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Abstract:
Recent advances in both electrophysiological recording techniques and hardware capabilities have enabled
researchers to simultaneously record from a large number of neurons in different areas of the brain. This opens
the door for a wide range of complex analyses potentially leading to a better understanding of the principles
underlying neural network computations. At the same time, due to the increasing amount of data with
increasing complexity, significantly more emphasis has to be put on the data analysis task. Although
high-level scripting languages such as Matlab can speed up the development of analysis tools, in our
experience, a too large amount of time is still spent on (re)structuring and (re)organizing data for specific
analyses.
Therefore, our goal was to develop a system which enables experimental neuroscientists to spend less time on
organizing their data and more on data collection and creative analysis. We developed an object oriented
Matlab toolbox which supplies the user with basic data types and functions to organize and structure various
types of electrophysiological data. By using an object oriented, hierarchical layout, basic functionality, such as
integration of metadata, or storage and retrieval of data and results, is implemented independent of specific
data formats or experimental designs. This provides maximal flexibility and compatibility with future
experiments and new data formats. All data and experimental results are stored in a database, so the
experimenter can choose which data to keep in memory for faster access and which to save to disk to save
resources. Additionally, we have created an extensive library of basic analysis and visualization tools that can
be used to get an overview of the data.
