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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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Left prefrontal cortex control of novel occurrences during recollection: a psychopharmacological study using scopolamine and event-related fMRI.

TL;DR: A drug modulation in left prefrontal and perirhinal cortex during recollection was specifically driven by novelty and showed an inverse correlation with accuracy performance, and a direct correlation between drug-related signal change in left cortex and perIRhinal cortices is shown.
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Unimpaired discrimination of fearful prosody after amygdala lesion

TL;DR: Evidence is provided that the amygdala is not required for recognition of fearful prosody, and twins with bilateral amygdala lesions due to Urbach-Wiethe syndrome are unimpaired in a multinomial emotional prosody classification task and demonstrate increased ability to discriminate fearful and neutral prosody.
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Functional neuroimaging in psychiatry and the case for failing better

TL;DR: A critical commentary on this impasse and suggest how the field might fare better and deliver impactful neurobiological insights is provided in this article , where the authors offer a critical analysis of the current state of the art in functional neuroimaging.
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Dopamine, Salience, and Response Set Shifting in Prefrontal Cortex

TL;DR: A novel within-subject psychopharmacological and combined functional neuroimaging paradigm is used, investigating the interaction between hedonic salience, dopamine, and response set shifting, distinct from effects on action learning or motor execution.
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Prospective and Pavlovian mechanisms in aversive behaviour

TL;DR: A computational model of aversion is proposed that combines goal-directed and Pavlovian forms of control into a unifying framework in which their relative importance is regulated by factors such as threat distance and controllability.