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Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package
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Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
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The 110 checked references that resolve
resolves10.1016/j.psychres.2006.03.026
Ultimatum bargaining behavior of people affected by schizophrenia
resolves10.1016/j.cobeha.2016.02.001
Challenges and promises for translating computational tools into clinical practice
resolves10.1080/03640210802352992
Comparison of Decision Learning Models Using the Generalization Criterion Method
resolves10.1037/a0020684
A model-based fMRI analysis with hierarchical Bayesian parameter estimation.
resolves10.3389/fpsyt.2016.00034
Utility of Machine-Learning Approaches to Identify Behavioral Markers for Substance Use Disorders: Impulsivity Dimensions as Predictors of Current Cocaine Dependence
resolves10.1037/a0023333
Temporal discounting of rewards in patients with bipolar disorder and schizophrenia.
resolves10.1016/j.drugalcdep.2016.02.008
Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence
resolves10.3389/fpsyg.2014.00849
Decision-making in stimulant and opiate addicts in protracted abstinence: evidence from computational modeling with pure users
resolves10.1371/journal.pone.0152781
Reduction of Pavlovian Bias in Schizophrenia: Enhanced Effects in Clozapine-Administered Patients
resolves10.1016/j.jmp.2013.12.002
A Bayesian hierarchical mixture approach to individual differences: Case studies in selective attention and representation in category learning
resolves10.1016/0010-0277(94)90018-3
Insensitivity to future consequences following damage to human prefrontal cortex
resolves10.1016/S0028-3932(00)00136-6
Decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers
resolves10.1037/0894-4105.18.1.152
Impaired Decision Making Related to Working Memory Deficits in Individuals With Substance Addictions.
resolves10.1016/S1053-8119(03)00113-7
Orbitofrontal cortex dysfunction in abstinent cocaine abusers performing a decision-making task
resolves10.1007/BF02294361
Model Selection and Akaike's Information Criterion (AIC): The General Theory and its Analytical Extensions
resolves10.1006/jmps.1999.1282
Model Comparisons and Model Selections Based on Generalization Criterion Methodology
resolves10.1002/eat.22223
Differential impairments underlying decision making in anorexia nervosa and bulimia nervosa: A cognitive modeling analysis
resolves10.1523/JNEUROSCI.22-11-04563.2002
Defining the Neural Mechanisms of Probabilistic Reversal Learning Using Event-Related Functional Magnetic Resonance Imaging
resolves10.1038/sj.npp.1301153
L-DOPA Disrupts Activity in the Nucleus Accumbens during Reversal Learning in Parkinson's Disease
resolves10.1016/j.psychres.2010.10.005
Are patients with schizophrenia rational maximizers? Evidence from an ultimatum game study
resolves10.1371/journal.pcbi.1003441
VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data
resolves10.1016/j.neuron.2013.08.030
Dissociable Effects of Dopamine and Serotonin on Reversal Learning
resolves10.1287/mnsc.1060.0671
The Fragility of Time: Time-Insensitivity and Valuation of the Near and Far Future
resolves10.1002/bdm.683
A choice prediction competition: Choices from experience and from description
resolves10.1007/s00213-007-1051-1
Chronic cocaine but not chronic amphetamine use is associated with perseverative responding in humans
resolves10.1093/brain/awg180
Ventromedial frontal cortex mediates affective shifting in humans: evidence from a reversal learning paradigm
resolves10.1016/j.jmp.2009.10.002
Cognitive mechanisms underlying risky decision-making in chronic cannabis users
resolves10.1214/06-BA117A
Prior distributions for variance parameters in hierarchical models (comment on
article by Browne and Draper)
resolves10.1016/j.neuron.2010.04.016
States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning
resolves10.1093/cercor/bhn098
Determining a Role for Ventromedial Prefrontal Cortex in Encoding Action-Based Value Signals During Reward-Related Decision Making
resolves10.1016/S0028-3932(99)00158-X
Drug abusers show impaired performance in a laboratory test of decision making
resolves10.1037/0033-2909.130.5.769
A Discounting Framework for Choice With Delayed and Probabilistic Rewards.
resolves10.1523/JNEUROSCI.2906-14.2015
Necessary, Yet Dissociable Contributions of the Insular and Ventromedial Prefrontal Cortices to Norm Adaptation: Computational and Lesion Evidence in Humans
resolves10.1016/j.neuroimage.2012.04.024
Go and no-go learning in reward and punishment: Interactions between affect and effect
resolves10.1523/JNEUROSCI.1010-06.2006
The Role of the Ventromedial Prefrontal Cortex in Abstract State-Based Inference during Decision Making in Humans
resolves10.1037/a0021810
Imagining the future: Degraded representations of future rewards and events in schizophrenia.
