We used tasks that evoked three distinct forms of control demands – response, decision, and strategy – and found strong evidence for a posterior to anterior topography within the DMPFC. Three distinct foci of activation were identified based on separate behavioral measures using data from the same individuals. These results both provide new insight into the functional organization of DMPFC and suggest a reconciliation of recent controversies about that region's role in complex decision-making and cognitive control.
Control demands play an important role in adaptive decision-making, particularly since decision preferences are strongly influenced by context (Simonson and Tversky, 1992
; Tversky and Simonson, 1993
). For example, people avoid decision options that seem extreme, whether compared to their alternatives or whether having attributes with highly disparate values (Chernev, 2004
). Options that are balanced (e.g., their scores on various attributes are more equal) thus frequently serve as a desirable compromise relative to options containing attributes with high dispersion. We introduced a similar biasing context in the current study, which used an abstract market environment with anonymized options to control for subjects' differential prior exposure to stocks. This task allowed us to manipulate the degree of decision-related and strategy-related control independently, the former by varying the relative desirability of the choices and the latter by measuring individual variability in strategic bias.
Several aspects of our experimental design allow us to conclude that these distinct forms of control were represented in distinct regions within DMPFC. First, we explicitly separated the decision phase from the response phase so that activations related to decision control cannot be attributed to confounding effects from response selection or motor preparation (Pochon et al., 2008
). Second, subjects received no immediate feedback about their decisions when choosing between different stocks; instead, feedback was provided in a separate, later run. This allowed us to rule out effects of outcome history when characterizing our subjects' decision preferences, while also precluding alternative explanations for the observed DMPFC activation like error detection, reinforcement learning, and signaling reward prediction errors (Kiehl et al., 2000
; Kerns et al., 2004
; Kennerley et al., 2006
; Kim et al., 2006
). We do not claim that DMPFC plays no role in these functions, but note that they did not contribute to the activations observed in this experiment. Third, we used an independent counting Stroop task to elucidate neural mechanisms of response-related control. Fourth, all analyses were conducted within the same set of subjects, as critical for making clear spatial comparisons. And, finally, our distinct forms of control demands were each associated with a unique and independent behavioral covariate that was well-controlled within each task, eliminating potential effects of task-specific materials.
Several studies have found increased activation in the DMPFC associated with complex decision making (Paulus et al., 2002
; Walton et al., 2003
; Rushworth et al., 2004
; Zysset et al., 2006
; Botvinick and Rosen, 2008
; Pochon et al., 2008
), though these findings could be confounded by activation related to response preparation (Pochon et al., 2008
). A more recent study using a perceptual decision-making task sought to explore the role of DMPFC in decision conflict, defined as the difficulty arising from choosing between two equally likely choices, while accounting for response-related activation (Pochon et al., 2008
). They demonstrated greater DMPFC activation for decisions involving alternatives that were equally attractive, even in the absence of an explicit response (e.g., precluding an explanation in terms of response-related control). Activation within this region also varied with subjective ratings of decision difficulty. While Pochon and colleagues did not include additional conditions to allow testing of topographic organization, the manipulation of decision conflict in that study led to activation in regions of the DMPFC similar to those associated with decision-related control in our current study.
Moreover, there are initial suggestions that DMPFC is also recruited when individuals make choices that run counter to general behavioural tendencies or strategies (Paulus et al., 2002
; De Martino et al., 2006
; Hampton and O'Doherty, 2007
), although these have heretofore been discussed in terms of decision preferences. Studies involving complex decision making have often focused on identifying brain systems that shape behaviour towards or against particular choices. Yet, it is becoming increasingly apparent that people employ a variety of strategies to simplify the representations of decision problems and reduce computational demands (Tversky and Kahneman, 1974
; Payne et al., 1988
; Payne et al., 1992
; Gigerenzer and Goldstein, 1996
). In this study, we show that activation in a similar region of the DMPFC predicts variability in strategy-related control across subjects. Specifically, individuals with greater bias for the balancing strategy exhibited a greater increase in activation for the extreme choices compared to the balanced choices, and vice versa. Strikingly, the cluster within DMPFC associated with strategy-related control was anterior to and functionally distinct from the clusters associated with decision-related control and response-related control. Therefore, a parsimonious explanation for the role of DMPFC in complex decision making is that distinct functional clusters might be associated with distinct aspects of decision making, including strategy preferences and response preparation.
One potential conjecture for functional specialization within the DMPFC is related to differences in connectivity of these clusters to other regions in the brain. A commonly held framework, one advanced in different guises by different theorists, suggests that lateral prefrontal cortex contains a topographic organization along its posterior to anterior axis (Koechlin et al., 2000
; Koechlin et al., 2003
). More posterior regions, those immediately adjacent to premotor cortex, are associated with setting up general rules for behavior. Conversely, more anterior regions support the instantiation of rules for behavior based on the current context. Findings from functional neuroimaging studies argue for further divisions within anterior prefrontal cortex, such that regions around the frontal pole support relational integration, or the combination of disparate information into a single judgment (Christoff et al., 2001
). We speculate that the different regions of DMPFC differ in their lateral prefrontal targets.
Initial evidence for such a functional organization stems from a recent study that demonstrates choice-specific changes in the functional connectivity of the DMPFC with other regions involved in decision-making (Venkatraman et al., 2009
). Similarly, Beckmann and colleagues used magnetic resonance diffusion tractography to delineate probabilistic anatomical connectivity of the cingulate cortex to other brain regions (Beckmann et al., 2009
). The authors found that the lateral prefrontal cortex exhibited the highest probability of anatomical connectivity with a cluster that corresponds spatially to the region that predicts decision-related control in our study, while the premotor and precentral cortices showed highest probability of connection with a cluster that predicted response-related control in the present study. Under this perspective, the current results point to a generalized role for the DMPFC in cognitive control, but specific computational roles for its subregions depending upon the task demands and current context. Elucidating the functional connectivity of the different clusters in the DMPFC with other brain regions – ideally, using within-task measures derived from the same subjects – may hold the key to fully understanding its role in decision-making.