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Raymond Dolan

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https://www.readbyqxmd.com/read/29643456/publisher-correction-metacognitive-impairments-extend-perceptual-decision-making-weaknesses-in-compulsivity
#1
Tobias U Hauser, Micah Allen, Geraint Rees, Raymond J Dolan
A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.
April 11, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29549530/risk-preference-and-choice-stochasticity-during-decisions-for-other-people
#2
Francesco Rigoli, Katrin H Preller, Raymond J Dolan
In several contexts, such as finance and politics, people make choices that are relevant for others but irrelevant for oneself. Focusing on decision-making under risk, we compared monetary choices made for one's own interest with choices made on behalf of an anonymous individual. Consistent with the previous literature, other-interest choices were characterized by an increased gambling propensity. We also investigated choice stochasticity, which captures how much decisions vary in similar conditions. An aspect related to choice stochasticity is how much decisions are tuned to the option values, and we found that this was higher during self-interest than during other-interest choices...
March 16, 2018: Cognitive, Affective & Behavioral Neuroscience
https://www.readbyqxmd.com/read/29481966/value-encoding-in-the-globus-pallidus-fmri-reveals-an-interaction-effect-between-reward-and-dopamine-drive
#3
Vincenzo G Fiore, Tobias Nolte, Francesco Rigoli, Peter Smittenaar, Xiaosi Gu, Raymond J Dolan
The external part of the globus pallidus (GPe) is a core nucleus of the basal ganglia (BG) whose activity is disrupted under conditions of low dopamine release, as in Parkinson's disease. Current models assume decreased dopamine release in the dorsal striatum results in deactivation of dorsal GPe, which in turn affects motor expression via a regulatory effect on other nuclei of the BG. However, recent studies in healthy and pathological animal models have reported neural dynamics that do not match with this view of the GPe as a relay in the BG circuit...
February 23, 2018: NeuroImage
https://www.readbyqxmd.com/read/29456782/other-people-s-money-the-role-of-reciprocity-and-social-uncertainty-in-decisions-for-others
#4
Ivo Vlaev, Brian Wallace, Nicholas Wright, Antoinette Nicolle, Paul Dolan, Raymond Dolan
Many important decisions are taken not by the person who will ultimately gain or lose from the outcome, but on their behalf, by somebody else. We examined economic decision-making about risk and time in situations in which deciders chose for others who also chose for them. We propose that this unique setting, which has not been studied before, elicits perception of reciprocity that prompts a unique bias in preferences. We found that decision-makers are less patient (more discounting), and more risk averse for losses than gains, with other peoples' money, especially when their choices for others are more uncertain...
June 2017: Journal of Neuroscience, Psychology, and Economics
https://www.readbyqxmd.com/read/29440429/locus-coeruleus-integrity-in-old-age-is-selectively-related-to-memories-linked-with-salient-negative-events
#5
Dorothea Hämmerer, Martina F Callaghan, Alexandra Hopkins, Julian Kosciessa, Matthew Betts, Arturo Cardenas-Blanco, Martin Kanowski, Nikolaus Weiskopf, Peter Dayan, Raymond J Dolan, Emrah Düzel
The locus coeruleus (LC) is the principal origin of noradrenaline in the brain. LC integrity varies considerably across healthy older individuals, and is suggested to contribute to altered cognitive functions in aging. Here we test this hypothesis using an incidental memory task that is known to be susceptible to noradrenergic modulation. We used MRI neuromelanin (NM) imaging to assess LC structural integrity and pupillometry as a putative index of LC activation in both younger and older adults. We show that older adults with reduced structural LC integrity show poorer subsequent memory...
February 12, 2018: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/29325701/developmental-cognitive-neuroscience-using-latent-change-score-models-a-tutorial-and-applications
#6
REVIEW
Rogier A Kievit, Andreas M Brandmaier, Gabriel Ziegler, Anne-Laura van Harmelen, Susanne M M de Mooij, Michael Moutoussis, Ian M Goodyer, Ed Bullmore, Peter B Jones, Peter Fonagy, Ulman Lindenberger, Raymond J Dolan
Assessing and analysing individual differences in change over time is of central scientific importance to developmental neuroscience. However, the literature is based largely on cross-sectional comparisons, which reflect a variety of influences and cannot directly represent change. We advocate using latent change score (LCS) models in longitudinal samples as a statistical framework to tease apart the complex processes underlying lifespan development in brain and behaviour using longitudinal data. LCS models provide a flexible framework that naturally accommodates key developmental questions as model parameters and can even be used, with some limitations, in cases with only two measurement occasions...
