging and early stages of preclinical and prodromal Alzheimer's disease. The contributions of physical factors that are essential to planning and executing movements during successful navigation, such as gait and dynamic balance, are often overlooked despite also being vulnerable to early stages of neurodegenerative disease. We review emerging evidence that spatial navigation and functional mobility each draw on highly overlapping sensory systems, cognitive processes, and brain structures that are susceptible to healthy and pathological aging processes. Based on this evidence, we provide an alternative to models that have focused primarily on spatial navigation as a higher order cognitive function dependent on brain areas such as the hippocampus and entorhinal cortex. Instead, we argue that spatial navigation may offer an ecologically valid cognitive-motor phenotype of age-related cognitive dysfunction. We propose that dual cognitive-motor deficits in spatial navigation may arise from early changes in neuromodulatory and peripheral sensory systems that precede changes in regions such as the entorhinal cortex.

Episodic memory enables the encoding and retrieval of novel associations, as well as the bridging across learned associations to draw novel inferences. A fundamental goal of memory science is to understand the factors that give rise to individual and age-related differences in memory-dependent cognition. Variability in episodic memory could arise, in part, from both individual differences in sustained attention and diminished attention in aging. We first report that, relative to young adults (N = 23; M = 20.0 years), older adults (N = 26, M = 68.7 years) demonstrated lower associative memory and memory-guided associative inference performance and that this age-related reduction in associative inference occurs even when controlling for associative memory performance. Next, we confirm these age-related memory differences by using a high-powered, online replication study (young adults: N = 143, M = 26.2 years; older adults N = 133, M = 67.7 years), further demonstrating that age-related differences in memory do not reflect group differences in sustained attention (as assayed by the gradual-onset continuous performance task; gradCPT). Finally, we report that individual differences in sustained attention explain between-person variability in associative memory and inference performance in the present, online young adult sample, but not in the older adult sample. These findings extend understanding of the links between attention and memory in young adults, demonstrating that differences in sustained attention was related to differences in memory-guided inference. By contrast, our data suggest that the present age-related differences in memory-dependent behavior and the memory differences between older adults are due to attention-independent mechanisms.

Healthy aging is associated with cognitive decline across multiple domains, including executive function, memory, and attention. These cognitive changes can often influence an individual's ability to function and quality of life. However, the degree to which individuals experience cognitive decline, as well as the trajectory of these changes, exhibits wide variability across people. These cognitive abilities are thought to depend on the coordinated activity of large-scale networks. Like behavioral effects, large variation can be seen in brain structure and function with aging, including in large-scale functional networks. However, tracking this variation requires methods that reliably measure individual brain networks and their changes over time. Here, we review the literature on age-related cognitive decline and on age-related differences in brain structure and function. We focus particularly on functional networks and the individual variation that exists in these measures. We propose that novel individual-centered fMRI approaches can shed new light on patterns of inter- and intra-individual variability in aging. These approaches may be instrumental in understanding the neural bases of cognitive decline.

Many new technologies, such as smartphones, computers, or public-access systems (like ticket-vending machines), are a challenge for older adults. One feature that these technologies have in common is that they involve underlying, partially observable, structures (state spaces) that determine the actions that are necessary to reach a certain goal (e.g., to move from one menu to another, to change a function, or to activate a new service). In this work we provide a theoretical, neurocomputational account to explain these behavioral difficulties in older adults. Based on recent findings from age-comparative computational- and cognitive-neuroscience studies, we propose that age-related impairments in complex goal-directed behavior result from an underlying deficit in the representation of state spaces of cognitive tasks. Furthermore, we suggest that these age-related deficits in adaptive decision-making are due to impoverished neural representations in the orbitofrontal cortex and hippocampus.

Resveratrol (RSV), a polyphenol with anti-aging properties affecting metabolism and energy balance, is considered as a mimetic candidate to calorie restriction (CR). However its potential effects on delaying the onset of age-related diseases and increasing longevity have not yet been demonstrated in non-obese models close to humans such as non-human primates. The longitudinal monitoring of cognitive and motor performances, occurrence of age-related pathologies, age-related brain atrophy and mortality was performed from adulthood to death in a cohort of male grey mouse lemurs (Microcebus murinus, N = 33), all receiving 105 kJ/day of food but with a subset of 18 animals receiving RSV (200 mg.kg-1 body weight.day-1). RSV supplementation improved cognitive and motor performance at middle age as compared to control (CTL) animals. Median-lifespan was greater in RSV-fed animals (7.9 years compared to 6.4 years for CTL) but long-term RSV supplementation did not significantly affect all-cause nor age-related mortality. Also, brain grey matter atrophy accelerated in the RSV group at old age as compared to the CTL group. Altogether, these results suggest that long-term RSV supplementation procures health benefits at middle-age in male mouse lemurs but has limited long-term effects on health and longevity and might even impair brain integrity at older ages.

