Research Report Electrophysiological correlates of decision making under varying levels of uncertainty Amy R. Bland a, ⁎ , Alexandre Schaefer b a University of Leeds, UK b Durham University, UK ARTICLE INFO ABSTRACT Article history: Accepted 15 August 2011 Available online 22 August 2011 When making decisions we are often faced with uncertainty about the potential outcomes of a choice. We therefore must rely upon a stimulus–response–outcome (S–R–O) rule learned from previous experiences of gains and losses. Here we report a study that used event- related potentials (ERP) to examine the neural and cognitive mechanisms involved in deci- sion making when S–R–O rules are changing in a volatile manner. Thirty-one participants engaged in a reward-based decision-making task in which two contextual determinants of decision uncertainty were independently manipulated: Volatility (i.e. the frequency of changes in the S–R–O rules) and Feedback validity (i.e. the extent to which an S–R–O rule accu- rately predicts outcomes). Results of stimulus-locked ERPs showed that volatility of S–R–O rules was associated with two well-known neural signatures of cognitive control processes. First, increased S–R–O volatility in a high FV context was associated with frontally-based N2 (200–350 ms) and N400 (350–500 ms) components. Second, in a low FV context, volatility was associated with an enhanced late positive complex (LPC, 500–800 ms) largest on frontal sites. Feedback-locked ERPs showed an enhanced Feedback-Related Negativity (FRN) and P300 for losses compared to wins as well as a volatility driven FRN. These results suggest that, in a high FV context, coping with volatility might involve conflict monitoring processes. However, in a low FV context, coping with frequent changes in the S–R–O rule might require greater attentional and working memory (WM) resources. © 2011 Elsevier B.V. All rights reserved. Keywords: Uncertainty Volatility Feedback validity Reward Cognitive control EEG/ERP P300 Late positive complex (LPC) N2 N400 1. Introduction Our everyday decisions are often guided by an underlying “Stimulus–response–Outcome” (SRO) rule (de Wit and Dickinson, 2009), in which we learn that a specific association between a stimulus (S) and a response (R) is linked with a posi- tive or negative outcome (O). For instance, we may decide to enter (R) a specific restaurant (S) because that restaurant always serves our preferred dish (O). One of the implications of this prin- ciple is that optimal decision-making relies on the ability of an individual to form a stable representation of the underlying S– R–O rule learned from previous experiences (e.g. Ridderinkhof et al., 2004; Seymour et al., 2007; Sutton and Barto, 1998). However, the question of what happens in a volatile con- text, where the underlying S–R–O rule is changing, remains poorly understood. A likely way of successfully coping with volatility in decision-making relies on the ability to rapidly in- hibit outdated rules after each change and replace them with accurate rules. Therefore, the adaptation to volatile contexts should be facilitated by the implementation of cognitive control BRAIN RESEARCH 1417 (2011) 55 – 66 ⁎ Corresponding author at: University of Leeds, Institute of Psychological Sciences, Leeds LS2 9JT, UK. E-mail addresses: A.R.Bland04@leeds.ac.uk (A.R. Bland), alexandre.schaefer@durham.ac.uk (A. Schaefer). 0006-8993/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2011.08.031 Available online at www.sciencedirect.com www.elsevier.com/locate/brainres