Morphological homogeneity of neurons: Searching for outlier neuronal cells

Neuroinformatics

Volumn 10, Issue 4, 2012, Pages 379-389

  Zawadzki, Krissia ^a   Feenders, Christoph ^b,c   Viana, Matheus P ^a   Kaiser, Marcus ^b,d,e   Da Costa, F Luciano ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

^b NEWCASTLE UNIVERSITY   (United Kingdom)

^c UNIVERSITY OF OLDENBURG   (Germany)

^d NEWCASTLE UNIVERSITY   (United Kingdom)

^e Seoul National University   (South Korea)

Author keywords

Archetypes; NeuroMorpho.org; Neuromorphometry; Neuroscience; Outliers

Indexed keywords

ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; CLASSIFICATION; COMPUTER PROGRAM; CYTOLOGY; FACTUAL DATABASE; HUMAN; NERVE CELL; PHYSIOLOGY; PRINCIPAL COMPONENT ANALYSIS; STATISTICS;

ALGORITHMS; ANIMALS; DATABASES, FACTUAL; HUMANS; MODELS, NEUROLOGICAL; NEURONS; PRINCIPAL COMPONENT ANALYSIS; SOFTWARE;

EID: 84868303503     PISSN: 15392791     EISSN: None     Source Type: Journal    
DOI: 10.1007/s12021-012-9150-5     Document Type: Article

References (34)

1. Ascoli, G. A. (Ed.) (2002). Computational neuroanatomy: Principles and methods. Totawa, NJ: Humana Press.
2. Ascoli, G. A., Donohue, D. E., & Halavi, M. (2007). Neuromorpho. org: A central resource for neuronal morphologies. Journal of Neuroscience, 27(35), 9247.
3. Binzegger, T., Douglas, R. J., & Martin, K. A. (2005). Axons in cat visual cortex are topologically self-similar. Cereb Cortex, 15(2), 152-165. (Pubitemid 40111076)
4. Botev, Z. I., Grotowski, J. F., & Krose, D. P. (2010). Kernel density estimation via diffusion. The Annals of Statistics, 38(5), 2916.
5. Cajal, S. R. (1989). Recollections of my life. Massachussetts: MIT Press.
6. Cook, J. E. (1998). Getting to grips with neuronal diversity:What is a neuronal type? In L. Chalupa & B. Finlay (Eds.), Development and organization of the retina (pp. 91). New York: Plenum.
7. Costa, L. da F., Manoel, E. T. M., Faucereau, F., Chelly, J., van Pelt, J., & Ramakers, G. (2002). A shape analysis framework for neuromorphometry. Network: Computation in Neural Systems, 13(3), 283.
8. Costa, L. da F., Rodrigues, F. A., Hilgetag, C. C., & Kaiser, M. (2009). Beyond the average: Detecting global singular nodes from local features in complex networks. Europhysics Letters, 87, 18008.
9. Costa, L. da F. & Velte, T. J. (1999). Automatic characterization and classification of ganglion cells from salamander retina. Journal of Comparative Neurology, 404, 33.
10. Costa, L. da F., Zawadzki, K., Miazaki, M., Viana, M. P., & Taraskin, S. N. (2010). Unveiling the neuromorphological space. Frontiers in Neuroscience, 4, 1.
11. Donohue, D. E., & Ascoli, G. A. (2010). Automated reconstruction of neuronal morphology: An overview. Brain Research Review, 67,(1-2), 165.
12. Eadie, W. T., Drijard, D., James, F. E., Roos, M., & Sadoulet, B. (1971). Statistical methods in experimental physics. North- Holland, Amsterdam.
13. Echtermeyer, C., Costa, L. da F., Rodrigues, F. A., & Kaiser, M. (2011).Automatic network fingerprinting through singlenode motifs. PLoS ONE, 6(1), 9.
14. Echtermeyer, C., Han, C. E., Rotarska-Jagiela, A., Mohr, H., Uhlhass, P., & Kaiser, M. (2011). Integrating temporal and spatial scales: Human structural network motifs across age and region of interest size. Frontiers in Neuroinformatics, 5, 14.
15. Gleeson, P., Steuber, V., & Silver, R. A. (2007). Neuroconstruct: A tool for modeling networks of neurons in 3D space. Neuron, 54(2), 219.
16. Halavi, M., Polavaram, S., Donohue, D. E., Hamilton, G., Hoyt, J., Smith, K. P., et al. (2008). Neuromorpho.org implementation of digital neuroscience: Dense coverage and integration with the NIF. Journal of Neuroinformatics, 6(3), 241-252.
17. Härdle,W. K., & Simar, L. (2007). Applied multivariate statistical analysis (2nd ed.). Springer.
18. Kaiser, M., & Hilgetag, C. C. (2006). Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems. PLoS Computational Biology, 7(95), 806.
19. Kaiser, M., Hilgetag, C. C., & van Ooyen, A. (2009). A simple rule for axon outgrowth and synaptic competition generates realistic connection lengths and filling fractions. Cerebral Cortex, 19(12), 3001.
20. Loewi, O. (1921). Über humorale Übertragbarkeit der Herznervenwirkung. Pf lügers Archiv, 189, 239.
21. Loewi, O. (1955). Salute to Henry Hallet Dale. The British Medical Journal, 1(4926), 1356.
22. Lu, J., Fiala, F. C., & Lichtman, J. W. (2009). Semi-automated reconstruction of neural processes from large numbers of fluorescence images. PLoS ONE, 4(5), e5655.
23. McGhee, G. R. (2006). The geometry of evolution: Adaptive landscapes and theoretical morphospaces. Cambridge University Press.
24. Montague, P. R.,&Friedlander, M. J. (1991).Morphogenesis and territorial coverage by isolated mammalian retinal ganglion cells. Journal of Neuroscience, 11, 1440.
25. Poznanski, R. R. (1992). Modelling the electronic structure of starburst amacrine cells in the rabbit retina: Functional interpretation of dendritic morphology. Bulletin of Mathematical Biology, 54, 905.
26. Schierwagen, A. (2008). Neuronal morphology: Shape characteristics and model. Neurophysiology, 40(4), 310.
27. Scorcioni, R., Polavaram, S., & Ascoli, G. A. (2008). L-measure: A web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies. Nature Protocols, 3, 866.
28. Sholl, D. A. (1953). Dendritic organization in the neurons of the visual and motor cortices of the cat. Journal of Anatomy, 87, 387.
29. Sporns, O., Chialvo, D. R., Kaiser, M., & Hilgetag, C. C. (2004). Organization, development and function of complex brain networks. Trends in Cognitive Sciences, 8(9), 418.
30. Srinivasan, R., Zhou, X., Miller, E., Lu, J., Litchman, J., & Wong, S. T. C. (2007). Automated axon tracking of 3D confocal laser scanning microscopy images using guided probabilistic region merging. Neuroinformatics, 5(3), 189.
31. Stepanyants, A., & Chklovskii, D. B. (2005). Neurogeometry and potential synaptic connectivity. Trends in Neuroscience, 28(7), 387.
32. Stepanyants, A., Hof, P. R., & Chklovskii, D. B. (2002). Geometry and structural plasticity of synaptic connectivity. Neuron, 34(2), 275.
33. Toris, C. B., Eiesland, J. L., & Miller, R. F. (1995). Morphology of ganglion cells in the neotenous tiger salamander retina. Journal of Comparative Neurology, 352(4), 535.
34. Wen, Q., & Chklovskii, D. B. (2008). A cost-benefit analysis of neuronal morphology. Journal of Neurophysiology, 99, 497.