Background: In the field of clinical neuropsychology, researchers and clinicians often use predefined criteria to determine whether there are indications of cognitive impairment. However, corrections and expected false-positive rates are typically available only for uncorrelated tests and simple consensus criteria. Objective: To present an easy-to-use and freely available online tool as a solution for scenarios involving correlated tests and composite consensus criteria, as frequently encountered in clinical neuropsychological research and practice. Method: Our tool employs Monte Carlo simulations to account for the number of participants, thus addressing the uncertainty in estimating false positive rates with small samples. We demonstrate the tool's utility through an example involving cognitive impairment assessment in cancer patients after chemotherapy. Results: The tool reveals considerable uncertainty in false positive rates, especially with small sample sizes, where rates may be higher than traditionally assumed. We found that correlations between tests affect impairment rates differently depending on whether single or multiple test criteria are used. For single-test criteria, lower correlations are associated with more false positives, while for multiple-test criteria, lower correlations lead to fewer false positives. Conclusions: This innovative tool enables more accurate estimation of false positive rates in various neuropsychological conditions. By providing a user-friendly interface and accounting for real-world complexities such as test correlations and composite criteria, our tool empowers clinicians and researchers to: Make informed decisions when interpreting neuropsychological test results.Design more robust research protocols for cognitive impairment studies.Better understand the implications of sample size on false positive rates.

The precuneus is a site of early amyloid-beta (Aβ) accumulation. Previous cross-sectional studies reported increased precuneus fMRI activity in older adults with mild cognitive deficits or elevated Aβ. However, longitudinal studies in early Alzheimer's disease (AD) are lacking and the relationship to the Apolipoprotein-E (APOE) genotype is unclear. Investigating the PREVENT-AD dataset, we assessed how baseline and longitudinal precuneus activity during successful memory retrieval relates to future Aβ and tau burden and change in memory performance. We further studied the moderation by APOE4 genotype. We included 165 older adults (age, 62.8 ± 4.4 years; 113 female; 66 APOE4 carriers) who were cognitively normal at baseline with a family history of AD. All participants performed task-fMRI at baseline and underwent 18F-flortaucipir-PET and 18F-NAV4694-Aβ-PET on average 5 years later. We found that higher baseline activity and greater longitudinal increase in precuneus activity were associated with higher Aβ burden in APOE4 carriers but not noncarriers. We observed no effects of precuneus activity on tau burden. Finally, APOE4 noncarriers with low baseline precuneus activity exhibited better longitudinal performance in an independent memory test compared with (1) noncarriers with higher baseline activity and (2) APOE4 carriers. Our findings suggest that higher task-related precuneus activity during memory retrieval at baseline and over time are associated with greater Aβ burden in cognitively normal APOE4 carriers. Our results further indicate that the absence of "hyperactivation" and the absence of the APOE4 allele is related with better future cognitive outcomes in cognitively normal older adults at risk for AD.

Intrinsic timescales of brain regions exhibit heterogeneity, escalating with hierarchical levels, and are crucial for the temporal integration of external stimuli. Aging, often associated with cognitive decline, involves progressive neuronal and synaptic loss, reshaping brain structure and dynamics. However, the impact of these structural changes on temporal coding in the aging brain remains unclear. We mapped intrinsic timescales and gray matter volume (GMV) using magnetic resonance imaging (MRI) in young and elderly adults. We found shorter intrinsic timescales across multiple large-scale functional networks in the elderly cohort, and a significant positive association between intrinsic timescales and GMV. Additionally, age-related decline in performance on visual discrimination tasks was linked to a reduction in intrinsic timescales in the cuneus. To explain these age-related shifts, we developed an age-dependent spiking neuron network model. In younger subjects, brain regions were near a critical branching regime, while regions in elderly subjects had fewer neurons and synapses, pushing the dynamics toward a subcritical regime. The model accurately reproduced the empirical results, showing longer intrinsic timescales in young adults due to critical slowing down. Our findings reveal how age-related structural brain changes may drive alterations in brain dynamics, offering testable predictions and informing possible interventions targeting cognitive decline.

