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

Abstract

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.

Associations between nucleus accumbens structural connectivity, brain function, and initiation of binge drinking

“…Considering these effects may be partially attributed to premorbid differences, we anticipated that lower FA in 14 to 15 year olds would be associated with earlier onset of binge drinking. NAcc function during decision making has been linked to duration to onset of binge drinking in adolescents and to FA in adults; therefore, we hypothesized that FA would have an indirect effect on duration to onset binge drinking mediated by NAcc activation during decision making involving risk and reward.…”

A Joint Modelling Approach to Analyze Risky Decisions by Means of Diffusion Tensor Imaging and Behavioural Data

“…Such results might posit some constraints on the quantification of the actual role of risk propensity in enacting an optimal decision strategy. Participants were indeed required to adopt a balanced risky-oriented strategy in order to maximise earnings, and taking more risk at different stages of the task could be seen as an adaptive strategy which increases the chance to produce more positive outcome [32,56]. From this perspective, however, risk-taking propensity might not be the main component to fulfil the task of optimizing earnings.…”

“…FA is the most commonly used index for estimation of anisotropy using DTI, and reflects fiber tracts characteristics such as the extent of alignment of cellular structures within the fibers and their structural integrity [28,29]. Therefore, such a measure also proved to be a promising index to study the relation between brain structural integrity and both response variability and risky behaviour in both clinical and normal population [19,[30][31][32].…”

“…In this work, we were interested in relating cognitive functioning with connectivity measures of networks of regions of interest (ROIs). This choice was motivated by substantial evidences on the potential of functional-structural properties of distributed neural networks to account for complex decision processes [32][33][34]. Thus, the main purpose of our neurocognitive modelling approach consisted of linking connectivity-related information of network structures with the latent mechanisms captured by the computational cognitive model.…”

“…The entries f ij specify the fractional anisotropy of the custom tract connecting ROIs i and j. We refer to Network FA [32] to represent structural connectivity in a given network. Thus, network FA consists of the collection of f…”