Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks
Neuronal activity is the result of both the electrophysiology and chemophysiology. A neuron can be well-represented for the purposes of electrophysiological simulation as a tree composed of connected cylinders. This representation is also apt for 1D simulations of their chemophysiology, provided the...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Neuroinformatics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fninf.2022.847108/full |
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| author | Robert A. McDougal Robert A. McDougal Robert A. McDougal Cameron Conte Cameron Conte Cameron Conte Lia Eggleston Adam J. H. Newton Adam J. H. Newton Adam J. H. Newton Hana Galijasevic |
| author_facet | Robert A. McDougal Robert A. McDougal Robert A. McDougal Cameron Conte Cameron Conte Cameron Conte Lia Eggleston Adam J. H. Newton Adam J. H. Newton Adam J. H. Newton Hana Galijasevic |
| author_sort | Robert A. McDougal |
| collection | DOAJ |
| description | Neuronal activity is the result of both the electrophysiology and chemophysiology. A neuron can be well-represented for the purposes of electrophysiological simulation as a tree composed of connected cylinders. This representation is also apt for 1D simulations of their chemophysiology, provided the spatial scale is larger than the diameter of the cylinders and there is radial symmetry. Higher dimensional simulation is necessary to accurately capture the dynamics when these criteria are not met, such as with wave curvature, spines, or diffusion near the soma. We have developed a solution to enable efficient finite volume method simulation of reaction-diffusion kinetics in intracellular 3D regions in neuron and network models and provide an implementation within the NEURON simulator. An accelerated version of the CTNG 3D reconstruction algorithm transforms morphologies suitable for ion-channel based simulations into consistent 3D voxelized regions. Kinetics are then solved using a parallel algorithm based on Douglas-Gunn that handles the irregular 3D geometry of a neuron; these kinetics are coupled to NEURON's 1D mechanisms for ion channels, synapses, pumps, and so forth. The 3D domain may cover the entire cell or selected regions of interest. Simulations with dendritic spines and of the soma reveal details of dynamics that would be missed in a pure 1D simulation. We describe and validate the methods and discuss their performance. |
| first_indexed | 2024-04-12T16:49:44Z |
| format | Article |
| id | doaj.art-41653ecd244f433ea39076b7cfc50dff |
| institution | Directory Open Access Journal |
| issn | 1662-5196 |
| language | English |
| last_indexed | 2024-04-12T16:49:44Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj.art-41653ecd244f433ea39076b7cfc50dff2022-12-22T03:24:25ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962022-05-011610.3389/fninf.2022.847108847108Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and NetworksRobert A. McDougal0Robert A. McDougal1Robert A. McDougal2Cameron Conte3Cameron Conte4Cameron Conte5Lia Eggleston6Adam J. H. Newton7Adam J. H. Newton8Adam J. H. Newton9Hana Galijasevic10Department of Biostatistics, Yale School of Public Health, New Haven, CT, United StatesCenter for Medical Informatics, Yale University, New Haven, CT, United StatesProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United StatesCenter for Medical Informatics, Yale University, New Haven, CT, United StatesDepartment of Neuroscience, Yale School of Medicine, New Haven, CT, United StatesDepartment of Statistics, The Ohio State University, Columbus, OH, United StatesYale College, Yale University, New Haven, CT, United StatesDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, United StatesCenter for Medical Informatics, Yale University, New Haven, CT, United StatesDepartment of Physiology and Pharmacology, SUNY Downstate Health Sciences University, New York, NY, United StatesYale College, Yale University, New Haven, CT, United StatesNeuronal activity is the result of both the electrophysiology and chemophysiology. A neuron can be well-represented for the purposes of electrophysiological simulation as a tree composed of connected cylinders. This representation is also apt for 1D simulations of their chemophysiology, provided the spatial scale is larger than the diameter of the cylinders and there is radial symmetry. Higher dimensional simulation is necessary to accurately capture the dynamics when these criteria are not met, such as with wave curvature, spines, or diffusion near the soma. We have developed a solution to enable efficient finite volume method simulation of reaction-diffusion kinetics in intracellular 3D regions in neuron and network models and provide an implementation within the NEURON simulator. An accelerated version of the CTNG 3D reconstruction algorithm transforms morphologies suitable for ion-channel based simulations into consistent 3D voxelized regions. Kinetics are then solved using a parallel algorithm based on Douglas-Gunn that handles the irregular 3D geometry of a neuron; these kinetics are coupled to NEURON's 1D mechanisms for ion channels, synapses, pumps, and so forth. The 3D domain may cover the entire cell or selected regions of interest. Simulations with dendritic spines and of the soma reveal details of dynamics that would be missed in a pure 1D simulation. We describe and validate the methods and discuss their performance.https://www.frontiersin.org/articles/10.3389/fninf.2022.847108/fullreaction-diffusioncomputer simulation3Dmulti-scale modelingreusability |
| spellingShingle | Robert A. McDougal Robert A. McDougal Robert A. McDougal Cameron Conte Cameron Conte Cameron Conte Lia Eggleston Adam J. H. Newton Adam J. H. Newton Adam J. H. Newton Hana Galijasevic Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks Frontiers in Neuroinformatics reaction-diffusion computer simulation 3D multi-scale modeling reusability |
| title | Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks |
| title_full | Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks |
| title_fullStr | Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks |
| title_full_unstemmed | Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks |
| title_short | Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks |
| title_sort | efficient simulation of 3d reaction diffusion in models of neurons and networks |
| topic | reaction-diffusion computer simulation 3D multi-scale modeling reusability |
| url | https://www.frontiersin.org/articles/10.3389/fninf.2022.847108/full |
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