The neuron classification problem

A systematic account of neuron cell types is a basic prerequisite for determining the vertebrate nervous system global wiring diagram. With comprehensive lineage and phylogenetic information unavailable, a general ontology based on structure-function taxonomy is proposed and implemented in a knowledge management system, and a prototype analysis of select regions (including retina, cerebellum, and hypothalamus) presented. The supporting Brain Architecture Knowledge Management System (BAMS) Neuron ontology is online and its user interface allows queries about terms and their definitions, classification criteria based on the original literature and "Petilla Convention" guidelines, hierarchies, and relations-with annotations documenting each ontology entry. Combined with three BAMS modules for neural regions, connections between regions and neuron types, and molecules, the Neuron ontology provides a general framework for physical descriptions and computational modeling of neural systems. The knowledge management system interacts with other web resources, is accessible in both XML and RDF/OWL, is extendible to the whole body, and awaits large-scale data population requiring community participation for timely implementation.

[1]  E. S. Russell Form and Function: a Contribution to the History of Animal Morphology , 1916, Nature.

[2]  R W Rodieck,et al.  Retinal ganglion cells: properties, types, genera, pathways and trans-species comparisons. , 1983, Brain, behavior and evolution.

[3]  Asunción Gómez-Pérez,et al.  Ontological Engineering: With Examples from the Areas of Knowledge Management, e-Commerce and the Semantic Web , 2004, Advanced Information and Knowledge Processing.

[4]  C F Tyner,et al.  The naming of neurons: applications of taxonomic theory to the study of cellular populations. , 1975, Brain, behavior and evolution.

[5]  Larry W. Swanson,et al.  Brain architecture management system , 2007, Neuroinformatics.

[6]  Perry L. Miller,et al.  Neuronal database integration: the Senselab EAV data model , 1999, AMIA.

[7]  J. Kong,et al.  Diversity of ganglion cells in the mouse retina: Unsupervised morphological classification and its limits , 2005, The Journal of comparative neurology.

[8]  Jeremy E. Cook,et al.  Getting to Grips with Neuronal Diversity , 1998 .

[9]  T. Voigt,et al.  Cholinergic amacrine cells in the rat retina , 1986, The Journal of comparative neurology.

[10]  A. Goodchild,et al.  Retinal ganglion cells in the albino rat: Revised morphological classification , 1997, The Journal of comparative neurology.

[11]  P Sterling,et al.  Demonstration of cell types among cone bipolar neurons of cat retina. , 1990, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[12]  Andrew Lumsden,et al.  The Developing Brain , 2002 .

[13]  M. Aldenderfer,et al.  Cluster Analysis. Sage University Paper Series On Quantitative Applications in the Social Sciences 07-044 , 1984 .

[14]  S. Brenner,et al.  The structure of the nervous system of the nematode Caenorhabditis elegans. , 1986, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[15]  F. Amthor,et al.  Morphologies of rabbit retinal ganglion cells with concentric receptive fields , 1989, The Journal of comparative neurology.

[16]  V. Perry,et al.  Amacrine cells, displaced amacrine cells and interplexiform cells in the retina of the rat , 1980, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[17]  J. Hannibal,et al.  The Photopigment Melanopsin Is Exclusively Present in Pituitary Adenylate Cyclase-Activating Polypeptide-Containing Retinal Ganglion Cells of the Retinohypothalamic Tract , 2002, The Journal of Neuroscience.

[18]  Wenzhi Sun,et al.  Large-scale morophological survey of rat retinal ganglion cells. , 2002, Visual neuroscience.

[19]  Emden R. Gansner,et al.  An open graph visualization system and its applications to software engineering , 2000 .

[20]  Nicolas Le Novère,et al.  The Molecular Pages of the mesotelencephalic dopamine consortium (DopaNet) , 2004, BMC Bioinformatics.

[21]  Shahram Ghandeharizadeh,et al.  Database Challenges and Solutions in Neuroscientific Applications , 1997, NeuroImage.

[22]  R. Masland Neuronal cell types , 2004, Current Biology.

[23]  G. Shepherd,et al.  An integrated approach to classifying neuronal phenotypes , 2005, Nature Reviews Neuroscience.

