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Precursors to valuation
mardi 22 septembre 2015

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Descriptif

Conférence donnée par Timothy Behrens lors du colloquium du département d'études cognitives à l'ENS.

"Precursors to valuation - coding schemes linking hippocampal and association cortices"

I will present some data that try to link some of the responses that we see during value-guided choice to ones familiar from studies of memory and spatial navigation. In doing so, I will try to find ways to look at the precursors to valuation during choices. I will try to focus on ways in which relationships between objects might be coded, and I will try to find evidence for these kinds of code using some representational imaging measures. At some point or another I will try to imply that grid codes seen in spatial navigation are just one type of covariance code, that they are not limited to space, can be seen in nonspatial dimensions, and can even work in discrete domains like choice paradigms. Sotto voce, I will suggest that the reason we see the networks that we do during choice and learning experiments is nothing to do with value, but because the types of tasks we do require these covariance codes. If you get me drunk, I may even say that these global covariance codes are unique to a set of brain regions commonly referred to as the default-mode network; that is what separates these regions from regions in the dorsal and lateral prefrontal and parietal cortices; and that these codes and brain areas allow complex problems to be solved instantaneously rather than through sequential simulation. You are progressively unlikely to believe these things in the order that they appear in this abstract. I will however show something that you will have to believe, which is that connectivity amongst these default mode brain regions predicts successful outcomes in life with almost every measure that can be thought of, across a large sample of 500 subjects in the Human Connectome Project.


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Auteur(s)
Timothy Behrens
Université de Oxford
Professeur

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Timothy Behrens est professeur en neurosciences à l'Université d'Oxford.

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Dernière mise à jour : 28/10/2015