Age differences in BOLD modulation to task difficulty as a function of amyloid burden.

Effective cognitive performance often requires the allocation of additional neural resources (i.e. blood-oxygen-level-dependent [BOLD] activation) as task demands increase, and this demand-related modulation is affected by amyloid-beta deposition and normal aging. The present study investigated these complex relationships between amyloid, modulation, and cognitive function (i.e. fluid ability). Participants from the Dallas Lifespan Brain Study (DLBS, n = 252, ages 50-89) completed a semantic judgment task during functional magnetic resonance imaging (fMRI) where the judgments differed in classification difficulty. Amyloid burden was assessed via positron emission tomography (PET) using 18F-florbetapir. A quadratic relationship between amyloid standardized value uptake ratios (SUVRs) and BOLD modulation was observed such that modulation was weaker in those with moderately elevated SUVRs (e.g. just reaching amyloid-positivity), whereas those with very high SUVRs (e.g. SUVR > 1.5) showed strong modulation. Greater modulation was related to better fluid ability, and this relationship was strongest in younger participants and those with lower amyloid burden. These results support the theory that effective demand-related modulation contributes to healthy cognitive aging, especially in the transition from middle age to older adulthood, whereas high modulation may be dysfunctional in those with substantial amyloid deposition.

Computer gaming alters resting-state brain networks, enhancing cognitive and fluid intelligence in players: evidence from brain imaging-derived phenotypes-wide Mendelian randomization.

The debate on whether computer gaming enhances players' cognitive function is an ongoing and contentious issue. Aiming to delve into the potential impacts of computer gaming on the players' cognitive function, we embarked on a brain imaging-derived phenotypes (IDPs)-wide Mendelian randomization (MR) study, utilizing publicly available data from a European population. Our findings indicate that computer gaming has a positive impact on fluid intelligence (odds ratio [OR] = 6.264, P = 4.361 × 10-10, 95% confidence interval [CI] 3.520-11.147) and cognitive function (OR = 3.322, P = 0.002, 95% CI 1.563-7.062). Out of the 3062 brain IDPs analyzed, only one phenotype, IDP NET100 0378, was significantly influenced by computer gaming (OR = 4.697, P = 1.10 × 10-5, 95% CI 2.357-9.361). Further MR analysis suggested that alterations in the IDP NET100 0378 caused by computer gaming may be a potential factor affecting fluid intelligence (OR = 1.076, P = 0.041, 95% CI 1.003-1.153). Our MR study lends support to the notion that computer gaming can facilitate the development of players' fluid intelligence by enhancing the connectivity between the motor cortex in the resting-state brain and key regions such as the left dorsolateral prefrontal cortex and the language center.

A radiomics-based brain network in T1 images: construction, attributes, and applications.

T1 image is a widely collected imaging sequence in various neuroimaging datasets, but it is rarely used to construct an individual-level brain network. In this study, a novel individualized radiomics-based structural similarity network was proposed from T1 images. In detail, it used voxel-based morphometry to obtain the preprocessed gray matter images, and radiomic features were then extracted on each region of interest in Brainnetome atlas, and an individualized radiomics-based structural similarity network was finally built using the correlational values of radiomic features between any pair of regions of interest. After that, the network characteristics of individualized radiomics-based structural similarity network were assessed, including graph theory attributes, test-retest reliability, and individual identification ability (fingerprinting). At last, two representative applications for individualized radiomics-based structural similarity network, namely mild cognitive impairment subtype discrimination and fluid intelligence prediction, were exemplified and compared with some other networks on large open-source datasets. The results revealed that the individualized radiomics-based structural similarity network displays remarkable network characteristics and exhibits advantageous performances in mild cognitive impairment subtype discrimination and fluid intelligence prediction. In summary, the individualized radiomics-based structural similarity network provides a distinctive, reliable, and informative individualized structural brain network, which can be combined with other networks such as resting-state functional connectivity for various phenotypic and clinical applications.

Structural connectivity of the multiple demand network in humans and comparison to the macaque brain.

