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filtered content + shrinked some places to fit eppy trifold back to 2 pages
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flier/eppy-handout.tex

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Neuroshare is a standardized API for accessing neurophysiology
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data stored in vendor-specific binary formats in a vendor-neutral
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way. The G-Node Neuroshare Tools provide libraries and utilities
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built on Neuroshare and Python to work with Neuroshare compatible
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files on various platforms.
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way.
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% The G-Node Neuroshare Tools provide libraries and utilities
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%built on Neuroshare and Python to work with Neuroshare compatible
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%files on various platforms.
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\begin{itemize}[nolistsep,topsep=0em,leftmargin=1pc]
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\item High-level Python library to access Neuroshare compatible data-files
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\vspace{0.5em}
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G-Node provides a free cloud-based service neuroscientists can use for storage, management and sharing of data (\url{https://portal.g-node.org/data/}). An API for data access is provided (\url{http://g-node.github.com/g-node-portal/}), allowing developers to code their own clients. A web-based interface as well as a client for MATLAB$^\textrm{\textregistered}$ (\url{http://g-node.github.com/gnode-client-matlab/}) are already provided. A client for Python is currently under development. When completed it shall provide:
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G-Node provides a free cloud-based service neuroscientists can use for
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storage, management and sharing of data
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(\url{https://portal.g-node.org/data/}). An API for data access is
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provided (\url{http://g-node.github.com/g-node-portal/}), allowing
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developers to code their own clients.
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% A web-based interface as well as a client for
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% MATLAB$^\textrm{\textregistered}$
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% (\url{http://g-node.github.com/gnode-client-matlab/}) are already
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% provided.
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A client for Python is currently under development: %. When completed it shall provide:
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\begin{itemize}[nolistsep,topsep=0em,leftmargin=1pc]
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\item Compatibility with NEO: use it 'out-of-the-box' with existing code written for NEO and gain additional services provided by the G-Node 'for free'
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\item Compatibility with NEO%: use it 'out-of-the-box' with existing code written for NEO and gain additional services provided by the G-Node 'for free'
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\item Smart lazy loading and caching for frugal bandwidth and memory usage
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\item Possibility to work in a mixed workflow: work on the same data in Python and MATLAB$^\textrm{\textregistered}$
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\end{itemize}
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Stay tuned for development updates!
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%Stay tuned for development updates!
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%___________________________________________________________________________
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\ndsection{Metadata Management}%
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\vspace{0.5em} %some additional spacing
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LFPy is a Python module for simulation of extracellular electrical
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potentials evoked by activity of multi-compartment model neurons.
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LFPy runs on top of the NEURON-simulator, using the included Python interface
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(\url{http://www.neuron.yale.edu}).
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%LFPy runs on top of the NEURON-simulator, using the included Python interface
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%(\url{http://www.neuron.yale.edu}).
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LFPy provides:
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\begin{itemize}[nolistsep, topsep=0em, leftmargin=1pc]
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\item A forward modeling scheme for calculating extracellular
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potentials from compartmental membrane currents in an infinite
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homogeneous linear extracellular medium
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\item Python-classes for setting up cells, synapses and recording
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electrodes
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%\item Python-classes for setting up cells, synapses and recording
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% electrodes
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\item Scripting capabilities thanks to NEURON and the
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Python programming environment
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\item Simultaneous simulation of the model cell responses and
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statistics, multivariate decoding
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\end{itemize}
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\vspace{1em}
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%\vspace{1em}
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\includegraphics[width=\columnwidth]{mne_screenshot.pdf}
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% Selected set of citations, Here is an example:
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\ndcite{A. Gramfort, \emph{et.~al.}
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\item Use supplied plugins for common plots such as Raster Plot, PSTH, Correlogram and analog signals
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\end{itemize}
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\vspace{1em}
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%\vspace{1em}
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\includegraphics[width=\columnwidth]{spykeviewer_screenshot.png}
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% Selected set of citations, Here is an example:
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% No publication yet...
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formats and it is memory-efficient. Truely Open Source, BSD-licensed.
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\begin{itemize}[nolistsep,topsep=0em,leftmargin=1pc]
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\item User-friendly and customisable
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%\item User-friendly and customisable
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\item Interactive command-line interface in Python
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\item GUI and visualization widgets
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\item Automatic and manual clustering
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%\item Automatic and manual clustering
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\item Support for multi-channel data
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\item Based on: NumPy, PyTables, matplotlib, scikit-learn
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%\item Based on: NumPy, PyTables, matplotlib, scikit-learn
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\end{itemize}
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%___________________________________________________________________________
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pics/odml_editor_screenshot.png

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