Evidence map›Paper›PMID 39663407›Full record

ReviewNature reviews. Neuroscience2025

Structurally informed models of directed brain connectivity.

Matthew D Greaves, Leonardo Novelli, Sina Mansour L, Andrew Zalesky, Adeel Razi

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Article
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  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Spectral imprint of structural embedding in effective connectivity.bioRxiv : the preprint server for biology · 2025
    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

5 authors.

Matthew D GreavesSchool of Psychological Sciences, Monash University, Clayton, Victoria, Australia. matthew.greaves@monash.edu.ORCID http://orcid.org/0000-0002-3438-2874
Leonardo NovelliSchool of Psychological Sciences, Monash University, Clayton, Victoria, Australia.ORCID http://orcid.org/0000-0002-6081-3367
Sina Mansour LCentre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0002-5695-5696
Andrew ZaleskyDepartment of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.ORCID http://orcid.org/0000-0003-2298-9908
Adeel RaziSchool of Psychological Sciences, Monash University, Clayton, Victoria, Australia. adeel.razi@monash.edu.ORCID http://orcid.org/0000-0002-0779-9439

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding how one brain region exerts influence over another in vivo is profoundly constrained by models used to infer or predict directed connectivity. Although such neural interactions rely on the anatomy of the brain, it remains unclear whether, at the macroscale, structural (or anatomical) connectivity provides useful constraints on models of directed connectivity. Here, we review the current state of research on this question, highlighting a key distinction between inference-based effective connectivity and prediction-based directed functional connectivity. We explore the methods via which structural connectivity has been integrated into directed connectivity models: through prior distributions, fixed parameters in state-space models and inputs to structure learning algorithms. Although the evidence suggests that integrating structural connectivity substantially improves directed connectivity models, assessments of reliability and out-of-sample validity are lacking. We conclude this Review with a strategy for future research that addresses current challenges and identifies opportunities for advancing the integration of structural and directed connectivity to ultimately improve understanding of the brain in health and disease.

Indexed as

BrainNerve NetAnimalsConnectomeHumansModels, NeurologicalNeural Pathways

Identifiers

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.