In most human societies, grandparents often provide substantial care and support for their grandchildren, including as babies. Given that previous studies have shown that ageing is accompanied by a gradual decline in our ability to identify other people's emotions, does age also reduce our skill at understanding a baby's cries? Here, we show that older people with experience of caring for babies remain able to correctly decode the information conveyed by babies' cries. The results of our psychoacoustic experiments underline that older people were at least as good as younger adults at identifying whether a baby is crying in pain or rather as a result of simple discomfort. These results are consistent with the notion that humans are cooperative breeders where older generations can effectively help younger ones with alloparental care. Favouring intergenerational solidarity is likely to simultaneously benefit the quality of life of young parents and older, knowledgeable carers.

To apply machine learning approaches on EEG event-related oscillations (ERO) to discriminate preclinical Alzheimer's disease (AD) from age- and sex-matched controls.

Twenty-two cognitively normal preclinical AD participants with elevated amyloid and 21 cognitively normal controls without elevated amyloid completed n-back working memory tasks (n = 0, 1, 2). The absolute and relative power of ERO was extracted using the discrete wavelet transform in the delta, theta, alpha, and beta bands. Four machine learning methods were employed, and classification performance was assessed using three metrics.

The low-frequency bands produced higher discriminative performances compared to high-frequency bands. The 2-back task yielded the best classification capability among the three tasks. The highest area under the curve value (0.86) was achieved in the 2-back delta band nontarget condition data. The highest accuracy (80.47%) was obtained in the 2-back delta and theta bands nontarget data. The highest F1 score (0.82) was in the 2-back theta band nontarget data. The support vector machine achieved the highest performance among tested classifiers.

This study demonstrates the promise of using machine learning on EEG ERO from working memory tasks to detect preclinical AD.

EEG ERO may reveal pathophysiological differences in the earliest stage of AD when no cognitive impairments are apparent.

Working memory is an active system responsible for the temporary maintenance and processing of information in the support of cognition and action. In keeping with this, a growing body of research has explored the close links between working memory and attention, and how these might be harnessed to impact performance and possibly improve working memory efficiency. This is theoretically and practically important, given that working memory is a central hub in complex cognition yet is extremely capacity- and resource-limited. We review work carried out over the last 10 years or so looking at how high "value" items in working memory can be strategically prioritised through selective attention, drawing principally from visual working memory paradigms with young adult participants, while also discussing how the core effects extend to different task domains and populations. A consistent set of core findings emerges, with improved memory for items that are allocated higher value but no change in overall task performance, and a recency advantage regardless of point allocation when items are encountered sequentially. Value-directed prioritisation is effortful, under top-down strategic control, and appears to vary with perceptual distraction and executive load. It is driven by processes operating during encoding, maintenance, and retrieval, though the extent to which these are influenced by different features of the task context remains to be mapped out. We discuss implications for working memory, attention, and strategic control, and note some possible future directions of travel for this promising line of research.

The prefrontal cortex (PFC) is vital for higher cognitive functions and displays neuronal heterogeneity, with neuronal activity varying significantly across individual neurons. Using calcium imaging in the medial PFC (mPFC) of mice, we investigate whether differences in degree centrality-a measure of connectivity strength within local circuits-could explain this neuronal diversity and its functional implications. In young adults, neurons with high degree centrality, inferred from resting-state activity, exhibit reliable and stable action-plan selectivity during memory-guided tasks, suggesting that connectivity strength is closely linked to functional heterogeneity. This relationship, however, deteriorates in middle-aged and older mice. A computational model simulating age-related declines in synaptic plasticity reproduces these results. In young adults, degree centrality also predicts cross-modal action-plan selectivity, but this predictive power diminishes with age. Furthermore, neurons with high action-plan selectivity are spatially clustered, a pattern that fades with aging. These findings reveal the significant aging impact on the network properties in parallel with the functional and spatial organization of the mPFC.

Hand(s)-tapping tasks have been extensively studied in order to characterize the features of sensorimotor synchronization (SMS). These tasks frequently require participants to synchronize their tapping pace to an external, metronome-like sound. The impact of ageing on SMS abilities remains mainly unexplored. Thus, we conducted a series of hand tapping tasks on 15 young adults (YA) and 15 older adults (OA). The tasks included tapping with the dominant hand only (D), with the non-dominant hand only (ND), with both hands simultaneously (SIM), and alternating between the hands (ALT). Participants in each task performed a synchronization-continuation task, in which they had to tap for one minute according to an external sound set at their spontaneous motor tempo (separately identified), and then, after the sound stopped, continue tapping at the same tempo for another minute. Results indicated a set of preserved and degraded tapping behaviors in OA compared to YA. The ALT task produced the most deteriorated tapping performance, followed by the ND task; the other two tasks revealed no difference between the groups. These findings shed more light on how SMS declines across the lifespan and provide some preliminary but important information that may guide rehabilitation and diagnostic procedures.

