ArticleProceedings of the National Academy of Sciences of the United States of America2020
Stochastic sampling provides a unifying account of visual working memory limits.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- Reliability of computational versus noncomputational metrics of working memory and episodic memory in serious mental illness.Journal of psychopathology and clinical science · 2026Article
- Intrinsic rewards guide visual resource allocation via reinforcement learning.Nature human behaviour · 2026Article
- Beyond memory capacity: A probabilistic, dual store model of visuospatial working memory.PLoS computational biology · 2026Article
- Double-decision Response Time Models of Recall and Recognition Support Resource Accounts of Visual Working Memory.Computational brain & behavior · 2026Article
- Chunking, Attraction, Repulsion, and Ensemble Effects Are Ubiquitous in Visual Working Memory.Open mind : discoveries in cognitive science · 2026Article
- The perceptual average in ensemble representation: Neither perceptual nor an average.Attention, perception & psychophysics · 2025Article
- Probabilistic working memory representations in human cortex guide behavior.bioRxiv : the preprint server for biology · 2025Article
- Distributed and drifting signals for working memory load in human cortex.bioRxiv : the preprint server for biology · 2025Article
- Unexpected higher resilience to distraction during visual working memory in schizophrenia.Schizophrenia (Heidelberg, Germany) · 2025Article
- Neural mechanisms of resource allocation in working memory.Science advances · 2025Article
- Representational geometry explains puzzling error distributions in behavioral tasks.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Comparing retro-cue benefit mechanisms in visual working memory: completely valid vs. highly valid retro-cues.BMC psychology · 2024Article
- Is working memory domain-general or domain-specific?Trends in cognitive sciences · 2024Review
- Visual working memory for natural scenes: challenges and opportunities.Cognitive processing · 2024Review
- Visual working memory models of delayed estimation do not generalize to whole-report tasks.Journal of vision · 2024Article
- Representation and computation in visual working memory.Nature human behaviour · 2024Review
- A Neural Decision Signal during Internal Sampling from Working Memory in Humans.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Article
- Perceptual similarity judgments do not predict the distribution of errors in working memory.Journal of experimental psychology. Learning, memory, and cognition · 2024Article
- The role of recollection and familiarity in visual working memory: A mixture of threshold and signal detection processes.Psychological review · 2024Review
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Authors and funding
3 authors.
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Abstract
Research into human working memory limits has been shaped by the competition between different formal models, with a central point of contention being whether internal representations are continuous or discrete. Here we describe a sampling approach derived from principles of neural coding as a framework to understand working memory limits. Reconceptualizing existing models in these terms reveals strong commonalities between seemingly opposing accounts, but also allows us to identify specific points of difference. We show that the discrete versus continuous nature of sampling is not critical to model fits, but that, instead, random variability in sample counts is the key to reproducing human performance in both single- and whole-report tasks. A probabilistic limit on the number of items successfully retrieved is an emergent property of stochastic sampling, requiring no explicit mechanism to enforce it. These findings resolve discrepancies between previous accounts and establish a unified computational framework for working memory that is compatible with neural principles.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.