Neural Signatures of Prediction Errors in a Decision-Making Task Are Modulated by Action Execution Failures

Abstract

Highlights d Humans devalue choices less following execution versus selection errors d Reward prediction errors in the striatum are attenuated following execution errors d Different error classes have distinct neural signatures

Distinct Neural Signatures of Outcome Monitoring following Selection and Execution Errors

“…A recent fMRI experiment using a similar 3-arm bandit task to the one employed here, revealed an attenuation of the signal associated with negative reward prediction error in the striatum following execution failures (McDougle et al, 2019). Our observation of a larger negative deflection for execution error trials in the MFN may appear contrary to these previously reported striatal results.…”

“…Overall, this bandit was chosen on 39.49% (±9.38) of the trials, which was significantly greater than the Low Execution/High Selection error bandit (29.01%; ±6.89%, p < .001) and Neutral bandit (31.50%; ±8.64%, p = .046), with no difference for the latter two (p = .877). Consistent with previous work, when expected value is equal, participants prefer choices in which unrewarded trials are attributed to errors in movement execution rather than errors in action selection (Wu et al, 2009;Green et al, 2010;McDougle et al, 2016;Parvin et al, 2018;McDougle et al, 2019).…”

“…The authors 52 hypothesized that errors credited to the motor execution system block value updating in the 53 action selection system. Consistent with this, McDougle et al (2019) have subsequently 54 shown that reward prediction error coding in the human striatum is attenuated following 55 execution versus selection errors. Differences between responses to selection and execution 56 errors have been attributed to a greater sense of "agency" in the latter, with participants' 57 choice biases indicating a belief that they can reduce execution errors by making more 58 accurate movements (Parvin et al, 2018).…”

“…Although the majority of neuroscience decision-making research has focused almost exclusively on the former, a number of studies have shown that failed outcomes attributed to sensorimotor errors can markedly alter choice preferences (Green et al, 2010;McDougle et al, 2016;Parvin et al, 2018;McDougle et al, 2019). It has been postulated that these shifts arise from error signals credited to the sensorimotor system attenuating the operation of reinforcement learning processes (McDougle et al, 2016).…”

“…Two participants 98 were excluded due to excessive EEG artifacts, and a technical error during data collection 99 rendered one participant's dataset unusable. All analyses were performed on the resulting 100 Experiment 2 employed a three-armed bandit reaching task (Figure 1 C & D) in which we also 138 included outcomes where non-rewards could be the product of poorly executed actions 139 (McDougle et al, 2019). Following EEG set-up, the participant was seated in a chair 140 approximately 50 cm away from a 24" ASUS monitor (53.2 X 30 cm [2560 x 1600 pixels], 100 141…”