As the global population ages, there is an increasing prevalence of mild cognitive impairment and dementia. Protecting and preserving cognitive function in older adults has become a critical public health concern.

This study utilized data from four phases of the Chinese Longitudinal Healthy Longevity Survey conducted from 2008 to 2018, encompassing a total of 2454 participants. Latent growth curve modeling was employed to analyze the trajectory and role of protein intake frequency and cognitive function.

The frequency of protein intake among older adults tends to rise, with individuals exhibiting higher initial levels experiencing smaller subsequent increases. Conversely, cognitive function generally declines, with those starting at higher levels experiencing more pronounced decreases. Notably, the initial frequency of protein intake is positively correlated with the initial level of cognitive function (β = 0.227, 95% CI: 0.156 to 0.299, p < 0.001), but does not significantly influence the rate of change in cognitive function (β = -0.030, 95% CI: -0.068 to 0.009, p = 0.128). The rate of change in protein intake frequency is positively associated with the rate of change in cognitive function (β = 0.152, 95% CI: 0.023 to 0.280, p = 0.020).

The alterations in protein intake frequency are linked to alterations in cognitive function among older adults. Maintaining a stable high frequency of protein intake or increasing the frequency of protein intake may contribute to stabilizing cognitive function as well as reducing the risk of cognitive impairment and dementia in older adults.

This qualitative study explored the potential of piano training as a holistic intervention to enhance both cognitive and emotional well-being. The study aims to detail the experiences of older adults living with mild cognitive impairment (MCI) in a piano training program and recommend strategies to boost engagement.

Fourteen individuals (seven older adults with MCI and their family members) participated in individual semi-structured interviews before and after a 12-week group-based piano training program. These interviews were recorded, transcribed, open-coded, and analyzed by conventional content analysis.

Participants with MCI reported improvements in mood, cognitive function, and social interaction. The learning process elicited mixed emotions, with both enjoyment and frustration occurring during the learning phases. Skill mastery and positive social interactions were crucial for sustained engagement throughout the program, although group settings sometimes led to negative self-comparisons.

Findings highlighted the need to address both cognitive and emotional needs in interventions for MCI. Neglecting these aspects can exacerbate feelings of low self-esteem and other negative emotions.

Recommendations for cognitive training programs include positive reinforcement, personalized support, mental preparation for challenges, and rapport building to enhance participant motivation and adherence.

The cognitive neuroscience of human aging seeks to identify neural mechanisms behind the commonalities and individual differences in age-related behavioral changes. This goal has been pursued predominantly through structural or "task-free" resting-state functional neuroimaging. The former has elucidated the material foundations of behavioral decline, and the latter has provided key insight into how functional brain networks change with age. Crucially, however, neither is able to capture brain activity representing specific cognitive processes as they occur. In contrast, task-based functional imaging allows a direct probe into how aging affects real-time brain-behavior associations in any cognitive domain, from perception to higher-order cognition. Here, we outline why task-based functional neuroimaging must move center stage to better understand the neural bases of cognitive aging. In turn, we sketch a multi-modal, behavior-first research framework that is built upon cognitive experimentation and emphasizes the importance of theory and longitudinal design.

Aging is a heterogeneous process, so individuals of the same age may be aging at a different rate. A natural model of premature aging in mice have been proposed based on the poor response to the T-maze. Those that take longer to cross the intersection are known as Prematurely Aging Mice (PAM), while those that show an exceptional response are known as Exceptional non-PAM (E-NPAM), being the rest non-PAM (NPAM). Although many aspects of PAM and E-NPAM have been described, some aspects of their brain aging have not been studied. Similarly, it is known that PAM, NPAM and E-NPAM show a different rate of aging and longevity, but the differences between these three groups in behavior, immune function and oxidative-inflammatory state are unknown. The present study aims to deepen the study of brain aging in PAM and E-NPAM, and to study the differences in behavior, immunity, and oxidative-inflammatory state of peritoneal leukocytes between PAM, NPAM and E-NPAM. Results show deteriorated brains in PAM. Moreover, NPAM show an oxidative state similar to E-NPAM, an anxiety similar to PAM, and an intermediate immunity and lifespan between PAM and E-NPAM. In conclusion, immune function seems to be more associated with the longevity achieved.

The association between sleep quality and cognition is widely established, but the role of aging in this relationship is largely unknown.

