Unsupervised Analysis of Event-Related Potentials (ERPs) During an Emotional Go/NoGo Task

  • Paolo Masulli
  • Francesco Masulli
  • Stefano Rovetta
  • Alessandra Lintas
  • Alessandro E. P. Villa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10147)


We propose a framework for an unsupervised analysis of electroencephalography (EEG) data based on possibilistic clustering, including a preliminary noise and artefact rejection. The proposed data flow identifies the existing similarities in a set of segments of EEG signals and their grouping according to relevant experimental conditions. The analysis is applied to a set of event-related potentials (ERPs) recorded during the performance of an emotional Go/NoGo task. We show that the clusterization rate of trials in two experimental conditions is able to characterize the participants. The extension of the method and its generalization is discussed.


EEG ERP Possibilistic clustering Decoding Brain activity 



This work was partially supported by the Swiss National Science Foundation grant CR13I1-138032.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Paolo Masulli
    • 1
  • Francesco Masulli
    • 2
    • 3
  • Stefano Rovetta
    • 2
  • Alessandra Lintas
    • 1
  • Alessandro E. P. Villa
    • 1
  1. 1.NeuroHeuristic Research GroupUniversity of LausanneLausanneSwitzerland
  2. 2.Department of Computer Science, Bioengineering, Robotics and Systems EngineeringDIBRIS, University of GenovaGenovaItaly
  3. 3.Sbarro Institute for Cancer Research and Molecular MedicineTemple UniversityPhiladelphiaUSA

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