about
A computational psychiatry approach identifies how alpha-2A noradrenergic agonist Guanfacine affects feature-based reinforcement learning in the macaque.Learning to represent a multi-context environment: more than detecting changes.Electrophysiological responses to feedback during the application of abstract rules.Statistical computations underlying the dynamics of memory updating.Reinforcement learning in multidimensional environments relies on attention mechanismsIs Model Fitting Necessary for Model-Based fMRI?Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism.Dynamic Interaction between Reinforcement Learning and Attention in Multidimensional Environments.Attention, learning, and the value of informationNeural Mechanisms of Credit Assignment in a Multicue Environment.A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning.Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.Reward-related activity in ventral striatum is action contingent and modulated by behavioral relevance.Differential effects of reward and punishment in decision making under uncertainty: a computational studyCognitive control over learning: creating, clustering, and generalizing task-set structure.How can a Bayesian approach inform neuroscience?Making predictions in a changing world-inference, uncertainty, and learning.Orbitofrontal cortex as a cognitive map of task space.Comparative Analysis of Behavioral Models for Adaptive Learning in Changing Environments.Neural signature of hierarchically structured expectations predicts clustering and transfer of rule sets in reinforcement learning.Investigation of Biases and Compensatory Strategies Using a Probabilistic Variant of the Wisconsin Card Sorting Test.Applying novel technologies and methods to inform the ontology of self-regulation.Learning the value of information and reward over time when solving exploration-exploitation problems.Incremental implicit learning of bundles of statistical patterns.Exploring Feature Dimensions to Learn a New Policy in an Uninformed Reinforcement Learning Task.Feature-based learning improves adaptability without compromising precision.Solving the Credit Assignment Problem With the Prefrontal Cortex.Detecting change in stochastic sound sequences.Dual-Task Processing With Identical Stimulus and Response Sets: Assessing the Importance of Task Representation in Dual-Task Interference.
P2860
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P2860
description
2011 nî lūn-bûn
@nan
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
2011年论文
@zh
2011年论文
@zh-cn
name
Inferring relevance in a changing world.
@ast
Inferring relevance in a changing world.
@en
type
label
Inferring relevance in a changing world.
@ast
Inferring relevance in a changing world.
@en
prefLabel
Inferring relevance in a changing world.
@ast
Inferring relevance in a changing world.
@en
P2860
P356
P1476
Inferring relevance in a changing world.
@en
P2093
Robert C Wilson
P2860
P356
10.3389/FNHUM.2011.00189
P50
P577
2011-01-01T00:00:00Z