ReviewNature reviews. Neuroscience2018
On the nature and use of models in network neuroscience.
Review in Nature reviews. Neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 161 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
161 citing papers in PubMed, 2 syntheses or guidelines pooled it, 415 citations in OpenAlex.
- Functional and effective EEG connectivity patterns in Alzheimer's disease and mild cognitive impairment: a systematic review.Frontiers in aging neuroscience · 2025Pooled it
- Brain network analysis for the discrimination of dementia disorders using electrophysiology signals: A systematic review.Frontiers in aging neuroscience · 2023Pooled it
- Differential contribution of between and within-brain coupling to movement synchronization.Human brain mapping · 2023Trial
- Brain Functional Network in Chronic Asymptomatic Carotid Artery Stenosis and Occlusion: Changes and Compensation.Neural plasticity · 2020Trial
- Interrelationships of childhood trauma, psychiatric symptoms, neurocognition, and insomnia in chronic schizophrenia: a network perspective.European archives of psychiatry and clinical neuroscience · 2026Article
- Neural population models for EEG: From Canonical models to alternative model structures.PLoS computational biology · 2026Article
- Connectome-Guided Personalization of Optimal TDCS Intervention Selection in Alzheimer's Disease: A Modeling Study.eNeuro · 2026Article
- Spectral organization of individualized connectome harmonics across brain structure, function and cognition.bioRxiv : the preprint server for biology · 2026Article
- Review
- Spatial and network principles behind neural generation of locomotion.Nature communications · 2026Article
- How to Foster Challenging Interdisciplinary Collaborations: Can Philosophy Support Neuroscientists?The European journal of neuroscience · 2026Review
- Spatiotemporal asymmetries on brain energy landscape uncover system entrapment related to depression severity.Nature communications · 2026Article
- Task-induced topological and geometrical changes in whole-brain dynamics predict cognitive individual differences.bioRxiv : the preprint server for biology · 2026Article
- Competitive interactions shape mammalian brain network dynamics and computation.Nature neuroscience · 2026Article
- A principal component entropy metric for assessing global synchronicity in EEG signals.Scientific reports · 2026Article
- β-adrenergic receptors modulate CA1 population coding and synaptic plasticity during cumulative spatial memory formation and updating.Scientific reports · 2026Article
- Neurorehabilitation as Network Perturbation: Shaping Neuroplasticity with Robotics, Virtual Reality, and Neuromodulation.Biomedicines · 2026Article
- Multiscale network perspectives on glioma: from tumour biology to symptoms, survival and treatment.Nature reviews. Neurology · 2026Review
- The network architecture of general intelligence in the human connectome.Nature communications · 2026Article
- Habit learning is associated with efficiently controlled network dynamics in naive macaque monkeys.Npj complexity · 2026Article
101 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Network theory provides an intuitively appealing framework for studying relationships among interconnected brain mechanisms and their relevance to behaviour. As the space of its applications grows, so does the diversity of meanings of the term network model. This diversity can cause confusion, complicate efforts to assess model validity and efficacy, and hamper interdisciplinary collaboration. In this Review, we examine the field of network neuroscience, focusing on organizing principles that can help overcome these challenges. First, we describe the fundamental goals in constructing network models. Second, we review the most common forms of network models, which can be described parsimoniously along the following three primary dimensions: from data representations to first-principles theory; from biophysical realism to functional phenomenology; and from elementary descriptions to coarse-grained approximations. Third, we draw on biology, philosophy and other disciplines to establish validation principles for these models. We close with a discussion of opportunities to bridge model types and point to exciting frontiers for future pursuits.
Indexed as
Identifiers
What OpenQuestion holds
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.