To examine how age impacts the sleep-cognition relationship and determine whether there are sensitive ranges when the relationship between sleep and cognition is modified. This investigation could help identify individuals at risk for sleep-related cognitive impairment.

Sample included 711 individuals (ages 36.00-89.83, 59.66 ± 14.91, 55.7 % female) from the Human Connectome Project-Aging (HCP-A).

The association between sleep quality (Pittsburgh Sleep Quality Index, PSQI) and cognition (Crystallized Cognition Composite and Fluid Cognition Composite from the NIH Toolbox, the Trail Making Test, TMT, and the Rey Auditory Verbal Learning Test, RAVLT) was measured using linear regression models, with sex, race, use of sleep medication, hypertension, and years of education as covariates. The interaction between sleep and age on cognition was tested using the moderation analysis, with age as both continuous linear and nonlinear (quadratic) terms.

There was a significant interaction term between the PSQI and nonlinear age term (age2) on TMT-B (p = 0.02) and NIH Toolbox crystallized cognition (p = 0.02), indicating that poor sleep quality was associated with worse performance on these measures (sensitive age ranges 50-75 years for TMT-B and 66-70 years for crystallized cognition).

The sleep-cognition relationship may be modified by age. Individuals in the middle age to early older adulthood age band may be most vulnerable to sleep-related cognitive impairment.

The aim of this study was to explore the relationships among physical fitness, formal education levels, social educational experiences, and mild cognitive impairment in older adults.

Using the Korean version of the mini-mental state examination, senior fitness tests, and questionnaires on social educational experiences and physical activity, the study assessed data on 148 Korean participants 65 years and above. Multiple linear regression analysis was conducted to examine the relationships among the factors.

The average age of the participants was 79.54 ± 0.55 years. Educational level showed a significant negative relationship with cognitive function scores, explaining 17.7% of the variance (R² = 0.177, p < 0.001). Current social educational experiences were significantly associated with a lower prevalence of mild cognitive impairment. Those without current social educational experiences were 1.946 times more likely to have MCI (p < 0.05) than those with such experiences. Physical fitness components, such as right upper body strength (OR = 1.171, 95% CI: 1.001-1.370), agility (OR = 1.246, 95% CI: 0.961-1.616), and cardiorespiratory fitness (OR = 0.975, 95% CI: 0.950-0.999), were also significantly associated with cognitive function. Additionally, older adult men had a higher likelihood of MCI than older adult women did (OR = 0.276, 95% CI: 0.097-0.782).

The findings highlight the importance of education, ongoing social educational experiences, and physical fitness in maintaining cognitive health in older adults. Thus, promoting lifelong education and physical fitness programs may help reduce the risk of mild cognitive impairment in older adults.

Phosphorylated tau (p-tau) and amyloid beta (Aβ) in human plasma may provide an affordable and minimally invasive method to evaluate Alzheimer's disease (AD) pathophysiology. The medial temporal lobe (MTL) is susceptible to changes in structural integrity that are indicative of the disease progression. Among healthy adults, higher dynamic network flexibility within the MTL was shown to mediate better generalization of prior learning, a measure which has been demonstrated to predict cognitive decline and neural changes in preclinical AD longitudinally. Recent developments in cognitive, neural, and blood-based biomarkers of AD risk that may correspond with MTL changes. However, there is no comprehensive study on how these generalization biomarkers, long-term memory, MTL dynamic network flexibility, and plasma biomarkers are interrelated. This study investigated (1) the relationship between long-term memory, generalization performance, and MTL dynamic network flexibility and (2) how plasma p-tau231, p-tau181, and Aβ42/Aβ40 influence generalization, long-term memory, and MTL dynamics in cognitively unimpaired older African Americans.

148 participants (Meanage: 70.88,SDage: 6.05) were drawn from the ongoing longitudinal study, Pathways to Healthy Aging in African Americans conducted at Rutgers University-Newark. Cognition was evaluated with the Rutgers Acquired Equivalence Task (generalization task) and Rey Auditory Learning Test (RAVLT) delayed recall. MTL dynamic network connectivity was measured from functional Magnetic Resonance Imaging data. Plasma p-tau231, p-tau181, and Aβ42/Aβ40 were measured from blood samples.

There was a significant positive correlation between generalization performance and MTL Dynamic Network Flexibility (t = 3.372, β = 0.280, p < 0.001). There were significant negative correlations between generalization performance and plasma p-tau231 (t = -3.324, β = -0.265, p = 0.001) and p-tau181 (t = -2.408, β = -0.192, p = 0.017). A significant negative correlation was found between plasma p-tau231 and MTL Dynamic Network Flexibility (t = -2.825, β = -0.232, p = 0.005).

