R
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.
Papers
More filters
Book ChapterDOI
20 – The Neurobiology of Anxiety and Anxiety-Related Disorders: A Functional Neuroimaging Perspective
Phyllis Chua,Raymond J. Dolan +1 more
TL;DR: In this article, the authors define anxiety as "a sense of uncontrollability focused on possible future threat, danger, or other upcoming, potentially negative events." Anxiety is a normal psychological reaction to impending threat or uncertainty.
Journal ArticleDOI
Pharmacological modulation of behavioural and neuronal correlates of repetition priming
TL;DR: The results suggest that GABAergic and cholinergic systems influence the neuronal plasticity necessary for repetition priming, using event-related functional magnetic resonance imaging.
Posted ContentDOI
The value of what’s to come: neural mechanisms coupling prediction error and reward anticipation
Kiyohito Iigaya,Kiyohito Iigaya,Tobias U. Hauser,Zeb Kurth-Nelson,John P. O'Doherty,Peter Dayan,Peter Dayan,Raymond J. Dolan +7 more
TL;DR: Using a computational model of anticipatory value that captures participants’ decisions, it is shown that an anticipateatory value signal is orchestrated by influences from three brain regions, which is consistent with its known role in episodic future thinking.
Journal ArticleDOI
Developmental changes in effects of risk and valence on adolescent decision-making
TL;DR: In this paper, the authors adapted a risk-taking paradigm that provides precise metrics for the impacts of risk and valence on decision-making in 11-16 year old female adolescents.
Journal ArticleDOI
Older adults fail to form stable task representations during model-based reversal inference.
Dorothea Hämmerer,Dorothea Hämmerer,Philipp Schwartenbeck,Maria Gallagher,Maria Gallagher,Thomas H. B. FitzGerald,Thomas H. B. FitzGerald,Emrah Düzel,Emrah Düzel,Raymond J. Dolan +9 more
TL;DR: It is found that older adults overestimate the changeability of task states and consequently are less able to converge on unequivocal task representations through learning, a crucial factor underlying older adults' impaired model-based inference.