White matter correlates of temporal discounting in older adults

Now or Later? Examining Social and Financial Decision Making in Middle-to-Older Aged Adults

OBJECTIVES

Contextually driven decision making is multidimensional, as individuals need to contend with prioritizing both competing and complementary demands. However, data is limited as to whether temporal discounting rates vary as a function of framing (gains vs loss) and domain (monetary vs social) in middle-to-older aged adults. It is also unclear whether socioaffective characteristics like social isolation and loneliness are associated with temporal discounting.

METHODS

Temporal discounting rates were examined across monetary gain, monetary loss, social gain, and social loss conditions in 140 adults aged 50-90 during the Omicron stage of the pandemic. Self-report measures assessed loneliness and social isolation levels.

RESULTS

Results found evidence of steeper temporal discounting rates for gains as compared to losses in both domains. Social outcomes were also more steeply discounted than monetary outcomes, without evidence of an interaction with the framing condition. Socioeconomic and socioaffective factors were unexpectedly not associated with temporal discounting rates.

DISCUSSION

Community-dwelling middle-to-older aged adults showed a preference for immediate rewards and devalued social outcomes more than monetary outcomes. These findings have implications for tailoring social and financial incentive programs for middle to later adulthood.

Change in Decision-Making Analysis and Preferences in Old Age

OBJECTIVES

To test the hypotheses that decision making ability declines in old age and that a higher level of cognitive reserve is associated with a reduced rate of decline.

METHODS

As part of an ongoing cohort study, 982 older adults without dementia at study enrollment completed measures of purpose in life and cognitive activity which were used as markers of cognitive reserve. At annual intervals thereafter, they completed 6 tests of decision making.

RESULTS

In a factor analysis of baseline decision making scores, 3 measures (financial/health literacy, financial/health decision making, scam susceptibility) loaded on an "analytic" factor and 3 (temporal discounting small stakes, temporal discounting large stakes, risk aversion) loaded on a "preferences" (for temporal discounting and avoiding risk) factor. During a mean of 4.7 years of follow-up (standard deviation = 2.9), analytic factor scores decreased (mean = 0.042-unit per year, standard error [SE] = 0.006, p < .001) and preferences factor scores increased (mean = 0.021-unit per year, SE = 0.006, p < .001), with a correlation of 0.13 (p < .001) between rates of change. Evidence of an association between cognitive reserve and decision making was mixed with purpose in life related to change in analytic decision making, whereas past (but not current) cognitive activity was related to change in decision making preferences.

DISCUSSION

Decision making analysis and preferences change over time in late life. Change over time in decision making components is relatively independent and differentially related to age and cognitive reserve.

Decision Making and Blood Sugar Indicators in Older African American Adults

Objectives: Decision making is a modifiable behavior associated with health outcomes. We investigated the association of decision making with blood sugar indicators in older community-dwelling African American adults. Methods: Participants were 328 older African American adults from community-based studies (mean age = 78). Decision making was assessed using a performance-based measure (range: 0-12). Blood sugar indicators were non-fasting hemoglobin A1c and blood glucose. Using regression, we assessed the relationship between decision making and each blood sugar indicator, controlling for demographics. We additionally examined if an association varied by known diabetes diagnosis. Results: Lower decision making was associated with higher HbA1c (b: -0.05, p-value: .03), but not blood glucose. In an interaction analysis, the association of lower decision making with higher levels of HbA1c was present only among individuals with known diabetes (b (with diabetes): -0.13, p-value: <.01). Discussion: Decision making may contribute to glycemic control in African American older adults with diabetes.

Investigating associations of delay discounting with brain structure, working memory, and episodic memory

INTRODUCTION

Delay discounting (DD), the preference for smaller and sooner rewards over larger and later ones, is an important behavioural phenomenon for daily functioning of increasing interest within psychopathology. The neurobiological mechanisms behind DD are not well understood and the literature on structural correlates of DD shows inconsistencies.

