Evidence map›Paper›PMID 37983510›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Optimal information loading into working memory explains dynamic coding in the prefrontal cortex.

Jake P Stroud, Kei Watanabe, Takafumi Suzuki, Mark G Stokes, Máté Lengyel

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Article
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  5. Article
  6. Conjunctive population coding integrates sensory evidence to guide adaptive behavior.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Article
  8. Complex functions of human lateral frontopolar cortex.Brain : a journal of neurology · 2025
    Review
  9. Hierarchical dynamic coding coordinates speech comprehension in the human brain.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Timescales of learning in prefrontal cortex.Nature reviews. Neuroscience · 2024
    Review
  17. Article
  18. Article
  19. Recurrent neural network dynamical systems for biological vision.Advances in neural information processing systems · 2024
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jake P StroudComputational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, United Kingdom.ORCID 0000-0002-4263-5755
Kei WatanabeGraduate School of Frontier Biosciences, Osaka University, Osaka 565-0871, Japan.
Takafumi SuzukiCenter for Information and Neural Networks, National Institute of Communication and Information Technology, Osaka 565-0871, Japan.ORCID 0000-0001-9404-9654
Mark G StokesDepartment of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom.
Máté LengyelComputational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, United Kingdom.ORCID 0000-0001-7266-0049

Funding

Wellcome Trust
6 · The paper itself

Abstract

Working memory involves the short-term maintenance of information and is critical in many tasks. The neural circuit dynamics underlying working memory remain poorly understood, with different aspects of prefrontal cortical (PFC) responses explained by different putative mechanisms. By mathematical analysis, numerical simulations, and using recordings from monkey PFC, we investigate a critical but hitherto ignored aspect of working memory dynamics: information loading. We find that, contrary to common assumptions, optimal loading of information into working memory involves inputs that are largely orthogonal, rather than similar, to the late delay activities observed during memory maintenance, naturally leading to the widely observed phenomenon of dynamic coding in PFC. Using a theoretically principled metric, we show that PFC exhibits the hallmarks of optimal information loading. We also find that optimal information loading emerges as a general dynamical strategy in task-optimized recurrent neural networks. Our theory unifies previous, seemingly conflicting theories of memory maintenance based on attractor or purely sequential dynamics and reveals a normative principle underlying dynamic coding.

Indexed as

Memory, Short-TermNeuronsNeural Networks, ComputerPrefrontal Cortexattractor networksdynamic codingrecurrent neural networkstask-optimized networksworking memory

Identifiers

PMID37983510
PMCPMC10691340

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.