Fluid intelligence encompasses a wide range of abilities such as working memory, problem-solving, and relational reasoning. In the human brain, these abilities are associated with the Multiple Demand Network, traditionally thought to involve combined activity of specific regions predominantly in the prefrontal and parietal cortices. However, the structural basis of the interactions between areas in the Multiple Demand Network, as well as their evolutionary basis among primates, remains largely unexplored. Here, we exploit diffusion MRI to elucidate the major white matter pathways connecting areas of the human core and extended Multiple Demand Network. We then investigate whether similar pathways can be identified in the putative homologous areas of the Multiple Demand Network in the macaque monkey. Finally, we contrast human and monkey networks using a recently proposed approach to compare different species' brains within a common organizational space. Our results indicate that the core Multiple Demand Network relies mostly on dorsal longitudinal connections and, although present in the macaque, these connections are more pronounced in the human brain. The extended Multiple Demand Network relies on distinct pathways and communicates with the core Multiple Demand Network through connections that also appear enhanced in the human compared with the macaque.

Connectome-based predictive modeling of fluid intelligence: evidence for a global system of functionally integrated brain networks.

Cognitive neuroscience continues to advance our understanding of the neural foundations of human intelligence, with significant progress elucidating the role of the frontoparietal network in cognitive control mechanisms for flexible, intelligent behavior. Recent evidence in network neuroscience further suggests that this finding may represent the tip of the iceberg and that fluid intelligence may depend on the collective interaction of multiple brain networks. However, the global brain mechanisms underlying fluid intelligence and the nature of multi-network interactions remain to be well established. We therefore conducted a large-scale Connectome-based Predictive Modeling study, administering resting-state fMRI to 159 healthy college students and examining the contributions of seven intrinsic connectivity networks to the prediction of fluid intelligence, as measured by a state-of-the-art cognitive task (the Bochum Matrices Test). Specifically, we aimed to: (i) identify whether fluid intelligence relies on a primary brain network or instead engages multiple brain networks; and (ii) elucidate the nature of brain network interactions by assessing network allegiance (within- versus between-network connections) and network topology (strong versus weak connections) in the prediction of fluid intelligence. Our results demonstrate that whole-brain predictive models account for a large and significant proportion of variance in fluid intelligence (18%) and illustrate that the contribution of individual networks is relatively modest by comparison. In addition, we provide novel evidence that the global architecture of fluid intelligence prioritizes between-network connections and flexibility through weak ties. Our findings support a network neuroscience approach to understanding the collective role of brain networks in fluid intelligence and elucidate the system-wide network mechanisms from which flexible, adaptive behavior is constructed.

Balancing accuracy and speed in the development of inhibitory control.

Inhibitory control develops rapidly and nonlinearly, making its accurate assessment challenging. This research investigated the developmental dynamics of accuracy and response latency in inhibitory control assessment of 3- to 6-year-old children in a longitudinal study (N = 431; 212 girls; Mage = 4.86 years, SD = 0.99) and a cross-sectional study (N = 135; 71 girls; Mage = 4.24 years, SD = 0.61). We employed a computerized Stroop task to measure inhibitory control, with fluid intelligence serving as a covariate. A growth curve analysis revealed that children who reached an accuracy threshold of 80% earlier demonstrated faster improvements in response latency. Both the cross-sectional and longitudinal findings demonstrated a positive association between response latency in the inhibitory control task and fluid intelligence, but only when participants had achieved and maintained high accuracy. These results suggest that researchers should consider response latency as an indicator of inhibitory control only in children who manage to respond accurately in an inhibitory control task.

The near and far transfer effects of computerized working memory training in typically developing preschool children: Evidence from event-related potentials.

Working memory (WM) refers to the ability to actively maintain and process information needed to complete complex tasks such as comprehension, learning, and reasoning. Recent studies have examined the efficacy of computerized working memory training (WMT) in improving cognitive functions in general and WM in particular, with mixed results. Thus, to what extent can WMT produce near and far transfer effects to cognitive function is currently unclear. This study investigated the transfer effects of a computerized WMT for preschool children and also examined the possible neural correlates using the event-related potential (ERP) technique. A total of 50 Chinese preschoolers (64.44 ± 7.76 months old; 24 girls) received 4-week training during school hours. Compared with those in the active control group, children in the training group showed better gains in behavioral performance in the WM task and significantly more changes in ERP markers of the WM and inhibitory control tasks (near transfer effect). However, no evidence was found for transfer to fluid intelligence (far transfer effect). These findings suggest that WMT is capable of enhancing cognitive functioning in preschool children, and as such this work has important implications for educational practice and it may help to design and refine cognitive interventions for typically developing children and those with WM problems or other cognitive deficits (e.g., children with attention-deficit/hyperactivity disorder).

