Evidence map›Paper›PMID 39836111›Full record

ArticleeLife2025

Effects of noise and metabolic cost on cortical task representations.

Jake Patrick Stroud, Michal Wojcik, Kristopher Torp Jensen, Makoto Kusunoki, Mikiko Kadohisa, Mark J Buckley, John Duncan, Mark G Stokes, Mate Lengyel

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Jake Patrick StroudComputational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-4263-5755
Michal WojcikDepartment of Experimental Psychology, University of Oxford, Oxford, United Kingdom.
Kristopher Torp JensenComputational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0001-9242-5572
Makoto KusunokiDepartment of Experimental Psychology, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-5381-8506
Mikiko KadohisaDepartment of Experimental Psychology, University of Oxford, Oxford, United Kingdom.
Mark J BuckleyDepartment of Experimental Psychology, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0001-7455-8486
John DuncanMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.
Mark G StokesDepartment of Experimental Psychology, University of Oxford, Oxford, United Kingdom.
Mate LengyelComputational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.

Funding

Biotechnology and Biological Sciences Research Council BB/M010732/1Human Frontier Science Program RGP0044/2018James S. McDonnell Foundation 10.37717/220020405Medical Research Council MC_UU_00030/7Wellcome TrustWellcome Trust 10.35802/101092Wellcome Trust 10.35802/212262Wellcome Trust 10.35802/215909
6 · The paper itself

Abstract

Cognitive flexibility requires both the encoding of task-relevant and the ignoring of task-irrelevant stimuli. While the neural coding of task-relevant stimuli is increasingly well understood, the mechanisms for ignoring task-irrelevant stimuli remain poorly understood. Here, we study how task performance and biological constraints jointly determine the coding of relevant and irrelevant stimuli in neural circuits. Using mathematical analyses and task-optimized recurrent neural networks, we show that neural circuits can exhibit a range of representational geometries depending on the strength of neural noise and metabolic cost. By comparing these results with recordings from primate prefrontal cortex (PFC) over the course of learning, we show that neural activity in PFC changes in line with a minimal representational strategy. Specifically, our analyses reveal that the suppression of dynamically irrelevant stimuli is achieved by activity-silent, sub-threshold dynamics. Our results provide a normative explanation as to why PFC implements an adaptive, minimal representational strategy.

Indexed as

CognitionPrefrontal CortexAnimalsLearningMacaca mulattaMaleModels, NeurologicalNerve NetNeuronscognitiondynamical systemsneuroscienceprefrontal cortexrecurrent neural networksrhesus macaque

Identifiers

PMID39836111
PMCPMC11750133

What Socratic holds

Textmetadata
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 Socratic graph.