Computational principles of memory
Abstract
The ability to store and later use information is essential for a variety of adaptive behaviors, including integration, learning, generalization, prediction and inference. In this Review, we survey theoretical principles that can allow the brain to construct persistent states for memory. We identify requirements that a memory system must satisfy and analyze existing models and hypothesized biological substrates in light of these requirements. We also highlight open questions, theoretical puzzles and problems shared with computer science and information theory.
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Computational neuroscience has developed mathematical models of elementary computational components including sensory coding, normalization, working memory, evidence accumulation and decision mechanisms, and motor control.
“These include components for sensory coding29,30, normalization31, working memory32, evidence accumulation and decision mechanisms33–35, and motor control36.”
From Cognitive computational neuroscience (2018) · cites this paper as [32]
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Self-citation
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“A popular rationale for this idea is that information stored in continuous form will inevitably get corrupted by noise (which is always present in the physical environment, including our brains, and which can be induced by thermal, sensory, external, synaptic noise, etc.) [27, 58].”
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- Authors
- Chaudhuri, R., & Fiete, I.
- Affiliations
- The University of Texas at Austin (US)
- Corresponding author
- Fiete, Ila
- Venue
- Nature Neuroscience
- Published
- 2016-02-23
- Volume
- 19
- Issue
- 3
- Pages
- 394-403
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2275929617
- Cited by
- 213
- References
- 151
- Citations by year
- 2026: 7 · 2025: 19 · 2024: 24 · 2023: 19 · 2022: 24 · 2021: 29 · 2020: 24 · 2019: 19 · 2018: 26 · 2017: 16 · 2016: 6
- FWCI
- 2.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- memory, computational principles, short-term memory, long-term memory, persistent state, memory storage, memory models, information theory, learning, prediction, inference
- MeSH terms
- Computer Simulation, Humans, Information Theory, Memory, Models, Neurological
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