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Unconscious Associative Learning with Decoded Neuroreinforcement
- Cherkaoui, Mouslim
- Advisor(s): Rissman, Jesse
Abstract
The question of what role consciousness plays in memory is as old as modern memory research. While most studies have used techniques that briefly present the stimuli to study unconscious learning, these studies tend to show small effect sizes and are not always successful. This makes it difficult to compare the mechanisms of conscious and unconscious learning. As a result, a debate has ensued about whether learning the relationship between two events is possible without awareness. One thing proponents of both camps with opposite views on this matter agree on, is the need for better methods. This dissertation aims to test whether multi-voxel neuroreinforcement is one such method. Understanding unconscious learning is however only half of the problem, as conscious associative learning also needs investigation. To address these gaps, In Chapter 2, I show that unconscious neuroreinforcement can affect the relative status of a cue by affecting variability in choice behavior. In Chapter 3, I explore a form of associative learning called higher-order conditioning to understand how conscious learning unfolds, and show how two mechanisms that differ in their computational complexity can be utilized to learn and guide behavior. Lastly, Chapter 4 investigated whether the more computationally complex form of learning can be supported unconsciously and found further evidence in support of variability on choice behavior as a result of neuroreinforcement. These chapters highlight a need for using a range of experimental techniques to elucidate the mechanisms of conscious and unconscious learning.
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