# PANDORA's Toolbox and Other Utilities

## Contents

The PANDORA Toolbox

CGunay's Matlab Plots (CGMPLOT)

Gencompress Utility

Related Projects

Translations:

- [ Bulgarian ] Thanks to Mark Pozner and courtesy of Samostroika
- [ Danish ] Translated by ScienceLakes
- [ Romanian ] Thanks to Alexandra Seremina from Novosibirsk State University and courtesy of azoft
- [ Slovenian ] Translated by NextRanks

## The PANDORA Toolbox

PANDORA is a Matlab Toolbox that makes database management accessible from your electrophysiology project.

PANDORA works by extracting user-defined characteristics from raw neural data (e.g., voltage traces) and creating numerical database tables from them. These tables can then be subjected to further analyses, such as invariant effects, statistical, correlation, and principal components. Publication-ready plots can be produced with an embedded plotting system.

### Features:

- Makes database management accessible from your electrophysiology project;
- Works offline within Matlab;
- Requires no external software;
- Is object oriented and allows easy extensions;
- Can easily tie with existing Matlab scripts;
- Can query database as in SQL.

### Requirements:

- Basic Matlab installation for native database support.
- Optional: Matlab Database Toolbox to import/export from/to external SQL server.
- Optional: PANDORA will automatically use better filtering functions if the Matlab Signal Processing Toolbox is available.

### Licensing:

PANDORA is free to use with the Academic Free License 3.0, but please cite the following paper from your software or publication:

> Günay C, Edgerton JR, Li S, Sangrey T, Prinz AA, Jaeger D (2009). Database analysis of simulated and recorded electrophysiological datasets with Pandora's toolbox. Neuroinformatics, 7(2):93-111. doi: 10.1007/s12021-009-9048-z.

### Documentation:

- Use Matlab Help to access the most up-to-date documentation for PANDORA.
- Project and wiki pages at the INCF Software Center.
- Two papers with supplemental materials and examples.
- HTML documentation (browse online, download) (old!)
- PDF documentation (old!)

### Help

- Discuss your questions at the Parameter Search Google Group.
- Or, send private questions to >cgunay at emory dot edu<.

### Download:

Stable release:

- Version 1.3b (ZIP,TGZ) (beta release).

See the revision history.

If you start using PANDORA, please register with me by sending me a short email with your name and affiliation so that I can provide you with upgrade and bugfix information in the future. Thanks!

## CGunay's Matlab Plots (CGMPLOT)

CGMPLOT improves Matlab plotting by:

- Adding intelligent controls to produce publication-quality figures from Matlab
- Wrapping existing plot commands into objects that can be modularly stacked and superposed
- In stacked multiplots:
  - Modular horizontal and vertical stack plots can be nested
  - Minimizes lost space by intelligent options to put axis labels only once
- In superposed plots:
  - Legends automatically appear matching plotted info
  - Inset plots can be produced.
- Specialized bar, errorbar and image plots are defined.

Documentation: see PANDORA manual above.

Requirements: Matlab.

Download:

- Version 1.1b (beta release).

Contact: >cgunay at emory dot edu<.

If you start using CGMPLOT, please register with me by sending me a short email with your name and affiliation so that I can provide you with upgrade and bugfix information in the future. Thanks!

## The Gencompress Utility

Gencompress can compress binary files from the Genesis neural simulator with average compression rates of 10:1*.

While the compression is lossless, the data is initially truncated to 16-bit resolution. The FLAC lossless audio codec is adapted to achieve this performance.

* In single-channel intracellular voltage traces. Your mileage may vary with other inputs.

### Download:

Stable version:

- Binary packages for i686 and x86_64 architecture Linux platforms.
- Source package for all other architectures and platforms.

Testing version that can handle files >2GB and with >32767 channels:

- Source package for all architectures and platforms.

## Related Projects

- The FIND Matlab Toolbox is an open-source analysis toolbox for multiple-neuron recordings and network simulations. FIND stands for Finding Information in Neural Data. It features:
  - Wide selection of acquisition and simulator input formats based on the Neuroshare Project.
  - Spike detection and sorting from extracellular recordings.
- NeuroTools is a set of tools written in Python to manage, store and analyse computational neuroscience simulations, developed under the umbrella NeuralEnsemble initiative.

Last modified: Thu Dec 20 18:07:19 EST 2012