Reward-based decision-making and aging

Marschner, Alexander; Mell, Thomas; Wartenburger, Isabell; Villringer, Arno; Reischies, Friedel M.; Heekeren, Hauke R.

doi:10.1016/j.brainresbull.2005.06.010

Cited by 110 publications

(88 citation statements)

References 89 publications

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“…2 A). This result is in accordance with a recent report of decreased striatal activity in older subjects during reward association learning (22), although another study (23) failed to detect age-related differences in striatal activity during reward anticipation, and did not report results at the time of rewarded outcome. The discrepancy in the results between studies may be explained by differences in experimental paradigms.…”

Section: Discussionsupporting

confidence: 81%

“…The discrepancy in the results between studies may be explained by differences in experimental paradigms. Specifically, one study used a probabilistic object reversal task including learning and search components (22), whereas the other study explored neural activity during a canonical monetary incentive delay task combining gains and losses (23). In addition to brain regions showing age-related differences during reward anticipation, we found a single brain area, the intraparietal region ( Fig.…”

Section: Discussionmentioning

confidence: 93%

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Age-related changes in midbrain dopaminergic regulation of the human reward system

Dreher

Meyer‐Lindenberg

Kohn

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

207

153

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The dopamine system, which plays a crucial role in reward processing, is particularly vulnerable to aging. Significant losses over a normal lifespan have been reported for dopamine receptors and transporters, but very little is known about the neurofunctional consequences of this age-related dopaminergic decline. In animals, a substantial body of data indicates that dopamine activity in the midbrain is tightly associated with reward processing. In humans, although indirect evidence from pharmacological and clinical studies also supports such an association, there has been no direct demonstration of a link between midbrain dopamine and rewardrelated neural response. Moreover, there are no in vivo data for alterations in this relationship in older humans. Here, by using 6-[ 18 F]FluoroDOPA (FDOPA) positron emission tomography (PET) and event-related 3T functional magnetic resonance imaging (fMRI) in the same subjects, we directly demonstrate a link between midbrain dopamine synthesis and reward-related prefrontal activity in humans, show that healthy aging induces functional alterations in the reward system, and identify an age-related change in the direction of the relationship (from a positive to a negative correlation) between midbrain dopamine synthesis and prefrontal activity. These results indicate an age-dependent dopaminergic tuning mechanism for cortical reward processing and provide system-level information about alteration of a key neural circuit in healthy aging. Taken together, our findings provide an important characterization of the interactions between midbrain dopamine function and the reward system in healthy young humans and older subjects, and identify the changes in this regulatory circuit that accompany aging.aging ͉ dopamine ͉ fMRI ͉ PET ͉ reinforcement S uccessful aging has become one of the most crucial public health challenges of our time. Achieving an understanding of age-related changes in the neurobiology of key brain circuits, such as the reward system, is an integral part of rising to this challenge. Detecting, predicting, and responding to reward information are fundamental capabilities of simple life forms that have evolved in humans into complex behavioral patterns, such as learning, motivation, and appetitive and hedonic activities, which remain essential as we age. A substantial body of data in animals indicates that dopamine is closely associated with reward processing (1-3), and that midbrain dopamine neurons send reward-related signals to postsynaptic sites, particularly the prefrontal cortex. In humans, although indirect evidence from pharmacological (4, 5) and clinical (6-8) studies also suggests a fundamental role of dopamine in reward processing, there has been no direct demonstration of a link between midbrain dopamine and reward-related neural response. Moreover, although the dopamine system is known to be particularly vulnerable to aging (9, 10), there has been no search for alterations in this predicted relationship in older humans. Here, by using 6-[ 18 F]fluoroDOPA ...

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Section: Discussionsupporting

confidence: 81%

Section: Discussionmentioning

confidence: 93%

Age-related changes in midbrain dopaminergic regulation of the human reward system

Dreher

Meyer‐Lindenberg

Kohn

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

207

153

View full text Add to dashboard Cite

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“…Eppinger et al, 2008Eppinger et al, , 2009Marschner et al, 2005;Mell et al, 2005). This age difference in learning increased with decreasing differences in reward likelihood between the two choices.…”

Section: Age Differences In Reinforcement Learning and Its Relation Tmentioning

confidence: 90%

“…On the basis of previous findings, we expected that children and older adults would need more trials than adolescents and younger adults to identify the better choice option (cf. Eppinger et al, 2008Eppinger et al, , 2009Marschner et al, 2005;Mell et al, 2005). Figure 1A shows age differences in the probabilistic reinforcement learning task.…”

Section: Behavioral Datamentioning

confidence: 99%

“…These studies showed that children and older adults experience more difficulties in learning from probabilistic performance feedback than younger adults and adolescents (cf. Eppinger, Mock, & Kray, 2009;Eppinger, Kray, Mock, & Mecklinger, 2008;Marschner et al, 2005;Mell et al, 2005;Crone, Jennings, & van der Molen, 2004). However, compared with other cognitive mechanisms and functions such as executive control, working memory, or episodic memory, the monitoring of outcomes for the shaping of behavior has rarely been investigated systematically across different age groups that cover development from childhood to old age.…”

Section: Introductionmentioning

confidence: 99%

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Life Span Differences in Electrophysiological Correlates of Monitoring Gains and Losses during Probabilistic Reinforcement Learning

Hämmerer¹,

Li²,

Müller³

et al. 2011

Journal of Cognitive Neuroscience

164

208

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Abstract■ By recording the feedback-related negativity (FRN) in response to gains and losses, we investigated the contribution of outcome monitoring mechanisms to age-associated differences in probabilistic reinforcement learning. Specifically, we assessed the difference of the monitoring reactions to gains and losses to investigate the monitoring of outcomes according to task-specific goals across the life span. The FRN and the behavioral indicators of learning were measured in a sample of 44 children, 45 adolescents, 46 younger adults, and 44 older adults. The amplitude of the FRN after gains and losses was found to decrease monotonically from childhood to old age. Furthermore, relative to adolescents and younger adults, both children and older adults (a) showed smaller differences between the FRN after losses and the FRN after gains, indicating a less differentiated classification of outcomes on the basis of task-specific goals; (b) needed more trials to learn from choice outcomes, particularly when differences in reward likelihood between the choices were small; and (c) learned less from gains than from losses. We suggest that the relatively greater loss sensitivity among children and older adults may reflect ontogenetic changes in dopaminergic neuromodulation. ■

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Association of Epigenetic Metrics of Biological Age With Cortical Thickness

et al. 2020

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Key Points Question Are DNA methylation–based metrics of biological age associated with cortical thickness, and does a biological age acceleration index capture unique changes in cortical thinning compared with chronological age measures? Findings In this cross-sectional study of 82 healthy adults, both biological and chronological age were associated with widespread cortical thinning, but biological age acceleration was also associated with additional changes in cortical morphological features. Older biological age relative to chronological age was associated with accentuated thinning within prefrontal and temporal regions. Meaning These findings suggest that DNA methylation–based biological age may yield additional insight into healthy and pathological cortical aging compared with chronological age alone.

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Reward-based decision-making and aging

Cited by 110 publications

References 89 publications

Age-related changes in midbrain dopaminergic regulation of the human reward system

Age-related changes in midbrain dopaminergic regulation of the human reward system

Life Span Differences in Electrophysiological Correlates of Monitoring Gains and Losses during Probabilistic Reinforcement Learning

Association of Epigenetic Metrics of Biological Age With Cortical Thickness

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