Behavioral Clustering for Point Processes

  • Christian Braune
  • Christian Borgelt
  • Rudolf Kruse
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8207)


Groups of (parallel) point processes may be analyzed with a variety of different goals. Here we consider the case in which one has a special interest in finding subgroups of processes showing a behavior that differs significantly from the other processes. In particular, we are interested in finding subgroups that exhibit an increased synchrony. Finding such groups of processes poses a difficult problem as its naïve solution requires enumerating the power set of all processes involved, which is a costly procedure. In this paper we propose a method that allows us to efficiently filter the process set for candidate subgroups. We pay special attention to the possibilities of temporal imprecision, meaning that the synchrony is not exact, and selective participation, meaning that only a subset of the related processes participates in each synchronous event.


point processes clustering spike train analysis 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Christian Braune
    • 1
  • Christian Borgelt
    • 2
  • Rudolf Kruse
    • 1
  1. 1.Otto-von-Guericke-University of MagdeburgMagdeburgGermany
  2. 2.European Centre for Soft ComputingMieres (Asturias)Spain

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