Simulating a story character ’s thoughts: Evidence from the directed forgetting task
Publication date: October 2017 Source:Journal of Memory and Language, Volume 96 Author(s): Danielle N. Gunraj, Sri Siddhi N. Upadhyay, Kenneth J. Houghton, Deanne L. Westerman, Celia M. Klin Readers’ memory representations have been shown to include the sensory details of characters’ movement, dialogue, and navigation through space and time (e.g., Glenberg & Kaschak, 2002; Gunraj, Drumm-Hewitt, & Klin, 2014; Levine & Klin, 2001; Zwaan, 1996). We ask whether readers also encode the mental experiences of story characters, such as their thoughts and goals. To examine this question, we used a variation of the list-method directed forgetting paradigm (Bjork, 1970), with two word-lists embedded within a narrative. In contrast with the traditional directed forgetting paradigm, it was the story character, rather than the participant, who needed to remember List 1 or forget List 1. If readers take the character’s perspective, the character’s intention to remember or forget List 1 should influence the reader’s intention to remember or forget List 1. This, in turn, should produce the typical pattern of effects for directed forgetting: decreased recall for List 1 (costs) and increased recall for List 2 (benefits) in the Forget condition relative to the Remember condition. The List 2 benefits were found across experiments, even without explicit instructions to forget or remember List 1. However, the List 1 costs were not reliable. Results are dis...
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This article is protected by copyright. All rights reserved. The phosphodiesterase VieA regulates gene expression by modifying the intracellular cyclic diguanylate pool. This article reveals the differential regulation of VieA in Vibrio cholerae O1 biotypes. Expression of VieA is repressed by the nucleoid‐associated protein H‐NS and the LysR‐type regulator LeuO in classical biotype V. cholerae, and by H‐NS and the quorum sensing regulator HapR in the El Tor biotype.
We describe approaches for back‐calculating model parameter estimates and their standard errors from available summary statistics with various techniques, including approximate Bayesian computation. We propose to use a quadratic approximation to the log‐likelihood for each historical trial based on 2 independent terms for the log mean rate and the log of the dispersion parameter. A Bayesian hierarchical meta‐analysis model then provides the posterior predictive distribution for these parameters. Simulations show this approach with back‐calculated parameter estimates results in very similar inference as using parame...