Hebbian learning and temporary storage in the convergence-zone model of episodic memory
نویسندگان
چکیده
منابع مشابه
Hebbian learning and temporary storage in the convergence-zone model of episodic memory
The Convergence-Zone model shows how sparse, random memory patterns can lead to one-shot storage and high capacity in the hippocampal component of the episodic memory system. This paper presents a biologically more realistic version of the model, with continuously-weighted connections and storage through Hebbian learning and normalization. In contrast to the gradual weight adaptation in many ne...
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Human episodic memory provides a seemingly unlimited storage for everyday experiences, and a retrieval system that allows us to access the experiences with partial activation of their components. The system is believed to consist of a fast, temporary storage in the hippocampus, and a slow, long-term storage within the neocortex. This paper presents a neural network model of the hippocampal epis...
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Human episodic memory provides a seemingly unlimited storage for everyday experiences, and a retrieval system that allows us to access the experiences with partial activation of their components. This paper presents a computational model of episodic memory inspired by Damasio's idea of Convergence Zones. The model consists of a layer of perceptual feature maps and a binding layer. A perceptual ...
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Human episodic memory provides a seemingly unlimited storage for everyday experiences, and a retrieval system that allows us to access the experiences with partial activation of their components. The system is believed to consist of a fast, temporary storage in the hippocampus, and a slow, long-term storage within the neocortex. This paper presents a neural network model of the hippocampal epis...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2000
ISSN: 0925-2312
DOI: 10.1016/s0925-2312(00)00248-4