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      NFTsim: Theory and Simulation of Multiscale Neural Field Dynamics

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          Abstract

          A user ready, portable, documented software package, NFTsim, is presented to facilitate numerical simulations of a wide range of brain systems using continuum neural field modeling. NFTsim enables users to simulate key aspects of brain activity at multiple scales. At the microscopic scale, it incorporates characteristics of local interactions between cells, neurotransmitter effects, synaptodendritic delays and feedbacks. At the mesoscopic scale, it incorporates information about medium to large scale axonal ranges of fibers, which are essential to model dissipative wave transmission and to produce synchronous oscillations and associated cross-correlation patterns as observed in local field potential recordings of active tissue. At the scale of the whole brain, NFTsim allows for the inclusion of long range pathways, such as thalamocortical projections, when generating macroscopic activity fields. The multiscale nature of the neural activity produced by NFTsim has the potential to enable the modeling of resulting quantities measurable via various neuroimaging techniques. In this work, we give a comprehensive description of the design and implementation of the software. Due to its modularity and flexibility, NFTsim enables the systematic study of an unlimited number of neural systems with multiple neural populations under a unified framework and allows for direct comparison with analytic and experimental predictions. The code is written in C++ and bundled with Matlab routines for a rapid quantitative analysis and visualization of the outputs. The output of NFTsim is stored in plain text file enabling users to select from a broad range of tools for offline analysis. This software enables a wide and convenient use of powerful physiologically-based neural field approaches to brain modeling. NFTsim is distributed under the Apache 2.0 license.

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              The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields

              The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years; however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space–time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG). Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: MethodologyRole: ResourcesRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Software
                Role: InvestigationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: InvestigationRole: SoftwareRole: VisualizationRole: Writing – original draft
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: InvestigationRole: Software
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                August 2018
                22 August 2018
                : 14
                : 8
                : e1006387
                Affiliations
                [1 ] School of Physics, University of Sydney, Sydney, Australia
                [2 ] Center for Integrative Brain Function, University of Sydney, Sydney, Australia
                [3 ] Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
                [4 ] Downstate Medical Center, State University of New York, Brooklyn, New York, United States of America
                Hebrew University of Jerusalem, ISRAEL
                Author notes

                The authors have declared that no competing interests exist.

                [¤]

                Current address: School of Physics, University of Sydney, New South Wales, Australia

                Author information
                http://orcid.org/0000-0002-1545-6380
                http://orcid.org/0000-0002-9618-6457
                Article
                PCOMPBIOL-D-17-02123
                10.1371/journal.pcbi.1006387
                6122812
                30133448
                989bd6b6-4eb2-4a49-9a15-40c034858930
                © 2018 Sanz-Leon et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 11 January 2018
                : 22 July 2018
                Page count
                Figures: 10, Tables: 5, Pages: 37
                Funding
                Funded by: Australian Research Council - Laureate Fellowship
                Award ID: FL1401000025
                Award Recipient :
                Funded by: Centre of Excellence Integrative Brain Function Australian Research Council
                Award ID: CE140100007
                Award Recipient :
                This work was supported by an Australian Research Council ( www.arc.gov.au) Laureate Fellowship (grant number FL1401000025) and the Australian Research Council Center of Excellence for Integrative Brain Function (grant number CE140100007). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Research and Analysis Methods
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                Custom metadata
                vor-update-to-uncorrected-proof
                2018-09-04
                All relevant data are within the paper and its Supporting Information files. In addition, all configuration files used in the paper are available from the public repository: https://github.com/BrainDynamicsUSYD/nftsim.

                Quantitative & Systems biology
                Quantitative & Systems biology

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