November 22, 2017: Developmental Cognitive Neuroscience
https://www.readbyqxmd.com/read/29276055/morphometric-similarity-networks-detect-microscale-cortical-organization-and-predict-inter-individual-cognitive-variation
#7
Jakob Seidlitz, František Váša, Maxwell Shinn, Rafael Romero-Garcia, Kirstie J Whitaker, Petra E Vértes, Konrad Wagstyl, Paul Kirkpatrick Reardon, Liv Clasen, Siyuan Liu, Adam Messinger, David A Leopold, Peter Fonagy, Raymond J Dolan, Peter B Jones, Ian M Goodyer, Armin Raznahan, Edward T Bullmore
Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organization comprising modules and high-degree hubs...
January 3, 2018: Neuron
https://www.readbyqxmd.com/read/29274746/structural-covariance-networks-are-coupled-to-expression-of-genes-enriched-in-supragranular-layers-of-the-human-cortex
#8
Rafael Romero-Garcia, Kirstie J Whitaker, František Váša, Jakob Seidlitz, Maxwell Shinn, Peter Fonagy, Raymond J Dolan, Peter B Jones, Ian M Goodyer, Edward T Bullmore, Petra E Vértes
Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions...
May 1, 2018: NeuroImage
https://www.readbyqxmd.com/read/29249811/increased-decision-thresholds-trigger-extended-information-gathering-across-the-compulsivity-spectrum
#9
Tobias U Hauser, Michael Moutoussis, Peter Dayan, Raymond J Dolan
Indecisiveness and doubt are cognitive phenotypes of compulsive disorders, including obsessive-compulsive disorder. Little is known regarding the cognitive mechanisms that drive these behaviours across a compulsivity spectrum. Here, we used a sequential information gathering task to study indecisiveness in subjects with high and low obsessive-compulsive scores. These subjects were selected from a large population-representative database, and matched for intellectual and psychiatric factors. We show that high compulsive subjects sampled more information and performed better when sampling was cost-free...
December 18, 2017: Translational Psychiatry
https://www.readbyqxmd.com/read/29190275/correction-approach-induced-biases-in-human-information-sampling
#10
Laurence T Hunt, Robb B Rutledge, W M Nishantha Malalasekera, Steven W Kennerley, Raymond J Dolan
[This corrects the article DOI: 10.1371/journal.pbio.2000638.].
November 2017: PLoS Biology
https://www.readbyqxmd.com/read/29177462/cohort-profile-the-nspn-2400-cohort-a-developmental-sample-supporting-the-wellcome-trust-neuroscience-in-psychiatry-network
#11
Beatrix Kiddle, Becky Inkster, Gita Prabhu, Michael Moutoussis, Kirstie J Whitaker, Edward T Bullmore, Raymond J Dolan, Peter Fonagy, Ian M Goodyer, Peter B Jones
No abstract text is available yet for this article.
February 1, 2018: International Journal of Epidemiology
https://www.readbyqxmd.com/read/29061228/neural-and-computational-processes-underlying-dynamic-changes-in-self-esteem
#12
Geert-Jan Will, Robb B Rutledge, Michael Moutoussis, Raymond J Dolan
Self-esteem is shaped by the appraisals we receive from others. Here, we characterize neural and computational mechanisms underlying this form of social influence. We introduce a computational model that captures fluctuations in self-esteem engendered by prediction errors that quantify the difference between expected and received social feedback. Using functional MRI, we show these social prediction errors correlate with activity in ventral striatum/subgenual anterior cingulate cortex, while updates in self-esteem resulting from these errors co-varied with activity in ventromedial prefrontal cortex (vmPFC)...
October 24, 2017: ELife
https://www.readbyqxmd.com/read/29028323/benchmarking-of-computational-methods-for-creation-of-retention-models-in-quantitative-structure-retention-relationships-studies
#13
Ruth I J Amos, Eva Tyteca, Mohammad Talebi, Paul R Haddad, Roman Szucs, John W Dolan, Christopher A Pohl
Quantitative structure-retention relationship (QSRR) models are powerful techniques for the prediction of retention times of analytes, where chromatographic retention parameters are correlated with molecular descriptors encoding chemical structures of analytes. Many QSRR models contain geometrical descriptors derived from the three-dimensional (3D) spatial coordinates of computationally predicted structures for the analytes. Therefore, it is sensible to calculate these structures correctly, as any error is likely to carry over to the resulting QSRR models...
