ArticlePLoS computational biology2018
Toward a theory of coactivation patterns in excitable neural networks.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Categories of important edges in dynamics on graphs.Royal Society open science · 2025Article
- Article
- The effect of deep brain stimulation on cortico-subcortical networks in Parkinson's disease patients with freezing of gait: Exhaustive exploration of a basic model.Network neuroscience (Cambridge, Mass.) · 2024Article
- Structural basis of envelope and phase intrinsic coupling modes in the cerebral cortex.NeuroImage · 2023Article
- Aberrant temporal-spatial complexity of intrinsic fluctuations in major depression.European archives of psychiatry and clinical neuroscience · 2023Article
- The brainstem connectome database.Scientific data · 2022Article
- Two classes of functional connectivity in dynamical processes in networks.Journal of the Royal Society, Interface · 2021Article
- Brain Connectivity Studies on Structure-Function Relationships: A Short Survey with an Emphasis on Machine Learning.Computational intelligence and neuroscience · 2021Review
- Link-usage asymmetry and collective patterns emerging from rich-club organization of complex networks.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Asymmetric high-order anatomical brain connectivity sculpts effective connectivity.Network neuroscience (Cambridge, Mass.) · 2020Article
- Age-Associated Differences of Modules and Hubs in Brain Functional Networks.Frontiers in aging neuroscience · 2020Article
- Network motifs and their origins.PLoS computational biology · 2019Review
- Topological reinforcement as a principle of modularity emergence in brain networks.Network neuroscience (Cambridge, Mass.) · 2019Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The relationship between the structural connectivity (SC) and functional connectivity (FC) of neural systems is of central importance in brain network science. It is an open question, however, how the SC-FC relationship depends on specific topological features of brain networks or the models used for describing neural dynamics. Using a basic but general model of discrete excitable units that follow a susceptible-excited-refractory activity cycle (SER model), we here analyze how the network activity patterns underlying functional connectivity are shaped by the characteristic topological features of the network. We develop an analytical framework for describing the contribution of essential topological elements, such as common inputs and pacemakers, to the coactivation of nodes, and demonstrate the validity of the approach by comparison of the analytical predictions with numerical simulations of various exemplar networks. The present analytic framework may serve as an initial step for the mechanistic understanding of the contributions of brain network topology to brain dynamics.
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