Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits.

Kael Dai,Richard Xu,Sergey L Gratiy,Binghuang Cai,Anton Arkhipov,Atle E Rimehaug,Stefan Mihalas,Yazan N Billeh,Alexander J Stasik,Nicholas Cain,Christof Koch,Gaute T Einevoll,Daniele Marinazzo

doi:10.1371/journal.pcbi.1008386

Abstract

Experimental studies in neuroscience are producing data at a rapidly increasing rate, providing exciting opportunities and formidable challenges to existing theoretical and modeling approaches. To turn massive datasets into predictive quantitative frameworks, the field needs software solutions for systematic integration of data into realistic, multiscale models. Here we describe the Brain Modeling ToolKit (BMTK), a software suite for building models and performing simulations at multiple levels of resolution, from biophysically detailed multi-compartmental, to point-neuron, to population-statistical approaches. Leveraging the SONATA file format and existing software such as NEURON, NEST, and others, BMTK offers a consistent user experience across multiple levels of resolution. It permits highly sophisticated simulations to be set up with little coding required, thus lowering entry barriers to new users. We illustrate successful applications of BMTK to large-scale simulations of a cortical area. BMTK is an open-source package provided as a resource supporting modeling-based discovery in the community.

Highlights

Recent emergence of systematic large-scale efforts for comprehensive characterization of brain cell types, their connectivity, and in vivo activity (e.g. [1,2,3,4,5,6]) is fundamentally reshaping neuroscience research
The BioNet module provides an interface to NEURON [8] for simulations that involve biophysically detailed, compartmental neuronal models or point-neuron models; PointNet–to NEST [9] for highly efficient point-neuron simulations; PopNet–to the package diPDE [26], which implements a population density approach for simulations of coupled networks of neuronal populations; and FilterNet–to Brain Modeling ToolKit (BMTK)’s built-in solver of filter input-output transformations
Does the SONATA format enable this simple workflow under BMTK, it supports easy model sharing across software packages, as SONATA is implemented in a broad range of modeling tools, such as Blue Brain’s Brion/Brain, pyNeuroML [21,22], pyNN [23], and NetPyNE [20]

Summary

Introduction

Recent emergence of systematic large-scale efforts for comprehensive characterization of brain cell types, their connectivity, and in vivo activity (e.g. [1,2,3,4,5,6]) is fundamentally reshaping neuroscience research. We use an example of a simple network consisting of two uniform populations of neurons (excitatory and inhibitory), which we instantiate and simulate using biophysically-detailed compartmental neuronal models in BioNet, point-neuron models in PointNet, and neuronal populations in PopNet. we describe the FilterNet module, which permits one to process stimuli through arrays of filters, currently focusing on converting visual stimuli to spikes that can be used as inputs to simulations of neural networks of vision.

Results

Conclusion