Biology subjects

Palminteri, S.

Publications and source records attributed to Palminteri, S..

20 records · Page 2Linked to original sources

bioRxiv2017

Neural Computations Underpinning The Strategic Management Of Influence In Advice Giving

Research on social influence has mainly focused on the target of influence (e.g. consumer, voter), while the cognitive and neurobiological underpinnings of the source of the influence (e.g. marketer, politician) remain unexplored. Here we show that advisers managed their influence over their client strategically, by modulating the confidence of their advice, depending on the interaction between advisers level of influence on the client (i.e., being ignored or chosen by the client), and relative merit (i.e., their accuracy in comparison with a rival). Functional magnetic resonance imaging showed that these sources of social information were tracked in distinct regions of the brains social and valuation systems: relative merit in the medial-prefrontal cortex, and selection by client in the temporo-parietal junction. In addition, increased functional connectivity between these two regions during positive merit trials predicted their effect on behaviour. Both sources of social information modulated the activity in the ventral striatum. These results further our understanding of human interactions and provide a framework for investigating the neurobiology of how we try to influence others.

neuroscience↗

bioRxiv2016

Confirmation bias in human reinforcement learning: evidence from counterfactual feedback processing

Previous studies suggest that factual learning, that is learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two cohorts of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valance influences learning. Concerning factual learning, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice. By documenting these valence-induced learning biases, our findings demonstrate the presence of a confirmation bias in human reinforcement learning.

animal behavior and cognition↗