The current study examined how the brain evaluates information when updating uncertainty about a future decision. Although dACC activity was correlated with objective uncertainty when observing evidence, the pattern of activity between the first and last draw suggests that this region was not tracking probabilities in a strict sense. Activity in dACC became greater between draw 1 and 4 as calculated posterior probabilities decreased (i.e., objective uncertainty increased) in Type 2:2 sequences, yet it also increased (albeit to a lesser degree) when posterior probabilities increased (i.e., objective uncertainty decreased) in Type 3:1 sequences. Indeed, even at an uncorrected threshold, we did not find any regions that behaved as if they were tracking objective probabilities (i.e., decreasing activity between draw 1 and draw 4 in Type 4:0 and 3:1 sequences in parallel with increasing posteriors, and increasing activity in Type 2:2 sequences in parallel with decreasing posteriors).
These findings may be interpreted in light of major theories of dACC functioning that have focused on evaluative and monitoring processes. Error detection theory suggests that dACC monitors mismatches between actual and intended responses (Scheffers and Coles, 2000
), while conflict monitoring theory states that dACC detects conflict between co-activated responses (Botvinick et al., 2001
). By contrast, Brown and Braver (2005)
proposed that dACC does not respond to errors or conflicts per se
, but instead is activated in situations where error likelihood is greatest, and, as such, has a role in risk prediction. Finally, reinforcement learning (RL) theory suggests that dACC is involved in learning after obtaining an outcome that is worse than expected, i.e. a reward prediction error (Holroyd and Coles, 2002
), with later expansion of this theory to include outcomes that are merely different than expected (Oliveira et al., 2007
), i.e., prediction errors not restricted to conditions of reward omission.
The pattern of results in dACC cannot be explained by existing error detection, conflict monitoring, or error likelihood theories. There were no overt errors during evidence accumulation, and both the response conflict associated with choosing a deck and the likelihood of making a future error in response to the decision would have been reduced in Type 3:1 sequences as uncertainty decreased, yet our data show that the dACC signal increased between the first and last draw. Our findings are instead compatible with a role for dACC in responding to unexpected or unpredicted outcomes (Oliveira et al., 2007
). During evidence accumulation, dACC may have increased between draws 1 and 4 on Type 3:1 and 2:2 sequences because at least one draw was observed that was inconsistent with expectations established through prior observations of draws in a sequence (see supplemental Figures 1 and 2
), with the largest increase occurring in situations when expectations were repeatedly violated (i.e., Type 2:2 sequences). By contrast, dACC activity did not increase as evidence accumulated on Type 4:0 sequences because all draws consistently pointed to the same deck.
Frontal regions including OFC/IFC, superior and middle frontal gyri, and dorsomedial frontal cortex, as well as bilateral inferior parietal cortex, were uniquely associated with greater uncertainty when executing a decision at the end of the sequence as compared to observing the last draw, even though objective uncertainty was the same. Although making ratings and executing the decision both involve choices regarding the identity of the deck supplying the cards, only the decision made at the end of the sequence is associated with incentive consequences. For this reason, unlike other studies that have identified OFC in uncertainty processing (Critchley et al., 2001
; Tobler et al., 2007
), the current paradigm was able to disentangle activations related to the cognitive experience of uncertainty from those associated with motivational processes such as reward risk that often vary along with uncertainty. The lack of significant modulation of OFC by uncertainty when subjects accumulated evidence in the absence of risk suggests that this region does not detect cognitive uncertainty per se
, but instead responds to uncertainty only when there are incentive consequences. This is consistent with the well-documented role of OFC in associating stimuli with the value of outcomes (Rushworth et al., 2007
; Wallis, 2007
), with lateral regions preferentially involved in processing punishment and disappointment (O’Doherty et al., 2001
; Ursu and Carter, 2005
). Indeed, uncertain sequences in our task should elicit a greater expectation of not receiving a reward, which may lead to disappointment when executing the decision. Alternatively, OFC/IFC activity may reflect a “safety signal” associated with opting-out of making a decision, given prior work identifying a relationship between safe choices among risk-averse individuals and activity in a region of IFC located slightly superior to our own (Christopoulos et al., 2009
Although we did find activity in OFC/IFC, we did not replicate previous findings linking decision uncertainty to nearby anterior insula (Grinband et al., 2006
; Huettel, 2006
, Preuschoff et al., 2008
; Volz et al., 2003
), which may be due to the fact that greater decision uncertainty in prior studies often also signals an increased likelihood for error. Errors robustly activate anterior insula, perhaps due to the aversive emotional response they elicit (Simmons et al., 2004
), even in the absence of incentives or feedback (see Taylor et al., 2007
). Thus, the lack of insula activation in the present study may be due to our design, which dissociated increased uncertainty from error likelihood by allowing subjects to avoid an error by declining to make a decision on uncertain sequences.
