Decision making in the ageing brain: changes in affective and motivational circuits - PubMed (original) (raw)

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Decision making in the ageing brain: changes in affective and motivational circuits

Gregory R Samanez-Larkin et al. Nat Rev Neurosci. 2015 May.

Abstract

As the global population ages, older decision makers will be required to take greater responsibility for their own physical, psychological and financial well-being. With this in mind, researchers have begun to examine the effects of ageing on decision making and associated neural circuits. A new 'affect-integration-motivation' (AIM) framework may help to clarify how affective and motivational circuits support decision making. Recent research has shed light on whether and how ageing influences these circuits, providing an interdisciplinary account of how ageing can alter decision making.

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Figure 1

Figure 1. Critical components of the Affect-Integration-Motivation (AIM) framework

The AIM framework implies that three hierarchical and sequential processes can occur prior to and promote choice. a| Affect, in which ventral tegmental area (VTA) dopamine neurons project to the ventral striatum (VS, including the NAcc), locus coeruleus (LC) norepinephrine neurons project to the AI (AI), and AI glutamatergic neurons (blue) project to the VS, potentiating anticipation of gain and loss. b| Integration, in which VTA dopamine neurons and LC norepinephrine neurons modulate medial prefrontal cortex (MPFC) activity, VS indirectly projects to the MPFC via GABA connections in the pallidum (not depicted) and glutamate projections from the thalamus, AI projects to the MPFC, and MPFC glutamatergic neurons directly project back to the VS, facilitating integration of value and modulatory signals (for instance, from the medial temporal and lateral frontal cortical regions). c| Motivation, in which dorsal striatal and insular glutamatergic neurons project to the pre-supplementary motor area (pSMA), potentiating motor action. Healthy ageing is predicted to degrade glutamatergic projections from the prefrontal cortex to the striatum, thus diminishing value integration (b), and compromising choice optimality.

Figure 2

Figure 2. Age-related differences in incentive anticipation and risky decision making

a| In an incentive anticipation task in which subjects saw cues signalling the potential gain or loss of varying amounts of money, gain anticipation increased nucleus accumbens (NAcc) activity in both younger (ages 19–27) and older (ages 65–81) adults (left panels). Loss anticipation, however, increased AI activity in younger, but not older, adults (right panels). Shaded error bars indicate standard error of the group mean. Y-axis represents percentage FMRI activity change in the ventral striatum (VS, including the NAcc).b| In a financially risky choice task, older adults make more mistakes than younger adults when seeking risk (selection of stocks) but not when avoiding risk (selection of bonds) (left panel). Age-related differences in behaviour (ages 19–85) were associated with age-related increased variability in striatal activity, including the NAcc (right panel; coloured areas overlaid on the brain are voxels for which a statistical test of the linear effect of age exceeded p <.0001, uncorrected). This increased variability mediated the association between increased age and risky stock (RS) mistakes. Figures in part a adapted from . Figures in part b adapted from .

Figure 3

Figure 3. Age-related differences in temporal decision making and value learning

a| Younger adults show reduced NAcc activity for rewards available at longer (grey line) versus shorter (orange line) time delays, but older adults show comparable activity for both short and long delays. Shaded error bars indicate standard error of group means. Y-axis represents percentage FMRI activity change in the ventral striatum (VS, including the NAcc). b| Structural coherence along a frontostriatal axonal tract extending from the dorsomedial nucleus of the thalamus (Thal) to the medial prefrontal cortex (MPFC; light blue) and from the MPFC to the ventral striatum (dark blue) was reduced in older age but associated with better learning. White matter coherence was indexed by measuring fractional anisotropy. Individual differences in learning were calculated as the percentage of choices of the higher expected value option. Left panels in part a adapted from . Right panels in part a adapted from . Figure in part b adapted from .

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