Collaborative
Research : Application
Overview
The NeuroMAX toolboxes (Spike Detection, Spike
Sorting, Spike Train Analysis, and Display Tools) address
several specific deficiencies of software tools currently
available to the electrophysiology community. Most importantly,
NeuroMAX enhances the ability of researchers to easily collaborate
and share algorithms and processing results by providing a
consistent data processing and results visualization software
platform.
Several key features of NeuroMAX have been implemented specifically
to encourage collaborative research among researchers in the
neuroscience community. These include the fact that NeuroMAX
is built in MATLAB, with an open implementation platform1,
and utilizes the Neuroshare Native (NsN) data format
MATLAB Coded
NeuroMAX is a “plug-in” to the successful and widely
available MATLAB environment, specifically with its Object Oriented
Programming (OOP) architecture. MATLAB provides an environment
that is conducive to quickly producing workable prototypes for
testing. Building on MATLAB gives you the power to leverage
its flexible display and analysis tools.
In addition, there are numerous third party applications compatible
with MATLAB that offer processing time speed-up, including products
that will compile MATLAB code to C and C++ for re-hosting on
high performance computers. Because NeuroMAX starts with MATLAB,
a platform that is commonly found in research labs, its tools
and results can be readily shared with the research community.
Open Implementation Platform1
The NeuroMAX toolboxes are offered in an open implementation
platform1 format to facilitate user modifications and additions.
The MATLAB m-files are always available, either for modification
or as a starting point for the creation of new tools unique
to your application.
NsN Common Data Format
Data input and storage are based on the Neuroshare Native (NsN)
open standards format. From the Neuroshare website (http://neuroshare.sourceforge.net/index.shtml):
“The neuroshare.org website is a collaborative, vendor-neutral
area dedicated to public domain standards and software for neurophysiology.”
Because the input data to NeuroMAX and the results of NeuroMAX
analyses are saved in .nsn format, raw data and results files
can be readily shared among researchers.
NsN input/output formats include:
Analog (continuous data streams)
Segment (non-continuous blocks of data)
Event (small time-stamped text or binary
data that represent discrete events such as trial markers,
embedded user comments, or digital input values).
Neural Event (timestamps of events that are
known to represent neural action potential firing times).
Another primary goal of using these widely available tools
and formats is the sharing of user-created analysis algorithms
within the neuroscience community. As the last step in this
process, we will periodically release user-submitted, R.C.
Electronics Inc., evaluated tools for the NeuroMAX toolboxes
via the NeuroMAX website, neuromax.org.
1 Open implementation platform: allows developers of a
program to alter pieces of the underlying software to fit
their specific needs. Because we provide the standard tools
and structures, you don’t have to start with a blank
slate when creating a unique analysis algorithm.
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