Name: Adaptive Behaviour Research Group
Type: User
Company: Department of Psychology, University of Sheffield
Bio: This contains repositories of computational models developed by members of the Adaptive Behaviour Research Group in Sheffield. Managed by @sebjameswml
Location: Sheffield, UK
Blog: http://www.abrg.group.shef.ac.uk/
Adaptive Behaviour Research Group's Projects
Soft body models with point cloud collision detection
Evolution, genetics and the Baldwin effect explored by means of a Boolean network model
Emergence of whisker barrels with modified Karbowski-Ermentrout-like axon branching population model
John Brooke's extension of Ermentrout2009
Modular Library - Dockerfile Synthesizer
An implementation of reaction-diffusion whisker barrel patterns after Ermentrout et al 2009 (PLOS Comp Biol)
A Git Tutorial for Computational Neuroscience students and researchers
The Gurney-Prescott-Redgrave Basal Ganglia model.
A SpineML implementation of the GPR-like model implemented by Basab Sen Bhattacharya and run on SpiNNaker.
The Gurney-Prescott-Redgrave model coded up with Izhikevich model neurons
An example Izhikevic neuron model implemented in SpineML, with an Ipython Notebook to explore it
testing just the docs template
Data and analysis code for the paper 'Target-distractor Synchrony Affects Performance in a Novel Motor Task for Studying Action Selection'
For models and work forming the MammalBot architecture
Collaborative MiRo-E development
A library of supporting code for numerical modelling (JSON config, HDF5 data, Modern OpenGL visualization)
An example project that uses morphologica. Demonstrates how you incorporate morphologica into your own program.
Neo-cortex arealization modelling
ABRG Oculomotor model extended to make antisaccade decisions
Oculomotor model which will integrate with neuro-muscular model of eye
Seb James's working repository
Stuart's self-organising map models
Spatial Analysis of ISH Brain Slice Data
John Brooke's Tessellate project
Code for the paper Biological Action at a Distance
A semi-implemented version of a visual attention model due to Cope and Gurney