Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2019 Jul 18;9:10448. doi: 10.1038/s41598-019-46908-z

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

PMC Copyright notice

Hierarchical model results. (a) Value of the induced p₁₆ in the model simulations as a function of α. Blue line is the average of the value of p₁₆ with a confidence interval of 95%. (b) Scatter plot of the performance as a function of p₁₆ both data and model. For each session the number of words retrieved in FFR is shown against the p₁₆ score. (c) Scatter plot for the number of sequences retrieved as a function of p₁₆ for each session both data and model. (d) Scatter plot for the percentage of words not retrieved in the IFR but recalled in the FFR as a function of p₁₆ for each session both data and model.