Evidence map›Paper›PMID 40185714›Full record

ArticleNature communications2025

Ex vivo cortical circuits learn to predict and spontaneously replay temporal patterns.

Benjamin Liu, Dean V Buonomano

Abstract readComment
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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Can a single brain cell be surprised?Nature communications · 2025
    Article
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Benjamin LiuDepartment of Neurobiology, Deparment of Psychology, and Psychology, Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, CA, USA.
Dean V BuonomanoDepartment of Neurobiology, Deparment of Psychology, and Psychology, Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, CA, USA. dbuono@ucla.edu.ORCID http://orcid.org/0000-0002-8528-9231

Funding

CRCNS: Multiple Clocks for the Encoding of Time in Corticostriatal CircuitsR01NS125877 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUONOMANO, DEAN V, MASMANIDIS, SOTIRIS · 2021 to 2025
$1.9M
Multiplexing working memory and timing: Encoding retrospective and prospective information in transient neural trajectories.RF1NS116589 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUONOMANO, DEAN V, GOLSHANI, PEYMAN · 2020 to 2020
$1.8M
Multiplexing working memory and timing: Encoding retrospective and prospective information in transient neural trajectories.R01NS116589 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUONOMANO, DEAN V, GOLSHANI, PEYMAN · 2023 to 2024
$1.2M
NINDS NIH HHS R01 NS116589NINDS NIH HHS R01 NS125877NINDS NIH HHS RF1 NS116589U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) NS116589
6 · The paper itself

Abstract

It has been proposed that prediction and timing are computational primitives of neocortical microcircuits, specifically, that neural mechanisms are in place to allow neocortical circuits to autonomously learn the temporal structure of external stimuli and generate internal predictions. To test this hypothesis, we trained cortical organotypic slices on two temporal patterns using dual-optical stimulation. After 24-h of training, whole-cell recordings revealed network dynamics consistent with training-specific timed prediction. Unexpectedly, there was replay of the learned temporal structure during spontaneous activity. Furthermore, some neurons exhibited timed prediction errors as revealed by larger responses when the expected stimulus was omitted compared to when it was present. Mechanistically our results indicate that learning relied in part on asymmetric connectivity between distinct neuronal ensembles with temporally-ordered activation. These findings further suggest that local cortical microcircuits are intrinsically capable of learning temporal information and generating predictions, and that the learning rules underlying temporal learning and spontaneous replay can be intrinsic to local cortical microcircuits and not necessarily dependent on top-down interactions.

Indexed as

Cerebral CortexLearningNeocortexNerve NetNeuronsAnimalsMicePatch-Clamp Techniques

Identifiers

PMID40185714
PMCPMC11971321

What OpenQuestion holds

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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.