Engram Memory Encoding and Retrieval: A Neurocomputational Perspective

TL;DR

This paper reviews and synthesizes biological and computational insights into engram-based memory encoding and retrieval, proposing a unified framework that highlights the roles of sparsity and plasticity in stable, efficient memory storage.

Contribution

It offers a comprehensive theoretical model integrating neurobiological findings with computational approaches to better understand engram mechanisms and memory stability.

Findings

Memory efficiency and capacity emerge from plasticity and sparsity interactions

Computational models like sparse regularization and spiking networks elucidate engram functions

The framework guides future research and potential therapies for memory disorders

Abstract

Despite substantial research into the biological basis of memory, the precise mechanisms by which experiences are encoded, stored, and retrieved in the brain remain incompletely understood. A growing body of evidence supports the engram theory, which posits that sparse populations of neurons undergo lasting physical and biochemical changes to support long-term memory. Yet, a comprehensive computational framework that integrates biological findings with mechanistic models remains elusive. This work synthesizes insights from cellular neuroscience and computational modeling to address key challenges in engram research: how engram neurons are identified and manipulated; how synaptic plasticity mechanisms contribute to stable memory traces; and how sparsity promotes efficient, interference-resistant representations. Relevant computational approaches -- such as sparse regularization, engram gating, and biologically inspired architectures like Sparse Distributed Memory and spiking neural networks -- are also examined. Together, these findings suggest that memory efficiency, capacity, and stability emerge from the interaction of plasticity and sparsity constraints. By integrating neurobiological and computational perspectives, this paper provides a comprehensive theoretical foundation for engram research and proposes a roadmap for future inquiry into the mechanisms underlying memory, with implications for the diagnosis and treatment of memory-related disorders.