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Morphological Neuron Classification Based on Dendritic Tree Hierarchy

  • Evelyn Perez Cervantes
  • Cesar Henrique Comin
  • Roberto Marcondes Cesar Junior
  • Luciano da Fontoura Costa
Original Article

Abstract

The shape of a neuron can reveal interesting properties about its function. Therefore, morphological neuron characterization can contribute to a better understanding of how the brain works. However, one of the great challenges of neuroanatomy is the definition of morphological properties that can be used for categorizing neurons. This paper proposes a new methodology for neuron morphological analysis by considering different hierarchies of the dendritic tree for characterizing and categorizing neuronal cells. The methodology consists in using different strategies for decomposing the dendritic tree along its hierarchies, allowing the identification of relevant parts (possibly related to specific neuronal functions) for classification tasks. A set of more than 5000 neurons corresponding to 10 classes were examined with supervised classification algorithms based on this strategy. It was found that classification accuracies similar to those obtained by using whole neurons can be achieved by considering only parts of the neurons. Branches close to the soma were found to be particularly relevant for classification.

Keywords

Neuron Morphological reconstruction Morphometry Dendritic arborization Dendritic tree Digital neuronal reconstruction Data sharing Morphological classification Supervised classification Feature selection 

Notes

Acknowledgements

C. H. Comin thanks FAPESP (Grant No. 15/18942-8) for financial support. L. da F. Costa thanks CNPq (Grant No. 307333/2013-2) for support. This work has also been supported by the FAPESP grant 2015/22308-2, Capes and CNPq.

Compliance with Ethical Standards

Conflict of interests

The authors declare no conflict of interest.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Mathematics and StatisticsUniversity of São PauloSão PauloBrazil
  2. 2.Department of Computer ScienceFederal University of São CarlosSão CarlosBrazil
  3. 3.São Carlos Institute of PhysicsUniversity of São PauloSão CarlosBrazil

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