Classification of neocortical interneurons using affinity propagation


Autoria(s): Santana Hermida, Roberto; McGarry, Laura M.; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafel
Data(s)

05/02/2014

05/02/2014

01/12/2013

Resumo

In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbiased identification of distinct neuronal subtypes. However, better and more robust classification methods are needed for increasingly complex and larger datasets. We explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. In fact, using a combined anatomical/physiological dataset, our algorithm differentiated parvalbumin from somatostatin interneurons in 49 out of 50 cases. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

Identificador

Frontiers in Neural Circuits 7 : (2013) // Article N. 185

1662-5110

http://hdl.handle.net/10810/11365

10.3389/fncir.2013.00185

Idioma(s)

eng

Publicador

Frontiers Reseach Foundation

Relação

http://www.frontiersin.org/Journal/10.3389/fncir.2013.00185/full

Direitos

© 2013 Santana, McGarry, Bielza, Larrañaga and Yuste. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

info:eu-repo/semantics/openAccess

Palavras-Chave #affinity propagation #cortex #interneurons #cell types
Tipo

info:eu-repo/semantics/article