Interference in Learning Context‐dependent Words

AbstractThe context-dependent memory effect, in which memory for an item is better when the retrieval context matches the original learning context, has proved to be difficult to reproduce in a laboratory setting. In an effort to identify a set of features that generate a robust context-dependent memory effect, we developed a paradigm in virtual reality using two semantically distinct virtual contexts: underwater and Mars environments, each with a separate body of knowledge (schema) associated with it. We show that items are better recalled when retrieved in the same context as the study context; we also show that the size of the effect is larger for items deemed context-relevant at encoding, suggesting that context-dependent memory effects may depend on items being integrated into an active schema.

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Skills transfer across dissimilar robots by learning context-dependent rewards

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems ◽

10.1109/iros.2013.6696585 ◽

2013 ◽

Cited By ~ 6

Author(s):

Milad S. Malekzadeh ◽

Danilo Bruno ◽

Sylvain Calinon ◽

Thrishantha Nanayakkara ◽

Darwin G. Caldwell

Keyword(s):

Learning Context ◽

Skills Transfer ◽

Context Dependent

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Learning Context-dependent Personal Preferences for Adaptive Recommendation

ACM Transactions on Interactive Intelligent Systems ◽

10.1145/3359755 ◽

2020 ◽

Vol 10 (3) ◽

pp. 1-26

Author(s):

Keita Higuchi ◽

Hiroki Tsuchida ◽

Eshed Ohn-Bar ◽

Yoichi Sato ◽

Kris Kitani

Keyword(s):

Learning Context ◽

Context Dependent

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Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Re)consolidation: A Connectionist Model

Computational Intelligence and Neuroscience ◽

10.1155/2017/8091780 ◽

2017 ◽

Vol 2017 ◽

pp. 1-16 ◽

Cited By ~ 1

Author(s):

Justin Lines ◽

Kelsey Nation ◽

Jean-Marc Fellous

Keyword(s):

Experimental Data ◽

Memory Consolidation ◽

Memory Item ◽

Neural Mechanisms ◽

Connectionist Model ◽

Recurrent Networks ◽

Learning Context ◽

Memory Reactivation ◽

Subsequent Recall ◽

Context Dependent

The context in which learning occurs is sufficient to reconsolidate stored memories and neuronal reactivation may be crucial to memory consolidation during sleep. The mechanisms of context-dependent and sleep-dependent memory (re)consolidation are unknown but involve the hippocampus. We simulated memory (re)consolidation using a connectionist model of the hippocampus that explicitly accounted for its dorsoventral organization and for CA1 proximodistal processing. Replicating human and rodent (re)consolidation studies yielded the following results. (1) Semantic overlap between memory items and extraneous learning was necessary to explain experimental data and depended crucially on the recurrent networks of dorsal but not ventral CA3. (2) Stimulus-free, sleep-induced internal reactivations of memory patterns produced heterogeneous recruitment of memory items and protected memories from subsequent interference. These simulations further suggested that the decrease in memory resilience when subjects were not allowed to sleep following learning was primarily due to extraneous learning. (3) Partial exposure to the learning context during simulated sleep (i.e., targeted memory reactivation) uniformly increased memory item reactivation and enhanced subsequent recall. Altogether, these results show that the dorsoventral and proximodistal organization of the hippocampus may be important components of the neural mechanisms for context-based and sleep-based memory (re)consolidations.

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Context-aware mobile computing: learning context- dependent personal preferences from a wearable sensor array

IEEE Transactions on Mobile Computing ◽

10.1109/tmc.2006.18 ◽

2006 ◽

Vol 5 (2) ◽

pp. 113-127 ◽

Cited By ~ 130

Author(s):

A. Krause ◽

A. Smailagic ◽

D.P. Siewiorek

Keyword(s):

Mobile Computing ◽

Sensor Array ◽

Context Aware ◽

Wearable Sensor ◽

Learning Context ◽

Context Dependent

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Learning context-dependent preferences from raw data

Proceedings of the 12th workshop on the Economics of Networks, Systems and Computation - NetEcon '17 ◽

10.1145/3106723.3106731 ◽

2017 ◽

Author(s):

Alexander Peysakhovich ◽

Johan Ugander

Keyword(s):

Learning Context ◽

Raw Data ◽

Context Dependent

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Context-dependent memory effects in VR

10.31234/osf.io/prdb7 ◽

2020 ◽

Author(s):

Yeon Soon Shin ◽

Rolando Masís-Obando ◽

Neggin Keshavarzian ◽

Riya Davé ◽

Kenneth Norman

Keyword(s):

Virtual Reality ◽

Memory Effect ◽

Original Learning ◽

Memory Effects ◽

Laboratory Setting ◽

Learning Context ◽

Body Of Knowledge ◽

Context Dependent ◽

Study Context

The context-dependent memory effect, in which memory for an item is better when the retrieval context matches the original learning context, has proved to be difficult to reproduce in a laboratory setting. In an effort to identify a set of features that generate a robust context-dependent memory effect, we developed a paradigm in virtual reality using two semantically distinct virtual contexts: underwater and Mars environments, each with a separate body of knowledge (schema) associated with it. We show that items are better recalled when retrieved in the same context as the study context; we also show that the size of the effect is larger for items deemed context-relevant at encoding, highlighting the importance of integrating items into an active schema in generating this effect.

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