This may be interesting for folks interested in learning modelling using
----- Forwarded message from Padraig Gleeson -----
Date: Fri, 26 Feb 2021 16:00:07 +0000
From: Padraig Gleeson <p.gleeson(a)ucl.ac.uk>
Subject: [Neuroml-technology] Announcing 3 NeuroML hackathon sessions at HARMONY 2021
List-Id: NeuroML main mailing list <neuroml-technology.lists.sourceforge.net>
We will be running 3 online hackathon sessions during the upcoming HARMONY 2021
meeting on 23-25th March. The general theme of the sessions will be: Learn to
build, visualise, analyse and simulate your models using NeuroML.
Why take part?
These hackathons will give members of the modelling community the chance to:
• Get high level introductions to the NeuroML language and tool chain
• Meet the NeuroML core development team and editors
• Find out the latest information on which simulators/applications support
• Open, discuss and work on issues related to converting your model to
NeuroML, or supporting NeuroML in your simulator
• Learn how to share your models with the community
Times and dates
All sessions will be online and take place over 3 hours (9am-noon Pacific;
12-3pm EST time; 4-7pm UK/UTC; 5-8pm CET, 9:30pm-12:30am IST; note non-standard
US/EU time differences that week). The broad focus of each of the sessions
(dependent on interests of attendees) is:
Tues 23rd March: Introduction to NeuroML, general questions about usage
Wed 24th March: Detailed cell/conductance based models (e.g. converting
channels to NeuroML)
Thus 25th March: Abstract/point neuron networks including PyNN interactions
To take part in the hackathon, please register at http://co.mbine.org/events/
HARMONY_2021 for the HARMONY meeting (registration is free). You will get sent
details to access the agenda on https://harmony2021.sched.com, which will have
links to the Zoom sessions for each of the days.
Open an issue beforehand!
While it will be possible to raise and discuss new issues at the hackathons, it
will be easier to manage and plan work/discussions if you open an issue with a
description of the problem you are trying to address at: https://github.com/
To aid communication with the community during (and after) the meeting, we have
a Slack channel for NeuroML related discussions. Please reply to this mail for
We look forward to working with the community to drive further uptake of
NeuroML compliant models and tools!
Room 321, Anatomy Building
Department of Neuroscience, Physiology& Pharmacology
University College London
London WC1E 6BT
+44 207 679 3214
Neuroml-technology mailing list
----- End forwarded message -----
Ankur Sinha "FranciscoD" (He / Him / His) | https://fedoraproject.org/wiki/User:Ankursinha
Time zone: Europe/London
Apologies for the cross-posts.
The INCF/OCNS Software Working Group (WG) is happy to announce the
next "Dev session" on Neurolib where Caglar Cakan will introduce the
software and then discuss its *development* pipeline.
The session will be held on Feb 23, 2021 at 1700 UTC. Zoom link:
The aim of these sessions is to stimulate discussion of the development
practices and tools used by different teams to improve the software we
use while also improving our knowledge of these practices and tools.
We also hope to encourage more users of these tools to contribute to
their development to ensure their longevity.
The abstract of the talk is below:
neurolib is a computational framework for whole-brain modelling written
in Python. It provides a set of neural mass models that represent the
average activity of a brain region on a mesoscopic scale. In a
whole-brain network model, brain regions are connected with each other
based on structural connectivity data, i.e. the connectome of the brain.
neurolib can load structural and functional data sets, set up a
whole-brain model, manage its parameters, simulate it, and organize its
outputs for later analysis. The activity of each brain region can be
converted into a simulated BOLD signal in order to calibrate the model
to empirical data from functional magnetic resonance imaging (fMRI).
Extensive model analysis is possible using a parameter exploration
module, which allows to characterize the model’s behaviour given a set
of changing parameters. An optimization module allows for fitting a
model to multimodal empirical data using an evolutionary algorithm.
Besides its included functionality, neurolib is designed to be
extendable such that custom neural mass models can be implemented
easily. neurolib offers a versatile platform for computational
neuroscientists for prototyping models, managing large numerical
experiments, studying the structure-function relationship of brain
networks, and for in-silico optimization of whole-brain models.
If you develop software for neuroscience, we would love to hear about
your development pipeline. Please get in touch with the Software WG
either on INCF's Neurostars platform or on our GitHub repository.
The WG is a community based group that is open to everyone at all levels
of their careers (academic or otherwise). Please introduce yourself to
the community on our channels to get involved.
On behalf of the WG,
Ankur Sinha (He / Him / His)
Research Fellow at the Silver Lab | http://silverlab.org/
Department of Neuroscience, Physiology, & Pharmacology
University College London, London, UK
Time zone: Europe/London
Hello Neuro SIG,
My name is Josh, and I have been a member of the Fedora community since 2014 (although haven’t been very active). I am excited to start helping out in packaging for compneuro.
Brief background in case you find yourself needing assistance in an area that involves something I am experienced in (love to help, and try for transparency when I don’t know something):
* 2-3 years python
* 4-5 years golang
* Hobby/minimal experience in Node/Ruby/C#/Haskell/Scala
* NGINX experience
Looking forward to helping in any way I can.