Increased levels of p-tau231 are associated with impaired generalization abilities and reduced dynamic network flexibility within the MTL. Plasma p-tau231 may serve as a potential biomarker for assessing cognitive decline and neural changes in cognitively unimpaired older African Americans.

Regular physical activity is associated with healthier brains and improved cognition among older adults. Yet, the impact of a short bout of exercise on older adults' cognition still is not fully clarified. The present study explored the effects of 20 min of moderate-intensity aerobic exercise (on a cycle ergometer) on cognition. Forty-eight healthy older adults were randomly assigned to an exercise or a control group and completed four cognitive tests: Affective Go/No-Go (AGN), Simple Reaction Time (SRT), Spatial Working Memory (SWM) and a Backward Counting task. Tests were administered prior to and immediately after 20 min of cycling (exercise group) or rest (control group). Mixed-design 2 × 2 ANOVAs indicated a significant interaction of Group x Session, for commission errors on the positive valence of the Affective Go/No-go task, indicating that the exercise group performed better on one aspect of this inhibition test after cycling (p = 0.004), while the control group's performance declined after rest. A similar pattern was found for the SWM, with the exercise group showing a significantly better performance after the exercise both for total error (p = 0.027) and the strategy (p = 0.002), while no improvement was observed after rest (controls). The study suggests that inhibitory control functions and working memory may be improved by a single relatively short bout of moderate exercise. However, the null effects of exercise on the other cognitive measures indicate that the neurocognitive benefits of acute exercise for older adults may be selectively sensitive to exercise parameters and to specific aspects of cognition.

Resting-state functional magnetic resonance imaging (rs-fMRI) and brain functional connectome (we use 'brain connectome' hereafter for simplicity) have advanced our understanding of the ageing brain and age-related changes in cognitive function. Previous studies have investigated the association among brain connectome and age, global cognition, and memory function separately. However, very few have predicted age, overall cognitive functioning and memory performance in a single study to better understand their complex relationship. In this cross-sectional study, we applied an exploratory, data-driven method to investigate the brain connectome markers that could predict ageing, overall cognitive functioning assessed as intelligence quotient (IQ, measured by Wechsler Memory Scale) and memory performance assessed as memory quotient (MQ, measured by Wechsler Memory Scale) in a carefully designed, multicentre, normal ageing cohort (n = 313). Our results showed that brain connectome could predict ageing and IQ, but the association with MQ was weak. We found that the connectivity with orbital frontal cortex was associated with both ageing and IQ. Mediation analysis further showed that the brain connectome mediated the relationship between age and overall cognitive functioning, suggesting a protective brain connectomic mechanism for maintaining normal cognitive functions during healthy ageing. This work may shed light on the potential neural correlates of healthy ageing, overall cognitive functioning and memory performance.

Although numerous studies have discussed about the impact of air pollution on cognitive function, a consensus has yet to be reached, necessitating further exploration of their relationship. The aim of this study is to reveal the effects of major air pollutants on cognitive function in Chinese middle-aged and older adults, while considering the lagged effects of pollution.

Panel data were constructed by integrating the air pollutants concentration (particulate matter diameter ≤1 µm (μm) (PM1), PM2.5, PM10, nitrogen dioxide (NO2), and ozone (O3)) among 28 provinces in China and the personal characteristics from China Health and Retirement Longitudinal Study participants during the period of 2011-2015. To explore the effects of single pollutants and their interactions on cognitive function, panel linear regression using ordinary least squares method was employed, and first-order lag effects (two-year interval) of air pollution were introduced into the models.

Our study revealed that, after adjusting for confounding factors, higher levels of particulate matter (PM1, coefficient (Coef.) = -0.093, P = 0.001; PM2.5, Coef. = -0.051, P = 0.001; PM10, Coef. = -0.030, P = 0.001) and NO2 (Coef. = -0.094, P = 0.006) were associated with lower cognitive function scores among the participants. Moreover, the interaction between the five major pollutants exhibited a negative effect on cognitive function(Coef. = -2.89, P = 0.004).

PM1, PM2.5, PM10 have detrimental effects on the cognitive function of middle-aged and elderly adults in China, where increasing particle diameter correlates with a less negative impacts, providing theoretical underpinnings for the formulation of environmental protection policies.

Divergent thinking (DT), the ability to generate alternative responses to open-ended problems, has become an increasingly relevant topic in aging research due to its inverse relationship with cognitive decline.

