Pinned Repositories
neuroConstruct
neuroConstruct: biophysically detailed neuronal modelling in 3D
NeuroML2
This repository hosts the NeuroML 2 Schema, the ComponentType definitions in LEMS and the core documentation of NeuroML2.
NeuroMLlite
Work towards creating a common JSON based format for compact network specification
pyNeuroML
A single package in Python unifying scripts and modules for reading, writing, simulating and analysing NeuroML2/LEMS models.
OSBv2
An updated version of the Open Source Brain platform
c302
The c302 framework for generating multiscale network models of C. elegans
Cvapp-NeuroMorpho.org
Version of Cvapp as used on NeuroMorpho.org. Based on Robert Cannon's initial implementation.
libNeuroML
This package provides Python libNeuroML, for working with neuronal models specified in NeuroML
pyelectro
Analysis of electrophysiology in Python
redmine
Redmine is a flexible project management web application written using Ruby on Rails framework.
pgleeson's Repositories
pgleeson/Cvapp-NeuroMorpho.org
Version of Cvapp as used on NeuroMorpho.org. Based on Robert Cannon's initial implementation.
pgleeson/neuralensemble-docker
Docker images for neuroscience
pgleeson/nrn
NEURON Simulator
pgleeson/Biosimulators_XPP
XPP mathematical simulation program via BioSimulators-compliant command-line interface and Docker container
pgleeson/Brain-Cog
Brain-inspired Cognitive Intelligence Engine (BrainCog) is a brain-inspired spiking neural network based platform for simulating the cognitive brains of different animal species at multiple scales and realizing brain-inspired Artificial Intelligence. The long term goal of BrainCog is to provide a comprehensive theory and system to decode the mechanisms and principles of human intelligence and its evolution, and develop artificial brains for brain-inspired conscious living machines in future human-machine society.
pgleeson/CE_locomotion
Neuromechanical model of locomotion in C. elegans (in collaboration with Dr. Erick Olivares and Prof. Randall Beer)
pgleeson/codespacesDemo
pgleeson/dandi-archive
DANDI API server and Web app
pgleeson/DANDIArchiveShowcase
Scripts for interacting with the DANDI Archive
pgleeson/eden
Read-only mirror code repository for the EDEN neural simulator, on Github. ❗Please go to the main repo for issues, pull requests, and other interaction: https://gitlab.com/neurocomputing-lab/Inferior_OliveEMC/eden
pgleeson/FunctionalScala
The website for Functional Scala
pgleeson/GoCModel_Basic
network of gocs with low frequency background inputs
pgleeson/gsoc2016__brian2lems
Google Summer of Code project 2016 (Importing and exporting simulator-independent model-descriptions with the Brian simulator)
pgleeson/M1_NetPyNE_CellReports_2023
Multiscale model of mouse primary motor cortex (M1) circuits developed in NetPyNE
pgleeson/MDF
This repository contains the source for the MDF specification and Python API
pgleeson/modelspec
Functionality for specifying models & enabling automatic serialization - will be used by MDF & NeuroMLlite
pgleeson/NetPyNE-UI
NetPyNE User interface
pgleeson/Neuropeptide-Connectome
Scripts to run the analysis shown in the paper https://doi.org/10.1101/2022.10.30.514396
pgleeson/ngc-learn
NGC-Learn: Predictive Coding and Neurobiologically-Motivated Learning in Python
pgleeson/NLP-MDF
pgleeson/nwb_conversion
pgleeson/openneurolab
Gleeson Lab of Open Neuroscience & AI @ UCL
pgleeson/PsyNeuLink
A block modeling system for cognitive neuroscience
pgleeson/sibernetic
This is a C++ implementation of the Contractile SPH (Electrofluid) algorithm applied to C. elegans locomotion
pgleeson/TDANN
Topographic Deep Artificial Neural Networks
pgleeson/test_jlab
pgleeson/testerweb
Senses in Motion Symposium website
pgleeson/testpoint3
Test
pgleeson/UCL_NeuroDataShare2023
examples of scripts how to use IBL-BWM dataset
pgleeson/wormneuroatlas
Neural signal propagation atlas (Randi et al.), genome (WormBase), single-cell transcriptome (Taylor et al.), neuropeptide/GPCR deorphanization (Beets et al.), monoaminergic connectome (Bentley et al.), and chemical-synapse sign predictions (Fenyves et al.) all in one place. Read the docs: https://francescorandi.github.io/wormneuroatlas/