Previous studies, including the analyses described above, have examined brain regions responding to uncertainty as defined by experimental stimuli. However, uncertainty is not only determined by external information, but is also modulated by internal cognitive or emotional states, which vary between individuals. The VMPFC activity that correlated with underconfidence during evidence accumulation is not likely to be due to greater difficulty among underconfident subjects, as considerable evidence suggests that VMPFC activation decreases with cognitive effort (Simpson et al., 2001
). Instead, we suggest that increased VMPFC activity may be related to greater arousal in autonomic and emotional systems when evaluating evidence. VMPFC has been conceptualized as part of a network important for integrating emotional-somatic states with factual information in order to guide decision-making (Damasio et al., 1996
), due to strong interconnectivity with limbic/autonomic regions including the amygdala, nucleus accumbens, hypothalamus, and midbrain (Kringelbach and Rolls, 2004
; Price, 2007
). VMPFC activity is associated with greater arousal as measured by skin conductance (Critchley et al., 2000
), and is part of the “default mode” network that deactivates during directed attention (Simpson et al., 2001
). Damage to this region leads to an increase in risk-taking behavior (Clark et al., 2008
), possibly because patients do not generate appropriate emotional-somatic anticipatory reactions prior to making a risky choice (Bechara et al., 2000
Our results indicate that VMPFC activity is associated with relatively conservative ratings of certainty, even in the absence of overt risk when subjects are merely evaluating evidence. In theory, increased subjective uncertainty could be driven by a cognitive mechanism, such as an incorrect judgment of likelihood, or an emotional/motivational process involving the experience of increased arousal or appraisal of risk when evaluating evidence. While correlational data cannot completely rule out the influence of aberrant cognition, our findings in VMPFC suggest that somatic/emotional mechanisms play an important role in determining subjective uncertainty, at least among healthy subjects. Of interest, individual variability in underconfidence was greater, and the relationship between VMPFC and underconfidence was stronger, on the first draw as compared to later draws. This suggests that the neural signatures of conservatism have their greatest influence when observing limited information, and that increasing evidence allows underconfident subjects to recover from initial uncertainty.
Overall, our data provide insight into how the brain updates beliefs during evidence accumulation, and how emotional responses may interact with cognitive functioning to process uncertainty. Updating beliefs in a roughly Bayesian manner involves the activation of dorsal ACC regions to evaluate whether evidence is consistent or inconsistent with expectations, while the simultaneous activation of emotional-related processes by VMPFC may lead to a phenomenological experience of uncertainty that is greater (i.e., more underconfident) than what would be expected from the monitoring of dACC output alone.
While results from the current study serve to elucidate the mechanisms of uncertainty during decision-making, limitations and questions remain for future research. Although subjective ratings after each piece of information served a critical role in our design and analysis, it is possible that the mere process of rating uncertainty (in addition to experiencing uncertainty) lead to artificial reductions in emotionality (Taylor et al., 2003
), which may have minimized the involvement of limbic/paralimbic brain regions in our task. Further, methodological constraints required that we use a categorical scale for uncertainty ratings, yet a continuous visual-analog scale would have been preferable for detecting subtle differences between subjects. As such, our results may underestimate the full scope of brain regions involved in underconfidence. Despite these limitations, the current results represent an important step toward understanding how uncertainty is processed during different phases of decision-making, and point to the need to investigate evidence accumulation in disorders characterized by pathological uncertainty.