Exploring wavelet transforms for morphological differentiation between functionally different cat retinal ganglion cells
Brain and Mind 4 (1):67-90 (2003)
|Abstract||Cognition or higher brain activity is sometimes seen as a phenomenon greater than the sum of its parts. This viewpoint however is largely dependent on the state of the art of experimental techniques that endeavor to characterize morphology and its association to function. Retinal ganglion cells are readily accessible for this work and we discuss recent advances in computational techniques in identifying novel parameters that describe structural attributes possibly associated with specific function. These parameters are based on calculating wavelet gradients from cell images followed by the extraction of meaningful measures including 2nd wavelet moment, entropy of orientation, and curvature. For the three cell types analyzed, the mean 2nd wavelet moment, which relates to the field of influence of the dendritic-tree segments was significantly different. cells had the highest mean 2nd wavelet moment, followed by the and cells (134 ± 22, 93 ± 19 and 63 ± 12, respectively). There was no significant difference between cells for entropy of orientation, indicating no class with a preferential orientation of their dendritic tree. Curvature provided similar results to the 2nd wavelet moment with cells having the highest curvature followed by and the cells (mean ± SD: 161 ± 15; 134 ± 22; 121 ± 15). Our feature space analysis also indicated a difference between these cell types. No difference was found between the and cell types and their physiological counterparts the Y and X cells based on wavelet analysis. Both the X and Y cells can be divided into two subtypes, the ON- and OFF-center cells based on the stratification level of the dendritic tree within the retina. Using 2nd wavelet moment, a difference in their morphological attributes, not reported previously, was noted for these subtypes. The 2nd wavelet moment and curvature are further discussed with respect to explaining regularity of spacing and coverage associated with retinal ganglion cell mosaics.|
|Keywords||No keywords specified (fix it)|
|Through your library||Configure|
Similar books and articles
Jürgen Bereiter-Hahn (1985). Architecture of Tissue Cells the Structural Basis Which Determines Shape and Locomotion of Cells. Acta Biotheoretica 34 (2-4).
W. Schwemmler (1982). The Endoeytobiotic Cell Theory and the Periodic System of Cells. Acta Biotheoretica 31 (1).
Melinda B. Fagan (2011). Social Experiments in Stem Cell Biology. Perspectives on Science 19 (3):235-262.
U. Heiden & G. Roth (1987). Mathematical Model and Simulation of Retina and Tectum Opticum of Lower Vertebrates. Acta Biotheoretica 36 (3).
Luiz Carlos L. Silveira (2004). Parallel Visual Pathways From the Retina to the Visual Cortex – How Do They Fit? Behavioral and Brain Sciences 27 (1):50-51.
José Pierrez & Xavier Ronot (1992). Flow Cytometric Analysis of the Cell Cycle: Mathematical Modeling and Biological Interpretation. Acta Biotheoretica 40 (2-3).
Hisao Honda, Masaharu Tanemura & Akihiro Yoshida (2000). Differentiation of Wing Epidermal Scale Cells in a Butterfly Under the Lateral Inhibition Model - Appearance of Large Cells in a Polygonal Pattern. Acta Biotheoretica 48 (2).
Luciano Fontoura Costdaa, Marconi Soares Barbosa, Vincent Coupez & Dietrich Stauffer (2003). Morphological Hopfield Networks. Brain and Mind 4 (1):91-105.
Luciano Fontoura Costdaa (2003). Morphological Hopfield Networks. Brain and Mind 4 (1):91-105.
Sorry, there are not enough data points to plot this chart.
Added to index2009-01-28
Recent downloads (6 months)0
How can I increase my downloads?