Functional and Structural Signatures of the Anterior Insula are associated with Risk-taking Tendency of Analgesic Decision-making

Abstract

In a medical context, decision-making is associated with complicated assessment of gains, losses and uncertainty of outcomes. We here provide novel evidence about the brain mechanisms underlying decision-making of analgesic treatment. Thirty-six healthy participants were recruited and completed the Analgesic Decision-making Task (ADT), which quantified individual tendency of risk-taking (RPI), as the frequency of choosing a riskier option to relieve pain. All the participants received resting-state (rs) functional magnetic resonance imaging (MRI) and structural MRI. On rs-functional connectome, degree centrality (DC) of the bilateral anterior insula (aINS) was positively correlated with the RPI. The functional connectivity between the aINS, the nucleus accumbens and multiple brain regions, predominantly the medial frontal cortex, was positively correlated with the RPI. On structural signatures, the RPI was positively correlated with grey matter volume at the right aINS, and such an association was mediated by DC of the left aINS. Regression analyses revealed that both DC of the left aINS and participants' imagined pain relief, as the utility of pain reduction, could predict the individual RPI. The findings suggest that the functional and structural brain signature of the aINS is associated with the individual differences of risk-taking tendency in the context of analgesic decision-making.

Figure 1. The Analgesic Decision-making Task (ADT).

In the Analgesic Effect sub-task, the participant needs to choose between the two treatment options, which are opposite in pain-relieving potency and the probability that the treatment would successfully work. In the Adverse Effect sub-task, the participant needs to choose between the options that are opposite in pain-relieving potency and the probability to have an adverse effect. In the Time-course Effect sub-task, the participant needs to choose between the options that are opposite in pain-relieving potency and the time for the treatment to reach its maximal effect (Panel A). The difference in pain experience across the three categories of clinical pain was statistically insignificant (Friedman test, χ²₍₂₎ = 0.55, P = 0.76) (Panel B). The difference in imagined pain relief across the three figurative conditions was statistically significant (Friedman test, χ²₍₂₎ = 71.51, P < 0.001). The subsequent pairwise comparison showed that the imagined pain relief in Δ9 → 0 was significantly higher than those in Δ9 → 3 (P < 0.01), and the imagined pain relief in Δ9 → 3 was significantly higher than those in Δ9 → 6 (P < 0.01) (Panel C). The difference in RPI across the three sub-tasks of the ADT was statistically insignificant (Friedman test, χ²₍₂₎ = 4.46, P = 0.11) (Panel D). In Panel B–D, the bar denotes the median and the horizontal lines denote the first and the third quartiles. The correlation was statistically significant between imagined pain relief Δ9 → 6 and the RPI calculated from all task scenarios (RPI_TOTAL) (Panel E), RPI_ANE (Panel F) and RPI_TE (Panel G).

Figure 2. The risk-related network derived from an imaging meta-analysis implemented using Neurosynth (see SI Methods for detailed procedures).

The network composed of anterior insula, nucleus accumbens, the orbitofrontal cortex, the anterior cingulate gyrus, and the lateral and medial prefrontal cortex (Panel A). The brain regions (i.e., the nodes) of the risk-related network in the rsFC connectome analysis (Panel B).

Figure 3. Results of the Analgesic Decision-making Task.

The color image presents the frequency that a participant would choose the riskier treatment option. The value ranges from 0–8 in the Analgesic Effect Task (ANE) and the Adverse Effect task (ADE), which both consisted of 8 scenarios. The value ranges from 0–6 in the Time-course Effect Task (TE), which consists of 6 scenarios (Panel A). The change of risk-taking preference in different conditions of the sub-tasks. In the ANE task, the risk-taking preference of the group (i.e., group RPI) increases as the overall probability to have an analgesic effect decreases. In the ADE task, group RPI increases as the overall probability to have an adverse effect decreases. In the TE task, group RPI increases as the time delayed to reach maximal effect decreases (Panel B).

Figure 4. Results of the rsFC connectome analysis.

DC of the bilateral aINS is positively correlated with RPI_TOTAL, controlled for participants’ sex and age. The lower panel revealed that a participant with a higher RPI_TOTAL showed denser FC at the bilateral aINS, compared to a participant with a lower RPI_TOTAL (Panel A). DC of the bilateral aINS and the NAc is positively correlated with RPI_ANE, but not RPI_ADE or RPI_TE, controlled for participants’ sex and age (Panel B).

Figure 5. Results of the analyses of aINS/NAc FC.

RPI_TOTAL is positively correlated with the rsFC between left aINS and multiple brain regions including the right pallidum and putamen, the right dACC and the right aINS (Panel A). RPI_ANE is positively correlated with the rsFC between the left NAc and the right pre-SMA/IFG (Panel B). RPI_ANE is positively correlated with the rsFC between the right Nac and the right dmPFC (Panel C). In all panels, the clusters larger than 350 voxels were visualized.

Figure 6. Results of the structural signatures and mediation analysis.

GMV of the right aINS is positively correlated with RPI_TOTAL (Panel A). GMV of the right frontal pole is positively correlated with RPI_TE (Panel B). The mediation analysis revealed that the association between right aINS GMV and RPI_TOTAL is mediated by DC of the left aINS. The number denotes the non-standardized coefficient from the regression model that predicts the relationship between the IV, DV and mediator. All models are controlled for sex and age (Panel C).