001). In principle, SOA alone could have provided information to guide betting; monkeys could have ignored their trial-by-trial decisions and just bet high more often if the masks appeared later or the task seemed easier. We analyzed the data from each SOA separately to address this potential

confound. Trial-by-trial analyses revealed that for each monkey, within each SOA, bets were correlated appropriately with decisions (χ2 test, p < 0.001 for each SOA and each monkey; details in Middlebrooks and Sommer, 2011). We quantified performance across SOAs using two phi correlation methods (Kornell et al., 2007; Zar, 1999). Phi correlation values could range from zero (random betting) to one (perfect association between decisions and bets). Both monkeys’ phi correlations, assessed with either method (Figure 1C; Figure S1 available online), were significant at each SOA and constant across SOAs Alpelisib manufacturer (one-way ANOVA,

p > 0.05). Another potential confound is the use of motor-related cues. Monkeys could possibly detect Y-27632 molecular weight their saccade latencies during the decision stage and use this information to help place bets. This explanation is feasible if latency distributions differ between correct-high versus correct-low trials and between incorrect-high and incorrect-low trials, but they did not (Table S1). All of these results replicate our prior findings (Middlebrooks and Sommer, 2011) and indicate that, within each trial during neuronal recordings, monkeys maintained information about their decision to guide their bet, a metacognitive strategy. We studied 87 neurons in the FEF (Monkey N: 35, Monkey S: 52), 112 in the PFC (N: 54, S: 58), and 133 in the SEF (N: 61, S: 72). As expected, neurons in all three areas were highly modulated during the task (Figure S2). The monkeys’ betting behavior did not vary significantly between recording sessions in the three unless cortical areas (phi correlations for Monkey N: FEF, 0.51; PFC, 0.49; SEF, 0.47; for Monkey S: FEF, 0.59; PFC, 0.54; SEF, 0.54;

no differences between areas by ANOVAs, p > 0.05, for both monkeys). Because the monkeys were well trained, the neuronal recording data included more correct-high and incorrect-low trials (the appropriate decision-bet pairings) than correct-low and incorrect-high trials (Table S2 shows the breakdown of trial outcomes). To test whether neurons encoded the decision, we compared all correct with all incorrect trials, regardless of subsequent bets (i.e., high and low bet trials pooled). First, we focused on neuronal activity related to the visual target. Using a similar masked target task, Thompson and Schall (1999) demonstrated that signals predictive of a monkey’s decision occur in the early visual responses of FEF neurons, prior to the start of motor-related processes (reviewed by Schall and Thompson, 1999; Schall, 2001; see also Schall et al., 1995; Sato and Schall, 2003).