Classifying GABAergic interneurons with semi-supervised projected model-based clustering.

Journal: Artificial intelligence in medicine
PMID: 25595673

Abstract

OBJECTIVES: A recently introduced pragmatic scheme promises to be a useful catalog of interneuron names. We sought to automatically classify digitally reconstructed interneuronal morphologies according to this scheme. Simultaneously, we sought to discover possible subtypes of these types that might emerge during automatic classification (clustering). We also investigated which morphometric properties were most relevant for this classification.

Authors

  • Bojan Mihaljević
    Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte 28660, Spain. Electronic address: bmihaljevic@fi.upm.es.
  • Ruth Benavides-Piccione
    Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón 28223, Spain. Electronic address: rbp@cajal.csic.es.
  • Luis Guerra
    Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte 28660, Spain. Electronic address: luispelayo84@gmail.com.
  • Javier DeFelipe
    Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón 28223, Spain. Electronic address: defelipe@cajal.csic.es.
  • Pedro Larrañaga
    Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte 28660, Spain.
  • Concha Bielza
    Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte 28660, Spain. Electronic address: mcbielza@fi.upm.es.

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