RT Journal Article
SR Electronic
T1 NetPyNE: a tool for data-driven multiscale modeling of brain circuits
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 461137
DO 10.1101/461137
A1 Salvador Dura-Bernal
A1 Benjamin A Suter
A1 Padraig Gleeson
A1 Matteo Cantarelli
A1 Adrian Quintana
A1 Facundo Rodriguez
A1 David J Kedziora
A1 George L Chadderdon
A1 Cliff C Kerr
A1 Samuel A Neymotin
A1 Robert McDougal
A1 Michael Hines
A1 Gordon M G Shepherd
A1 William W Lytton
YR 2018
UL http://biorxiv.org/content/early/2018/11/03/461137.abstract
AB Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The widely used NEURON tool enables simulation ranging from the molecular to the network level. However, building data-driven large-scale network models and running parallel simulations using NEURON remains a technically difficult task. Additionally, the lack of standardization makes it hard to understand, reproduce and reuse many existing models. Here we present NetPyNE, a tool that provides both a programmatic and graphical interface to facilitate the definition, parallel simulation and analysis of data-driven multiscale network models in NEURON. Users can provide specifications at a high level via a standardized declarative language, e.g. a connectivity rule, instead of millions of explicit cell-to-cell connections. NetPyNE clearly separates model parameters from implementation code. With a single command, NetPyNE can then generate the NEURON network model and run efficiently parallelized simulations. The user can select from a variety of built-in functions to visualize and analyze the results, including connectivity matrices, voltage traces, raster plots, local field potentials or information transfer measures. NetPyNE also includes a graphical user interface, which allows users to intuitively access all key functionality, including interactive visualizations of the 3D network. NetPyNE models and results can be saved and loaded using common file formats, and imported/exported to the NeuroML standardized language, facilitating model sharing and simulator interoperability. NetPyNE automates parameter exploration via batch simulations and provides pre-defined, configurable setups to submit jobs in supercomputers. The tool’s website (www.netpyne.org) includes comprehensive documentation, tutorials and Q&A forums. NetPyNE is currently being used to develop models of different brain regions – including thalamus, cortex, claustrum, hippocampus and basal ganglia – and phenomena – including dendritic computations, oscillations, epilepsy, and transcranial magnetic stimulation. It is also employed by the Open Source Brain portal to run parallel simulation of NeuroML-based models, and by the Human Neocortical Solver (hnn.brown.edu) tool to flexibly build cortical models. NetPyNE enables both expert and inexperienced modelers to tackle challenging problems in neuroscience.