title: Part-based motor neuron recognition in the Drosophila ventral nerve cord.
abstract: We exploit the morphological stereotypy and relative simplicity of the Drosophila nervous system to model the diverse neuronal morphologies of individual motor neurons and understand underlying principles of synaptic connectivity in a motor circuit. In our analysis, we use images depicting single neurons labeled with green fluorescent protein (GFP) and serially imaged with laser scanning confocal microscopy. We model morphology with a novel formulation of Conditional Random Fields, a hierarchical latent-state CRF, to capture the highly varying compartment-based structure of the neurons (soma-axon-dendrites). In the training phase, we follow two approaches: (i) hierarchical learning, where compartment labels are given, and (ii) latent-state learning, where compartment labels are not given in the samples. We demonstrate the accuracy of our approach using wild-type motor neurons in the larval ventral nerve cord. However, our method can also be used for the identification of motor neuron mutations, as well as the automated annotation of the motor circuitry in wild type and mutant animals. Our method is directly applicable to the recognition of compartment-defined structures.
authors.affiliation: Computer and Information Science Department, Indiana University-Purdue University Indianapolis, 723 W, Michigan St., SL 280, Indianapolis, IN 46202, USA. Electronic address: xiaochan@iupui.edu.
authors.forename: Xiao
authors.initials: X
authors.lastname: Chang
authors.affiliation: Molecular and Cellular Pharmacology Department, University of Miami Miller School of Medicine, 1600 NW, 10th Avenue, RMSB 6056, Miami, FL 33136, USA. Electronic address: mkim2@med.miami.edu.
authors.forename: Michael D
authors.initials: MD
authors.lastname: Kim
authors.affiliation: Computer and Information Science Department, Indiana University-Purdue University Indianapolis, 723 W, Michigan St., SL 280, Indianapolis, IN 46202, USA. Electronic address: rstep_14@yahoo.com.
authors.forename: Rachel
authors.initials: R
authors.lastname: Stephens
authors.affiliation: Computer and Information Science Department, Indiana University-Purdue University Indianapolis, 723 W, Michigan St., SL 280, Indianapolis, IN 46202, USA. Electronic address: tonyqu1120@hotmail.com.
authors.forename: Tiange
authors.initials: T
authors.lastname: Qu
authors.affiliation: Biology Department, University of Miami, 1301 Memorial Drive, Coral Gables, FL 33124, USA. Electronic address: akira.chiba@me.com.
authors.forename: Akira
authors.initials: A
authors.lastname: Chiba
authors.affiliation: Computer and Information Science Department, Indiana University-Purdue University Indianapolis, 723 W, Michigan St., SL 280, Indianapolis, IN 46202, USA. Electronic address: gavriil@cs.iupui.edu.
authors.forename: Gavriil
authors.initials: G
authors.lastname: Tsechpenakis
mesh_terms: D000818:Animals; D019521:Body Patterning / Q000502:physiology; D002490:Central Nervous System / Q000166:cytology / Q000196:embryology*; D004331:Drosophila melanogaster / Q000196:embryology*; D018613:Microscopy, Confocal; D008959:Models, Neurological; D009046:Motor Neurons / Q000166:cytology*; D055495:Neurogenesis / Q000502:physiology*
keywords: Drosophila; Latent-state Conditional Random Fields; Motor neuron classification; Part-based recognition