Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex

• Published in: Nature communications Vol. 7; no. 1; pp. 12327 - 13
• Main Authors: Wittmann, Marco K., Kolling, Nils, Akaishi, Rei, Chau, Bolton K. H., Brown, Joshua W., Nelissen, Natalie, Rushworth, Matthew F. S.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.08.2016; Nature Publishing Group; Nature Portfolio
• Subjects: 59/36; 631/378/2649/1409; 631/477/2811; Adult; Attention - physiology; Choice Behavior - physiology; Decision making; Female; Foraging behavior; Gyrus Cinguli - diagnostic imaging; Gyrus Cinguli - physiology; Humanities and Social Sciences; Humans; Learning - physiology; Magnetic Resonance Imaging; Male; Models, Biological; multidisciplinary; Natural environment; Prefrontal Cortex - diagnostic imaging; Prefrontal Cortex - physiology; Reward; Science; Science (multidisciplinary); Time Factors; Trends; Young Adult; Hong Kong China; Indiana; United Kingdom > UK; United States > US; China
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms12327

In many natural environments the value of a choice gradually gets better or worse as circumstances change. Discerning such trends makes predicting future choice values possible. We show that humans track such trends by comparing estimates of recent and past reward rates, which they are able to hold simultaneously in the dorsal anterior cingulate cortex (dACC). Comparison of recent and past reward rates with positive and negative decision weights is reflected by opposing dACC signals indexing these quantities. The relative strengths of time-linked reward representations in dACC predict whether subjects persist in their current behaviour or switch to an alternative. Computationally, trend-guided choice can be modelled by using a reinforcement-learning mechanism that computes a longer-term estimate (or expectation) of prediction errors. Using such a model, we find a relative predominance of expected prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice signals in the ventromedial prefrontal cortex. Past experiences and future predictions both shape our decisions. Here, the authors trained participants in a foraging task in which reward rates varied systematically over time and find the dACC tracks both recent and past reward rates, leading to opposing effects on decisions about whether to stay or leave a reward environment.