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vor_cerebellum

Cerebellum learning to perform the VOR.

https://github.com/spinnakermanchester/vor_cerebellum

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 5 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 2 committers (100.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (11.5%) to scientific vocabulary

Keywords

cerebellum cerebellum-model learning spiking-neural-network spinnaker spinnaker-hardware
Last synced: 6 months ago · JSON representation ·

Repository

Cerebellum learning to perform the VOR.

Basic Info
  • Host: GitHub
  • Owner: SpiNNakerManchester
  • License: gpl-3.0
  • Language: Jupyter Notebook
  • Default Branch: master
  • Homepage:
  • Size: 52.8 MB
Statistics
  • Stars: 0
  • Watchers: 10
  • Forks: 0
  • Open Issues: 10
  • Releases: 0
Topics
cerebellum cerebellum-model learning spiking-neural-network spinnaker spinnaker-hardware
Created over 5 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.MD

Neuromorphic cerebellum learning to perform the vestibulo-ocular reflex (VOR)

This work presents the implementation of a biologically inspired and adaptive robot control system on neuromorphic hardware. The control system is built from spiking neurons organised in a structure inspired by the cerebellum. The network learns to perform the vestibulo-ocular reflex (VOR) in real-time. The system is shown to perform the task in simulated and physical environments.

This work uses a model designed by Naveros et al (F. Naveros, J. A. Garrido, A. Arleo, E. Ros and N. R. Luque, Exploring Vestibulo-Ocular Adaptation in a Closed-Loop Neuro-Robotic Experiment Using STDP. A Simulation Study, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, 2018, pp. 1-9, doi: 10.1109/IROS.2018.8594019.).

The model is ported onto SpiNNaker and simulated using sPyNNaker. The circuit's ability is shown in a tightly-coupled simulated environment (SpiNNGym), in a loosely-coupled simulated environment (NRP) and in a physical robot (iCub).

Installation

This installation assumes the existence of either sPyNNaker or NEST, for brevity. For installation instructions for NEST, please follow official directions. For SpiNNaker, 3 shell scripts are provided for quick installation.

A complete installation (assuming no errors) could be done by running (in this order):

bash ./install.sh && ./setup_develop.sh && ./automatic_make.sh

The software package can be installed in a local virtual environment. The following can be run inside the unarchived folder to install the package:

python setup.py develop

or

pip install .

Use

Each experiment script is stand-alone. However, full-scale experiments can have arguments passed to them via the argparser.

Citation

When citing this work, the authors would prefer you to cite the related journal article.

Owner

  • Name: SpiNNaker - University of Manchester
  • Login: SpiNNakerManchester
  • Kind: organization
  • Email: spinnakerusers@googlegroups.com
  • Location: Manchester, UK

Software for the SpiNNaker Million Core Neuromorphic Machine. Part of the Human Brain Project and EBRAINS

Citation (CITATION.cff) 

# Copyright (c) 2017 The University of Manchester
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

cff-version: 1.1.0
message: If you use this software, please cite it as below.
title: Towards a Bio-Inspired Real-Time Neuromorphic Cerebellum
repository-code: https://github.com/SpiNNakerManchester/vor_cerebellum/
version: 0.0.1
url: https://doi.org/10.3389/fncel.2021.622870
license: GPL-3.0-or-later
date-released: 2021-05-31
identifier: vor_cerebellum
authors:
- affiliation: University Of Manchester
  family-names: Bogdan
  given-names: Petruţ A.
  orcid: https://orcid.org/0000-0001-5535-7865
- affiliation: University Of Pavia
  family-names: Marcinnò
  given-names: Beatrice
- affiliation: University Of Pavia
  family-names: Casellato
  given-names: Claudia
  orcid: https://orcid.org/0000-0002-8729-0391
- affiliation: University Of Pavia
  family-names: Casali
  given-names: Stefano
  orcid: https://orcid.org/0000-0003-3952-8059
- affiliation: University Of Manchester
  email: Andrew.Rowley@manchester.ac.uk
  family-names: Rowley
  given-names: Andrew
  orcid: https://orcid.org/0000-0002-2646-8520
  website: https://www.researchgate.net/profile/Andrew_Rowley2
- affiliation: University Of Manchester
  family-names: Hopkins
  given-names: Michael
- affiliation: University Of Pavia
  family-names: Leporati
  given-names: Francesco
  orcid: https://orcid.org/0000-0003-2901-4935
- affiliation: University Of Pavia
  family-names: D'Angelo
  given-names: Egidio
  orcid: https://orcid.org/0000-0002-6007-7187
- affiliation: University Of Manchester
  family-names: Rhodes
  given-names: Oliver
  orcid: https://orcid.org/0000-0003-1728-2828
contact:
- address: University of Manchester, Oxford Road
  city: Manchester
  country: GB
  name: SpiNNaker Software Team
  post-code: M13 9PL
email: spinnakerusers@googlegroups.com
keywords:
  - spinnaker
  - neuromorphics
  - "spiking neural networks"
  - cerebellum

GitHub Events

Total
Last Year

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 68
  • Total Committers: 2
  • Avg Commits per committer: 34.0
  • Development Distribution Score (DDS): 0.118
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Petrut Bogdan p****n@m****k 60
Donal K. Fellows d****s@m****k 8
Committer Domains (Top 20 + Academic)
manchester.ac.uk: 2

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 12
  • Total pull requests: 3
  • Average time to close issues: N/A
  • Average time to close pull requests: 16 days
  • Total issue authors: 1
  • Total pull request authors: 2
  • Average comments per issue: 1.25
  • Average comments per pull request: 1.67
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • ChiaraBartolozzi (9)
Pull Request Authors
  • andrewgait (1)
  • dkfellows (1)
Top Labels
Issue Labels
Pull Request Labels
enhancement (1) incomplete_left_for_further_release (1)

Dependencies

requirements.txt pypi
  • argparse *
  • brian2 *
  • elephant ==0.7.0
  • matplotlib *
  • neo ==0.8.0
  • numpy *
  • quantities ==0.12.4
  • spinngym *
setup.py pypi
  • argparse *
  • brian2 *
  • elephant ==0.7.0
  • matplotlib *
  • neo ==0.8.0
  • numpy *
  • quantities ==0.12.4
  • spinngym *