![]() ![]() Although the direct communication between most parts of the nervous system is based on spikes as unique and discrete events, graded potentials are seen as reflections of neural population activity in both, invasive and non-invasive techniques. Time series are recorded in various fields of neuroscience to infer information about neural processing. It further allows to define own algorithms, or to integrate and use already existing libraries. ![]() The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. It is illustrated how users and developers can interface the software and execute offline and online modes. In the presented work, the structural hierarchies are described. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. ![]() The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). With the presented software pySPACE ( ), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. 2Robotics Innovation Center, DFKI GmbH, Bremen, Germany.1Robotics Group, Faculty 3 - Mathematics and Computer Science, University of Bremen, Bremen, Germany.Krell 1 * Sirko Straube 1 Anett Seeland 2 Hendrik Wöhrle 2 Johannes Teiwes 1 Jan H. ![]()
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