Learning the value of information in an uncertain world

By Timothy Edward John Behrens, Mark William Woolrich, M. Walton, Matthew F. S. Rushworth. 2007

2,010 citations recorded by the source corpus.

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In Cognitive Neuroscience

Citations in the corpus

Human Reinforcement Learning Subdivides Structured Action Spaces by Learning Effector-Specific Values (2009, methodology): “We tested our hypotheses concerning decomposition using the chosen action value (rather than, say, the option-specific action value for some particular option such as the triangle) since this is the value most often reported to correlate with BOLD signaling (Daw et al., 2006a; Behrens et al., 2007; ”
Neural computations associated with goal-directed choice. (2010, background): “The conditioning theory has been extensively reviewed elsewhere [2,9,18,31], therefore we focus on what is known about the validity of the integration hypothesis.”
Counterfactual Choice and Learning in a Neural Network Centered on Human Lateral Frontopolar Cortex (2011, methodology): “An optimal Bayesian learner [13] was used to model participant estimates of the probabilities of reward associated with the options given the history of recent choice outcomes (i.”
The neural correlates of tinnitus-related distress (2010, neutral): “Interestingly, whenever new information is presented, activity levels of the dACC reflect the salience of the new information for predicting future outcomes (Behrens et al., 2007; Critchley, 2005), guiding optimal decision making in an uncertain world (Kennerley et al., 2006).”
Behavioral / Systems / Cognitive Striatal Prediction Error Modulates Cortical Coupling (2010, neutral): “For example, human subjects can infer changing conditional probabilities among sensory events (Behrens et al., 2007; Brodersen et al., 2008), even when these probabilities are not relevant for overt behavior (den Ouden et al., 2009).”
The Cognitive Neuroscience of Metacognition (2014, methodology): “At the beginning of experimental psychology William James, for one, believed that one method to study the mind should be the direct, inner observation of consciousness [6].”
Informatic parcellation of the network involved in the computation of subjective value. (2014, background): “This area has had several wide classes of computations attributed to it, including decision and strategic control (Venkatraman et al., 2009), environment volatility (Behrens et al., 2007) and multiplexing of decision parameters (Kennerley et al., 2009; Hayden and Platt, 2010; Hare et al., 2011b).”
Exploration from Generalization Mediated by Multiple Controllers (2013, background): “Furthermore, this learning rate is represented in a neural structure (the anterior cingulate cortex) that is likely involved in model-based control (Behrens et al. 2007).”
Prefrontal cortex as a meta-reinforcement learning system (2018, methodology): “human subjects performed in Behrens et al.(34).”
Cognitive control over learning: creating, clustering, and generalizing task-set structure. (2013, neutral): “S 1 S 2 + + 0 0 0 0 0 0 0 0 0 0 0 0 + + + 0 0 0 0 0 0 + 0 0 0 0 0 0 + C 1 C 2 C 3 C 4 TS 2 TS 3 TS 1 C 1 C 2 C 3 C 4”
Midbrain dopamine neurons signal preference for advance information about upcoming rewards (2009, background): “Indeed, signals encoding the amount and timing of reward information, and dissociated from preference coding of traditional rewards, have been found in several cortical areas (Nakamura, 2006; Behrens et al., 2007; Luhmann et al., 2008).”