The factorial structure of executive functions in preschool and elementary school children and relations with intelligence.

The timing of structural changes in executive functions (EFs) across development is a matter of controversy; whereas some studies suggest a uniform structure of EFs in early childhood, findings in middle and late childhood are mixed. There are results indicating uniformity of EFs as well as several studies suggesting multidimensionality of the construct. In addition, studies demonstrate an age-related differentiation of the relation between EFs and intelligence. We conducted a comparative analysis of the EF structure and relations with fluid intelligence in two distinct age groups. A sample of n = 145 preschool children (5.2-6.7 years of age) and n = 109 elementary school children (8.8-11.8 years) completed measures of working memory, inhibition, cognitive flexibility, and fluid intelligence. Confirmatory factor analysis (CFA) revealed that a single-factor model best represented performance on EF tasks in both preschool and elementary school children. Multi-group CFA indicated equivalent and strong relations between EFs and intelligence across both age groups (r = .64 in preschool and elementary school children). Our results confirm that EFs are significantly related to fluid intelligence but might not underlie a uniform pattern of successive differentiation into multiple EF components in childhood. We discuss how methodological artifacts such as simultaneous interference might have contributed to previous findings on differentiation in middle and late childhood.

Evidence for separate backward recall and n-back working memory factors: a large-scale latent variable analysis.

Multiple studies have explored the factor structure of working memory (WM) tasks, yet few have done so controlling for both the domain and category of the memory items in a single study. In the current pre-registered study, we conducted a large-scale latent variable analysis using variant forms of n-back and backward recall tasks to test whether they measured a single underlying construct, or were distinguished by stimuli-, domain-, or paradigm-specific factors. Exploratory analyses investigated how the resulting WM factor(s) were linked to fluid intelligence. Participants (N = 703) completed a fluid reasoning test and multiple n-back and backward recall tasks containing memoranda that varied across (spatial or verbal material) and within (verbal digits or letters) domain, allowing the variance specific to task content and paradigm to be assessed. Two distinct but related backward recall and n-back constructs best captured the data, in comparison to other plausible model constructions (single WM factor, two-factor domain, and three-factor materials models). Common variance associated with WM was a stronger predictor of fluid reasoning than a residual n-back factor, but the backward recall factor predicted fluid reasoning as strongly as the common WM factor. These data emphasise the distinctiveness between backward recall and n-back tasks.

Analysis of associations between dietary patterns, genetic disposition, and cognitive function in data from UK Biobank.

PURPOSE: Research suggests that diet influences cognitive function and the risk for neurodegenerative disease. The present study aimed to determine whether a recently developed diet score, based on recommendations for dietary priorities for cardio metabolic health, was associated with fluid intelligence, and whether these associations were modified by individual genetic disposition. METHODS: This research has been conducted using the UK Biobank Resource. Analyses were performed using self-report data on diet and the results for the verbal-numerical reasoning test of fluid intelligence of 104,895 individuals (46% male: mean age at recruitment 57.1 years (range 40-70)). For each participant, a diet score and a polygenic score (PGS) were constructed, which evaluated predefined cut-offs for the intake of fruit, vegetables, fish, processed meat, unprocessed meat, whole grain, and refined grain, and ranged from 0 (unfavorable) to 7 (favorable). To investigate whether the diet score was associated with fluid intelligence, and whether the association was modified by PGS, linear regression analyses were performed. RESULTS: The average diet score was 3.9 (SD 1.4). After adjustment for selected confounders, a positive association was found between baseline fluid intelligence and PGS (P < 0.001). No association was found between baseline fluid intelligence and diet score (P = 0.601), even after stratification for PGS, or in participants with longitudinal data available (n = 9,482). CONCLUSION: In this middle-aged cohort, no evidence was found for an association between the investigated diet score and either baseline or longitudinal fluid intelligence. However, as in previous reports, fluid intelligence was strongly associated with a PGS for general cognitive function.

Association between urinary iodine excretion, genetic disposition and fluid intelligence in children, adolescents and young adults: the DONALD study.

