Abstract: "Competing successfully against an intelligent adversary requires the ability to mentalize an opponent’s state of mind to anticipate his/her future behavior. Although much is known about what brain regions are activated during mentalizing, the question of how this function is implemented has received little attention to date. Here we formulated a computational model describing the capacity to mentalize in games. We scanned human subjects with functional MRI while they participated in a simple two-player strategy game and correlated our model against the functional MRI data. Different model components captured activity in distinct parts of the mentalizing network. While medial prefrontal cortex tracked an individual’s expectations given the degree of model predicted influence, posterior superior temporal sulcus was found to correspond to an influence update signal, capturing the difference between expected and actual influence exerted. These results suggest dissociable contributions of different parts of the mentalizing network to the computations underlying higher-order strategizing in humans."
http://www.pnas.org/cgi/reprint/105/18/6741
The computational models for reinforcement learning are worth a look over also, there's a lot of thought condensed into these two pages! http://www.pnas.org/cgi/reprint/105/18/6741
Prof. John O'Doherty will be discussing 'Model based analysis of fMRI' at the Mathematics Applications Consortium for Science and Industry(MACSI) at TCD on Wednesday 4th June, the room is the Salmon Lecture Theatre, Hamilton Building.http://www.tcd.ie/Maps/hamilton.html
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