Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics
Development of credible clinically-relevant brain simulations has been slowed due to a focus on electrophysiology in computational neuroscience, neglecting the multiscale whole-tissue modeling approach used for simulation in most other organ systems. We have now begun to extend the NEURON simulation...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-07-01
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| Series: | Frontiers in Neuroinformatics |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fninf.2018.00041/full |
| _version_ | 1818547933596876800 |
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| author | Adam J. H. Newton Adam J. H. Newton Robert A. McDougal Robert A. McDougal Michael L. Hines William W. Lytton William W. Lytton |
| author_facet | Adam J. H. Newton Adam J. H. Newton Robert A. McDougal Robert A. McDougal Michael L. Hines William W. Lytton William W. Lytton |
| author_sort | Adam J. H. Newton |
| collection | DOAJ |
| description | Development of credible clinically-relevant brain simulations has been slowed due to a focus on electrophysiology in computational neuroscience, neglecting the multiscale whole-tissue modeling approach used for simulation in most other organ systems. We have now begun to extend the NEURON simulation platform in this direction by adding extracellular modeling. The extracellular medium of neural tissue is an active medium of neuromodulators, ions, inflammatory cells, oxygen, NO and other gases, with additional physiological, pharmacological and pathological agents. These extracellular agents influence, and are influenced by, cellular electrophysiology, and cellular chemophysiology—the complex internal cellular milieu of second-messenger signaling and cascades. NEURON's extracellular reaction-diffusion is supported by an intuitive Python-based where/who/what command sequence, derived from that used for intracellular reaction diffusion, to support coarse-grained macroscopic extracellular models. This simulation specification separates the expression of the conceptual model and parameters from the underlying numerical methods. In the volume-averaging approach used, the macroscopic model of tissue is characterized by free volume fraction—the proportion of space in which species are able to diffuse, and tortuosity—the average increase in path length due to obstacles. These tissue characteristics can be defined within particular spatial regions, enabling the modeler to account for regional differences, due either to intrinsic organization, particularly gray vs. white matter, or to pathology such as edema. We illustrate simulation development using spreading depression, a pathological phenomenon thought to play roles in migraine, epilepsy and stroke. Simulation results were verified against analytic results and against the extracellular portion of the simulation run under FiPy. The creation of this NEURON interface provides a pathway for interoperability that can be used to automatically export this class of models into complex intracellular/extracellular simulations and future cross-simulator standardization. |
| first_indexed | 2024-12-12T08:13:16Z |
| format | Article |
| id | doaj.art-3765be7ef5e344e8bd97ccf6f84deb1c |
| institution | Directory Open Access Journal |
| issn | 1662-5196 |
| language | English |
| last_indexed | 2024-12-12T08:13:16Z |
| publishDate | 2018-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj.art-3765be7ef5e344e8bd97ccf6f84deb1c2022-12-22T00:31:41ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962018-07-011210.3389/fninf.2018.00041372342Using NEURON for Reaction-Diffusion Modeling of Extracellular DynamicsAdam J. H. Newton0Adam J. H. Newton1Robert A. McDougal2Robert A. McDougal3Michael L. Hines4William W. Lytton5William W. Lytton6Department of Neuroscience, Yale University, New Haven, CT, United StatesSUNY Downstate Medical Center, The State University of New York, New York, NY, United StatesDepartment of Neuroscience, Yale University, New Haven, CT, United StatesCenter for Medical Informatics, Yale University, New Haven, CT, United StatesDepartment of Neuroscience, Yale University, New Haven, CT, United StatesSUNY Downstate Medical Center, The State University of New York, New York, NY, United StatesNeurology, Kings County Hospital Center, Brooklyn, NY, United StatesDevelopment of credible clinically-relevant brain simulations has been slowed due to a focus on electrophysiology in computational neuroscience, neglecting the multiscale whole-tissue modeling approach used for simulation in most other organ systems. We have now begun to extend the NEURON simulation platform in this direction by adding extracellular modeling. The extracellular medium of neural tissue is an active medium of neuromodulators, ions, inflammatory cells, oxygen, NO and other gases, with additional physiological, pharmacological and pathological agents. These extracellular agents influence, and are influenced by, cellular electrophysiology, and cellular chemophysiology—the complex internal cellular milieu of second-messenger signaling and cascades. NEURON's extracellular reaction-diffusion is supported by an intuitive Python-based where/who/what command sequence, derived from that used for intracellular reaction diffusion, to support coarse-grained macroscopic extracellular models. This simulation specification separates the expression of the conceptual model and parameters from the underlying numerical methods. In the volume-averaging approach used, the macroscopic model of tissue is characterized by free volume fraction—the proportion of space in which species are able to diffuse, and tortuosity—the average increase in path length due to obstacles. These tissue characteristics can be defined within particular spatial regions, enabling the modeler to account for regional differences, due either to intrinsic organization, particularly gray vs. white matter, or to pathology such as edema. We illustrate simulation development using spreading depression, a pathological phenomenon thought to play roles in migraine, epilepsy and stroke. Simulation results were verified against analytic results and against the extracellular portion of the simulation run under FiPy. The creation of this NEURON interface provides a pathway for interoperability that can be used to automatically export this class of models into complex intracellular/extracellular simulations and future cross-simulator standardization.https://www.frontiersin.org/article/10.3389/fninf.2018.00041/fullreusabilitycomputer simulationmultiscale modelingspreading depressionstroke |
| spellingShingle | Adam J. H. Newton Adam J. H. Newton Robert A. McDougal Robert A. McDougal Michael L. Hines William W. Lytton William W. Lytton Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics Frontiers in Neuroinformatics reusability computer simulation multiscale modeling spreading depression stroke |
| title | Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics |
| title_full | Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics |
| title_fullStr | Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics |
| title_full_unstemmed | Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics |
| title_short | Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics |
| title_sort | using neuron for reaction diffusion modeling of extracellular dynamics |
| topic | reusability computer simulation multiscale modeling spreading depression stroke |
| url | https://www.frontiersin.org/article/10.3389/fninf.2018.00041/full |
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