resolves10.1111/j.0956-7976.2004.00715.x
Decisions from Experience and the Effect of Rare Events in Risky Choice
resolves10.1371/journal.pcbi.1002028
Disentangling the Roles of Approach, Activation and Valence in Instrumental and Pavlovian Responding
resolves10.1038/nn.4238
Computational psychiatry as a bridge from neuroscience to clinical applications
resolves10.1016/j.neuron.2013.09.009
Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning
resolves10.1176/appi.ajp.2014.14020138
The NIMH Research Domain Criteria (RDoC) Project: Precision Medicine for Psychiatry
resolves10.1016/j.jmp.2016.03.007
How hierarchical models improve point estimates of model parameters at the individual level
resolves10.1016/j.tins.2004.10.007
The Bayesian brain: the role of uncertainty in neural coding and computation
resolves10.1177/1745691611406925
Bayesian Assessment of Null Values Via Parameter Estimation and Model Comparison
resolves10.1016/j.jmp.2010.08.013
How cognitive modeling can benefit from hierarchical Bayesian models
resolves10.1023/A:1008929526011
WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility
resolves10.1002/jeab.4
INTEGRATING BEHAVIORAL ECONOMICS AND BEHAVIORAL GENETICS: DELAYED REWARD DISCOUNTING AS AN ENDOPHENOTYPE FOR ADDICTIVE DISORDERS
resolves10.1523/JNEUROSCI.2925-08.2008
Trial-by-Trial Fluctuations in the Event-Related Electroencephalogram Reflect Dynamic Changes in the Degree of Surprise
resolves10.3389/fpsyg.2013.00918
Release the BEESTS: Bayesian Estimation of Ex-Gaussian STop-Signal reaction time distributions
resolves10.1017/S0033291702007018
Neuropsychological impairment in patients with major depressive disorder: the effects of feedback on task performance
resolves10.1523/JNEUROSCI.23-21-07931.2003
Dissociating Valence of Outcome from Behavioral Control in Human Orbital and Ventral Prefrontal Cortices
resolves10.1126/science.1094285
Dissociable Roles of Ventral and Dorsal Striatum in Instrumental Conditioning
resolves10.1196/annals.1390.022
Model‐Based fMRI and Its Application to Reward Learning and Decision Making
resolves10.1523/JNEUROSCI.2322-15.2015
Transcranial Stimulation over Frontopolar Cortex Elucidates the Choice Attributes and Neural Mechanisms Used to Resolve Exploration–Exploitation Trade-Offs
resolves10.1037/dec0000030
Individual differences and fitting methods for the two-choice diffusion model of decision making.
resolves10.1136/jnnp.57.12.1518
Emotion-related learning in patients with social and emotional changes associated with frontal lobe damage.
resolves10.1080/03640210802414826
A Survey of Model Evaluation Approaches With a Tutorial on Hierarchical Bayesian Methods
resolves10.1093/scan/nss002
Emotion regulation reduces loss aversion and decreases amygdala responses to losses
resolves10.1073/pnas.0806761106
Thinking like a trader selectively reduces individuals' loss aversion
resolves10.1037/dec0000005
Absolute performance of reinforcement-learning models for the Iowa Gambling Task.
resolves10.1016/S2215-0366(15)00361-2
Charting the landscape of priority problems in psychiatry, part 1: classification and diagnosis
resolves10.1016/S2215-0366(15)00360-0
Charting the landscape of priority problems in psychiatry, part 2: pathogenesis and aetiology
resolves10.1016/S0028-3932(99)00103-7
Probabilistic learning and reversal deficits in patients with Parkinson’s disease or frontal or temporal lobe lesions: possible adverse effects of dopaminergic medication
resolves10.1371/journal.pone.0068962
Computational Modeling Reveals Distinct Effects of HIV and History of Drug Use on Decision-Making Processes in Women
resolves10.1016/j.addbeh.2007.04.017
Are all drug addicts impulsive? Effects of antisociality and extent of multidrug use on cognitive and motor impulsivity
resolves10.3758/s13428-015-0672-2
Hierarchical Bayesian estimation and hypothesis testing for delay discounting tasks
resolves10.32614/RJ-2014-005
The RWiener Package: an R Package Providing Distribution Functions for the Wiener Diffusion Model
resolves10.1016/j.schres.2007.03.010
Probabilistic reversal learning impairments in schizophrenia: Further evidence of orbitofrontal dysfunction
resolves10.1016/j.jmp.2008.12.001
Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task
resolves10.1177/2167702614565359
Model-Based Cognitive Neuroscience Approaches to Computational Psychiatry
resolves10.3389/fninf.2013.00014
HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python
resolves10.3389/fpsyg.2013.00640
Decomposing the roles of perseveration and expected value representation in models of the Iowa gambling task
resolves10.1523/JNEUROSCI.1642-12.2013
Computational Substrates of Norms and Their Violations during Social Exchange
The 2 references without a DOI — listed, not checked
no DOI — not checkedHoffman, M.
D. & Gelman,
A. (2014). The No-U-Turn Sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo. Journal of Machine Learning Research, 15, 1593–1623.
no DOI — not checkedPlummer,
M. (2003, March). JAGS: A program for analysis of Bayes ian graphical models using Gibbs sampling. Article presented at the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), Vienna, Austria.
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