Measures of resting-state brain network segregation and integration vary in relation to data quantity: implications for within and between subject comparisons of functional brain network organization.

Measures of functional brain network segregation and integration vary with an individual's age, cognitive ability, and health status. Based on these relationships, these measures are frequently examined to study and quantify large-scale patterns of network organization in both basic and applied research settings. However, there is limited information on the stability and reliability of the network measures as applied to functional time-series; these measurement properties are critical to understand if the measures are to be used for individualized characterization of brain networks. We examine measurement reliability using several human datasets (Midnight Scan Club and Human Connectome Project [both Young Adult and Aging]). These datasets include participants with multiple scanning sessions, and collectively include individuals spanning a broad age range of the adult lifespan. The measurement and reliability of measures of resting-state network segregation and integration vary in relation to data quantity for a given participant's scan session; notably, both properties asymptote when estimated using adequate amounts of clean data. We demonstrate how this source of variability can systematically bias interpretation of differences and changes in brain network organization if appropriate safeguards are not included. These observations have important implications for cross-sectional, longitudinal, and interventional comparisons of functional brain network organization.

Participant diversity is necessary to advance brain aging research.

An absence of population-representative participant samples has limited research in healthy brain aging. We highlight examples of what can be gained by enrolling more diverse participant cohorts, and propose recommendations for specific reforms, both in terms of how researchers accomplish this goal and how institutions support and benchmark these efforts.

Dissociable Effects of Alzheimer's Disease-Related Cognitive Dysfunction and Aging on Functional Brain Network Segregation.

Alzheimer's disease (AD) is associated with changes in large-scale functional brain network organization. Individuals with AD exhibit less segregated resting-state brain networks compared with individuals without dementia. However, declines in brain network segregation are also evident as adult individuals grow older. Determining whether these observations reflect unique or overlapping alterations on the functional connectome of the brain is essential for understanding the impact of AD on network organization and incorporating measures of functional brain network organization toward AD characterization. Relationships between AD dementia severity and participant's age on resting-state brain system segregation were examined in 326 cognitively healthy and 275 cognitively impaired human individuals recruited through the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 601; age range, 55-96 years; 320 females). Greater dementia severity and increasing age were independently associated with lower brain system segregation. Further, dementia versus age relationships with brain network organization varied according to the processing roles of brain systems and types of network interactions. Aging was associated with alterations to association systems, primarily among within-system relationships. Conversely, dementia severity was associated with alterations that included both association systems and sensory-motor systems and was most prominent among cross-system interactions. Dementia-related network alterations were evident regardless of the presence of cortical amyloid burden, revealing that the measures of functional network organization are unique from this marker of AD-related pathology. Collectively, these observations demonstrate the specific and widespread alterations in the topological organization of large-scale brain networks that accompany AD and highlight functionally dissociable brain network vulnerabilities associated with AD-related cognitive dysfunction versus aging.SIGNIFICANCE STATEMENT Alzheimer's disease (AD)-associated cognitive dysfunction is hypothesized to be a consequence of brain network damage. It is unclear exactly how brain network alterations vary with dementia severity and whether they are distinct from alterations associated with aging. We evaluated functional brain network organization measured at rest among individuals who varied in age and dementia status. AD and aging exerted dissociable impacts on the brain's functional connectome. AD-associated brain network alterations were widespread and involved systems that subserve not only higher-order cognitive operations, but also sensory and motor operations. Notably, AD-related network alterations were independent of amyloid pathology. The research furthers our understanding of AD-related brain dysfunction and motivates refining existing frameworks of dementia characterization with measures of functional network organization.

The relationship of functional hippocampal activity, amyloid deposition, and longitudinal memory decline to memory complaints in cognitively healthy older adults.

