Trial-by-trial data analysis using computational models

496 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis (2012, unknown): “…we also conﬁrmed that the results reported below hold for a simple hierarchical ﬁtting procedure in which summary statistics for each parameter were estimated across the entire group of subjects and which then acted as priors for the estimation of individual subject parameters (Daw, 2011).”
Abstract context representations in primate amygdala and prefrontal cortex (2015, methodology): “Neither the presence of the contextual cue nor how recently a contextual cue appeared had a significant impact on the monkey’s propensity to anticipate reinforcement correctly (Figure S1).”
Generalization of value in reinforcement learning by humans (2012, methodology): “Structural images were collected using a high-resolution T1weighted MPRAGE pulse sequence (1 · 1 · 1 mm voxel size).”
Ten simple rules for the computational modeling of behavioral data (2019, methodology): “…advanced modeling techniques should consult the many excellent tutorials, didactic examples, and books on the topic (Busemeyer and Diederich, 2010; Daw, 2011; Daw and Tobler, 2014; Heathcote et al., 2015; Huys, 2017; Turner et al., 2013; Vandekerckhove et al., 2015; Wagenmakers and Farrell, 2004;…”