ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2018
Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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
20 citing papers in PubMed.
- Synchronization properties in C. elegans: Relating behavioral circuits to structural and functional neuronal connectivity.PLoS computational biology · 2026Article
- Habit learning is associated with efficiently controlled network dynamics in naive macaque monkeys.Npj complexity · 2026Article
- The Controllability ofBiomimetics (Basel, Switzerland) · 2025Article
- A network control theory pipeline for studying the dynamics of the structural connectome.Nature protocols · 2024Article
- Neural network architecture of a mammalian brain.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Innate Orientating Behavior of a Multi-Legged Robot Driven by the Neural Circuits ofBiomimetics (Basel, Switzerland) · 2024Article
- Article
- Fibration symmetries and cluster synchronization in the Caenorhabditis elegans connectome.PloS one · 2024Article
- Semantic Representation of Neural Circuit Knowledge inbioRxiv : the preprint server for biology · 2023Article
- Using network control theory to study the dynamics of the structural connectome.bioRxiv : the preprint server for biology · 2023Article
- The expanding horizons of network neuroscience: From description to prediction and control.NeuroImage · 2022Review
- Network controllability mediates the relationship between rigid structure and flexible dynamics.Network neuroscience (Cambridge, Mass.) · 2022Article
- Computing Temporal Sequences Associated With Dynamic Patterns on theFrontiers in systems neuroscience · 2021Article
- Network structure of cascading neural systems predicts stimulus propagation and recovery.Journal of neural engineering · 2020Article
- A practical guide to methodological considerations in the controllability of structural brain networks.Journal of neural engineering · 2020Article
- Models of communication and control for brain networks: distinctions, convergence, and future outlook.Network neuroscience (Cambridge, Mass.) · 2020Article
- Path-dependent connectivity, not modularity, consistently predicts controllability of structural brain networks.Network neuroscience (Cambridge, Mass.) · 2020Article
- Synthetic ablations in theNetwork neuroscience (Cambridge, Mass.) · 2020Article
- No Country for Old Worms: A Systematic Review of the Application ofMetabolites · 2018Review
- Connectome to behaviour: modellingPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Control is essential to the functioning of any neural system. Indeed, under healthy conditions the brain must be able to continuously maintain a tight functional control between the system's inputs and outputs. One may therefore hypothesize that the brain's wiring is predetermined by the need to maintain control across multiple scales, maintaining the stability of key internal variables, and producing behaviour in response to environmental cues. Recent advances in network control have offered a powerful mathematical framework to explore the structure-function relationship in complex biological, social and technological networks, and are beginning to yield important and precise insights on neuronal systems. The network control paradigm promises a predictive, quantitative framework to unite the distinct datasets necessary to fully describe a nervous system, and provide mechanistic explanations for the observed structure and function relationships. Here, we provide a thorough review of the network control framework as applied to
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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.