November 27, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28981514/a-unifying-bayesian-account-of-contextual-effects-in-value-based-choice
#14
Francesco Rigoli, Christoph Mathys, Karl J Friston, Raymond J Dolan
Empirical evidence suggests the incentive value of an option is affected by other options available during choice and by options presented in the past. These contextual effects are hard to reconcile with classical theories and have inspired accounts where contextual influences play a crucial role. However, each account only addresses one or the other of the empirical findings and a unifying perspective has been elusive. Here, we offer a unifying theory of context effects on incentive value attribution and choice based on normative Bayesian principles...
October 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28949824/learning-contextual-reward-expectations-for-value-adaptation
#15
Francesco Rigoli, Benjamin Chew, Peter Dayan, Raymond J Dolan
Substantial evidence indicates that subjective value is adapted to the statistics of reward expected within a given temporal context. However, how these contextual expectations are learned is poorly understood. To examine such learning, we exploited a recent observation that participants performing a gambling task adjust their preferences as a function of context. We show that, in the absence of contextual cues providing reward information, an average reward expectation was learned from recent past experience...
January 2018: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/28808037/separate-mesocortical-and-mesolimbic-pathways-encode-effort-and-reward-learning-signals
#16
Tobias U Hauser, Eran Eldar, Raymond J Dolan
Optimal decision making mandates organisms learn the relevant features of choice options. Likewise, knowing how much effort we should expend can assume paramount importance. A mesolimbic network supports reward learning, but it is unclear whether other choice features, such as effort learning, rely on this same network. Using computational fMRI, we show parallel encoding of effort and reward prediction errors (PEs) within distinct brain regions, with effort PEs expressed in dorsomedial prefrontal cortex and reward PEs in ventral striatum...
August 29, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28747627/metacognitive-impairments-extend-perceptual-decision-making-weaknesses-in-compulsivity
#17
Tobias U Hauser, Micah Allen, Geraint Rees, Raymond J Dolan
Awareness of one's own abilities is of paramount importance in adaptive decision making. Psychotherapeutic theories assume such metacognitive insight is impaired in compulsivity, though this is supported by scant empirical evidence. In this study, we investigate metacognitive abilities in compulsive participants using computational models, where these enable a segregation between metacognitive and perceptual decision making impairments. We examined twenty low-compulsive and twenty high-compulsive participants, recruited from a large population-based sample, and matched for other psychiatric and cognitive dimensions...
July 26, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28736307/local-striatal-reward-signals-can-be-predicted-from-corticostriatal-connectivity
#18
Peter Smittenaar, Zeb Kurth-Nelson, Siawoosh Mohammadi, Nikolaus Weiskopf, Raymond J Dolan
A defining feature of the basal ganglia is their anatomical organization into multiple cortico-striatal loops. A central tenet of this architecture is the idea that local striatal function is determined by its precise connectivity with cortex, creating a functional topography that is mirrored within cortex and striatum. Here we formally test this idea using both human anatomical and functional imaging, specifically asking whether within striatal subregions one can predict between-voxel differences in functional signals based on between-voxel differences in corticostriatal connectivity...
October 1, 2017: NeuroImage
https://www.readbyqxmd.com/read/28678984/association-of-neural-and-emotional-impacts-of-reward-prediction-errors-with-major-depression
#19
Robb B Rutledge, Michael Moutoussis, Peter Smittenaar, Peter Zeidman, Tanja Taylor, Louise Hrynkiewicz, Jordan Lam, Nikolina Skandali, Jenifer Z Siegel, Olga T Ousdal, Gita Prabhu, Peter Dayan, Peter Fonagy, Raymond J Dolan
Importance: Major depressive disorder (MDD) is associated with deficits in representing reward prediction errors (RPEs), which are the difference between experienced and predicted reward. Reward prediction errors underlie learning of values in reinforcement learning models, are represented by phasic dopamine release, and are known to affect momentary mood. Objective: To combine functional neuroimaging, computational modeling, and smartphone-based large-scale data collection to test, in the absence of learning-related concerns, the hypothesis that depression attenuates the impact of RPEs...
August 1, 2017: JAMA Psychiatry
https://www.readbyqxmd.com/read/28626018/dissecting-the-function-of-hippocampal-oscillations-in-a-human-anxiety-model
#20
RANDOMIZED CONTROLLED TRIAL
Saurabh Khemka, Gareth Barnes, Raymond J Dolan, Dominik R Bach
Neural oscillations in hippocampus and medial prefrontal cortex (mPFC) are a hallmark of rodent anxiety models that build on conflict between approach and avoidance. Yet, the function of these oscillations, and their expression in humans, remain elusive. Here, we used magnetoencephalography (MEG) to investigate neural oscillations in a task that simulated approach-avoidance conflict, wherein 23 male and female human participants collected monetary tokens under a threat of virtual predation. Probability of threat was signaled by color and learned beforehand by direct experience...
July 19, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
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