Debian Science Electrophysiology packages

GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc.

This package provides the header files.

SigViewer is a viewing and scoring software for biomedical signal data. It relies on biosig4c++ library which supports a number of data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED .

Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events.

Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility; cairo subpixel drawing on screen or to file; conventional PSD and EEG Micrcontinuity profiles; Independent Component Analysis; artifact detection; and Process S simulation following Achermann et al, 1993.

KlustaKwik is a program for automatic clustering of continuous data into a mixture of Gaussians. The program was originally developed for sorting of neuronal action potentials, but can be applied to any sort of data.

BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://pub.ist.ac.at/~schloegl/biosig/TESTED .

This package provides header files and static library.

eegdev is a library that provides a unified interface for accessing various EEG (and other biosignals) acquisition systems. This interface has been designed to be both flexible and efficient. The device specific part is implemented by the means of plugins which makes adding new device backend fairly easy even if the library does not support them yet officially.

The core library not only provides to users a unified and consistent interface to the acquisition device but it also provides many functionalities to the device backends (plugins) ranging from configuration to data casting and scaling making writing new device backend an easy task.

This library is particularly useful to handle the acquisition part of a Brain Computer Interface (BCI) or any realtime multi-electrode acquisition in neurophysiological research.

This package contains the files needed to compile and link programs which use eegdev. It provides also the headers needed to develop new device plugins. The manpages and examples are shipped in this package.

rtfilter is a library that provides a set of routines implementing realtime digital filter for multichannel signals (i.e. filtering multiple signals with the same filter parameters). It implements FIR, IIR filters and downsampler for float and double data type (both for real and complex valued signal). Additional functions are also provided to design few usual filters: Butterworth, Chebyshev, windowed sinc, analytical filter...

One of the main differences from other libraries providing digital signal processing is that the filter functions have been specifically designed and optimized for multichannel signals (from few channels to several hundred).

This package contains the files needed to compile and link programs which use rtfilter.

xdffileio is a library that provides a unified interface for writing and reading various biosignal file formats in realtime (i.e. streaming). It has been designed to provide a flexible, consistent and generic interface to all supported file formats while minimizing the overhead the function calls: the heaviest operations (type casting, scaling and formatting) are offloaded into a separated thread. This design makes its particularly suitable to be directly used in a data acquisition loop (like in electrophysiology recording or in Brain-Computer Interfaces (BCI)).

The genericity of the interface makes trivial various operations like transformation of a recorded file or its conversion to another file format. xdffileio currently supports EDF, BDF, GDF1 and GDF2 file formats and more will be added in future.

This package contains the files needed to compile and link programs which use xdffileio.

BioXTAS RAW is a GUI based, Python program for reduction and analysis of small-angle X-ray solution scattering (SAXS) data. The package is designed for biological SAXS data.

BioXTAS RAW provides an alternative to closed source programs such as Primus and Scatter for primary data analysis. Because it can calibrate, mask, and integrate images it also provides an alternative to synchrotron beamline pipelines that scientists can install on their own computers and use both at home and at the beamline.

NEO stands for Neural Ensemble Objects and is a project to provide common classes and concepts for dealing with electro-physiological (in vivo and/or simulated) data to facilitate collaborative software/algorithm development. In particular Neo provides: a set a classes for data representation with precise definitions, an IO module with a simple API, documentation, and a set of examples.

NEO offers support for reading data from numerous proprietary file formats (e.g. Spike2, Plexon, AlphaOmega, BlackRock, Axon), read/write support for various open formats (e.g. KlustaKwik, Elan, WinEdr, WinWcp, PyNN), as well as support common file formats, such as HDF5 with Neo-structured content (NeoHDF5, NeoMatlab).

Neo's IO facilities can be seen as a pure-Python and open-source Neuroshare replacement.

This metapackage will install Debian Science packages related to data acquisition. This might be used in several sciences (as for instance science-viewing and science-typesetting).

This metapackage will install Debian packages which might be useful for scientists interested in modeling of real neural systems at different levels (from single neuron to complex networks).

The selection of packages is targeting the application of simulation techniques. Methods developers are referred to the science-statistics, science-imageanalysis, science-numericalcomputation, med-imaging, and med-imaging-dev metapackages for a variety of additional software that might be useful for neuroscience research.

Stimfit je slobodný, rýchly a jednoduchý program na prehliadanie a analýzu elektrofysiologických dát. Obsahuje vnorený shell jazyka Python, ktorý vým umožňuje rozširovať funkcie programu pomocou numerických knižníc ako sú NumPy a SciPy.

This software allows one to display EEG signal in realtime as well as record them. It is the minimal recording panel needed to do simple experiment.

This package provides a library written in C implementing a set of widgets designed to view in realtime multichannels signals. Despite it has been initially design to view signals coming from a BIOSEMI Activetwo EEG system, it is totally system agnostic and any user of other system might find it useful.

