Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders
Deep brain stimulation (DBS) has been used successfully as symptomatic treatment in several neurodegenerative disorders, including Parkinson’s disease (PD). However, the mechanisms of its activity inside the brain network are unclear. Many virtual DBS models investigate the dynamics of a subnetwork...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | Brain Multiphysics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666522022000156 |
| _version_ | 1811298014530109440 |
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| author | Hina Shaheen Swadesh Pal Roderick Melnik |
| author_facet | Hina Shaheen Swadesh Pal Roderick Melnik |
| author_sort | Hina Shaheen |
| collection | DOAJ |
| description | Deep brain stimulation (DBS) has been used successfully as symptomatic treatment in several neurodegenerative disorders, including Parkinson’s disease (PD). However, the mechanisms of its activity inside the brain network are unclear. Many virtual DBS models investigate the dynamics of a subnetwork surrounding the basal ganglia (BG) as a spiking network has been attracting a growing body of research in neuroscience. Connectomic data, on the other hand, show that DBS has a wide range of impacts on many distinct cortical and subcortical sites. Notably, the nonlinear reaction–diffusion multiscale mathematical models demonstrate the effectiveness of capturing crucial disease characteristics and are used to simulate large-scale brain activity. The BG and associated nuclei comprise many subcortical cell groups in the brain, and their couplings commonly revealed MRI-based assessments of the strength of anatomical connections. We have developed a hybrid modeling formalism and a unique co-simulation technique that allows us to compute electrodiffusive ion dynamics for the cortex–BG–thalamus (BGTH) brain network model within a large-scale brain connectome. We collect data from the Human Connectome Project (HCP) and propose a closed-loop DBS approach based on the brain network model. Moreover, we select regions in the parameter space that reflect the healthy and Parkinsonian states as well as the impact of DBS on the subthalamic nucleus (STN) and globus pallidus internus (GPi) neurons. We predicted that if we apply the DBS to the system described by the temporal model, the brain maintains a healthy state until 0.05ms for STN neurons and 0.035ms for GPi neurons. A local regulatory mechanism known as feedback inhibition control (FIC) points to the existence of underlying network dynamics in the white matter of connected brain regions. The model showed unanticipated effects that in the presence of diffusion, the human brain maintained a healthy state for a long time after the DBS had been applied to STN and GPi neurons. This research helps us better understand the changes in brain activity caused by DBS and enhances this clinical therapy, thus shedding new light on the importance of DBS mechanisms in BGTH brain network models of neurodegenerative disorders. |
| first_indexed | 2024-04-13T06:13:27Z |
| format | Article |
| id | doaj.art-7ff02de2d6b1416a887f55e7e75b9a28 |
| institution | Directory Open Access Journal |
| issn | 2666-5220 |
| language | English |
| last_indexed | 2024-04-13T06:13:27Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Brain Multiphysics |
| spelling | doaj.art-7ff02de2d6b1416a887f55e7e75b9a282022-12-22T02:58:56ZengElsevierBrain Multiphysics2666-52202022-01-013100058Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disordersHina Shaheen0Swadesh Pal1Roderick Melnik2Corresponding author.; MS2 Discovery Interdisciplinary Research Institute, Wilfrid Laurier University, Waterloo, CanadaMS2 Discovery Interdisciplinary Research Institute, Wilfrid Laurier University, Waterloo, CanadaMS2 Discovery Interdisciplinary Research Institute, Wilfrid Laurier University, Waterloo, CanadaDeep brain stimulation (DBS) has been used successfully as symptomatic treatment in several neurodegenerative disorders, including Parkinson’s disease (PD). However, the mechanisms of its activity inside the brain network are unclear. Many virtual DBS models investigate the dynamics of a subnetwork surrounding the basal ganglia (BG) as a spiking network has been attracting a growing body of research in neuroscience. Connectomic data, on the other hand, show that DBS has a wide range of impacts on many distinct cortical and subcortical sites. Notably, the nonlinear reaction–diffusion multiscale mathematical models demonstrate the effectiveness of capturing crucial disease characteristics and are used to simulate large-scale brain activity. The BG and associated nuclei comprise many subcortical cell groups in the brain, and their couplings commonly revealed MRI-based assessments of the strength of anatomical connections. We have developed a hybrid modeling formalism and a unique co-simulation technique that allows us to compute electrodiffusive ion dynamics for the cortex–BG–thalamus (BGTH) brain network model within a large-scale brain connectome. We collect data from the Human Connectome Project (HCP) and propose a closed-loop DBS approach based on the brain network model. Moreover, we select regions in the parameter space that reflect the healthy and Parkinsonian states as well as the impact of DBS on the subthalamic nucleus (STN) and globus pallidus internus (GPi) neurons. We predicted that if we apply the DBS to the system described by the temporal model, the brain maintains a healthy state until 0.05ms for STN neurons and 0.035ms for GPi neurons. A local regulatory mechanism known as feedback inhibition control (FIC) points to the existence of underlying network dynamics in the white matter of connected brain regions. The model showed unanticipated effects that in the presence of diffusion, the human brain maintained a healthy state for a long time after the DBS had been applied to STN and GPi neurons. This research helps us better understand the changes in brain activity caused by DBS and enhances this clinical therapy, thus shedding new light on the importance of DBS mechanisms in BGTH brain network models of neurodegenerative disorders.http://www.sciencedirect.com/science/article/pii/S2666522022000156Deep brain stimulationBrain connectomeParkinson’s diseaseBasal gangliaLaplacian operatorNeurodegenerative disorders |
| spellingShingle | Hina Shaheen Swadesh Pal Roderick Melnik Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders Brain Multiphysics Deep brain stimulation Brain connectome Parkinson’s disease Basal ganglia Laplacian operator Neurodegenerative disorders |
| title | Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders |
| title_full | Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders |
| title_fullStr | Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders |
| title_full_unstemmed | Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders |
| title_short | Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders |
| title_sort | multiscale co simulation of deep brain stimulation with brain networks in neurodegenerative disorders |
| topic | Deep brain stimulation Brain connectome Parkinson’s disease Basal ganglia Laplacian operator Neurodegenerative disorders |
| url | http://www.sciencedirect.com/science/article/pii/S2666522022000156 |
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