Large scale modeling tools for computational neuroscience

Dnr:

SNIC 2017/1-90

Type:

SNAC Medium

Principal Investigator:

Mikael Djurfeldt

Affiliation:

Kungliga Tekniska högskolan

Start Date:

2017-03-09

End Date:

2018-04-01

Primary Classification:

30105: Neurovetenskaper

Secondary Classification:

10203: Bioinformatik (beräkningsbiologi) (tillämpningar under 10610)

Tertiary Classification:

10201: Datavetenskap (= Datalogi)

Webpage:

http://github.com/INCF/MUSIC

Allocation

Abstract

MUSIC and CSA are two tools useful for large scale modeling in computational neuroscience. MUSIC is a framework for co-simulation which allows neuronal network simulators and other tools to communicate on-line during simulation. CSA (the Connection-set Algebra) is a formalism for expressing neuronal network connectivity as well as a scalable implementation. The purpose of this project is to test and improve the scalability of these tools.