Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems
Behavioral tasks are often used to study the different memory systems present in humans and animals. Such tasks are usually designed to isolate and measure some aspect of a single memory system. However, it is not necessarily clear that any given task actually does isolate a system or that the strat...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2008-12-01
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| Series: | Frontiers in Computational Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/neuro.10.006.2008/full |
| _version_ | 1811221255816216576 |
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| author | Eric A Zilli Michael E Hasselmo |
| author_facet | Eric A Zilli Michael E Hasselmo |
| author_sort | Eric A Zilli |
| collection | DOAJ |
| description | Behavioral tasks are often used to study the different memory systems present in humans and animals. Such tasks are usually designed to isolate and measure some aspect of a single memory system. However, it is not necessarily clear that any given task actually does isolate a system or that the strategy used by a subject in the experiment is the one desired by the experimenter. We have previously shown that when tasks are written mathematically as a form of partially-observable Markov decision processes, the structure of the tasks provide information regarding the possible utility of certain memory systems. These previous analyses dealt with the disambiguation problem: given a specific ambiguous observation of the environment, is there information provided by a given memory strategy that can disambiguate that observation to allow a correct decisionµ Here we extend this approach to cases where multiple memory systems can be strategically combined in different ways. Specifically, we analyze the disambiguation arising from three ways by which episodic-like memory retrieval might be cued (by another episodic-like memory, by a semantic association, or by working memory for some earlier observation). We also consider the disambiguation arising from holding earlier working memories, episodic-like memories or semantic associations in working memory. From these analyses we can begin to develop a quantitative hierarchy among memory systems in which stimulus-response memories and semantic associations provide no disambiguation while the episodic memory system provides the most flexible |
| first_indexed | 2024-04-12T07:56:12Z |
| format | Article |
| id | doaj.art-0352982ed4834f4cb2f92c6b51dc1c7c |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-04-12T07:56:12Z |
| publishDate | 2008-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-0352982ed4834f4cb2f92c6b51dc1c7c2022-12-22T03:41:29ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882008-12-01210.3389/neuro.10.006.2008291Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systemsEric A Zilli0Michael E Hasselmo1Boston UniversityBoston UniversityBehavioral tasks are often used to study the different memory systems present in humans and animals. Such tasks are usually designed to isolate and measure some aspect of a single memory system. However, it is not necessarily clear that any given task actually does isolate a system or that the strategy used by a subject in the experiment is the one desired by the experimenter. We have previously shown that when tasks are written mathematically as a form of partially-observable Markov decision processes, the structure of the tasks provide information regarding the possible utility of certain memory systems. These previous analyses dealt with the disambiguation problem: given a specific ambiguous observation of the environment, is there information provided by a given memory strategy that can disambiguate that observation to allow a correct decisionµ Here we extend this approach to cases where multiple memory systems can be strategically combined in different ways. Specifically, we analyze the disambiguation arising from three ways by which episodic-like memory retrieval might be cued (by another episodic-like memory, by a semantic association, or by working memory for some earlier observation). We also consider the disambiguation arising from holding earlier working memories, episodic-like memories or semantic associations in working memory. From these analyses we can begin to develop a quantitative hierarchy among memory systems in which stimulus-response memories and semantic associations provide no disambiguation while the episodic memory system provides the most flexiblehttp://journal.frontiersin.org/Journal/10.3389/neuro.10.006.2008/fullreinforcement learningcontent addressable sequential retrievalgated active maintenancemultiple memory systemspartially-observable Markov decision process |
| spellingShingle | Eric A Zilli Michael E Hasselmo Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems Frontiers in Computational Neuroscience reinforcement learning content addressable sequential retrieval gated active maintenance multiple memory systems partially-observable Markov decision process |
| title | Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems |
| title_full | Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems |
| title_fullStr | Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems |
| title_full_unstemmed | Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems |
| title_short | Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems |
| title_sort | analyses of markov decision process structure regarding the possible strategic use of interacting memory systems |
| topic | reinforcement learning content addressable sequential retrieval gated active maintenance multiple memory systems partially-observable Markov decision process |
| url | http://journal.frontiersin.org/Journal/10.3389/neuro.10.006.2008/full |
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