sprenger 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
..
doc 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
examples 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
neo 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
LICENSE.txt 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
MANIFEST.in 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
PKG-INFO 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
README.rst 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
setup.cfg 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás
setup.py 8edaa8d0e1 gin commit from nit-ope-de04 3 anos atrás

README.rst

===
Neo
===

Neo is a Python package for working with electrophysiology data in Python, together
with support for reading a wide range of neurophysiology file formats, including
Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, and support for
writing to a subset of these formats plus non-proprietary formats including HDF5.

The goal of Neo is to improve interoperability between Python tools for
analyzing, visualizing and generating electrophysiology data by providing a common,
shared object model. In order to be as lightweight a dependency as possible,
Neo is deliberately limited to represention of data, with no functions for data
analysis or visualization.

Neo is used by a number of other software tools, including
SpykeViewer_ (data analysis and visualization), Elephant_ (data analysis),
the G-node_ suite (databasing), PyNN_ (simulations), tridesclous_ (spike sorting)
and ephyviewer_ (data visualization).
OpenElectrophy_ (data analysis and visualization) uses an older version of neo.

Neo implements a hierarchical data model well adapted to intracellular and
extracellular electrophysiology and EEG data with support for multi-electrodes
(for example tetrodes). Neo's data objects build on the quantities package,
which in turn builds on NumPy by adding support for physical dimensions. Thus
Neo objects behave just like normal NumPy arrays, but with additional metadata,
checks for dimensional consistency and automatic unit conversion.

A project with similar aims but for neuroimaging file formats is `NiBabel`_.

Code status
-----------

.. image:: https://travis-ci.org/NeuralEnsemble/python-neo.png?branch=master
:target: https://travis-ci.org/NeuralEnsemble/python-neo
:alt: Unit Test Status (TravisCI)
.. image:: https://circleci.com/gh/NeuralEnsemble/python-neo.svg?style=svg
:target: https://circleci.com/gh/NeuralEnsemble/python-neo
:alt: Unit Test Status (CircleCI)
.. image:: https://coveralls.io/repos/NeuralEnsemble/python-neo/badge.png
:target: https://coveralls.io/r/NeuralEnsemble/python-neo
:alt: Unit Test Coverage
.. image:: https://requires.io/github/NeuralEnsemble/python-neo/requirements.png?branch=master
:target: https://requires.io/github/NeuralEnsemble/python-neo/requirements/?branch=master
:alt: Requirements Status

More information
----------------

- Home page: http://neuralensemble.org/neo
- Mailing list: https://groups.google.com/forum/?fromgroups#!forum/neuralensemble
- Documentation: http://neo.readthedocs.io/
- Bug reports: https://github.com/NeuralEnsemble/python-neo/issues

For installation instructions, see doc/source/install.rst

To cite Neo in publications, see CITATION.txt

:copyright: Copyright 2010-2020 by the Neo team, see doc/source/authors.rst.
:license: 3-Clause Revised BSD License, see LICENSE.txt for details.

Funding
-------

Development of PyNN has been partially funded by the European Union Sixth Framework Program (FP6) under
grant agreement FETPI-015879 (FACETS), by the European Union Seventh Framework Program (FP7/2007­-2013)
under grant agreements no. 269921 (BrainScaleS) and no. 604102 (HBP),
and by the European Union’s Horizon 2020 Framework Programme for
Research and Innovation under the Specific Grant Agreements No. 720270 (Human Brain Project SGA1),
No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3).

.. _OpenElectrophy: https://github.com/OpenElectrophy/OpenElectrophy
.. _Elephant: http://neuralensemble.org/elephant
.. _G-node: http://www.g-node.org/
.. _Neuroshare: http://neuroshare.org/
.. _SpykeViewer: https://spyke-viewer.readthedocs.org/en/latest/
.. _NiBabel: http://nipy.sourceforge.net/nibabel/
.. _PyNN: http://neuralensemble.org/PyNN
.. _quantities: http://pypi.python.org/pypi/quantities
.. _`NeuralEnsemble mailing list`: http://groups.google.com/group/neuralensemble
.. _`issue tracker`: https://github.c
.. _tridesclous: https://github.com/tridesclous/tridesclous
.. _ephyviewer: https://github.com/NeuralEnsemble/ephyviewer
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