2018
DOI: 10.7554/elife.36395
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Model-based fMRI reveals dissimilarity processes underlying base rate neglect

Abstract: Extensive evidence suggests that people use base rate information inconsistently in decision making. A classic example is the inverse base rate effect (IBRE), whereby participants classify ambiguous stimuli sharing features of both common and rare categories as members of the rare category. Computational models of the IBRE have posited that it arises either from associative similarity-based mechanisms or from dissimilarity-based processes that may depend on higher-level inference. Here we develop a hybrid mode… Show more

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Cited by 13 publications
(14 citation statements)
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References 63 publications
(125 reference statements)
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“…The parametric increase in the ventral precuneus and the vmPFC, and the link between BOLD activity in the ventral precuneus and performance at the final test, could thus demonstrate a process of aiding retrieval, and response selection of stronger memory representations between trials. For example, exemplar-based processes in the vmPFC corroborates well recent findings linking this region to the level of evidence for similarity-based category decisions (Davis et al, 2017; O’Bryan et al, 2018). The ventral precuneus was consistently engaged during learning, and activity levels in the ventral precuneus and the vmPFC predicted EBM fit at the final test.…”
Section: Discussionsupporting
confidence: 85%
“…The parametric increase in the ventral precuneus and the vmPFC, and the link between BOLD activity in the ventral precuneus and performance at the final test, could thus demonstrate a process of aiding retrieval, and response selection of stronger memory representations between trials. For example, exemplar-based processes in the vmPFC corroborates well recent findings linking this region to the level of evidence for similarity-based category decisions (Davis et al, 2017; O’Bryan et al, 2018). The ventral precuneus was consistently engaged during learning, and activity levels in the ventral precuneus and the vmPFC predicted EBM fit at the final test.…”
Section: Discussionsupporting
confidence: 85%
“…There was no significant difference between the two groups for stress (Table 1). For the fMRI data, an analysis pipeline was used in the previous studies for both preprocessing and univariate analysis (O'Bryan et al, 2018). The primary contrast of interest was comparing differences in activation between the hospitality and nonhospitality groups when viewing the angry, neutral, or happy faces.…”
Section: Methodology and Analysis Instrumentation And Participantsmentioning
confidence: 99%
“…In the highlighting effect, BC trials elicit a preference for the late outcome, O2. While research on the inverse base-rate effect was most prominent between the late-1980s and early-2000s, it has recently received renewed interest (e.g., Don & Livesey, 2017;Don, Beesley, & Livesey, 2019a;Inkster, Milton, Edmunds, Benattayallah, & Wills, 2019a;Inkster, Mitchell, Schlegelmilch, & Wills, 2019b;Le Pelley et al, 2016;O'Bryan, Worthy, Livesey, & Davis, 2018;Wills et al, 2014). Specifically, for reasons that are discussed below, the inverse base-rate effect has been highlighted as an important phenomenon because it may discriminate between different attentionbased models of learning.…”
Section: Why Is the Inverse Base-rate Effect Important?mentioning
confidence: 99%
“…The dissGCM incorporates standard computations of similarity to memories of learned exemplars (Nosofsky, 1986), with calculations of dissimilarity to those exemplars, with both contributing to decisions about category membership. O'Bryan et al (O'Bryan et al, 2018) used this model to find independent neural correlates of similarity and dissimilarity processes while participants performed an inverse base-rate task. While it remains open to debate whether similarity and dissimilarity processes reflect the operation of qualitatively distinct psychological operations (like reasoning and associative memory), they do at least appear to engage different neural circuits.…”
Section: Self-report Measuresmentioning
confidence: 99%