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In this paper, we analyze the spatiotemporal mean field model developed by Liley et al. [1] in order to advance our understanding of the wide effects of pharmacological agents and anesthetics. Specifically, we use the spatiotemporal mean field model in [1] for capturing the electrical activity in the neocortex to computationally study the emergence of α- and gamma-band rhythmic activity in the brain. We show that a oscillations in the solutions of the model appear globally across the neocortex, whereas gamma oscillations can emerge locally as a result of a bifurcation in the dynamics of the model. We solve the dynamic equations of the model using a finite element solver package and show that our results verify the predictions made by bifurcation analysis.
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A Computational Study of a Spatiotemporal Mean Field Model Capturing the Emergence of Alpha and Gamma Rhythmic Activity in the Neocortex
In this paper, we analyze the spatiotemporal mean field model developed by Liley et al. in order to advance our understanding of the wide effects of pharmacological agents and anesthetics. Specifically, we use the spatiotemporal mean field model for capturing the electrical activity in the neocortex to computationally study the emergence of α - and γ -band rhythmic activity in the brain. We show that α oscillations in the solutions of the model appear globally across the neocortex, whereas γ oscillations can emerge locally as a result of a bifurcation in the dynamics of the model. We solve the dynamic equations of the model using a finite element solver package and show that our results verify the predictions made by bifurcation analysis.
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- Award ID(s):
- 1708792
- PAR ID:
- 10093148
- Date Published:
- Journal Name:
- Symmetry
- Volume:
- 10
- Issue:
- 11
- ISSN:
- 2073-8994
- Page Range / eLocation ID:
- 568
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/sym10110568
