NeuroMaC: Neuronal Morphologies & Circuits

We think that to fully understand neuronal morphologies, circuits and their variance we have to look at the substrate at large. That is, how neurons developed and interactions between a developing neuron and the substrate (e.g., toher neurons, boundaries, capillaries,...) influence their morphology. For this purpose we developed NeuroMaC

NeuroMaC is a phenomenological, computational framework to generate \ large numbers of virtual neuronal morphologies (and resultant \ microcircuits) simultaneously according to growth-rules expressed in \ terms of interactions with the environment.

• NeuroMaC: Neuronal Morphologies & Circuits
• Computational framework: a suite of software tools built around \ a central concept
• Virtual neuronal morphologies: 3D digital descriptions of \ neuronal shape (both axons and dendrites)
• Microcircuits: Morphologies are generated together in a \ simulated volume. With the addition of connections rules circuits emerge.
• Interactions: Growth-cones branch, terminate and elongate. Each \ of these steps can be influenced by environmental cues. Most obvious \ is guidance through repulsion and attraction to simulated cues.
• Phenomenological: Neither biochemical pathways nor physics are \ simulated. As such, growth is purely phenomenological. NeuroMaC is \ not a simulator of actual neuronal development.

.. warning:: Currenly, a prototype of NeuroMaC is implemented in Python. \ This version is a proof-of-principle and nothing beyond that. This \ prototype has many limitations and we are working towards a \ non-prototype version, which should be released in the next year. \ The current prototype code is freely available.

Documentation <http://b-torbennielsen.home.oist.jp/neuromac/>_

Main author: Ben Torben-Nielsen <http://b-torbennielsen.home.oist.jp/>_