Overview

morphforge is a high level, simulator independent, Python library for building simulations of small populations of multi-compartmental neurons, in which membrane voltage is calculated from the sum of individual ionic currents flowing across a membrane. It was built as part of Mike Hull’s Ph.D thesis; investigating the role of electrical coupling in small populations of interneurons in Xenopus laevis tadpoles.

The use-case of the API is to allows the user to quickly construct simulations of small populations of neurons and synaptic connections, with particular focus on:

1. allowing simulation specification, with visualisation and analysis in a minimal, clean, human readable language;
2. reduction of complex simulation tool chains to a single python script;
3. promoting reproducible research through automatic self-documentation;
4. encourage the re-use of components such like morphologies, neurons and channels such so that specific and stochastic variation in parameters is simple;
5. transparent handling of different units;
6. allowing the use of established formats, (e.g. NEURON nmodl files), but also simplify the definition and sharing of new channel types easily, including the possibility to support other libraries and standards easily (e.g. PyNN, 9ML, NeuroML, CSA)

Morphforge is not a simulator; it is a high layer interface to simulators (currently NEURON), providing a set of high-level primitives for specifying morphologies, channel distributions, synapses, in python. It was designed to remove a lot of tedious code currently needed to specify such simulations and what to record from them and provides an API to make visualising results simpler.

Example Use-Case

Consider the following example:

“I would like to build a network, of 30 neurons. Each soma should be 20(± 3) µm diameter, and axons are 1000µm long with have a hillock of radius 5um for the first 10µm, then tapers into a axon of radius 0.3µm which. I will use a single compartment for the soma, divide the hillock into compartments of length 1um, and the axon into 100 compartments. We will use the sodium and potassium voltage-gated channels as specified by the equations and parameters in paper X, but we want to use 3 times the density of sodium channels on the axon hillock.

The neurons should be connected by gap junctions, distributed according to algorithm X, with resistances of 1GOhm ± 500MOhm. The neurons also self-excite other neurons in the population with AMPA synapses, with a probability of connections between any pair of neurons of 20%. I would like to stimulate this network with NMDA synaptic input to ~50% of the neurons at fixed times, as well as different levels of step current injections to cell 12, and measure plot graphs of the ionic currents flowing across the membrane of cells 2, 12, and any cells that spike, as well as the membrane voltage of all the neurons. I want to compare against with the case when the gap junctions have been blocked.”

The morphforge allows the specification of this complete simulation and visualisation of the results in a single python scripts of less than 100 lines, only requiring a single command to run. It is designed to make it possible to specify connection algorithms, morphologies, channel descriptions and simulation parameters as high-level objects, such that they can be reused in across other simulations, without the need to copy and paste code. Units are handled transparently, reports of the simulation setup can be automatically generated, and a clean separation between of simulation and visualisation is achieved through a mechanism of tagging in the framework. The library is built on standard Python libraries, (Numpy, matplotlib), making it easy to integrate with other libraries.

The framework is under active development, with a NEURON backend, currently supporting everything in the above example.

Installing Morphforge

Examples

Users Guide

For more indepth API information, please see the Morphforge Users Guide

Contact Information

• Email me: ?ike?ulluk@googlemail.com where ?s can be found at the top of the page!
• Mailing list: http://groups.google.com/group/morphforge
• GitHub: https://github.com/mikehulluk/morphforge