Decomposing risky decision-making in methamphetamine use disorder: Behavioral updating and D2 dopamine receptors.

BACKGROUND: Escalating misuse of amphetamine-type stimulants, mainly methamphetamine, has led to a staggering rise in associated overdose deaths and a pressing need to understand the basis of methamphetamine use disorder (MUD). MUD is characterized by disadvantageous decision-making, and people with MUD perform below controls on the Balloon Analogue Risk Task (BART), a laboratory test of decision-making under uncertainty. The BART presents a series of choices with progressively higher stakes-greater risk of loss and greater potential monetary reward. This research aimed to clarify whether impaired behavioral updating contributes to maladaptive performance on the BART. METHODS: Two groups (28 drug-abstinent participants with MUD and 16 healthy control participants) were compared on BART performance. Using a computational model, we deconstructed behavior into risk-taking and behavioral updating. A subset of participants (22 MUD, 15 healthy control) underwent [18F]fallypride positron emission tomography scans to measure dopamine D2-type receptor availability (BPND) in the striatum (caudate and accumbens nuclei and putamen) and the globus pallidus. RESULTS: Participants with MUD exhibited slower behavioral updating than the healthy controls (p = 0.0004, d=1.77). BPND in all four bilateral volumes of interest were higher in the healthy control group (ps < 0.005, ds < 2.16), and updating rate correlated positively with BPND in the caudate nucleus (p = 0.002), putamen (p = 0.002), and globus pallidus (p = 0.03). CONCLUSIONS: The findings indicate that behavioral updating contributes to maladaptive decision-making in MUD and suggest that dysregulation of D2-type receptor signaling in the striatum and globus pallidus contributes to this behavioral deficit.

Age Influences Loss Aversion Through Effects on Posterior Cingulate Cortical Thickness.

Decision-making strategies shift during normal aging and can profoundly affect wellbeing. Although overweighing losses compared to gains, termed "loss aversion," plays an important role in choice selection, the age trajectory of this effect and how it may be influenced by associated changes in brain structure remain unclear. We therefore investigated the relationship between age and loss aversion, and tested for its mediation by cortical thinning in brain regions that are susceptible to age-related declines and are implicated in loss aversion - the insular, orbitofrontal, and anterior and posterior cingulate cortices. Healthy participants (n = 106, 17-54 years) performed the Loss Aversion Task. A subgroup (n = 78) provided structural magnetic resonance imaging scans. Loss aversion followed a curvilinear trajectory, declining in young adulthood and increasing in middle-age, and thinning of the posterior cingulate cortex mediated this trajectory. The findings suggest that beyond a threshold in middle adulthood, atrophy of the posterior cingulate cortex influences loss aversion.

A neural network that links brain function, white-matter structure and risky behavior.

The ability to evaluate the balance between risk and reward and to adjust behavior accordingly is fundamental to adaptive decision-making. Although brain-imaging studies consistently have shown involvement of the dorsolateral prefrontal cortex, anterior insula and striatum during risky decision-making, activation in a neural network formed by these regions has not been linked to structural connectivity. Therefore, in this study, white-matter connectivity was measured with diffusion-weighted imaging in 40 healthy research participants who performed the Balloon Analogue Risk Task, a test of risky decision-making, during fMRI. Fractional anisotropy within a network that includes white-matter pathways connecting four regions (the prefrontal cortex, insula and midbrain to the striatum) was positively correlated with the number of risky choices and total amount earned on the task, and with the parametric modulation of activation in regions within the network to the level of risk during choice selection. Furthermore, analysis using a mixed model demonstrated how relationships of the parametric modulation of activation in each of the four aforementioned regions are related to risk probabilities, and how previous trial outcomes and task progression influence the choice to take risk. The present findings provide the first direct evidence that white-matter integrity is linked to function within previously identified components of a network that is activated during risky decision-making, and demonstrate that the integrity of white-matter tracts is critical in consolidating and processing signals between cortical and striatal circuits during the decision-making process.