ReviewNature reviews. Neuroscience2022
Null models in network neuroscience.
Review in Nature reviews. Neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers.
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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.
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Who cites it
124 citing papers in PubMed.
- Spatial Collinearity Constrains Multivariate Molecular-Enriched Network Estimation.Human brain mapping · 2026Article
- Comprehensive profiling of brain dynamics during anesthesia across phylogeny.Nature neuroscience · 2026Article
- Spatial organization of AQP4 water channel expression in the human brain.Science advances · 2026Article
- Human cortical networks trade communication efficiency for computational reliability.Science advances · 2026Article
- Organoid intelligence: a promising paradigm for autism spectrum disorder research.Molecular psychiatry · 2026Review
- Anatomical white matter tracts span the cortical hierarchy to support cognitive diversity.Nature human behaviour · 2026Article
- Cellular signatures underlying functional resilience in presymptomatic frontotemporal dementia.Brain : a journal of neurology · 2026Article
- Molecular, cellular and network mapping of brain structural deviations in patients with Post-COVID19 syndrome.Brain, behavior, & immunity - health · 2026Article
- Charting higher-order models of brain function beyond pairwise interactions.Nature communications · 2026Article
- Assessing Strengths and Limitations of Magnetoencephalography Source Imaging With Intracerebral EEG.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Global network and local vulnerabilities underlie brain atrophy across Parkinson's disease stages.Brain : a journal of neurology · 2026Article
- Circuit response to neuromodulation characterized with simultaneous deep brain stimulation and precision neuroimaging in humans.Nature neuroscience · 2026Article
- Mapping the Disrupted Connectome in Spinocerebellar Ataxia Type 3: A Network-Based Statistics Study Identifying Novel Therapeutic Targets for Neuromodulation.CNS neuroscience & therapeutics · 2026Article
- Molecular and cellular correlates of human cortical lateralization.Communications biology · 2026Article
- Mapping the functional connectome between grey matter and white matter.Communications biology · 2026Article
- Longitudinal brain structural changes during clozapine treatment: associations with neuroreceptor architecture and clinical response.medRxiv : the preprint server for health sciences · 2026Article
- Mapping shared and specific cortical after-effects of repetitive TMS on brain function.BMC medicine · 2026Article
- Gray Matter Volume Loss in Parkinson's Disease Psychosis and Cannabinoid Receptor Gene Expression in the Brain.Movement disorders : official journal of the Movement Disorder Society · 2026Article
- Opportunities and pitfalls of data contextualization in neuroimaging.Nature reviews. Neuroscience · 2026Review
- Aging and metabolism contribute separately to brain-body health.PLoS biology · 2026Article
64 more citing papers are in PubMed but not listed here.
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2 authors.
Funding
Abstract
Recent advances in imaging and tracing technology provide increasingly detailed reconstructions of brain connectomes. Concomitant analytic advances enable rigorous identification and quantification of functionally important features of brain network architecture. Null models are a flexible tool to statistically benchmark the presence or magnitude of features of interest, by selectively preserving specific architectural properties of brain networks while systematically randomizing others. Here we describe the logic, implementation and interpretation of null models of connectomes. We introduce randomization and generative approaches to constructing null networks, and outline a taxonomy of network methods for statistical inference. We highlight the spectrum of null models - from liberal models that control few network properties, to conservative models that recapitulate multiple properties of empirical networks - that allow us to operationalize and test detailed hypotheses about the structure and function of brain networks. We review emerging scenarios for the application of null models in network neuroscience, including for spatially embedded networks, annotated networks and correlation-derived networks. Finally, we consider the limits of null models, as well as outstanding questions for the field.
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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.