PURPOSE: Iodine deficiency increases the risk of cognitive impairment and delayed physical development in children. It is also associated with cognitive impairment in adults. Cognitive abilities are among the most inheritable behavioural traits. However, little is known about the consequences of insufficient postnatal iodine intake and whether the individual genetic disposition modifies the association between iodine intake and fluid intelligence in children and young adults. METHODS: The cultural fair intelligence test was used to assess fluid intelligence in the participants of the DONALD study (n = 238; mean age, 16.5 [SD = 7.7] years). Urinary iodine excretion, a surrogate iodine intake marker, was measured in 24-h urine. Individual genetic disposition (n = 162) was assessed using a polygenic score, associated with general cognitive function. Linear regression analyses were conducted to determine whether Urinary iodine excretion was associated with fluid intelligence and whether this association was modified by individual genetic disposition. RESULTS: Urinary iodine excretion above the age-specific estimated average requirement was associated with a five-point higher fluid intelligence score than that below the estimated average requirement (P = 0.02). The polygenic score was positively associated with the fluid intelligence score (ß = 2.3; P = 0.03). Participants with a higher polygenic score had a higher fluid intelligence score. CONCLUSION: Urinary iodine excretion above the estimated average requirement in childhood and adolescence is beneficial for fluid intelligence. In adults, fluid intelligence was positively associated with a polygenic score for general cognitive function. No evidence showed that the individual genetic disposition modifies the association between Urinary iodine excretion and fluid intelligence.

Executive functioning skills and (low) math achievement in primary and secondary school.

Schoolchildren with better executive functioning skills achieve better mathematics results. It is less clear how inhibition, cognitive flexibility, and working memory combine to predict mathematics achievement and difficulty throughout primary and secondary school. This study aimed to find the best combination of executive function measures for predicting mathematical achievement in Grades 2, 6, and 10 and to test whether this combination predicts the probability of having mathematical difficulties across school grades even when fluid intelligence and processing speed were included in the models. A total of 426 students-141 2nd graders (72 girls), 143 6th graders (72 girls), and 142 10th graders (79 girls)-were cross-sectionally assessed with 12 executive tasks, one standardized mathematical task, and a standardized test of intelligence. Bayesian regression analyses found various combinations of executive predictors of mathematical achievement for each school grade spanning Grade 2 to measures of cognitive inhibition (negative priming) and cognitive flexibility (verbal fluency); Grade 6 to measures of inhibition: resistance to distractor interference (receptive attention), cognitive flexibility (local-global), and working memory (counting span); and Grade 10 to measures of inhibition: resistance to distractor interference (receptive attention) and prepotent response inhibition (stop signal) and working memory (reading span). Logistic regression showed that the executive models derived from the Bayesian analyses had a similar ability to classify students with mathematical difficulty and their peers with typical achievement to broader cognitive models that included fluid intelligence and processing speed. Measures of processing speed, cognitive flexibility (local-global), and prepotent response inhibition (stop signal) were the main risk factors in Grades 2, 6, and 10, respectively. Cognitive flexibility (verbal fluency) in Grade 2 and fluid intelligence, which was more stable in all three grades, acted as protective factors against mathematical difficulty. These findings inform practical considerations for establishing preventive and intervention proposals.

Challenging the stability of RAN development: Acknowledging PA and Gf in relation to reading.

This study had two overriding goals, (1) examine the stability of rapid automatized naming (RAN) in predicting reading achievement while taking into account two other frequently studied constructs, phonological awareness and fluid intelligence (Gf) and (2) examine the predictive power of RAN measured at age 4 on reading ability. The stable pattern of RAN development found in a previously reported growth model was challenged by relating phonological awareness and Gf to the model. Children (N = 364) were followed from age 4 to age 10. At age 4, Gf related strongly to phonological awareness, which in turn related strongly to RAN. The relations between the RAN measures over time was largely unaffected by the inclusion of Gf and phonological awareness. RAN, Gf and phonological awareness at age 4 independently predicted latent factors reflecting reading-related abilities in grade 1 and grade 4. However, when scrutinizing type of reading measure in grade 4, Gf, phonological awareness and RAN at age 4 predicted both spelling and reading fluency, whereas RAN in grade 2 did not predict spelling but was the strongest predictor of reading fluency.

Olfactory training effects in children after mild traumatic brain injury.

