Event Abstract Back to Event Learning from competitors Paul A. Howard-Jones1*, Rafal Bogacz2, Jee H. Yoo2, Ute Leonards3 and Skevi Demetriou1 1 University of Bristol, Graduate School of Education, United Kingdom 2 University of Bristol, Department of Computer Science, United Kingdom 3 University of Bristol, Department of Experimental Psychology, United Kingdom Previous NEnet research has linked memory performance during an educational game to reward-based signals arising from the gaming events, possibly because such signals can mediate attention. Indeed, existing models of reward-learning can be used to estimate dopamine levels arising from prediction errors made by the player during the game, and these are related to subsequent memory performance. Such models, however, cannot be applied to competitive games, since no models exist for competitive reward-learning. Learning from competitors poses a challenge for existing theories of reward based learning, which assume that rewarded actions are more likely to be executed in the future. Such a learning mechanism would disadvantage a player in a competitive situation because, since the competitor’s loss is the player’s gain, reward might become associated with an action the player should themselves avoid. Using fMRI, we investigated the neural activity of humans competing with a computer in a foraging task. We observed neural activity that represented the variables required for learning from competitors: the actions of the competitor (in the player’s motor and premotor cortex) and the prediction error arising from the competitor’s feedback (in the player’s response inhibition system). Our results support a model of competitive reward learning in which the player generates neural representations of their competitor’s actions prior to outcomes becoming known, possibly in readiness to initiate these actions. At the outcome of the competitor’s selection, we observed activities suggesting reward-based response inhibition and the appraisal of alternatives, in relation to a learning signal provided by the competitor’s unexpected losses. In competitive foraging, processes involving the mirror neuron, response inhibition and reward systems may cooperate in supporting efficient reward exploitation and loss avoidance. Our results suggest that, in educational games, a competitor’s unexpected failure, rather than their success, may be most predictive of engagement by the player. Conference: EARLI SIG22 - Neuroscience and Education, Zurich, Switzerland, 3 Jun - 5 Jun, 2010. Presentation Type: Poster Presentation Topic: Motivation and emotion Citation: Howard-Jones PA, Bogacz R, Yoo JH, Leonards U and Demetriou S (2010). Learning from competitors. Front. Neurosci. Conference Abstract: EARLI SIG22 - Neuroscience and Education. doi: 10.3389/conf.fnins.2010.11.00016 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 28 May 2010; Published Online: 28 May 2010. * Correspondence: Paul A Howard-Jones, University of Bristol, Graduate School of Education, Bristol, United Kingdom, paul.howard-jones@bristol.ac.uk Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Paul A Howard-Jones Rafal Bogacz Jee H Yoo Ute Leonards Skevi Demetriou Google Paul A Howard-Jones Rafal Bogacz Jee H Yoo Ute Leonards Skevi Demetriou Google Scholar Paul A Howard-Jones Rafal Bogacz Jee H Yoo Ute Leonards Skevi Demetriou PubMed Paul A Howard-Jones Rafal Bogacz Jee H Yoo Ute Leonards Skevi Demetriou Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.