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Main Author: de Cheveigné, Alain
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2502.11105
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author de Cheveigné, Alain
author_facet de Cheveigné, Alain
contents A rational framework is proposed to explain how we accommodate unbounded sensory input within bounded memory. According to this framework, memory is stored as a statistic-like representation that is repeatedly summarized and compressed to make room for new input. Summarization of sensory input must be rapid; that of abstract trace might be slower and more deliberative, drawing on elaborative processes some of which might occasionally reach consciousness (as in mind-wandering). Short-term sensory traces are summarized as simple statistics organized into structures such as a time series, graph or dictionary, and longer-term abstract traces as more complex statistic-like structures. Summarization at multiple time scales requires an intensive process of memory curation which might account for the high metabolic consumption of the brain at rest. Summarization may be guided by heuristics to help choose which statistics to apply at each step, so that the trace is useful for a wide range of future needs, the objective being to "represent the past" rather than tune for a specific task. However, the choice of statistics (or of heuristics to guide that choice) is a potential target for learning, possibly over long-term scales of development or evolution. The framework is intended as an aid to make sense of our extensive empirical and theoretical knowledge of memory and bring us closer to understanding it in functional and mechanistic terms.
format Preprint
id arxiv_https___arxiv_org_abs_2502_11105
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Graceful forgetting: Memory as a process
de Cheveigné, Alain
Neurons and Cognition
Information Retrieval
Machine Learning
A rational framework is proposed to explain how we accommodate unbounded sensory input within bounded memory. According to this framework, memory is stored as a statistic-like representation that is repeatedly summarized and compressed to make room for new input. Summarization of sensory input must be rapid; that of abstract trace might be slower and more deliberative, drawing on elaborative processes some of which might occasionally reach consciousness (as in mind-wandering). Short-term sensory traces are summarized as simple statistics organized into structures such as a time series, graph or dictionary, and longer-term abstract traces as more complex statistic-like structures. Summarization at multiple time scales requires an intensive process of memory curation which might account for the high metabolic consumption of the brain at rest. Summarization may be guided by heuristics to help choose which statistics to apply at each step, so that the trace is useful for a wide range of future needs, the objective being to "represent the past" rather than tune for a specific task. However, the choice of statistics (or of heuristics to guide that choice) is a potential target for learning, possibly over long-term scales of development or evolution. The framework is intended as an aid to make sense of our extensive empirical and theoretical knowledge of memory and bring us closer to understanding it in functional and mechanistic terms.
title Graceful forgetting: Memory as a process
topic Neurons and Cognition
Information Retrieval
Machine Learning
url https://arxiv.org/abs/2502.11105