A framework for studying the neurobiology of value-based decision making

By Antonio Rangel, Colin F. Camerer, P. R. Montague. Nature Reviews Neuroscience, 2008

2,092 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, General Decision Sciences

View Paper: https://www.semanticscholar.org/paper/d485360c620388cc03d4331323c35bfb95a90c20

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Citations in the corpus

Evidence for a Common Representation of Decision Values for Dissimilar Goods in Human Ventromedial Prefrontal Cortex (2009, methodology): “Recently, many different types of value signal have been found to be encoded in brain structures such as the orbitofrontal cortex (OFC) and adjacent medial prefrontal cortex, amygdala, ventral striatum, and elsewhere (Buchel et al., 1998; Gallagher et al., 1999; O’Doherty et al., 2000; Knutson et al”
How the brain integrates costs and benefits during decision making (2010, result): “Consistent with theoretical proposals and behavioral modeling results (3, 4, 8, 12, 13), we hypothesized that the same basic brain mechanisms that were successfully used to explain perceptual decision making can also explain value-based decision making.”
The Computation of Stimulus Values in Simple Choice (2014, background): “…seeks to produce detailed computational and neurobiological accounts of the choice process that can serve as a common foundation for understanding human behavior across the natural and social sciences (Clithero et al., 2008; Fehr and Rangel, 2011; Glimcher, 2011; Rangel et al., 2008; Wilson, 1998).”
Hyperbolic Discounting and Learning over Multiple Horizons (2019, background): “…present issues since the simple forms are inconsistent (Daw & Touretzky, 2000; Redish & Kurth-Nelson, 2010) RL models have been proposed to explain behavioral effects of humans and animals (Fu & Anderson, 2006; Rangel et al., 2008) Towards more ﬂexible discounting in reinforcement learning.”
Informatic parcellation of the network involved in the computation of subjective value. (2014, background): “There is a growing consensus that the assignment of values to stimuli is a critical part of both processes (Rangel et al., 2008; Glimcher, 2011; Grabenhorst and Rolls, 2011; Rushworth et al., 2011, Wallis, 2012), and that the ventromedial prefrontal cortex (VMPFC) plays a critical role in the comput”
Collective decision-making (2017, background): “Conceptualising value-based decisions shows, however, that there are similarities between perceptual and valuebased decision making [17,18], although the usage of the term ‘value’ may vary with context [19]; value may refer to stimulus intensity, or to reward magnitude.”
The orbitofrontal cortex and beyond: from affect to decision-making. (2008, background): “…expected value, this is not exactly the case, with subjects typically undervaluing high rewards, and being over-sensitive to high punishments (Bernoulli, 1738/1954; Gintis, 2000; Kahneman and Tversky, 1979, 1984; Rangel et al., 2008; Tversky and Kahneman, 1986; von Neumann and Morgenstern, 1944).”
Goals and Habits in the Brain (2013, neutral): “Many of the issues that we lack space to discuss are treated by others (Rangel et al., 2008; Botvinick, 2012; Berridge, 2001; Padoa-Schioppa and Assad, 2006; Daw et al., 2006a; Dayan and Daw, 2008; Balleine and O’Doherty, 2010; Yin and Knowlton, 2006; Maia, 2009; Niv, 2009; Doll et al., 2012).”
Burst timing-dependent plasticity of NMDA receptor-mediated transmission in midbrain dopamine neurons: A putative cellular substrate for reward learning (2009, positive): “Efficient reward learning is of obvious adaptive value – the more accurate the internal model of environmental reward contingency, the better the decisions about which options to pursue in a complex world, and the higher the chances of survival and reproductive success (Doya, 2008; Floresco et al., ”
Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package (2016, background): “However, in RA models they control the valuations of the possible choices under consideration, as opposed to the evaluation of outcomes after they are experienced (Rangel et al., 2008).”
Social and monetary reward learning engage overlapping neural substrates. (2012, background): “…to the different stimuli associated with each choice option [which we refer to as stimulus values (SV)]; these are subsequently compared in order to choose the option with the highest value (Wallis, 2007; Rangel et al., 2008; Kable and Glimcher, 2009; Rushworth et al., 2009; Rangel and Hare, 2010).”
Emotion Regulation: Current Status and Future Prospects (2015, background): “In Figure 7A, I present a highly schematized valuation system (see Carver & Scheier, 1982, 2013; Magen & Gross, 2010; Miller, Galanter, & Pribram, 1960; Powers, Clark, & McFarland, 1960a, 1960b; Rangel et al., 2008; Wiener, 1948).”
Counterfactual Choice and Learning in a Neural Network Centered on Human Lateral Frontopolar Cortex (2011, background): “for decision making [1].”