Journal of Computational Neuroscience

, Volume 29, Issue 1–2, pp 213–229 | Cite as

A self-adapting approach for the detection of bursts and network bursts in neuronal cultures

  • Valentina Pasquale
  • Sergio Martinoia
  • Michela Chiappalone


Dissociated networks of neurons typically exhibit bursting behavior, whose features are strongly influenced by the age of the culture, by chemical/electrical stimulation or by environmental conditions. To help the experimenter in identifying the changes possibly induced by specific protocols, we developed a self-adapting method for detecting both bursts and network bursts from electrophysiological activity recorded by means of micro-electrode arrays. The algorithm is based on the computation of the logarithmic inter-spike interval histogram and automatically detects the best threshold to distinguish between inter- and intra-burst inter-spike intervals for each recording channel of the array. An analogous procedure is followed for the detection of network bursts, looking for sequences of closely spaced single-channel bursts. We tested our algorithm on recordings of spontaneous as well as chemically stimulated activity, comparing its performance to other methods available in the literature.


Logarithmic ISI histogram Non-parametric burst detection Network bursts Neuronal cultures Micro-electrode arrays 



Micro-electrode array


Burst detection


Network burst detection


Days in vitro




D-2-amino-5-phosphonopentanoic acid


Inter-spike interval


Logarithmic inter-spike interval histogram


Inter-spike interval threshold


Inter-burst event interval


Logarithmic inter-burst event interval histogram


Inter-burst event interval threshold


New burst detection algorithm


Selinger’s algorithm


Chiappalone’s algorithm


Wagenaar’s algorithm


Gourevitch-Eggermont’s algorithm


Standard error of the mean



The authors wish to thank Dr. Mariateresa Tedesco for excellent culture preparation and maintenance and for providing images for Fig. 1(a). The authors are very grateful to Dr Luca Leonardo Bologna, who provided the recordings of spontaneous activity during development.

Supplementary material

10827_2009_175_MOESM1_ESM.doc (46 kb)
S1 A self-adapting approach for the detection of bursts and network bursts in neuronal cultures (DOC 46 kb)


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Valentina Pasquale
    • 1
  • Sergio Martinoia
    • 2
    • 1
  • Michela Chiappalone
    • 1
  1. 1.Neuroscience and Brain Technologies DepartmentItalian Institute of TechnologyGenovaItaly
  2. 2.Neuroengineering and Bio-nanoTechnology Laboratory, Department of Biophysical and Electronic EngineeringUniversity of GenovaGenovaItaly

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