In this narrative review, we explore the latest evidence supporting DT training as a potential strategy for dementia prevention.

We identify two pathways through which DT may protect against cognitive decline: (1) by fostering creative cognition and (2) by stimulating DT-related domains. Our findings suggest that verbal DT remains relatively well preserved in older adults, although there is limited empirical evidence to support the idea that DT training enhances creative cognition or DT-related domains in this population.

Therefore, while tools designed to enhance DT in older individuals seem promising, it is crucial to rigorously test their effects on the target population to maximize their impact on both the cognitive and psychological domains.

Depression is a heterogeneous syndrome that impacts an individual's emotional, social, cognitive and bodily functioning. Depression is associated with biases in emotional processing, but alterations in basic sensory processing have received less attention in depression research. Here, we measured event-related potentials (ERPs) in response to changes in the intensity of auditory stimuli and the location of somatosensory stimuli in participants with depression and in non-depressed control participants. We tested whether auditory mismatch negativity, P3a or N1 intensity dependence response or somatosensory mismatch response, P3a, P50 or N80 can dissociate depressed participants and non-depressed controls, and we also analysed the effects of depression medication and age in this sample. N1 intensity dependence response was increased in unmedicated depressed participants relative to non-depressed controls. When age was controlled for in the analysis, the effect of depression was only at a trend level. N1 intensity dependence response correlated with depression severity at the whole sample level. We did not observe any depression-related alterations in auditory mismatch negativity or P3a or somatosensory ERPs. Our results may reflect an association between the N1 intensity dependence response and altered neurotransmitter activity in depression, but this should be confirmed in future studies.

Emotional prosody is the reflection of emotion types such as happiness, sadness, fear and anger in the speaker's tone of voice. Accurately perceiving, interpreting and expressing emotional prosody is an inseparable part of successful communication and social interaction. There are few studies on emotional prosody, which is crucial for communication, and the results of these studies have inconsistent information regarding age and gender.

The primary aim of this study is to assess the perception of emotional prosody in healthy ageing. The other aim is to examine the effects of variables such as age, gender, language and neurocognitive capacity on the prediction of emotional prosody recognition skills.

Sixty-nine participants between the ages of 18-75 were included in the study. Participants were grouped as the young group aged 18-35 (n = 26), the middle-aged group aged 36-55 (n = 24) and the elderly group aged 56-75 (n = 19). Perceptual emotional prosody test, motor response time test, and neuropsychological test batteries were administered to the participants. Participants were asked to recognise the emotion in the sentences played on the computer. Natural (neutral, containing neither positive nor negative emotion), happy, angry, surprised and panic emotions were evaluated with sentences composed of pseudoword stimuli.

It was observed that the elderly group performed worse in recognising angry, panic, natural and happy emotions and in total recognition, which gives the correct recognition performance in recognition of all emotions. There was no age-related difference in recognition of the emotion of surprise. The women were more successful in recognising angry, panic, happy and total emotions compared to men. Age and Motor Reaction Time Test scores were found to be significant predictors in the emotional response time regression model. Age, language, attention and gender variables were found to have a significant effect on the regression model created for the success of total recognition of emotions (p < 0.05).

This was a novel study in which emotional prosody was assessed in the elderly by eliminating lexical-semantic cues related to emotional prosody and associating emotional prosody results with neuropsychiatric tests. All our findings revealed the importance of age for the perception of emotional prosody. In addition, the effects of cognitive functions such as attention, which decline with age, were found to be important. Therefore, it should not be forgotten that many factors contribute to the success of recognising emotional prosody correctly. In this context, clinicians should consider variables such as cognitive health and education when assessing the perception of emotional prosody in elderly individuals.

What is already known on the subject Most of the studies compare young and old groups, and these studies evaluate the perception of emotional prosody by using sentences formed by observing the speech sounds, syllables, words and grammar rules in the vocabulary of the language. It has been reported that the perception of emotional prosody is lower, mostly in the elderly group, but there is inconsistent information in terms of age and gender. What this paper adds to existing knowledge Perceptual Prosody Recognition was evaluated with an experimental design in which sentence structures consisting of lexemes were used as stimuli and neurocognitive tests were included, taking into account the phonological and syntactic rules of language. This study was a novel study in diagnosing emotional prosody in terms of comparing different age groups and determining the factors affecting multidimensional emotional prosody, including neuropsychiatric features. What are the clinical implications of this work? All our findings revealed the importance of age for the perception of emotional prosody. In addition, it was determined that the effects of cognitive functions such as attention were important with age.