OBJECTIVE: Mild traumatic brain injury (mTBI) might impair the sense of smell and cognitive functioning. Repeated, systematic exposure to odors, i.e., olfactory training (OT) has been proposed for treatment of olfactory dysfunctions, including post-traumatic smell loss. Additionally, OT has been shown to mitigate cognitive deterioration in older population and enhance selected cognitive functions in adults. We aimed to investigate olfactory and cognitive effects of OT in the pediatric population after mTBI, likely to exhibit cognitive and olfactory deficits. METHODS: Our study comprised 159 children after mTBI and healthy controls aged 6-16 years (M = 9.68 ± 2.78 years, 107 males), who performed 6-months-long OT with a set of 4 either high- or low-concentrated odors. Before and after OT we assessed olfactory functions, fluid intelligence, and executive functions. RESULTS: OT with low-concentrated odors increased olfactory sensitivity in children after mTBI. Regardless of health status, children who underwent OT with low-concentrated odors had higher fluid intelligence scores at post-training measurement, whereas scores of children performing OT with high-concentrated odors did not change. CONCLUSION: Our study suggests that OT with low-concentrated odors might accelerate rehabilitation of olfactory sensitivity in children after mTBI and support cognitive functions in the area of fluid intelligence regardless of head trauma.

Graph Mapping: A novel and simple test to validly assess fluid reasoning.

We present Graph Mapping - a simple and effective computerized test of fluid intelligence (reasoning ability). The test requires structure mapping - a key component of the reasoning process. Participants are asked to map a pair of corresponding nodes across two mathematically isomorphic but visually different graphs. The test difficulty can be easily manipulated - the more complex structurally and dissimilar visually the graphs, the higher response error rate. Graph Mapping offers high flexibility in item generation, ranging from trivial to extremally difficult items, supporting progressive item sequences suitable for correlational studies. It also allows multiple item instances (clones) at a fixed difficulty level as well as full item randomization, both particularly suitable for within-subject experimental designs, longitudinal studies, and adaptive testing. The test has short administration times and is unfamiliar to participants, yielding practical advantages. Graph Mapping has excellent psychometric properties: Its convergent validity and reliability is comparable to the three leading traditional fluid reasoning tests. The convenient software allows a researcher to design the optimal test variant for a given study and sample. Graph Mapping can be downloaded from: https://osf.io/wh7zv/.

Cross-cohort replicability and generalizability of connectivity-based psychometric prediction patterns.

An increasing number of studies have investigated the relationships between inter-individual variability in brain regions' connectivity and behavioral phenotypes, making use of large population neuroimaging datasets. However, the replicability of brain-behavior associations identified by these approaches remains an open question. In this study, we examined the cross-dataset replicability of brain-behavior association patterns for fluid cognition and openness predictions using a previously developed region-wise approach, as well as using a standard whole-brain approach. Overall, we found moderate similarity in patterns for fluid cognition predictions across cohorts, especially in the Human Connectome Project Young Adult, Human Connectome Project Aging, and Enhanced Nathan Kline Institute Rockland Sample cohorts, but low similarity in patterns for openness predictions. In addition, we assessed the generalizability of prediction models in cross-dataset predictions, by training the model in one dataset and testing in another. Making use of the region-wise prediction approach, we showed that first, a moderate extent of generalizability could be achieved with fluid cognition prediction, and that, second, a set of common brain regions related to fluid cognition across cohorts could be identified. Nevertheless, the moderate replicability and generalizability could only be achieved in specific contexts. Thus, we argue that replicability and generalizability in connectivity-based prediction remain limited and deserve greater attention in future studies.

Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects.

Brain aging is a complex process that requires a multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization, and vascular dynamics. However, most neuroimaging studies of aging have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and their relevance to cognitive decline in aging. Here, we used a data-driven multimodal approach, linked independent component analysis (ICA), to jointly analyze magnetic resonance imaging (MRI) of grey matter volume, cerebrovascular, and functional network topographies in relation to measures of fluid intelligence. Neuroimaging and cognitive data from the Cambridge Centre for Ageing and Neuroscience study were used, with healthy participants aged 18-88 years (main dataset n = 215 and secondary dataset n = 433). Using linked ICA, functional network activities were characterized in independent components but not captured in the same component as structural and cerebrovascular patterns. Split-sample (n = 108/107) and out-of-sample (n = 433) validation analyses using linked ICA were also performed. Global grey matter volume with regional cerebrovascular changes and the right frontoparietal network activity were correlated with age-related and individual differences in fluid intelligence. This study presents the insights from linked ICA to bring together measurements from multiple imaging modalities, with independent and additive information. We propose that integrating multiple neuroimaging modalities allows better characterization of brain pattern variability and changes associated with healthy aging.