We evaluated whether self-reports of worse cognition in older adults with normal cognitive function reflected actual memory decline, amyloid pathology, and subtle vulnerabilities in hippocampal function. We measured subjective cognitive decline (SCD) in 156 older participants from the Dallas Lifespan Brain Study. Functional hippocampal activation during encoding, measured with fMRI, and longitudinal memory change that was measured in the four years preceding the SCD measures were used to predict the magnitude of SCD. A subsample (N=105) also underwent 18F-Florbetapir PET imaging that measured amyloid burden. Results showed that increased SCD were associated with greater prior memory decline and amyloid deposition. Importantly, decreased hippocampal activation during encoding was a significant predictor of SCD, particularly in young-old adults below 69 years old, above and beyond prior memory change and amyloid deposition. These results indicate that multiple measures of neural and cognitive dysfunction are simultaneously associated with SCD. Moreover, SCD in younger seniors appears to reflect deficient hippocampal activity that increases their reports of poorer memory, independent of amyloid. This manuscript is part of the Special Issue entitled "Cognitive Neuroscience of Healthy and Pathological Aging" edited by Drs. M. N. Rajah, S. Belleville, and R. Cabeza. This article is part of the Virtual Special Issue titled COGNITIVE NEU-ROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect at https://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

Long-term prognosis and educational determinants of brain network decline in older adult individuals.

Older adults with lower education are at greater risk for dementia. It is unclear which brain changes lead to these outcomes. Longitudinal imaging-based measures of brain structure and function were examined in adult individuals (baseline age, 45-86 years; two to five visits per participant over 1-9 years). College degree completion differentiates individual-based and neighborhood-based measures of socioeconomic status and disadvantage. Older adults (~65 years and over) without a college degree exhibit a pattern of declining large-scale functional brain network organization (resting-state system segregation) that is less evident in their college-educated peers. Declining brain system segregation predicts impending changes in dementia severity, measured up to 10 years past the last scan date. The prognostic value of brain network change is independent of Alzheimer's disease (AD)-related genetic risk (APOE status), the presence of AD-associated pathology (cerebrospinal fluid phosphorylated tau, cortical amyloid) and cortical thinning. These results demonstrate that the trajectory of an individual's brain network organization varies in relation to their educational attainment and, more broadly, is a unique indicator of individual brain health during older age.

The manipulation of affect: A meta-analysis of affect induction procedures.

Affect inductions have become essential for testing theories of affect and for conducting experimental research on the effects of mood and emotion. The current review takes stock of the vast body of existing literature on affect induction procedures (AIPs; also referred to as mood inductions) to evaluate the effectiveness of affect inductions as research tools and to test theories of affect (e.g., the bipolarity hypothesis, negativity bias, positivity offset, and theories of emotionality and gender) using meta-analytic data. In doing so, we seek to address whether AIPs are effective for inducing affective states, what conditions maximize their effectiveness, for which emotions they are most effective, for whom they are most effective, and whether affect induction findings can provide insight into theories of affect. A meta-analysis of 874 samples and 53,509 participants suggests that affect inductions are effective on average (δ = 1.32), but this effectiveness varies with the type of affect induction, the emotion being induced, and the gender of the participants. Further, results indicate coupled activation where the induction of positive (negative) emotions leads to a corresponding reduction in negative (positive) emotions, which provides support for the bipolar continuum of positive and negative affect. Results also revealed a negativity bias in which individuals display stronger reactions to negative stimuli than positive stimuli. A practical guide in the choice of affect induction procedures for researchers is presented and implications for emotion theory are discussed. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Regional amyloid accumulation and cognitive decline in initially amyloid-negative adults.

OBJECTIVE: To assess whether global or regional changes in amyloid burden over 4 years predict early declines in episodic memory in initially amyloid-negative adults. METHODS: One hundred twenty-six initially amyloid-negative, cognitively normal participants (age 30-89 years) were included from the Dallas Lifespan Brain Study who completed florbetapir PET and a cognitive battery at baseline and 4-year follow-up. Standardized uptake value ratio (SUVR) change was computed across 8 bilateral regions of interest. Using general linear models, we examined the relationship between change in global and regional SUVR and change in episodic memory, controlling for baseline SUVR, baseline memory, age, sex, education, and APOE status. RESULTS: In initially amyloid-negative adults, we detected a regionally specific relationship between declining episodic memory and increasing amyloid accumulation across multiple posterior cortical regions. In addition, these amyloid-related changes in memory persisted when we focused on middle-aged adults only and after controlling for atrophy in global cortical, hippocampal, and Alzheimer disease signature cortical volume. CONCLUSION: Our results indicate that assessing regional changes in amyloid, particularly in posterior cortical regions, can aid in the early detection of subclinical amyloid-related decline in episodic memory as early as middle age. Future research incorporating tau and other markers of neurodegeneration is needed to clarify the sequence of events that lead to this early, subclinical memory decline.

