Academic journal article Cognitive, Affective and Behavioral Neuroscience

Risk Prediction and Aversion by Anterior Cingulate Cortex

Academic journal article Cognitive, Affective and Behavioral Neuroscience

Risk Prediction and Aversion by Anterior Cingulate Cortex

Article excerpt

The recently proposed error-likelihood hypothesis suggests that anterior cingulate cortex (ACC) and surrounding areas will become active in proportion to the perceived likelihood of an error. The hypothesis was originally derived from a computational model prediction. The same computational model now makes a further prediction that ACC will be sensitive not only to predicted error likelihood, but also to the predicted magnitude of the consequences, should an error occur. The product of error likelihood and predicted error consequence magnitude collectively defines the general "expected risk" of a given behavior in a manner analogous but orthogonal to subjective expected utility theory. New fMRI results from an incentive change signal task now replicate the error-likelihood effect, validate the further predictions of the computational model, and suggest why some segments of the population may fail to show an error-likelihood effect. In particular, error-likelihood effects and expected risk effects in general indicate greater sensitivity to earlier predictors of errors and are seen in risk-averse but not risk-tolerant individuals. Taken together, the results are consistent with an expected risk model of ACC and suggest that ACC may generally contribute to cognitive control by recruiting brain activity to avoid risk.

The anterior cingulate cortex (ACC) is critically involved in performance monitoring and cognitive control (Blakemore, Rees, & Frith, 1998; Botvinick, Nystrom, Fissel, Carter, & Cohen, 1999; Braver, Barch, Gray, Molfese, & Snyder, 2001; Carter etal., 1998; Carter, MacDonald, Ross, & Stenger, 2001; Gehring & Knight, 2000; Kerns et al., 2004; Liddle et al., 1992; MacDonald, Cohen, Stenger, & Carter, 2000; Menon, Adleman, White, Glover, & Reiss, 2001; Nordahl et al., 2001; Scheffers & Coles, 2000; Ullsperger & von Cramon, 2001; van Veen, Cohen, Botvinick, Stenger, & Carter, 2001). Performance monitoring is essential to theories of executive control hi which a central executive or supervisory attentional system takes control when it detects that automated processes (or schema) may lead to undesirable outcomes (Norman & Shallice, 1986). The ACC was first highlighted as an area that responds to errors, stemming from electophysiological studies in both monkeys (Gemba, Sasaki, & Brooks, 1986) and, later, humans (Gehring, Coles, Meyer, & Donchin, 1990; Hohnsbein, Falkenstein, & Hoorman, 1989). As of the late 1990s, one influential model of performance monitoring proposes that ACC detects response conflict. In this account, when two mutually incompatible response processes are active, the ACC detects the state of conflict and drives control processes to resolve the internal conflict and facilitate appropriate behavior (Botvinick et al., 1999; Carter et al., 1998; MacDonald et al., 2000). Doing so allows individuals to suppress prepotent, automatic responses and instead generate more appropriate responses to achieve current goals. Subsequent monkey studies of ACC and the surrounding medial frontal cortex (MFC) have revealed error, reward, and conflict effects (Amiez, Joseph, & Procyk, 2005, 2006; Ito, Stuphorn, Brown, & Schall, 2003; Olson & Gettner, 2002; Shidara & Richmond, 2002; Stuphorn, Taylor, & Schall, 2000).

The ACC and other MFC regions have recently been found to also be important in decision making, as highlighted by a number of neuroimaging and lesion studies. A prominent recent study of framing effects (de Martino, Kumaran, Seymour, & Dolan, 2006) has shown greater ACC activity when participants make decisions that are framed as being more likely to result in loss. Another recent study of certainty equivalent choices (Paulus & Frank, 2006) has shown that greater ACC activity uniquely predicts more normative decision-making behavior and less risk seeking. Similarly, others have found that ACC is particularly active when individuals avoid errors (Frank, Woroch, & Curran, 2005; Hewig et al. …

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