This package contains the files needed to compile and link programs which use mcpanel

NEO stands for Neural Ensemble Objects and is a project to provide common class names and concepts for dealing with electro-physiological (in vivo and/or simulated) data with the aim of getting OpenElectrophy, NeuroTools, G-node and maybe other projects with similar goals more close together.

In particular Neo provides:

• a set a classes with precise definitions
• an IO module that offer a simple API that fit many formats
• documentation.
• a set of examples like a format convertor

This package provides the startup script for the OpenElectrophy GUI.

EEGLAB is an interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data.

BlueSpike is an electrophysiology tool to perform real-time data acquisition, visualization and sorting of neuronal spikes. It continuously acquires data every 1 ms and realizes digital signal processing on retrieved data. Contains four components:

• KernelSpike: a kernel module.
• SpikeViewever
• SpikeSorter
• Channel Reviewer

Meabench is a set of interacting linux programs for recording data from MEAs and real time processing. It can be used to acquire and visualize data from MultiChannel Systems multi-electrode array hardware in real time. On-line spike detection is available, as well as suppression of artifacts induced by 60 Hz pickup and by stimulation. A growing number of small utilities for data analysis is included with the source code, and you can easily add your own. Meabench provides continuous and triggered recording of raw electrode data as well as extracted spike data. Meabench is very suitable for real-time feedback stimulation, since roundtrip times from pre-amplifier to stimulator is less than 200 ms worst-case (less than 50 ms average).

RELACS is designed as an framework for closed-loop experiments that may considerably speed up this traditional approach and in addition offers novel experimental possibilities. In a closed-loop experiment a stimulus is presented, the resulting response is immediately analyzed, and properties of the next stimulus (e.g. mean intensity) are adjusted as needed.

RELACS comes with an extensive set of data-analysis functions. The functions are implemented in C++ to allow fast and memory efficient data-analysis as it is required for closed-loop experiments:

• Basic statistics (e.g. mean, standard deviation)
• Spectral analysis: power spectrum, transfer function, coherence
• Linear and nonlinear fits (Levenberg-Marquardt and Simplex)
• Peak detection
• Histograms, interpolation
• Stimulus generation: pulse, saw tooth, band-pass filtered white noise, Ornstein-Uhlenbeck noise
• Firing rates: mean, binned, convolved with kernels (e.g. rectangle, triangle, Gaussian)
• Interspike intervals: histogram, CV, serial correlation, etc.
• Spike timing precision: vector strength, reliability, correlation, synchrony etc.

RELACS plugin infrastructure allows to adapt it to specific hardware drivers and they allow you to implement research protocols, filters, spike detectors, etc.

Based on the neo framework, it works with a wide variety of data formats. Plugin interfaces allow for rapid extension with custom analyses.

Chronux is a Matlab toolbox for signal processing of neural time series data, several specialized mini-packages for spike sorting, local regression, audio segmentation and other tasks. It also includes a graphical user interface (GUI). The current version of the GUI contains a number of features specialised to the analysis of electroencephalography (EEG) data. The eventual aim is to provide domain specific user interfaces (UIs) for each experimental modality, along with corresponding data management tools.

 MClust is a toolbox which enables a user to perform automated and
 manual clustering on single-electrode, stereotrode, and tetrode
 recordings. It allows manual corrections to automated clustering
 results. It outputs t-files, which contain (after a header) a list
 of timestamps in binary format. Timestamps are 32-bit longs at a
 resolution of 10 timestamps/ms.

Currently, neurodata has an Octave/MATLAB program to analyze electroneurogram traces of coupled oscillators, and a Perl library for the analysis of voltage trace data.

This project is a electrophysiological and behavioral data collection program that can distribute data collection tasks across multiple machines. It is designed to interface with the NSpike hardware system.

The ultimate aim is to create an extremely user-friendly software to perform the most common tasks of recording single channels and whole-cell currents

 PyMEG is a project in Python to do various neuroimaging processing
 with magnetoencephalography (MEG) data. The purpose of this project,
 is to create a suite of functions to do MEG analysis in Python.

QRtaiLab is a QT-based port of the software scope xrtailab of the RTAI project. It can be used as virtual oscilloscope and monitoring application for interacting with the real-time external.

The Real-Time eXperiment Interface (RTXI) is a collaborative open-source software development project aimed at producing a real-time Linux based software system for hard real-time data acquisition and control applications in biological research.

Core functionality of RTXI gets extended via plugins, such as - Data Recorder - Virtual Dendrite - Spike-triggered Average - Phase Response Curve - Signal processing

This toolbox implements several information-theoretic spike train analysis techniques. This implementation behaves like a typical MATLAB toolbox, but the underlying computations are coded in C and optimized for efficiency.

Trellis-Neuro is an Open Source, multi-platform application suite for interfacing with neurophysiology data acquisition and stimulation instruments. It is based on the eXtensible Instrument Processing Protocol (XIPP), QT 4, and C/C++.