Evidence map›Paper›PMID 28723889›Full record

ArticleNature2017

Distinct timescales of population coding across cortex.

Caroline A Runyan, Eugenio Piasini, Stefano Panzeri, Christopher D Harvey

Abstract read
In one paragraph

Article in Nature, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 218 papers.

0numbers the graph read from it
0cells of the map it votes in
218citing 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

218 citing papers in PubMed.

  1. Article
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  8. Review
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  10. Review
  11. Article
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  13. Control of cortical population activity with patterned microstimulation.bioRxiv : the preprint server for biology · 2026
    Article
  14. Article
  15. Review
  16. Article
  17. Design principles for cost functions in optimal sensory coding.Frontiers in computational neuroscience · 2026
    Review
  18. Article
  19. Article
  20. Distinct neural dynamics in the ventral hippocampus and medial prefrontal cortex during social information processing.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article

158 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Caroline A RunyanDepartment of Neurobiology, Harvard Medical School, Boston, Massachusetts 02115, USA.
Eugenio PiasiniNeural Computation Laboratory, Istituto Italiano di Tecnologia, 38068 Rovereto, Italy.
Stefano PanzeriNeural Computation Laboratory, Istituto Italiano di Tecnologia, 38068 Rovereto, Italy.
Christopher D HarveyDepartment of Neurobiology, Harvard Medical School, Boston, Massachusetts 02115, USA.

Funding

Viral ModuleP30EY012196 · NEI · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI Gabriel Kreiman · 1998 to 2026
$21.3M
Parietal Cortex Networks for Sensorimotor Processing During NavigationR01NS089521 · NINDS · HARVARD MEDICAL SCHOOL · PI HARVEY, CHRISTOPHER D · 2015 to 2024
$4.5M
New approaches to understand neuronal microcircuit dynamics for working memoryR01MH107620 · NIMH · HARVARD MEDICAL SCHOOL · PI HARVEY, CHRISTOPHER D · 2015 to 2019
$2.8M
NIMH NIH HHS R01 MH107620NINDS NIH HHS R01 NS089521Wellcome Trust
6 · The paper itself

Abstract

The cortex represents information across widely varying timescales. For instance, sensory cortex encodes stimuli that fluctuate over few tens of milliseconds, whereas in association cortex behavioural choices can require the maintenance of information over seconds. However, it remains poorly understood whether diverse timescales result mostly from features intrinsic to individual neurons or from neuronal population activity. This question remains unanswered, because the timescales of coding in populations of neurons have not been studied extensively, and population codes have not been compared systematically across cortical regions. Here we show that population codes can be essential to achieve long coding timescales. Furthermore, we find that the properties of population codes differ between sensory and association cortices. We compared coding for sensory stimuli and behavioural choices in auditory cortex and posterior parietal cortex as mice performed a sound localization task. Auditory stimulus information was stronger in auditory cortex than in posterior parietal cortex, and both regions contained choice information. Although auditory cortex and posterior parietal cortex coded information by tiling in time neurons that were transiently informative for approximately 200 milliseconds, the areas had major differences in functional coupling between neurons, measured as activity correlations that could not be explained by task events. Coupling among posterior parietal cortex neurons was strong and extended over long time lags, whereas coupling among auditory cortex neurons was weak and short-lived. Stronger coupling in posterior parietal cortex led to a population code with long timescales and a representation of choice that remained consistent for approximately 1 second. In contrast, auditory cortex had a code with rapid fluctuations in stimulus and choice information over hundreds of milliseconds. Our results reveal that population codes differ across cortex and that coupling is a variable property of cortical populations that affects the timescale of information coding and the accuracy of behaviour.

Indexed as

Decision MakingAnimalsAuditory CortexCerebral CortexMaleMiceMice, Inbred C57BLNeuronsParietal LobeTime Factors

Identifiers

PMID28723889
PMCPMC5859334

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Registered trials

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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.