Foundations of Neuroeconomic Analysis
By Paul Glimcher. 2010
256 citations recorded by the source corpus.
Subfields: General Decision Sciences
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In General Decision Sciences
- John A. Clithero
- Antonio Rangel
- H. Plassmann
- Scott A. Huettel
- E. Tan
- Martin E. P. Seligman
- Chandra Sekhar Sripada
- P. Railton
Citations in the corpus
- The Computation of Stimulus Values in Simple Choice (2014, methodology): “Further evidence for the stability of the vmPFC value signal across stimulus modalities is provided by Levy and Glimcher (2011).”
- Prospect Theory as Efficient Perceptual Distortion (2012, background): “Let visual processing be described by conditional probabilities p(r|x) of a subjective perception of brightness r in the case of objective log luminance x.2 The degree of distor- 1See, e.g., Paul W. Glimcher (2011), chap.”
- Human Capital Theory (2014, background): “As such, under a wide range of circumstances individuals rationally seek to maximize their profits although they may fail to express it verbally in the language of economics (Glimcher, 2011).”
- Inattentive Valuation and Reference-Dependent Choice ∗ (2012, background): “Here it is assumed that the probability of obtaining a particular subjective representation ra of attribute a depends only on the true value xa of this particular attribute; this is the meaning of the assumption of independent observations of the distinct attributes.29 The additional constraint…”
- Consumer Neuroscience: Applications, Challenges, and Possible Solutions (2015, methodology): “In conclusion, a vital next step for consumer neuroscience is the integration and aggregation of previous work applying a multimethod approach for establishing meaningful multilevel brain–behavior relationships (Glimcher 2010; Kable 2011; Kable and Glimcher 2009; Yarkoni et al. 2010).”
- Informatic parcellation of the network involved in the computation of subjective value. (2014, background): “An important step in constructing a biologically plausible model of value computation in the brain (Clithero et al., 2008; Fehr and Rangel, 2011; Glimcher, 2011) requires identifying accurate constraints on computations, and networks in the brain are one of those key constraints.”
- Navigating Into the Future or Driven by the Past (2013, background): “In particular, we have assumed nothing about the role indeterminism or stochasticity might play (Glimcher, 2011; Grabenhorst & Rolls, 2011; Neuringer, 2002).”