Stochastic models for learning.

Bush, Robert R.; Mosteller, Frederick

doi:10.1037/14496-000

Cited by 1,294 publications

(448 citation statements)

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“…One candidate mechanism widely developed in theories of learning (Bush and Mosteller 1955;Rescorla and Wagner 1972;Sutton and Barto 1981) that has been suggested to be critical for memory destabilization is prediction error (Pedreira et al 2004).The psychological intuition is that a discrepancy between what is expected (based on information stored in long-term memory) and what is experienced (during reactivation) triggers the destabilization process to update the memory, which then requires reconsolidation in order to stabilize the newly incorporated information (Pedreira et al 2004). This implies that memory reactivation will lead to memory destabilization if, and only if, a prediction error is experienced by the animal.…”

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confidence: 99%

Prediction error and trace dominance determine the fate of fear memories after post-training manipulations

et al. 2015

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Different mnemonic outcomes have been observed when associative memories are reactivated by CS exposure and followed by amnestics. These outcomes include mere retrieval, destabilization-reconsolidation, a transitional period (which is insensitive to amnestics), and extinction learning. However, little is known about the interaction between initial learning conditions and these outcomes during a reinforced or nonreinforced reactivation. Here we systematically combined temporally specific memories with different reactivation parameters to observe whether these four outcomes are determined by the conditions established during training. First, we validated two training regimens with different temporal expectations about US arrival. Then, using Midazolam (MDZ) as an amnestic agent, fear memories in both learning conditions were submitted to retraining either under identical or different parameters to the original training. Destabilization (i.e., susceptibly to MDZ) occurred when reactivation was reinforced, provided the occurrence of a temporal prediction error about US arrival. In subsequent experiments, both treatments were systematically reactivated by nonreinforced context exposure of different lengths, which allowed to explore the interaction between training and reactivation lengths. These results suggest that temporal prediction error and trace dominance determine the extent to which reactivation produces the different outcomes.

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confidence: 99%

Prediction error and trace dominance determine the fate of fear memories after post-training manipulations

et al. 2015

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“…In this class of theories, human choice is conceptualized as a learning process (Busemeyer & Myung, 1992 ;Bush & Mosteller, 1955 ). Learning consists in changing the propensity to select a gamble according to the experienced outcomes.…”

Section: Associative Learning Modelsmentioning

confidence: 99%

How Representations of Knowledge Shape Actions

Hertwig

Frey

2017

Knowledge and Space

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“…In such cases the player could learn through 'reinforcement' (e.g. Bush and Mosteller, 1955;Cross, 1983;Machine Learning, 1992;Roth and Erev, 1995). Reinforcement learning is based on two principles.…”

Section: Production: Learning Direction Theorymentioning

confidence: 99%

Inexperienced and experienced players in an oligopolistic market game with minimal information

Nagel¹

1999

Industrial and Corporate Change

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Stochastic models for learning.

Cited by 1,294 publications

References 0 publications

Prediction error and trace dominance determine the fate of fear memories after post-training manipulations

Prediction error and trace dominance determine the fate of fear memories after post-training manipulations

How Representations of Knowledge Shape Actions

Inexperienced and experienced players in an oligopolistic market game with minimal information

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