Background: The Learning Ratio (LR) is a novel learning score that has shown improved utility over other learning metrics in detecting Alzheimer's disease (AD) across multiple memory tasks. However, its utility on the Consortium to Establish a Registry for Alzheimer's Disease Word List Memory Test (CERAD WLMT), a widely used list learning measure sensitive to decline in neurodegenerative disease, is unknown. The goal of the current study was to determine the utility of LR on the CERAD WLMT in differentiating between diagnostic (MiNCD vs MaNCD) and etiologic groups (VaD vs AD) in a veteran sample. Methods: Raw learning slope (RLS) and LR scores were examined in 168 veterans diagnosed with major neurocognitive disorder (MaNCD), mild neurocognitive disorder (MiNCD), or normal aging following neuropsychological evaluation. Patients with MaNCD were further classified by suspected etiology (i.e. microvascular disease vs AD). Results: Whereas RLS scores were not significantly different between MiNCD and MaNCD, LR scores were significantly different between all diagnostic groups (p's < .05). Those with AD had lower LR scores and RLS scores compared to those with VaD (p's < .05). LR classification accuracy was acceptable for MiNCD (AUC = .76), excellent for MaNCD (AUC = .86) and VaD (AUC = .81), and outstanding for AD (AUC = .91). Optimal cutoff scores for WLMT LR were derived from Youden's index. Conclusion: Results support the use of LR scores over RLS when interpreting the CERAD WLMT and highlight the clinical utility of LR in differentiating between diagnostic groups and identifying suspected etiology.

Objective: This analysis explored relationships between mental health symptoms and conditions and cognitive function in a cohort of Vietnam-era women veterans from the Health of Vietnam Era Veteran Women's Study (HealthViEWS). Methods: Vietnam-era women veterans completed a mail survey assessing self-reported symptom severity of posttraumatic stress disorder (PTSD) and depression. A telephone-based structured interview assessed mental health conditions and cognitive function (telephone interview for cognitive status [TICS]). Participants were categorized using a TICS threshold of ≤29 to designate possible cognitive impairment versus nonimpaired. Separate logistic regression models were used to determine associations between possible cognitive impairment and each self-reported and interviewer-rated assessment of PTSD and depression while adjusting for age, education, race, marital status, and wartime service location. Results: The sample consisted of 4,077 women veterans who were ≥60 years old and completed the TICS. Of these women, 7.20% were categorized with possible cognitive impairment. Logistic regression models indicated that self-reported PTSD and depression symptom severity were each significantly associated with higher odds of possible cognitive impairment (adjusted odds ratios [aOR]: 1.03 [95% confidence interval [CI]: 1.02-1.04] and 1.07 [95% CI: 1.04-1.09], respectively). Women veterans with a probable diagnosis of depression had higher odds of possible cognitive impairment compared to those without depression (aOR: 1.61 [95% CI: 1.07-2.42]). No association was found for probable diagnosis of PTSD. Conclusions: Although further examination remains necessary, results suggest that Vietnam-era women veterans with self-reported PTSD and depression symptom severity or a probable diagnosis of depression may benefit from screening of cognitive function to inform clinical care.

This study aimed to establish normative data for the Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN), a brief computer-based test for global cognitive assessment through accuracy and response times on tasks related to memory, attention, temporal orientation, visuo-constructional abilities, math (calculation), executive functions, and reading speed.

A sample of 323 Italian individuals with Montreal Cognitive Assessment (MoCA) equivalent score ≥1 (180 females; average age: 61.33 years; average education: 11.32 years), stratified by age, education, and sex, completed SATURN using PsychoPy, and a paper-and-pencil protocol consisting of Mini-Mental State Examination (MMSE) and MoCA. Data analyses included: (i) correlations between the total accuracy scores of SATURN and those of MMSE and MoCA; (ii) multiple regressions to determine the impact of sex, age, and education, along with the computation of adjusted scores; (iii) the calculation of inner and outer tolerance limits, equivalent scores, and the development of correction grids.

The mean total time on tasks was 6.72 ± 3.24 min. Age and education significantly influence the SATURN total accuracy, while sex influences the total time on tasks. Specific sociodemographic characteristics influence subdomain accuracies and times on task differently. For the adjusted SATURN total score, the outer limit corresponds to 16.56 out of 29.00 (cut-off), while the inner limit is 18.57. SATURN significantly correlates with MMSE and MoCA.

In conclusion, SATURN is the first open-source digital tool for initial cognitive assessment in Italy, showing potential for self-administration in primary care, and remote administration. Future studies need to assess its sensitivity and specificity in detecting pathological cognitive decline.