METHODS

Here we leveraged a large openly available dataset (n = 1196) to investigate associations with memory performance and gray and white matter correlates of DD using linked independent component analysis.

RESULTS

Greater DD was related to smaller anterior temporal gray matter volume. Associations of DD with total cortical volume, subcortical volumes, markers of white matter microscopic organization, working memory, and episodic memory scores were not significant after controlling for education and income.

CONCLUSION

Effects of size comparable to the one we identified would be unlikely to be replicated with sample sizes common in many previous studies in this domain, which may explain the incongruities in the literature. The paucity and small size of the effects detected in our data underscore the importance of using large samples together with methods that accommodate their statistical structure and appropriate control for confounders, as well as the need to devise paradigms with improved task parameter reliability in studies relating brain structure and cognitive abilities with DD.

Achieving and sustaining behavior change for older adults: A Research Centers Collaborative Network workshop report

Modifying unhealthy behaviors and/or environments may improve or maintain an older adult's health. However, achieving and sustaining behavior change is challenging and depends upon clinical, social, psychological, and political domains. In an effort to highlight the multidisciplinary nature of behavior change, the NIA Research Centers Collaborative Network (RCCN) held a two-day workshop, Achieving and sustaining behavior change for older adults. The workshop was informed by the socioecological model and designed to initiate dialogue around individual, community, and systems-level determinants of behavior change. This paper summarizes key topics presented during the workshop, discusses opportunities for future research, education, and training, and recommends how each of the six NIA research centers may pursue work in behavior change for older adults.

Financial decision-making and self-awareness for financial decision-making is associated with white matter integrity in older adults

Financial decision-making (FDM) and awareness of the integrity of one's FDM abilities (or financial awareness) are both critical for preventing financial mistakes. We examined the white matter correlates of these constructs and hypothesized that the tracts connecting the temporal-frontal regions would be most strongly correlated with both FDM and financial awareness. Overall, 49 healthy older adults were included in the FDM analysis and 44 in the financial awareness analyses. The Objective Financial Competency Assessment Inventory was used to measure FDM. Financial awareness was measured by integrating metacognitive ratings into this inventory and was calculated as the degree of overconfidence or underconfidence. Diffusion tensor imaging data were processed with Tracts Constrained by Underlying Anatomy distributed as part of the FreeSurfer analytic suite, which produced average measures of fractional anisotropy and mean diffusivity in 18 white matter tracts along with the overall tract average. As expected, FDM showed the strongest negative associations with average mean diffusivity measure of the superior longitudinal fasciculus -temporal (SLFT; r = -.360, p = .011) and -parietal (r = -.351, p = .014) tracts. After adjusting for FDM, only the association between financial awareness and average mean diffusivity measure of the right SLFT (r = .310, p = .046) was significant. Overlapping white matter tracts were involved in both FDM and financial awareness. More importantly, these preliminary findings reinforce emerging literature on a unique role of right hemisphere temporal connections in supporting financial awareness.

Neural markers of procrastination in white matter microstructures and networks

More than 15% of adults suffer from pathological procrastination, which leads to substantial harm to their mental and psychiatric health. Our previous work demonstrated the role of three neuroanatomical networks as neural substrates of procrastination, but their potential interaction remains unknown. Three large-scale independent samples (total n = 901) were recruited. In sample A, tract-based spatial statistics (TBSS) and connectome-based graph-theoretical analysis was conducted to probe association between topological properties of white matter (WM) network and procrastination. In sample B, the above analysis was reproduced to demonstrate replicability. In sample C, machine learning models were built to predict individual procrastination. TBSS results showed a negative association between procrastination and WM integrity of limbic-prefrontal connection, and a positive relationship between intra-connection within the limbic system and procrastination. Also, both the efficiency and integrity of limbic WM network were found to be linked to procrastination. The above findings were all confirmed to replicate in an independent sample; prediction models demonstrated that these WM features can predict procrastination accurately in sample C. In conclusion, this study moves forward our understanding of procrastination by clarifying the role of interplay of self-control and emotional regulation with it.

