Evidence map›Paper›PMID 40759627›Full record

ArticleNature communications2025

Temporal coding carries more stable cortical visual representations than firing rate over time.

Hanlin Zhu, Fei He, Pavlo Zolotavin, Saumil Patel, Andreas S Tolias, Lan Luan, Chong Xie

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Hanlin Zhu *Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA. hanlin.zhu@rice.edu.ORCID http://orcid.org/0000-0002-8119-6871
Fei He *Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Pavlo ZolotavinDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Saumil PatelDepartment of Ophthalmology, Stanford University, Stanford, CA, USA.
Andreas S ToliasDepartment of Ophthalmology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-4305-6376
Lan LuanDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA. lan.luan@rice.edu.ORCID http://orcid.org/0000-0002-5327-2240
Chong XieDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA. chongxie@rice.edu.ORCID http://orcid.org/0000-0002-5544-2864

Funding

Computational foundations of active visual sensingUF1NS126566 · NINDS · STANFORD UNIVERSITY · PI MATHIS, MACKENZIE WEYGANDT, NIELL, CRISTOPHER M · 2022 to 2022
$4.8M
Maximizing flexibility: Optimized neural probes and electronics for long term, high bandwidth recordingsU01NS115588 · NINDS · RICE UNIVERSITY · PI FRANK, LOREN M, XIE, CHONG · 2020 to 2023
$4.6M
A Nanoelectronic Strategy for Reliable, Large-scale Chronic Neural RecordingR01NS102917 · NINDS · UNIVERSITY OF TEXAS AT AUSTIN · PI Chong Xie · 2017 to 2026
$3.5M
Longitudinal multimodal mapping to decipher the neurovascular impact of microinfarctsR01NS109361 · NINDS · UNIVERSITY OF TEXAS AT AUSTIN · PI LUAN, LAN · 2019 to 2023
$2.9M
Longitudinal neuronal and behavioral responses to microstimulation of LGN by ultraflexible electrodesR01EY036094 · NEI · RICE UNIVERSITY · PI Lan Luan, Chong Xie · 2025 to 2026
$1.2M
NEI NIH HHS R01 EY036094NINDS NIH HHS R01 NS102917NINDS NIH HHS R01 NS109361NINDS NIH HHS U01 NS115588NINDS NIH HHS UF1 NS126566ODNI | Intelligence Advanced Research Projects Activity (IARPA) D16PC00003Rice University (William Marsh Rice University) Internal fundsRice University (William Marsh Rice University) Internal FundsU.S. Department of Health & Human Services | NIH | National Eye Institute (NEI) R01EY036094U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) R01NS102917U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) R01NS109361U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) U01NS115588U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) UF1NS126566
6 · The paper itself

Abstract

Stably representing recurring visual scenes is crucial for behavior. However, previous studies report varying degrees of gradual neural activity changes over time in slow dynamic (1-5 seconds) firing rate code. Here we show that temporal codes, which capture structures in visually evoked fast (tens of milliseconds) spiking patterns, support the stability of visual representations. We tracked the spiking responses of the same visual cortical populations in male mice for 15 consecutive days using custom-developed, large-scale, ultraflexible electrode arrays. Across various stimuli, neurons exhibited different day-to-day stability in their firing rate-based tuning. The across day stability correlated with tuning reliability. Notably, temporal codes increased single neuron tuning stability, especially for less reliable neurons. Temporal coding further improved population representation discriminability and decoding accuracy. The stability of temporal codes was more correlated with network functional connectivity than rate coding. Thus, temporal coding may be essential in ensuring consistent sensory experiences over time.

Indexed as

Action PotentialsNeuronsVisual CortexVisual PerceptionAnimalsEvoked Potentials, VisualMaleMiceMice, Inbred C57BLPhotic StimulationTime Factors

Identifiers

PMID40759627
PMCPMC12322180

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.