Outputs (82)

Stability analysis of electrical microgrids and their control systems (2024)
Journal Article
Smith, O., Coombes, S., & O'Dea, R. D. (2024). Stability analysis of electrical microgrids and their control systems. PRX Energy, 3(1), Article 013011. https://doi.org/10.1103/PRXEnergy.3.013011

The drive towards renewable energy generation is causing fundamental changes in both the structure and dynamics of power grids. Their topology is becoming increasingly decentralised due to distributed, embedded generation, and the emergence of microg... Read More about Stability analysis of electrical microgrids and their control systems.

Insights into oscillator network dynamics using a phase-isostable framework (2024)
Journal Article
Nicks, R., Allen, R., & Coombes, S. (2024). Insights into oscillator network dynamics using a phase-isostable framework. Chaos: An Interdisciplinary Journal of Nonlinear Science, 34(1), Article 013141. https://doi.org/10.1063/5.0179430

Networks of coupled nonlinear oscillators can display a wide range of emergent behaviors under the variation of the strength of the coupling. Network equations for pairs of coupled oscillators where the dynamics of each node is described by the evolu... Read More about Insights into oscillator network dynamics using a phase-isostable framework.

Understanding the effect of white matter delays on large scale brain synchrony (2024)
Journal Article
Şaylı, M., & Coombes, S. (2024). Understanding the effect of white matter delays on large scale brain synchrony. Communications in Nonlinear Science and Numerical Simulation, 131, Article 107803. https://doi.org/10.1016/j.cnsns.2023.107803

The presence of myelin is a powerful structural factor that controls the conduction speed of mammalian axons. It is the combination of local synaptic activity and non-local delayed axonal interactions within the cortex that is believed to be the majo... Read More about Understanding the effect of white matter delays on large scale brain synchrony.

Next generation neural population models (2023)
Journal Article
Coombes, S. (2023). Next generation neural population models. Frontiers in Applied Mathematics and Statistics, 9, Article 112822. https://doi.org/10.3389/fams.2023.1128224

Low-dimensional neural mass models are often invoked to model the coarse-grained activity of large populations of neurons and synapses and have been used to help understand the coordination of large scale brain rhythms. However, they are phenomenolog... Read More about Next generation neural population models.

The two-process model for sleep–wake regulation: A nonsmooth dynamics perspective (2022)
Journal Article
Şaylı, M., Skeldon, A. C., Thul, R., Nicks, R., & Coombes, S. (2023). The two-process model for sleep–wake regulation: A nonsmooth dynamics perspective. Physica D: Nonlinear Phenomena, 444, Article 133595. https://doi.org/10.1016/j.physd.2022.133595

Since its inception four decades ago the two-process model introduced by Borbély has provided the conceptual framework to explain sleep–wake regulation across many species, including humans. At its core, high level notions of circadian and homeostati... Read More about The two-process model for sleep–wake regulation: A nonsmooth dynamics perspective.

Structure-function clustering in weighted brain networks (2022)
Journal Article
Crofts, J. J., Forrester, M., Coombes, S., & O’Dea, R. D. (2022). Structure-function clustering in weighted brain networks. Scientific Reports, 12(1), Article 16793. https://doi.org/10.1038/s41598-022-19994-9

Functional networks, which typically describe patterns of activity taking place across the cerebral cortex, are widely studied in neuroscience. The dynamical features of these networks, and in particular their deviation from the relatively static str... Read More about Structure-function clustering in weighted brain networks.

Neural fields with rebound currents: Novel routes to patterning (2021)
Journal Article
Modhara, S., Lai, Y. M., Thul, R., & Coombes, S. (2021). Neural fields with rebound currents: Novel routes to patterning. SIAM Journal on Applied Dynamical Systems, 20(3), 1596-1620. https://doi.org/10.1137/20M1364710

The understanding of how spatio-temporal patterns of neural activity may arise in the cortex of the brain has advanced with the development and analysis of neural field models. Replicating this success for subcortical tissues, such as the thalamus, r... Read More about Neural fields with rebound currents: Novel routes to patterning.

Interlayer connectivity reconstruction for multilayer brain networks using phase oscillator models (2021)
Journal Article
Tewarie, P., Prasse, B., Meier, J. M., Byrne, Á., De Domenico, M., Stam, C. J. (., …Van Mieghem, P. (2021). Interlayer connectivity reconstruction for multilayer brain networks using phase oscillator models. New Journal of Physics, 23(6), Article 063065. https://doi.org/10.1088/1367-2630/ac066d

Large-scale neurophysiological networks are often reconstructed from band-pass filtered time series derived from magnetoencephalography (MEG) data. Common practice is to reconstruct these networks separately for different frequency bands and to treat... Read More about Interlayer connectivity reconstruction for multilayer brain networks using phase oscillator models.

Mean-Field Models for EEG/MEG: From Oscillations to Waves (2021)
Journal Article
Byrne, Á., Ross, J., Nicks, R., & Coombes, S. (2022). Mean-Field Models for EEG/MEG: From Oscillations to Waves. Brain Topography, 35, 36–53. https://doi.org/10.1007/s10548-021-00842-4

Neural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological consideration... Read More about Mean-Field Models for EEG/MEG: From Oscillations to Waves.

Understanding sensory induced hallucinations: From neural fields to amplitude equations (2021)
Journal Article
Nicks, R., Cocks, A., Avitabile, D., Johnston, A., & Coombes, S. (2021). Understanding sensory induced hallucinations: From neural fields to amplitude equations. SIAM Journal on Applied Dynamical Systems, 20(4), 1683-1714. https://doi.org/10.1137/20M1366885

Explorations of visual hallucinations, and in particular those of Billock and Tsou [V. A. Billock and B. H. Tsou, Proc. Natl. Acad. Sci. USA, 104 (2007), pp. 8490-8495], show that annular rings with a background flicker can induce visual hallucinatio... Read More about Understanding sensory induced hallucinations: From neural fields to amplitude equations.