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README.md

odML libraries

The Python-odML library is available on GitHub <https://github.com/G-Node/python-odml>. If you are not familiar with the version control system git, but still want to use it, have a look at the documentaion available on the git-scm website <https://git-scm.com/>.

Dependencies

  • The Python-odML library runs under Python 2.7.
  • The Python-odML library depends on Enum (version 0.4.4).

Installation

To download the Python-odML library please either use git and clone the repository from GitHub:

$ cd /home/usr/toolbox/
$ git clone https://github.com/G-Node/python-odml.git

... or if you don't want to use git download the ZIP file also provided on GitHub to your computer (e.g. as above on your home directory under a "toolbox" folder).

To install the Python-odML library, enter the corresponding directory and run::

$ cd /home/usr/toolbox/python-odml/
$ python setup.py install

Documentation

Documentation

Bugs & Questions

Should you find a behaviour that is likely a bug, please file a bug report at the github bug tracker.

If you have questions regarding the use of the library or the editor, ask the question on Stack Overflow, be sure to tag it with odml and we'll do our best to quickly solve the problem.

datacite.yml
Title Massively parallel multi-electrode recordings of macaque motor cortex during an instructed delayed reach-to-grasp task
Authors Brochier,Thomas;Institut de Neurosciences de la Timone (INT), UMR 7289, CNRS – Aix Marseille Université, Marseille, France;orcid.org/0000-0001-6948-1234
Zehl,Lyuba;Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany;orcid.org/0000-0002-5947-9939
Hao,Yaoyao;Institut de Neurosciences de la Timone (INT), UMR 7289, CNRS – Aix Marseille Université, Marseille, France;orcid.org/0000-0002-9390-4660
Duret,Margaux;Institut de Neurosciences de la Timone (INT), UMR 7289, CNRS – Aix Marseille Université, Marseille, France;orcid.org/0000-0002-6557-748X
Sprenger,Julia;Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany;orcid.org/0000-0002-9986-7477
Denker,Michael;Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany;orcid.org/0000-0003-1255-7300
Grün,Sonja;Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany;orcid.org/0000-0003-2829-2220
Riehle,Alexa;Institut de Neurosciences de la Timone (INT), UMR 7289, CNRS – Aix Marseille Université, Marseille, France
Description We provide two electrophysiological datasets recorded via a 10-by-10 multi-electrode array chronically implanted in the motor cortex of two macaque monkeys during an instructed delayed reach-to-grasp task. The datasets contain the continuous measure of extracellular potentials at each electrode sampled at 30 kHz, the local field potentials sampled at 1 kHz and the timing of the online and offline extracted spike times. It also includes the timing of several task and behavioral events recorded along the electrophysiological data. Finally, the datasets provide a complete set of metadata structured in a standardized format. These metadata allow easy access to detailed information about the datasets such as the settings of the recording hardware, the array specifications, the location of the implant in the motor cortex, information about the monkeys, or the offline spike sorting.
License CC-BY (http://creativecommons.org/licenses/by/4.0/)
References Brochier, T., Zehl, L., Hao, Y., Duret, M., Sprenger, J., Denker, M., Grün, S. & Riehle, A. (2018). Massively parallel recordings in macaque motor cortex during an instructed delayed reach-to-grasp task, Scientific Data, 5, 180055. [] (IsPartOf)
Zehl, L., Jaillet, F., Stoewer, A., Grewe, J., Sobolev, A., Wachtler, T., … Grün, S. (2016). Handling Metadata in a Neurophysiology Laboratory. Frontiers in Neuroinformatics, 10, 26. [] (HasMetadata)
Riehle, A., Wirtssohn, S., Grün, S., & Brochier, T. (2013). Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements. Frontiers in Neural Circuits, 7, 48 [] (HasMetadata)
Funding Helmholtz Association, Supercomputing and Modeling for the Human Brain
EU, EU.604102
EU, EU.720270
DFG, DFG.GR 1753/4-2
DFG, DFG.DE 2175/2-1
RIKEN-CNRS, Collaborative Research Agreement
ANR, GRASP
CNRS, PEPS
CNRS, Neuro_IC2010
DAAD
LIA Vision for Action
Keywords Neuroscience
Electrophysiology
Utah Array
Spikes
Local Field Potential
Macaque
Motor Cortex
Resource Type Dataset