NFTsim: Theory and Simulation of Multiscale Neural Field Dynamics

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.

Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

“…Neural Field Theory (NFT) provides a nonlinear, statistical model for the dynamics of populations of neuronal cells and their interactions via dendrites and axons [15,16,25,26,27]. Population-averaged properties such as mean firing rate and axonal pulse rate are modeled as a function of time t. We have used the NFTsim model [23]. The mathematical description and parameter values are summarized in the Supplementary Material.…”

“…They have multiple projections to a population of layer 5 excitatory which also receive low-intensity direct stimulation from the TMS pulses. These three are modeled with NFTsim [23]. The axonal flux from the layer 5 cells stimulates a population of motoneurons within the spinal cord; each motoneuron firing produces a response from the muscle fibres.…”

“…The layer 2/3 excitatory, layer 2/3 inhibitory and layer 5 populations plus the external stimulation are modeled with NFTsim [23]. Although there are many parameters, many have physical constraints placed on them [29].…”

“…where z is a characteristic response timescale. [23] for the neural field modeling. The subscripts e, i and v denote layer 2/3 excitatory, layer 2/3 inhibitory and layer 5 populations respectively.…”

“…The NFTsim model [23] uses a neural field approach to calculate populationaveraged descriptions of neural behavior as a function of time and space. However, in this work we have excluded explicit spatial variation.…”