From transient patterns to persistent structures: A model of episodic memory formation via cortico-hippocampal interactions (0)
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BibTeX
@MISC{Shastri_fromtransient,
author = {Lokendra Shastri},
title = {From transient patterns to persistent structures: A model of episodic memory formation via cortico-hippocampal interactions},
year = {}
}
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Abstract
We readily acquire memories of events and situations in our daily lives. There is a broad consensus that the hippocampal system (HS) plays a critical role in the encoding and retrieval of such "episodic" memories. But how the HS subserves this mnemonic function is not fully understood. This article presents a computational model, SMRITI,that demonstrates how a transient pattern of activity representing an event can be transformed rapidly into a persistent and robust memory trace as a result of long-term potentiation within structures whose architecture and circuitry resemble those of the HS. Predictions and implications of the model are discussed. LONG ABSTRACT We readily remember events and situations in our daily lives and rapidly acquire memories of specific events by watching a telecast or reading a newspaper. There is a broad consensus that the hippocampal system (HS), consisting of the hippocampal formation and neighboring cortical areas, plays a critical role in the encoding and retrieval of such "episodic" memories. But how the HS subserves this mnemonic function is not fully understood. This article presents a computational model, SMRITI, that demonstrates how a cortically expressed transient pattern of activity representing an event can be transformed rapidly into a persistent and robust memory trace as a result of long-term potentiation within structures whose architecture and circuitry resemble those of the HS. Memory traces formed by the model respond to partial cues, and at the same time, reject similar but erroneous cues. During retrieval these memory traces, acting in concert with cortical circuits encoding semantic, causal, and procedural knowledge, can recreate activation-based representations of memorized events. The model explicates the representa...