Avalanche criticality in individuals, fluid intelligence, and working memory.

The critical brain hypothesis suggests that efficient neural computation can be achieved through critical brain dynamics. However, the relationship between human cognitive performance and scale-free brain dynamics remains unclear. In this study, we investigated the whole-brain avalanche activity and its individual variability in the human resting-state functional magnetic resonance imaging (fMRI) data. We showed that though the group-level analysis was inaccurate because of individual variability, the subject wise scale-free avalanche activity was significantly associated with maximal synchronization entropy of their brain activity. Meanwhile, the complexity of functional connectivity, as well as structure-function coupling, is maximized in subjects with maximal synchronization entropy. We also observed order-disorder phase transitions in resting-state brain dynamics and found that there were longer times spent in the subcritical regime. These results imply that large-scale brain dynamics favor the slightly subcritical regime of phase transition. Finally, we showed evidence that the neural dynamics of human participants with higher fluid intelligence and working memory scores are closer to criticality. We identified brain regions whose critical dynamics showed significant positive correlations with fluid intelligence performance and found that these regions were located in the prefrontal cortex and inferior parietal cortex, which were believed to be important nodes of brain networks underlying human intelligence. Our results reveal the possible role that avalanche criticality plays in cognitive performance and provide a simple method to identify the critical point and map cortical states on a spectrum of neural dynamics, ranging from subcriticality to supercriticality.

A lifestyle score in childhood and adolescence was positively associated with subsequently measured fluid intelligence in the DONALD cohort study.

PURPOSE: Lifestyle scores which combine single factors such as diet, activity, or sleep duration showed associations with cognitive decline in adults. However, the role of a favourable lifestyle in younger age and the build-up of cognitive reserve is less clear, which is why we investigated longitudinal associations between a lifestyle score in childhood and adolescence and fluid intelligence obtained on average 6 years later. METHODS: In the DONALD cohort, a lifestyle score of 0 to 4 points including healthy diet and duration of moderate-to-vigorous physical activity, sedentary behaviour and sleep was repeatedly assessed in participants aged 5 and 19 years. Data on fluid intelligence were assessed via a German version of the culture fair intelligence test (CFT), using CFT 1-R in children 8.5 years of age or younger (n = 62) or CFT 20-R in participants older than 8.5 years (n = 192). Multivariable linear regression models were used to investigate prospective associations between the lifestyle score and the fluid intelligence score. RESULTS: Mean lifestyle score of all participants was 2.2 (0.7-4) points. A one-point increase in the lifestyle score was associated with a higher fluid intelligence score (4.8 points [0.3-7.3], p = 0.0343) for participants completing the CFT 20-R. Furthermore, each additional hour of sedentary behaviour was associated with a lower fluid intelligence score (- 3.0 points [- 5.7 to - 0.3], p = 0.0313). For younger participants (CFT 1-R), no association was found in any analysis (p > 0.05). CONCLUSION: A healthy lifestyle was positively associated with fluid intelligence, whereby sedentary behaviour itself seemed to play a prominent role.

Lost Dynamics and the Dynamics of Loss: Longitudinal Compression of Brain Signal Variability is Coupled with Declines in Functional Integration and Cognitive Performance.

Reduced moment-to-moment blood oxygen level-dependent (BOLD) signal variability has been consistently linked to advanced age and poorer cognitive performance, showing potential as a functional marker of brain aging. To date, however, this promise has rested exclusively on cross-sectional comparisons. In a sample of 74 healthy adults, we provide the first longitudinal evidence linking individual differences in BOLD variability, age, and performance across multiple cognitive domains over an average period of 2.5 years. As expected, those expressing greater loss of BOLD variability also exhibited greater decline in cognition. The fronto-striato-thalamic system emerged as a core neural substrate for these change-change associations. Preservation of signal variability within regions of the fronto-striato-thalamic system also cohered with preservation of functional integration across regions of this system, suggesting that longitudinal maintenance of "local" dynamics may require across-region communication. We therefore propose this neural system as a primary target in future longitudinal studies on the neural substrates of cognitive aging. Given that longitudinal change-change associations between brain and cognition are notoriously difficult to detect, the presence of such an association within a relatively short follow-up period bolsters the promise of brain signal variability as a viable, experimentally sensitive probe for studying individual differences in human cognitive aging.