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Raymond J. Dolan

Researcher at University College London

Publications -  940
Citations -  150202

Raymond J. Dolan is an academic researcher from University College London. The author has contributed to research in topics: Prefrontal cortex & Functional magnetic resonance imaging. The author has an hindex of 196, co-authored 919 publications receiving 138540 citations. Previous affiliations of Raymond J. Dolan include VU University Amsterdam & McGovern Institute for Brain Research.

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Automatic relevance detection in the absence of a functional amygdala

TL;DR: Cortical and thalamic visual areas might support prioritised resource allocation in the absence of a functioning amygdala in patients with complete and specific amygdala lesions due to Urbach-Wiethe syndrome.
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Keep focussing: striatal dopamine multiple functions resolved in a single mechanism tested in a simulated humanoid robot.

TL;DR: A model combining tonic and phasic DA is presented to show how different outflows triggered by either intrinsically or extrinsically motivating stimuli dynamically affect the basal ganglia by impacting on a selection process this system performs on its cortical input.
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Is multivariate analysis of PET data more revealing than the univariate approach? Evidence from a study of episodic memory retrieval.

TL;DR: This analysis showed that the most significant source of task-related variance was accounted for by a nonlinear relationship not predicted by the prior hypothesis and not revealed by the standard univariate approach, which supports the assertion that multivariate analysis can provide an important adjunct to univariate approaches like statistical parametric mapping (SPM).
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Experience and Choice Shape Expected Aversive Outcomes

TL;DR: These findings indicate that subcortical regions known to track expected value such as the caudate nucleus, together with anterior cingulate cortical regions implicated in emotional modulation, mediate a revaluation in expectancies of aversive states.
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An MEG signature corresponding to an axiomatic model of reward prediction error.

TL;DR: The magnetic signature of prediction errors in the human brain was identified for the first time, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability.