A systematic investigation of neuronal morphology through the NeuroMorpho public database

• Grant number: 10/01994-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2010
• End date: December 31, 2011
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Luciano da Fontoura Costa
• Grantee: Krissia de Zawadzki
• Host Institution: Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated research grant: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications, AP.TEM

Abstract

The need to advance our knowledge about the structures and mechanisms that underlie the nervous system fostered researches based on computational resources. In this interdisciplinarity context, approaches such as the systematic study of neuronal cells shape has been recently improved by the incorporation of multivariated statistics and pattern recognition. This project aims at the systematic investigation of the thousands of neurons stored in the NeuroMorpho public database by using established methods of morphological characterization and classification. Our approach initially will use the morphological measurements already found in the repository. Afterwards, we will expand such an analysis by acquiring additional, more sophisticated measurements from two-dimensional images of the neurons from the base, such as fractal geometry, lacunarity and granulometry. Regarding the statistical analysis, we will investigate the correlation between each of the measurements, and then apply principal component analysis (PCA) and canonical discriminant analysis (LDA). The classification, on the other hand, will be performed by unsupervised clustering methods, especially k-means and hierarquical Ward's clustering, which will be applied to both available data from repository and the new measurements, then comparing these results. We will also quantify the contributions of each measurement to the classification, evaluate how much the original classes look like morphological cells features, and look for possible subgroups inside each of those classes. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

ZAWADZKI, KRISSIA; FEENDERS, CHRISTOPH; VIANA, MATHEUS P.; KAISER, MARCUS; COSTA, LUCIANO DA F.. Morphological Homogeneity of Neurons: Searching for Outlier Neuronal Cells. NEUROINFORMATICS, v. 10, n. 4, p. 379-389, OCT 2012. (05/00587-5, 10/01994-1)