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Raymond Dolan

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https://www.readbyqxmd.com/read/29190275/correction-approach-induced-biases-in-human-information-sampling
#1
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
#2
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.
November 21, 2017: International Journal of Epidemiology
https://www.readbyqxmd.com/read/29061228/neural-and-computational-processes-underlying-dynamic-changes-in-self-esteem
#3
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
#4
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...
October 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
#5
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
#6
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 learnt 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...
September 26, 2017: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/28808037/separate-mesocortical-and-mesolimbic-pathways-encode-effort-and-reward-learning-signals
#7
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
#8
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
#9
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
#10
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
#11
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
https://www.readbyqxmd.com/read/28607064/impact-of-nutrition-on-social-decision-making
#12
Sabrina Strang, Christina Hoeber, Olaf Uhl, Berthold Koletzko, Thomas F Münte, Hendrik Lehnert, Raymond J Dolan, Sebastian M Schmid, Soyoung Q Park
Food intake is essential for maintaining homeostasis, which is necessary for survival in all species. However, food intake also impacts multiple biochemical processes that influence our behavior. Here, we investigate the causal relationship between macronutrient composition, its bodily biochemical impact, and a modulation of human social decision making. Across two studies, we show that breakfasts with different macronutrient compositions modulated human social behavior. Breakfasts with a high-carbohydrate/protein ratio increased social punishment behavior in response to norm violations compared with that in response to a low carbohydrate/protein meal...
June 20, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28527671/inferences-about-moral-character-moderate-the-impact-of-consequences-on-blame-and-praise
#13
Jenifer Z Siegel, Molly J Crockett, Raymond J Dolan
Moral psychology research has highlighted several factors critical for evaluating the morality of another's choice, including the detection of norm-violating outcomes, the extent to which an agent caused an outcome, and the extent to which the agent intended good or bad consequences, as inferred from observing their decisions. However, person-centered accounts of moral judgment suggest that a motivation to infer the moral character of others can itself impact on an evaluation of their choices. Building on this person-centered account, we examine whether inferences about agents' moral character shape the sensitivity of moral judgments to the consequences of agents' choices, and agents' role in the causation of those consequences...
October 2017: Cognition
https://www.readbyqxmd.com/read/28489001/noradrenaline-blockade-specifically-enhances-metacognitive-performance
#14
Tobias U Hauser, Micah Allen, Nina Purg, Michael Moutoussis, Geraint Rees, Raymond J Dolan
Impairments in metacognition, the ability to accurately report one's performance, are common in patients with psychiatric disorders, where a putative neuromodulatory dysregulation provides the rationale for pharmacological interventions. Previously, we have shown how unexpected arousal modulates metacognition (Allen et al., 2016). Here, we report a double-blind, placebo-controlled, study that examined specific effects of noradrenaline and dopamine on both metacognition and perceptual decision making. Signal theoretic analysis of a global motion discrimination task with adaptive performance staircasing revealed that noradrenergic blockade (40 mg propranolol) significantly increased metacognitive performance (type-II area under the curve, AUROC2), but had no impact on perceptual decision making performance...
May 10, 2017: ELife
https://www.readbyqxmd.com/read/28486504/sequential-inference-as-a-mode-of-cognition-and-its-correlates-in-fronto-parietal-and-hippocampal-brain-regions
#15
Thomas H B FitzGerald, Dorothea Hämmerer, Karl J Friston, Shu-Chen Li, Raymond J Dolan
Normative models of human cognition often appeal to Bayesian filtering, which provides optimal online estimates of unknown or hidden states of the world, based on previous observations. However, in many cases it is necessary to optimise beliefs about sequences of states rather than just the current state. Importantly, Bayesian filtering and sequential inference strategies make different predictions about beliefs and subsequent choices, rendering them behaviourally dissociable. Taking data from a probabilistic reversal task we show that subjects' choices provide strong evidence that they are representing short sequences of states...
May 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28459442/moral-transgressions-corrupt-neural-representations-of-value
#16
Molly J Crockett, Jenifer Z Siegel, Zeb Kurth-Nelson, Peter Dayan, Raymond J Dolan
Moral systems universally prohibit harming others for personal gain. However, we know little about how such principles guide moral behavior. Using a task that assesses the financial cost participants ascribe to harming others versus themselves, we probed the relationship between moral behavior and neural representations of profit and pain. Most participants displayed moral preferences, placing a higher cost on harming others than themselves. Moral preferences correlated with neural responses to profit, where participants with stronger moral preferences had lower dorsal striatal responses to profit gained from harming others...
June 2017: Nature Neuroscience
https://www.readbyqxmd.com/read/28448253/a-map-of-abstract-relational-knowledge-in-the-human-hippocampal-entorhinal-cortex
#17
Mona M Garvert, Raymond J Dolan, Timothy Ej Behrens
The hippocampal-entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal-entorhinal system can represent relationships between objects using a metric that depends on associative strength...
April 27, 2017: ELife
https://www.readbyqxmd.com/read/28403164/characterising-the-latent-structure-and-organisation-of-self-reported-thoughts-feelings-and-behaviours-in-adolescents-and-young-adults
#18
Michelle C St Clair, Sharon Neufeld, Peter B Jones, Peter Fonagy, Edward T Bullmore, Raymond J Dolan, Michael Moutoussis, Umar Toseeb, Ian M Goodyer
Little is known about the underlying relationships between self-reported mental health items measuring both positive and negative emotional and behavioural symptoms at the population level in young people. Improved measurement of the full range of mental well-being and mental illness may aid in understanding the aetiological substrates underlying the development of both mental wellness as well as specific psychiatric diagnoses. A general population sample aged 14 to 24 years completed self-report questionnaires on anxiety, depression, psychotic-like symptoms, obsessionality and well-being...
2017: PloS One
https://www.readbyqxmd.com/read/28403139/increased-decision-thresholds-enhance-information-gathering-performance-in-juvenile-obsessive-compulsive-disorder-ocd
#19
Tobias U Hauser, Michael Moutoussis, Reto Iannaccone, Silvia Brem, Susanne Walitza, Renate Drechsler, Peter Dayan, Raymond J Dolan
Patients with obsessive-compulsive disorder (OCD) can be described as cautious and hesitant, manifesting an excessive indecisiveness that hinders efficient decision making. However, excess caution in decision making may also lead to better performance in specific situations where the cost of extended deliberation is small. We compared 16 juvenile OCD patients with 16 matched healthy controls whilst they performed a sequential information gathering task under different external cost conditions. We found that patients with OCD outperformed healthy controls, winning significantly more points...
April 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28382008/a-goal-directed-bayesian-framework-for-categorization
#20
Francesco Rigoli, Giovanni Pezzulo, Raymond Dolan, Karl Friston
Categorization is a fundamental ability for efficient behavioral control. It allows organisms to remember the correct responses to categorical cues and not for every stimulus encountered (hence eluding computational cost or complexity), and to generalize appropriate responses to novel stimuli dependant on category assignment. Assuming the brain performs Bayesian inference, based on a generative model of the external world and future goals, we propose a computational model of categorization in which important properties emerge...
2017: Frontiers in Psychology
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