Functional Parcellation of the Cerebral Cortex Across the Human Adult Lifespan.

Adult aging is associated with differences in structure, function, and connectivity of brain areas. Age-based brain comparisons have typically rested on the assumption that brain areas exhibit a similar spatial organization across age; we evaluate this hypothesis directly. Area parcellation methods that identify locations where resting-state functional correlations (RSFC) exhibit abrupt transitions (boundary-mapping) are used to define cortical areas in cohorts of individuals sampled across a large range of the human adult lifespan (20-93 years). Most of the strongest areal boundaries are spatially consistent across age. Differences in parcellation boundaries are largely explained by differences in cortical thickness and anatomical alignment in older relative to younger adults. Despite the parcellation similarities, age-specific parcellations exhibit better internal validity relative to a young-adult parcellation applied to older adults' data, and age-specific parcels are better able to capture variability in task-evoked functional activity. Incorporating age-specific parcels as nodes in RSFC network analysis reveals that the spatial topography of the brain's large-scale system organization is comparable throughout aging, but confirms that the segregation of systems declines with increasing age. These observations demonstrate that many features of areal organization are consistent across adulthood, and reveal sources of age-related brain variation that contribute to the differences.

Socioeconomic status moderates age-related differences in the brain's functional network organization and anatomy across the adult lifespan.

An individual's environmental surroundings interact with the development and maturation of their brain. An important aspect of an individual's environment is his or her socioeconomic status (SES), which estimates access to material resources and social prestige. Previous characterizations of the relation between SES and the brain have primarily focused on earlier or later epochs of the lifespan (i.e., childhood, older age). We broaden this work to examine the relationship between SES and the brain across a wide range of human adulthood (20-89 years), including individuals from the less studied middle-age range. SES, defined by education attainment and occupational socioeconomic characteristics, moderates previously reported age-related differences in the brain's functional network organization and whole-brain cortical structure. Across middle age (35-64 years), lower SES is associated with reduced resting-state system segregation (a measure of effective functional network organization). A similar but less robust relationship exists between SES and age with respect to brain anatomy: Lower SES is associated with reduced cortical gray matter thickness in middle age. Conversely, younger and older adulthood do not exhibit consistent SES-related difference in the brain measures. The SES-brain relationships persist after controlling for measures of physical and mental health, cognitive ability, and participant demographics. Critically, an individual's childhood SES cannot account for the relationship between their current SES and functional network organization. These findings provide evidence that SES relates to the brain's functional network organization and anatomy across adult middle age, and that higher SES may be a protective factor against age-related brain decline.

Social-class differences in self-concept clarity and their implications for well-being.

A consistent/stable sense of the self is more valued in middle-class contexts than working-class contexts; hence, we predicted that middle-class individuals would have higher self-concept clarity than working-class individuals. It is further expected that self-concept clarity would be more important to one's well-being among middle-class individuals than among working-class individuals. Supporting these predictions, self-concept clarity was positively associated with higher social class. Moreover, although self-concept clarity was associated with higher life satisfaction and better mental health, the association significantly attenuated among working-class individuals. In addition, self-concept clarity was not associated with physical health and its association with physical health did not interact with social class.

Resting-State Network Topology Differentiates Task Signals across the Adult Life Span.

Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20-89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system ("non-connector" nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems ("connector" nodes). This "activation selectivity" was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the "dedifferentiation" in brain activity observed in aging.SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20-89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance.

Motion-related artifacts in structural brain images revealed with independent estimates of in-scanner head motion.