[24]  Jonathan M.W. Slack,et al.  From egg to embryo : regional specification in early development , 1991 .

[25]  Larry W Swanson,et al.  From gene networks to brain networks , 2003, Nature Neuroscience.

[26]  Larry W Swanson,et al.  Online workbenches for neural network connections , 2007, The Journal of comparative neurology.

[27]  J. Sulston,et al.  The embryonic cell lineage of the nematode Caenorhabditis elegans. , 1983, Developmental biology.

[28]  R. Masland Neuronal diversity in the retina , 2001, Current Opinion in Neurobiology.

[29]  R. Masland The fundamental plan of the retina , 2001, Nature Neuroscience.

[30]  Susan Standring PhD DSc Gray's Anatomy: The Anatomical Basis of Clinical Practice , 2005 .

[31]  R. Linden,et al.  Massive retinotectal projection in rats , 1983, Brain Research.

[32]  Mnh,et al.  Histologie du Système Nerveux de Lʼhomme et des Vertébrés , 1998 .

[33]  H. Markram The Blue Brain Project , 2006, Nature Reviews Neuroscience.

[34]  E. Hartveit,et al.  Functional organization of cone bipolar cells in the rat retina. , 1997, Journal of neurophysiology.

[35]  G B Arden,et al.  The Visual System , 2021, AMA Guides to the Evaluation of Permanent Impairment, 6th Edition, 2021.

[36]  H. Markram,et al.  Interneurons of the neocortical inhibitory system , 2004, Nature Reviews Neuroscience.

[37]  J. Nathans,et al.  Quantitative analysis of neuronal morphologies in the mouse retina visualized by using a genetically directed reporter , 2004, The Journal of comparative neurology.

[38]  Jérôme Yelnik,et al.  Morphological taxonomy of the neurons of the primate striatum , 1991, The Journal of comparative neurology.

[39]  Michael Ashburner,et al.  On ontologies for biologists: the Gene Ontology--untangling the web. , 2002, Novartis Foundation symposium.

[40]  L. Swanson Brain Architecture: Understanding the Basic Plan , 2002 .

[41]  Raymond Dingledine,et al.  Interneuron Diversity series: Interneuron research – challenges and strategies , 2003, Trends in Neurosciences.

[42]  Robert Whittle,et al.  From egg to embryo. Regional specification in early development. 2nd edn.: By J. M. W. Slack. Pp. 328. Cambridge University Press. 1991. Hardback £45.00. US $75.00 ISBN 0521 401089; paperback £16.95, US $32.50 ISBN 0 521 40943 8 , 1992 .

[43]  K. Bailey Typologies and taxonomies: An introduction to classification techniques. , 1994 .

[44]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[45]  M. Ashburner,et al.  An ontology for cell types , 2005, Genome Biology.

[46]  G. Paxinos The Rat nervous system , 1985 .

[47]  Mike Uschold,et al.  A Framework for Understanding and Classifying Ontology Applications , 1999 .

[48]  C. Smith,et al.  The brain , 1970 .

[49]  R. Masland,et al.  The shapes and numbers of amacrine cells: Matching of photofilled with Golgi‐stained cells in the rabbit retina and comparison with other mammalian species , 1999, The Journal of comparative neurology.

[50]  S. Nelson,et al.  Molecular taxonomy of major neuronal classes in the adult mouse forebrain , 2006, Nature Neuroscience.

[51]  Larry W. Swanson,et al.  A new module for on-line manipulation and display of molecular information in the brain architecture management system , 2007, Neuroinformatics.

[52]  J M Bower,et al.  Quantitative Golgi study of the rat cerebellar molecular layer interneurons using principal component analysis , 1998, The Journal of comparative neurology.

[53]  J. Stone,et al.  Naming of neurones. Classification and naming of cat retinal ganglion cells. , 1977, Brain, behavior and evolution.

[54]  Larry W. Swanson,et al.  Brain maps : structure of the rat brain : a laboratory guide with printed and electronic templates for data, models and schematics , 1998 .

[55]  José L. V. Mejino,et al.  A reference ontology for biomedical informatics: the Foundational Model of Anatomy , 2003, J. Biomed. Informatics.