Target learning in event-based prospective memory
Event-based prospective memory (PM) tasks require individuals to remember to perform a previously planned action when they encounter a specific event. Often, the natural environments in which PM tasks occur are embedded are constantly changing, requiring humans to adapt by learning. We examine on...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
APA
2020
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| Online Access: | http://purl.org/au-research/grants/arc/DP160101891 http://hdl.handle.net/20.500.11937/81481 |
| _version_ | 1848764374211100672 |
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| author | Strickland, Luke Heathcote, Andrew Humphreys, Michael S Loft, Shayne |
| author_facet | Strickland, Luke Heathcote, Andrew Humphreys, Michael S Loft, Shayne |
| author_sort | Strickland, Luke |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Event-based prospective memory (PM) tasks require individuals to remember to perform a
previously planned action when they encounter a specific event. Often, the natural
environments in which PM tasks occur are embedded are constantly changing, requiring
humans to adapt by learning. We examine one such adaptation by integrating PM target
learning with the Prospective Memory Decision Control (PMDC) cognitive model. We
apply this augmented model to an experiment that manipulated exposure to PM targets,
comparing a single-target PM condition where the target was well learned from the outset,
to a multiple-target PM condition with less initial PM target exposure, allowing us to
examine the effect of continued target learning opportunities. Single-target PM accuracy
was near ceiling whereas multiple-target PM accuracy was initially poorer but improved
throughout the course of the experiment. PM response times were longer for the multiplecompared to single-target PM task but this difference also decreased over time. The model
indicated that PM trial evidence accumulation rates, and the inhibition of competing
responses, were initially higher for single compared to multiple PM targets, but that this
difference decreased over time due to the learning of multiple-targets over the target
repetitions. These outcomes provide insight into how the processes underlying event-based
PM can dynamically evolve over time, and a modelling framework to further investigate
the effect of learning on event-based PM decision processes. |
| first_indexed | 2025-11-14T11:18:20Z |
| format | Journal Article |
| id | curtin-20.500.11937-81481 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:18:20Z |
| publishDate | 2020 |
| publisher | APA |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-814812021-08-04T04:28:38Z Target learning in event-based prospective memory Strickland, Luke Heathcote, Andrew Humphreys, Michael S Loft, Shayne Event-based prospective memory (PM) tasks require individuals to remember to perform a previously planned action when they encounter a specific event. Often, the natural environments in which PM tasks occur are embedded are constantly changing, requiring humans to adapt by learning. We examine one such adaptation by integrating PM target learning with the Prospective Memory Decision Control (PMDC) cognitive model. We apply this augmented model to an experiment that manipulated exposure to PM targets, comparing a single-target PM condition where the target was well learned from the outset, to a multiple-target PM condition with less initial PM target exposure, allowing us to examine the effect of continued target learning opportunities. Single-target PM accuracy was near ceiling whereas multiple-target PM accuracy was initially poorer but improved throughout the course of the experiment. PM response times were longer for the multiplecompared to single-target PM task but this difference also decreased over time. The model indicated that PM trial evidence accumulation rates, and the inhibition of competing responses, were initially higher for single compared to multiple PM targets, but that this difference decreased over time due to the learning of multiple-targets over the target repetitions. These outcomes provide insight into how the processes underlying event-based PM can dynamically evolve over time, and a modelling framework to further investigate the effect of learning on event-based PM decision processes. 2020 Journal Article http://hdl.handle.net/20.500.11937/81481 10.1037/xlm0000900 http://purl.org/au-research/grants/arc/DP160101891 http://purl.org/au-research/grants/arc/DP160100575 APA fulltext |
| spellingShingle | Strickland, Luke Heathcote, Andrew Humphreys, Michael S Loft, Shayne Target learning in event-based prospective memory |
| title | Target learning in event-based prospective memory |
| title_full | Target learning in event-based prospective memory |
| title_fullStr | Target learning in event-based prospective memory |
| title_full_unstemmed | Target learning in event-based prospective memory |
| title_short | Target learning in event-based prospective memory |
| title_sort | target learning in event-based prospective memory |
| url | http://purl.org/au-research/grants/arc/DP160101891 http://purl.org/au-research/grants/arc/DP160101891 http://hdl.handle.net/20.500.11937/81481 |