Evidence map›Paper›PMID 38938692›Full record

ArticlePhysical review research

Spatial and temporal correlations in neural networks with structured connectivity.

Yan-Liang Shi, Roxana Zeraati, Anna Levina, Tatiana A Engel

Abstract read
In one paragraph

Article in Physical review research. 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. Review
  2. A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. 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

4 authors.

Yan-Liang ShiCold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA.
Roxana ZeraatiInternational Max Planck Research School for the Mechanisms of Mental Function and Dysfunction, University of Tübingen, Tübingen, Germany.
Anna LevinaMax Planck Institute for Biological Cybernetics, Tübingen, Germany.
Tatiana A EngelCold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA.

Funding

Multiscale computational frameworks for integrating large-scale cortical dynamics, connectivity, and behaviorRF1DA055666 · NIDA · PRINCETON UNIVERSITY · PI ENGEL, TATIANA · 2021 to 2021
$1.3M
NIDA NIH HHS RF1 DA055666
6 · The paper itself

Abstract

Correlated fluctuations in the activity of neural populations reflect the network's dynamics and connectivity. The temporal and spatial dimensions of neural correlations are interdependent. However, prior theoretical work mainly analyzed correlations in either spatial or temporal domains, oblivious to their interplay. We show that the network dynamics and connectivity jointly define the spatiotemporal profile of neural correlations. We derive analytical expressions for pairwise correlations in networks of binary units with spatially arranged connectivity in one and two dimensions. We find that spatial interactions among units generate multiple timescales in auto- and cross-correlations. Each timescale is associated with fluctuations at a particular spatial frequency, making a hierarchical contribution to the correlations. External inputs can modulate the correlation timescales when spatial interactions are nonlinear, and the modulation effect depends on the operating regime of network dynamics. These theoretical results open new ways to relate connectivity and dynamics in cortical networks via measurements of spatiotemporal neural correlations.

Identifiers

PMID38938692
PMCPMC11210526

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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.