Regionconnect: Rapidly extracting standardized brain connectivity information in voxel-wise neuroimaging studies

Reporting white matter findings in voxel-wise neuroimaging studies typically lacks specificity in terms of brain connectivity. Therefore, the purpose of this work was to develop an approach for rapidly extracting standardized brain connectivity information for white matter regions with significant findings in voxel-wise neuroimaging studies. The new approach was named regionconnect and is based on precalculated average healthy adult brain connectivity information stored in standard space in a fashion that allows fast retrieval and integration. Towards this goal, the present work first generated and evaluated the white matter connectome of the IIT Human Brain Atlas v.5.0. It was demonstrated that the edges of the atlas connectome are representative of those of individual participants of the Human Connectome Project in terms of the spatial organization of streamlines and spatial patterns of track-density. Next, the new white matter connectome was used to develop multi-layer, connectivity-based labels for each white matter voxel of the atlas, consistent with the fact that each voxel may contain axons from multiple connections. The regionconnect algorithm was then developed to rapidly integrate information contained in the multi-layer labels across voxels of a white matter region and to generate a list of the most probable connections traversing that region. Usage of regionconnect does not require high angular resolution diffusion MRI or any MRI data. The regionconnect algorithm as well as the white matter tractogram and connectome, multi-layer, connectivity-based labels, and associated resources developed for the IIT Human Brain Atlas v.5.0 in this work are available at www.nitrc.org/projects/iit. An interactive, online version of regionconnect is also available at www.iit.edu/~mri.

Examining delay of gratification in healthy aging

Delay of gratification (DofG) refers to the capacity to forego an immediate reward in order to receive a more desirable reward later. As a core executive function, it might be expected that DofG would follow the standard pattern of age-related decline observed in older adults for other executive tasks. However, there actually have been few studies of aging and DofG, and even these have shown mixed results, suggesting the need for further investigation and new approaches. The present study tested a novel reward-based decision-making paradigm enabling examination of age-related DofG effects in adult humans. Results showed that older adults earned fewer overall rewards than young adults, both before and after instruction regarding the optimal DofG strategy. Prior to instruction, learning this strategy was challenging for all participants, regardless of age. The finding of age-related impairments even after strategy instruction indicated that these impairments were not due to a failure to understand the task or follow the optimal strategy, but instead were related to self-reported difficulty in waiting for delayed rewards. These results suggest the presence of age-related changes in DofG capacity and highlight the advantages of this new experimental paradigm for use in future investigations, including both behavioral and neuroimaging studies.

Brain functional connectome-based prediction of individual decision impulsivity

Extensive neuroimaging research has attempted to identify neural correlates and predictors of decision impulsivity. However, the nature and extent of decision impulsivity-brain association have varied substantially across studies, likely due to small sample sizes, limited image quality, different imaging measurement selections, and non-specific methodologies. The objective of this study was to develop a reliable predictive model of decision impulsivity-brain relationship in a large sample by applying connectome-based predictive modeling (CPM), a recently developed machine learning approach, to whole-brain functional connectivity data ("neural fingerprints"). For 809 healthy young participants from the Human Connectome Project, high-quality resting-state functional MRI data were utilized to construct brain functional connectome and delay discounting test was used to assess decision impulsivity. Then, CPM with leave-one-out cross-validation was conducted to predict individual decision impulsivity from whole-brain functional connectivity. We found that CPM successfully and reliably predicted the delay discounting scores in novel individuals. Moreover, different feature selection thresholds, parcellation strategies and cross-validation approaches did not significantly influence the prediction results. At the neural level, we observed that the decision impulsivity-associated functional networks included brain regions within default-mode, subcortical, somato-motor, dorsal attention, and visual systems, suggesting that decision impulsivity emerges from highly integrated connections involving multiple intrinsic networks. Our findings not only may expand existing knowledge regarding the neural mechanism of decision impulsivity, but also may present a workable route towards translation of brain imaging findings into real-world economic decision-making.