ArticleNature physics2018
Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.
Article in Nature physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
What it found
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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.
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
62 citing papers in PubMed, 149 citations in OpenAlex.
- Control adjustment costs limit goal flexibility: Empirical evidence and a computational account.Psychological review · 2026Article
- Convergent transcriptomic and connectomic controllers of information integration and its anaesthetic breakdown across mammalian brains.Nature human behaviour · 2026Article
- Exploring the Role of the Rich Club in Network Control of Neurocognitive States.Human brain mapping · 2026Article
- Controlling the human connectome with spatially diffuse input signals.Communications biology · 2026Article
- Continuous input drives motor cortical dynamics during reaching.Research square · 2026Article
- A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Controllability of morphometric network colocalize with underlying neurobiology in major depression.Psychological medicine · 2026Article
- Effects of light on brain-state dynamics and energy landscape.Network neuroscience (Cambridge, Mass.) · 2026Article
- Inferring intrinsic neural timescales using optimal control theory.Nature communications · 2025Article
- High energy consumption characterizes abnormal brain state transitions in temporal lobe epilepsy.Neurobiology of disease · 2025Article
- Brain Network Controllability and Its Regional Gene Expression Profile Associated With Suicidal Tendencies in Major Depressive Disorder Patients.Depression and anxiety · 2025Article
- Sleep Deprivation Effects on Brain State Dynamics Are Associated With Dopamine DBiological psychiatry · 2025Article
- A network control theory pipeline for studying the dynamics of the structural connectome.Nature protocols · 2024Article
- Contributions of network structure, chemoarchitecture and diagnostic categories to transitions between cognitive topographies.Nature biomedical engineering · 2024Article
- Controllability in attention deficit hyperactivity disorder brains.Cognitive neurodynamics · 2024Article
- The mechanics of correlated variability in segregated cortical excitatory subnetworks.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder.Brain sciences · 2024Article
- Graph Analysis of the Visual Cortical Network during Naturalistic Movie Viewing Reveals Increased Integration and Decreased Segregation Following Mild TBI.Vision (Basel, Switzerland) · 2024Article
- Controlling the human connectome with spatially diffuse input signals.bioRxiv : the preprint server for biology · 2024Article
- Development of the brain network control theory and its implications.Psychoradiology · 2024Review
2 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
6 authors at 3 institutions in 1 country.
Funding
Abstract
Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behavior in its network architecture, and directly inspire new directions in network analysis and design via distributed control.
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.