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Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator
The parameters governing our behavior are in constant flux. Accurately capturing these dynamics in cognitive models poses a challenge to modelers. Here, we demonstrate a mapping of ACT‐R's declarative memory onto the linear ballistic accumulator (LBA), a mathematical model describing a competit...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790673/ https://www.ncbi.nlm.nih.gov/pubmed/35531959 http://dx.doi.org/10.1111/tops.12614 |
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author | van der Velde, Maarten Sense, Florian Borst, Jelmer P. van Maanen, Leendert van Rijn, Hedderik |
author_facet | van der Velde, Maarten Sense, Florian Borst, Jelmer P. van Maanen, Leendert van Rijn, Hedderik |
author_sort | van der Velde, Maarten |
collection | PubMed |
description | The parameters governing our behavior are in constant flux. Accurately capturing these dynamics in cognitive models poses a challenge to modelers. Here, we demonstrate a mapping of ACT‐R's declarative memory onto the linear ballistic accumulator (LBA), a mathematical model describing a competition between evidence accumulation processes. We show that this mapping provides a method for inferring individual ACT‐R parameters without requiring the modeler to build and fit an entire ACT‐R model. Existing parameter estimation methods for the LBA can be used, instead of the computationally expensive parameter sweeps that are traditionally done. We conduct a parameter recovery study to confirm that the LBA can recover ACT‐R parameters from simulated data. Then, as a proof of concept, we use the LBA to estimate ACT‐R parameters from an empirical dataset. The resulting parameter estimates provide a cognitively meaningful explanation for observed differences in behavior over time and between individuals. In addition, we find that the mapping between ACT‐R and LBA lends a more concrete interpretation to ACT‐R's latency factor parameter, namely as a measure of response caution. This work contributes to a growing movement towards integrating formal modeling approaches in cognitive science. |
format | Online Article Text |
id | pubmed-9790673 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97906732022-12-28 Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator van der Velde, Maarten Sense, Florian Borst, Jelmer P. van Maanen, Leendert van Rijn, Hedderik Top Cogn Sci Article The parameters governing our behavior are in constant flux. Accurately capturing these dynamics in cognitive models poses a challenge to modelers. Here, we demonstrate a mapping of ACT‐R's declarative memory onto the linear ballistic accumulator (LBA), a mathematical model describing a competition between evidence accumulation processes. We show that this mapping provides a method for inferring individual ACT‐R parameters without requiring the modeler to build and fit an entire ACT‐R model. Existing parameter estimation methods for the LBA can be used, instead of the computationally expensive parameter sweeps that are traditionally done. We conduct a parameter recovery study to confirm that the LBA can recover ACT‐R parameters from simulated data. Then, as a proof of concept, we use the LBA to estimate ACT‐R parameters from an empirical dataset. The resulting parameter estimates provide a cognitively meaningful explanation for observed differences in behavior over time and between individuals. In addition, we find that the mapping between ACT‐R and LBA lends a more concrete interpretation to ACT‐R's latency factor parameter, namely as a measure of response caution. This work contributes to a growing movement towards integrating formal modeling approaches in cognitive science. John Wiley and Sons Inc. 2022-05-09 2022-10 /pmc/articles/PMC9790673/ /pubmed/35531959 http://dx.doi.org/10.1111/tops.12614 Text en © 2022 The Authors. Topics in Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article van der Velde, Maarten Sense, Florian Borst, Jelmer P. van Maanen, Leendert van Rijn, Hedderik Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator |
title | Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator |
title_full | Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator |
title_fullStr | Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator |
title_full_unstemmed | Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator |
title_short | Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator |
title_sort | capturing dynamic performance in a cognitive model: estimating act‐r memory parameters with the linear ballistic accumulator |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790673/ https://www.ncbi.nlm.nih.gov/pubmed/35531959 http://dx.doi.org/10.1111/tops.12614 |
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