L
Laurence T. Hunt
Researcher at University of Oxford
Publications - 64
Citations - 4022
Laurence T. Hunt is an academic researcher from University of Oxford. The author has contributed to research in topics: Prefrontal cortex & Orbitofrontal cortex. The author has an hindex of 22, co-authored 59 publications receiving 3305 citations. Previous affiliations of Laurence T. Hunt include Wellcome Trust Centre for Neuroimaging & John Radcliffe Hospital.
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Journal ArticleDOI
Associative learning of social value
Timothy E.J. Behrens,Laurence T. Hunt,Laurence T. Hunt,Mark W. Woolrich,Matthew F. S. Rushworth,Matthew F. S. Rushworth +5 more
TL;DR: It is demonstrated that social information may be acquired using the same associative processes assumed to underlie reward-based learning, and suggested that human social valuation can be realized by means of the same Associative processes previously established for learning other, simpler, features of the environment.
Journal ArticleDOI
Mechanisms underlying cortical activity during value-guided choice
Laurence T. Hunt,Nils Kolling,Alireza Soltani,Mark W. Woolrich,Mark W. Woolrich,Matthew F. S. Rushworth,Matthew F. S. Rushworth,Timothy E.J. Behrens,Timothy E.J. Behrens +8 more
TL;DR: A mechanistic explanation of neural signals recorded during value-guided choice are provided and a means of distinguishing computational roles of different cortical regions whose activity covaries with value are distinguished.
Journal ArticleDOI
The Computation of Social Behavior
TL;DR: The recent application of formal behavioral models in the area of social cognitive neuroscience is reviewed, with a focus on regions active when a person must make estimates of another person’s intentions.
Journal ArticleDOI
Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks.
Diego Vidaurre,Laurence T. Hunt,Andrew J. Quinn,Hunt Bae.,Matthew J. Brookes,Anna C. Nobre,Mark W. Woolrich +6 more
TL;DR: It is reported using MEG that various brain networks show dynamic phase coupling through specific frequency bands in the alpha and delta/theta range transiently during the resting state.
Journal ArticleDOI
A distributed, hierarchical and recurrent framework for reward-based choice.
TL;DR: This Opinion article argues for an alternative viewpoint of reward-based choice, in which choices emerge from repeated computations that are distributed across many brain regions, and emphasizes how several features of neuroanatomy may support the implementation of choice.