Section: New Software and Platforms

BRIAN Contributions

Keywords: Spiking neurons models - Neurosciences - BRIAN

Functional Description

Spiking Neuron Templates

BRIAN-compatible libraries has been developed by the team for various ionic currents to be assembled together to create template neurons. The purpose of these is to speed up simulation set-up time and reduce code duplication across simulation scripts. Template neurons are defined by the ionic currents that flow through their membrane. Implemented templates include:

• Hodgkin-Huxley pyramidal neuron (leak, sodium and potassium)

• Hodgkin-Huxley pyramidal neuron with calcium-activated non-specific (CAN) receptors (leak, sodium, potassium, m-current, calcium, CAN)

• Hodgkin-Huxley fast-spiking inhibitory hippocampal (leak, sodium, potassium, m-current)

Implemented ionic current libraries include:

• Traub and Miles Hodgkin-Huxley ($I_{Leak},I_K,I_{Na}$) implementation;

• M-Current ($I_M$) implementation;

• Calcium current ($I_L$) implementation;

• Calcium pump mechanisms ($\frac{\mathrm{d}Ca}{\mathrm{d}t}$) implementation;

• Calcium-activated non-selective current ($I_{CAN}$) implementation;

• Wang and Buszáki inhibitory Hodgkin-Huxley ($I_{Leak},I_K,I_{Na}$) implementation;

The current library is easily extensible by third-party users due to its hierarchical design. The template neurons and their currents are defined as YAML (http://www.yaml.org/ ) files, which are conveniently parsed by a Python library which acts as an interface to the BRIAN simulator API's.

BRIAN Simulation Parameters

A python library which acts as a wrapper for BRIAN simulations, allowing the user to define simulation parameters in external YAML files, which are then parsed and forwarded to the BRIAN simulator. In addition, simulation parameters can be overridden via the command-line when invoking the python script containing the simulation.

• Participants: Francesco Giovannini

• Contact: Francesco Giovannini

• URL: http://www.briansimulator.org