Evidence map›Paper›PMID 28230844›Full record

ReviewNature neuroscience2017

Network neuroscience.

Danielle S Bassett, Olaf Sporns

Registry-linked trialAbstract readReview
In one paragraph

Review in Nature neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06389266 (Network-Targeted Neuromodulation for Nicotine Dependence in Schizophrenia), which is not on this map. Cited by 1,056 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,056citing papers in PubMed, 1 pooled it
–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.

NCT06389266 nacompletednot on this mapstarted 2023, after this paper: background citation

Network-Targeted Neuromodulation for Nicotine Dependence in Schizophrenia

TypeinterventionalSponsorVanderbilt University Medical CenterRan2023 to 2025Enrolled90ConditionsSchizophrenia, Nicotine DependenceArmsRepetitive Transcranial Magnetic Stimulation (rTMS)
3 · Its place in the literature

Who cites it

1,056 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Review
  7. A Variational Mean-Field Control Framework for Graph Representation Learning.IEEE transactions on pattern analysis and machine intelligence · 2026
    Article
  8. Article
  9. Review
  10. Lasting aversive consequences of a single dose of 4-hydroxytamoxifen.bioRxiv : the preprint server for biology · 2026
    Article
  11. Brain Architecture of Punishment Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Review
  19. Review
  20. Article

996 more citing papers are in PubMed but not listed here.

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.

Danielle S BassettDepartment of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Olaf SpornsDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA.

Funding

Research Education ComponentP30AG010133 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 1991 to 2020
$37.3M
Virtual Resection to Treat EpilepsyR01NS099348 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH, LITT, BRIAN · 2016 to 2019
$2.3M
Evolution of the Linked Architecture of Network Control and Executive Function in AdolescenceR21MH106799 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH, SATTERTHWAITE, THEODORE · 2016 to 2017
$515k
CRCNS: US-France Modeling & Predicting BCI Learning from Dynamic NetworksR01HD086888 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH · 2015 to 2018
$506k
CRCNS: Linking connectomic and large-Scale Dynamics of the Human BrainR01AT009036 · NCCIH · TRUSTEES OF INDIANA UNIVERSITY · PI SPORNS, OLAF · 2015 to 2017
$443k
NCCIH NIH HHS R01 AT009036NIA NIH HHS P30 AG010133NICHD NIH HHS R01 HD086888NIMH NIH HHS R21 MH106799NINDS NIH HHS R01 NS099348
6 · The paper itself

Abstract

Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system.

Indexed as

NeurosciencesAnimalsBrainCognitionHumansModels, NeurologicalNerve NetNeural Pathways

Identifiers

PMID28230844
PMCPMC5485642

What OpenQuestion holds

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Registered trials

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.