Fractal basins as a mechanism for the nimble brain
Abstract An interesting feature of the brain is its ability to respond to disparate sensory signals from the environment in unique ways depending on the environmental context or current brain state. In dynamical systems, this is an example of multi-stability, the ability to switch between multiple s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-45664-5 |
| _version_ | 1827603859867959296 |
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| author | Erik Bollt Jeremie Fish Anil Kumar Edmilson Roque dos Santos Paul J. Laurienti |
| author_facet | Erik Bollt Jeremie Fish Anil Kumar Edmilson Roque dos Santos Paul J. Laurienti |
| author_sort | Erik Bollt |
| collection | DOAJ |
| description | Abstract An interesting feature of the brain is its ability to respond to disparate sensory signals from the environment in unique ways depending on the environmental context or current brain state. In dynamical systems, this is an example of multi-stability, the ability to switch between multiple stable states corresponding to specific patterns of brain activity/connectivity. In this article, we describe chimera states, which are patterns consisting of mixed synchrony and incoherence, in a brain-inspired dynamical systems model composed of a network with weak individual interactions and chaotic/periodic local dynamics. We illustrate the mechanism using synthetic time series interacting on a realistic anatomical brain network derived from human diffusion tensor imaging. We introduce the so-called vector pattern state (VPS) as an efficient way of identifying chimera states and mapping basin structures. Clustering similar VPSs for different initial conditions, we show that coexisting attractors of such states reveal intricately “mingled” fractal basin boundaries that are immediately reachable. This could explain the nimble brain’s ability to rapidly switch patterns between coexisting attractors. |
| first_indexed | 2024-03-09T05:47:41Z |
| format | Article |
| id | doaj.art-f201dbe8bcda49018f1e500e2da8802c |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T05:47:41Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-f201dbe8bcda49018f1e500e2da8802c2023-12-03T12:19:59ZengNature PortfolioScientific Reports2045-23222023-11-0113111110.1038/s41598-023-45664-5Fractal basins as a mechanism for the nimble brainErik Bollt0Jeremie Fish1Anil Kumar2Edmilson Roque dos Santos3Paul J. Laurienti4Department of Electrical and Computer Engineering, Clarkson UniversityDepartment of Electrical and Computer Engineering, Clarkson UniversityDepartment of Electrical and Computer Engineering, Clarkson UniversityDepartment of Electrical and Computer Engineering, Clarkson UniversityDepartment of Radiology, Wake Forest University School of MedicineAbstract An interesting feature of the brain is its ability to respond to disparate sensory signals from the environment in unique ways depending on the environmental context or current brain state. In dynamical systems, this is an example of multi-stability, the ability to switch between multiple stable states corresponding to specific patterns of brain activity/connectivity. In this article, we describe chimera states, which are patterns consisting of mixed synchrony and incoherence, in a brain-inspired dynamical systems model composed of a network with weak individual interactions and chaotic/periodic local dynamics. We illustrate the mechanism using synthetic time series interacting on a realistic anatomical brain network derived from human diffusion tensor imaging. We introduce the so-called vector pattern state (VPS) as an efficient way of identifying chimera states and mapping basin structures. Clustering similar VPSs for different initial conditions, we show that coexisting attractors of such states reveal intricately “mingled” fractal basin boundaries that are immediately reachable. This could explain the nimble brain’s ability to rapidly switch patterns between coexisting attractors.https://doi.org/10.1038/s41598-023-45664-5 |
| spellingShingle | Erik Bollt Jeremie Fish Anil Kumar Edmilson Roque dos Santos Paul J. Laurienti Fractal basins as a mechanism for the nimble brain Scientific Reports |
| title | Fractal basins as a mechanism for the nimble brain |
| title_full | Fractal basins as a mechanism for the nimble brain |
| title_fullStr | Fractal basins as a mechanism for the nimble brain |
| title_full_unstemmed | Fractal basins as a mechanism for the nimble brain |
| title_short | Fractal basins as a mechanism for the nimble brain |
| title_sort | fractal basins as a mechanism for the nimble brain |
| url | https://doi.org/10.1038/s41598-023-45664-5 |
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