Evidence map›Paper›PMID 38918347›Full record

ReviewAdvances in experimental medicine and biology2024

Neural Sequences and the Encoding of Time.

Saray Soldado-Magraner, Dean V Buonomano

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Time, space, memory and brain-body rhythms.Nature reviews. Neuroscience · 2026
    Review
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

2 authors.

Saray Soldado-MagranerDepartment of Neurobiology, University of California, Los Angeles, Los Angeles, CA, USA.
Dean V BuonomanoDepartment of Neurobiology, University of California, Los Angeles, Los Angeles, CA, USA. dbuono@ucla.edu.

Funding

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 NS116589
6 · The paper itself

Abstract

Converging experimental and computational evidence indicate that on the scale of seconds the brain encodes time through changing patterns of neural activity. Experimentally, two general forms of neural dynamic regimes that can encode time have been observed: neural population clocks and ramping activity. Neural population clocks provide a high-dimensional code to generate complex spatiotemporal output patterns, in which each neuron exhibits a nonlinear temporal profile. A prototypical example of neural population clocks are neural sequences, which have been observed across species, brain areas, and behavioral paradigms. Additionally, neural sequences emerge in artificial neural networks trained to solve time-dependent tasks. Here, we examine the role of neural sequences in the encoding of time, and how they may emerge in a biologically plausible manner. We conclude that neural sequences may represent a canonical computational regime to perform temporal computations.

Indexed as

BrainNeural Networks, ComputerNeuronsAnimalsHumansModels, NeurologicalTime FactorsTime PerceptionNeural population clocksNeural sequencesRampingTemporal processingTiming

Identifiers

PMID38918347

What OpenQuestion holds

Textmetadata
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.