Outcome contingency selectively affects the neural coding of outcomes but not of tasks

Abstract

27Humans make choices every day, which are often intended to lead to desirable outcomes. While we often 28 have some degree of control over the outcomes of our actions, in many cases this control remains limited. 29Here, we investigate the effect of control over outcomes on the neural correlates of outcome valuation 30 and implementation of behavior, as desired outcomes can only be reached if choices are implemented as 31 intended. In a value-based decision-making task, reward outcomes were either contingent on trial-by-trial 32 choices between two different tasks, or were unrelated to these choices. Using fMRI, multivariate pattern 33 analysis, and model-based neuroscience methods, we identified reward representations in a large 34 network including the striatum, dorso-medial prefrontal cortex (dmPFC) and parietal cortex. These 35 representations were amplified when rewards were contingent on subjects' choices. We further assessed 36 the implementation of chosen tasks by identifying brain regions encoding tasks during a preparation or 37 maintenance phase, and found them to be encoded in the dmPFC and parietal cortex. Importantly, 38 outcome contingency did not affect neural coding of chosen tasks. This suggests that controlling choice 39 outcomes selectively affects the neural coding of these outcomes, but has no effect on the means to reach 40 them. Overall, our findings highlight the role of the dmPFC and parietal cortex in processing of value-41 related and task-related information, linking motivational and control-related processes in the brain. 42These findings inform current debates on the neural basis of motivational and cognitive control, as well 43 as their interaction. 44 Significance statement 45We all make hundreds of choices every day, and we want them to have positive consequences. Often, the 46 link between a choice and its outcomes is fairly clear (healthy diet -> lower risk of cardiovascular disease), 47 but we do not always have a high degree of control over the outcomes of our choices (genetic risk factors 48 -> high risk despite a healthy diet). Control over outcomes is a key factor for decision-making, yet its neural 49 correlates remain poorly understood. Here, subjects performed a value-based decision-making task, while 50 we manipulated the degree of control over choice outcomes. We found that more control enhances the 51 neural coding of choice outcomes, but had no effect on the implementation of the chosen behavior. 52 53 . CC-BY 4.0 International license It is made available under a was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

Representational Organization of Novel Task Sets during Proactive Encoding

“…Reward expectation boosts cue-locked activity across the FP network (Parro et al, 2018), and it has been recently linked to stronger anticipatory rule encoding (Etzel et al, 2016). Nonetheless, contradictory findings have also been observed (Wisniewski et al, 2019), and a comprehensive characterization of this interaction in complex, novel scenarios is still pending. Consequently, we included economic incentives in our paradigm and assessed the nature of their effect on instruction preparation.…”

Motivation and cognitive control in depression

“…In line with these findings, it has been shown that in the Stroop task a cue indicating high efficacy improves behavioral performance (Dean Wolf, Cory, & Shenhav, 2018). At the neural level it has been shown that higher perceived efficacy increases the value of outcomes (Wang & Delgado, 2019) and strengthens their representation in the brain network including the striatum, prefrontal and parietal cortex (Wisniewski, Forstmann, & Brass, 2019). While there is initial evidence to support the role of efficacy in the allocation of cognitive effort, the neural dynamics through which efficacy estimates are formed and the way in which they influence the allocation of cognitive control remain unclear.…”

Representational organization of novel task sets during proactive encoding

“…Reward expectation boosts cue-locked activity across the FP 93 network (Parro, Dixon, & Christoff, 2017), and it has been recently linked to stronger anticipatory 94 rule encoding (Etzel, Cole, Zacks, Kay, & Braver, 2016). Nonetheless, contradictory findings 95 have also been found (Wisniewski, Forstmann, & Brass, 2018), and a comprehensive 96 characterization of this interaction in complex, novel scenarios is still pending. Consequently, we 97 included economic incentives in our paradigm and assessed the nature of their effect on 98 instruction preparation.…”