Browsing by Author "Elliott, Maxwell L"
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Item Open Access Functional connectivity predicts the dispositional use of expressive suppression but not cognitive reappraisal.(Brain and behavior, 2020-02) Burr, Daisy A; d'Arbeloff, Tracy; Elliott, Maxwell L; Knodt, Annchen R; Brigidi, Bartholomew D; Hariri, Ahmad RINTRODUCTION:Previous research has identified specific brain regions associated with regulating emotion using common strategies such as expressive suppression and cognitive reappraisal. However, most research focuses on a priori regions and directs participants how to regulate, which may not reflect how people naturally regulate outside the laboratory. METHOD:Here, we used a data-driven approach to investigate how individual differences in distributed intrinsic functional brain connectivity predict emotion regulation tendency outside the laboratory. Specifically, we used connectome-based predictive modeling to extract functional connections in the brain significantly related to the dispositional use of suppression and reappraisal. These edges were then used in a predictive model and cross-validated in novel participants to identify a neural signature that reflects individual differences in the tendency to suppress and reappraise emotion. RESULTS:We found a significant neural signature for the dispositional use of suppression, but not reappraisal. Within this whole-brain signature, the intrinsic connectivity of the default mode network was most informative of suppression tendency. In addition, the predictive performance of this model was significant in males, but not females. CONCLUSION:These findings help inform how whole-brain networks of functional connectivity characterize how people tend to regulate emotion outside the laboratory.Item Open Access General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks.(NeuroImage, 2019-04) Elliott, Maxwell L; Knodt, Annchen R; Cooke, Megan; Kim, M Justin; Melzer, Tracy R; Keenan, Ross; Ireland, David; Ramrakha, Sandhya; Poulton, Richie; Caspi, Avshalom; Moffitt, Terrie E; Hariri, Ahmad RIntrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.Item Open Access Midlife as a window onto the aging brain: surrogate biomarkers, exposures, and biological aging(2022) Elliott, Maxwell LThe global population is aging with projections that the number of people over 60 will more than triple by 2050. While many organ systems are impacted by aging, deterioration of the brain is a particularly debilitating form of age-related disease. Alzheimer's disease and related dementias (ADRD) represent neurodegeneration that results in a loss of the ability to perform everyday tasks, maintain independence, and care for oneself. To date, ADRD interventions targeting older adults have largely proven to be ineffective at limiting morbidity and disability, suggesting that interventions may be failing to slow age-related disease because they are implemented too late in the aging process after decline has taken hold. However, to target ADRD interventions to younger adults we will need surrogate biomarkers that track sub-clinical signs of accelerated brain-aging that has yet to be fully cemented. This dissertation consists of 4 original studies that aim to measure and begin to validate magnetic resonance imaging (MRI)-based surrogate biomarkers for accelerated brain-aging in midlife adults. Each of these studies utilizes the Dunedin Study, a population-representative birth cohort of 1,037 adults, who have been followed longitudinally from birth to the most recent wave of data collection, completed when Study members were 45 years old. In Chapter 1, I found that individual differences in WMH volume, an established marker of dementia risk, cognitive decline, and dementia in older adults, were associated with cognitive decline from childhood to age-45. In Chapter 2, I found that individual differences in brainAGE were also associated with cognitive decline from childhood to age-45. In Chapter 3, I found that a known neurotoxicant, lead, was associated with cognitive decline from childhood to age 45, as well as with several MRI measures at age 45 including hippocampal volume, surface area, fractional anisotropy, and brainAGE. In chapter 4, I found that an accelerated Pace of Aging was associated with a thinner cortex, smaller surface area, lower hippocampal volume, higher WMH volume, and older brainAGE. Together, by triangulating evidence from cognitive aging, neurotoxic exposure, and biological aging, these studies help motivate the critical need for researchers to embrace midlife brain aging as a tool for better understanding the aging brain and dementia risk. I conclude with a discussion of the limitations of this research and opportunities for future research to target midlife brain aging itself as a target for clinical translation.
Item Open Access What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis.(Psychological science, 2020-07) Elliott, Maxwell L; Knodt, Annchen R; Ireland, David; Morris, Meriwether L; Poulton, Richie; Ramrakha, Sandhya; Sison, Maria L; Moffitt, Terrie E; Caspi, Avshalom; Hariri, Ahmad RIdentifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful biomarkers is limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring brain activity using task functional MRI (fMRI) is a major focus of biomarker development; however, the reliability of task fMRI has not been systematically evaluated. We present converging evidence demonstrating poor reliability of task-fMRI measures. First, a meta-analysis of 90 experiments (N = 1,008) revealed poor overall reliability-mean intraclass correlation coefficient (ICC) = .397. Second, the test-retest reliabilities of activity in a priori regions of interest across 11 common fMRI tasks collected by the Human Connectome Project (N = 45) and the Dunedin Study (N = 20) were poor (ICCs = .067-.485). Collectively, these findings demonstrate that common task-fMRI measures are not currently suitable for brain biomarker discovery or for individual-differences research. We review how this state of affairs came to be and highlight avenues for improving task-fMRI reliability.