Hierarchical decision making with dynamic reward structures
Decision making is an interdisciplinary field that studies how the brain processes information to come to a commitment or choice behaviour. Over the past decades, a cascade of psychological experiments have provided key insights in establishing principles of how the brain forms a decision. The major...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2021
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| _version_ | 1797084954614562816 |
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| author | Wang, M |
| author2 | O'Reilly, J |
| author_facet | O'Reilly, J Wang, M |
| author_sort | Wang, M |
| collection | OXFORD |
| description | Decision making is an interdisciplinary field that studies how the brain processes information to come to a commitment or choice behaviour. Over the past
decades, a cascade of psychological experiments have provided key insights in
establishing principles of how the brain forms a decision. The majority of evidence came from studies with simple value comparison or categorical judgement,
whereas in real life decisions usually require multiple levels of inferences, or integration of evidence that changes across time. This thesis will first evaluate relevant theories (chapter 1) and present two experiments with novel task paradigms
to examine hierarchical decision making (i.e. multiple levels of thought processes) with dynamic reward structures (i.e. underlying reward structures vary
across time). The first experiment (chapter 2) investigates foraging, a type of
patch leaving decision that emerged in Ecology, with a virtual foraging task in
which human participants choose between gold mines and decide when to leave
to re-enter or enter a different one. The second experiment (chapter 3) investigates hierarchical perceptual decisions with a visual perception task, in which
human participants find out the target patch and report its rotation by integrating sensory evidence and tracking reward contingency. I will demonstrate how
the two experiments, combined with computational models and neurophysiological recordings, probe into the cognitive mechanisms of how the brain tracks
changes and integrates evidence across time for a specific choice or long term
estimate of option values. Finally, I will discuss how the findings contribute to
extant theories and expand our knowledge of the neural basis of decision making
in relatively complex, real life scenarios (chapter 4). |
| first_indexed | 2024-03-07T02:02:20Z |
| format | Thesis |
| id | oxford-uuid:9dc7a554-38e3-4ac3-9d43-5f7808fc3abd |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T02:02:20Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | oxford-uuid:9dc7a554-38e3-4ac3-9d43-5f7808fc3abd2022-03-27T00:45:38ZHierarchical decision making with dynamic reward structuresThesishttp://purl.org/coar/resource_type/c_db06uuid:9dc7a554-38e3-4ac3-9d43-5f7808fc3abdEnglishHyrax Deposit2021Wang, MO'Reilly, JKolling, NUllsperger, MYeung, NDecision making is an interdisciplinary field that studies how the brain processes information to come to a commitment or choice behaviour. Over the past decades, a cascade of psychological experiments have provided key insights in establishing principles of how the brain forms a decision. The majority of evidence came from studies with simple value comparison or categorical judgement, whereas in real life decisions usually require multiple levels of inferences, or integration of evidence that changes across time. This thesis will first evaluate relevant theories (chapter 1) and present two experiments with novel task paradigms to examine hierarchical decision making (i.e. multiple levels of thought processes) with dynamic reward structures (i.e. underlying reward structures vary across time). The first experiment (chapter 2) investigates foraging, a type of patch leaving decision that emerged in Ecology, with a virtual foraging task in which human participants choose between gold mines and decide when to leave to re-enter or enter a different one. The second experiment (chapter 3) investigates hierarchical perceptual decisions with a visual perception task, in which human participants find out the target patch and report its rotation by integrating sensory evidence and tracking reward contingency. I will demonstrate how the two experiments, combined with computational models and neurophysiological recordings, probe into the cognitive mechanisms of how the brain tracks changes and integrates evidence across time for a specific choice or long term estimate of option values. Finally, I will discuss how the findings contribute to extant theories and expand our knowledge of the neural basis of decision making in relatively complex, real life scenarios (chapter 4). |
| spellingShingle | Wang, M Hierarchical decision making with dynamic reward structures |
| title | Hierarchical decision making with dynamic reward structures |
| title_full | Hierarchical decision making with dynamic reward structures |
| title_fullStr | Hierarchical decision making with dynamic reward structures |
| title_full_unstemmed | Hierarchical decision making with dynamic reward structures |
| title_short | Hierarchical decision making with dynamic reward structures |
| title_sort | hierarchical decision making with dynamic reward structures |
| work_keys_str_mv | AT wangm hierarchicaldecisionmakingwithdynamicrewardstructures |