Motion-contaminated T1-weighted (T1w) magnetic resonance imaging (MRI) results in misestimates of brain structure. Because conventional T1w scans are not collected with direct measures of head motion, a practical alternative is needed to identify potential motion-induced bias in measures of brain anatomy. Head movements during functional MRI (fMRI) scanning of 266 healthy adults (20-89 years) were analyzed to reveal stable features of in-scanner head motion. The magnitude of head motion increased with age and exhibited within-participant stability across different fMRI scans. fMRI head motion was then related to measurements of both quality control (QC) and brain anatomy derived from a T1w structural image from the same scan session. A procedure was adopted to "flag" individuals exhibiting excessive head movement during fMRI or poor T1w quality rating. The flagging procedure reliably reduced the influence of head motion on estimates of gray matter thickness across the cortical surface. Moreover, T1w images from flagged participants exhibited reduced estimates of gray matter thickness and volume in comparison to age- and gender-matched samples, resulting in inflated effect sizes in the relationships between regional anatomical measures and age. Gray matter thickness differences were noted in numerous regions previously reported to undergo prominent atrophy with age. Recommendations are provided for mitigating this potential confound, and highlight how the procedure may lead to more accurate measurement and comparison of anatomical features. Hum Brain Mapp 38:472-492, 2017. © 2016 Wiley Periodicals, Inc.

Social-Class Differences in Consumer Choices: Working-Class Individuals Are More Sensitive to Choices of Others Than Middle-Class Individuals.

The present research shows that, when making choices, working-class Americans are more affected by others' opinions than middle-class Americans due to differences in independent versus interdependent self-construal. Experiment 1 revealed that when working-class Americans made decisions to buy products, they were more influenced by the choices of others than middle-class Americans. In contrast, middle-class Americans were more likely to misremember others' choices to be consistent with their own choices. In other words, working-class Americans adjusted their choices to the preference of others, whereas middle-class Americans distorted others' preferences to fit their choices. Supporting our prediction that this social-class effect is closely linked to the independent versus interdependent self-construal, we showed that the differences in self-construal across cultures qualified the social-class effects on choices (Experiment 2). Moreover, when we experimentally manipulated self-construal in Experiment 3, we found that it mediated the corresponding changes in choices regardless of social class.

Training Older Adults to Use Tablet Computers: Does It Enhance Cognitive Function?

PURPOSE OF THE STUDY: Recent evidence shows that engaging in learning new skills improves episodic memory in older adults. In this study, older adults who were computer novices were trained to use a tablet computer and associated software applications. We hypothesize that sustained engagement in this mentally challenging training would yield a dual benefit of improved cognition and enhancement of everyday function by introducing useful skills. DESIGN AND METHODS: A total of 54 older adults (age 60-90) committed 15 hr/week for 3 months. Eighteen participants received extensive iPad training, learning a broad range of practical applications. The iPad group was compared with 2 separate controls: a Placebo group that engaged in passive tasks requiring little new learning; and a Social group that had regular social interaction, but no active skill acquisition. All participants completed the same cognitive battery pre- and post-engagement. RESULTS: Compared with both controls, the iPad group showed greater improvements in episodic memory and processing speed but did not differ in mental control or visuospatial processing. IMPLICATIONS: iPad training improved cognition relative to engaging in social or nonchallenging activities. Mastering relevant technological devices have the added advantage of providing older adults with technological skills useful in facilitating everyday activities (e.g., banking). This work informs the selection of targeted activities for future interventions and community programs.

Decreased segregation of brain systems across the healthy adult lifespan.

Healthy aging has been associated with decreased specialization in brain function. This characterization has focused largely on describing age-accompanied differences in specialization at the level of neurons and brain areas. We expand this work to describe systems-level differences in specialization in a healthy adult lifespan sample (n = 210; 20-89 y). A graph-theoretic framework is used to guide analysis of functional MRI resting-state data and describe systems-level differences in connectivity of individual brain networks. Young adults' brain systems exhibit a balance of within- and between-system correlations that is characteristic of segregated and specialized organization. Increasing age is accompanied by decreasing segregation of brain systems. Compared with systems involved in the processing of sensory input and motor output, systems mediating "associative" operations exhibit a distinct pattern of reductions in segregation across the adult lifespan. Of particular importance, the magnitude of association system segregation is predictive of long-term memory function, independent of an individual's age.