Modeling neurons that can self organize into building blocks and hierarchies : an exploration based on visual systems

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2012

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Polat, Aydın Göze

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Cell-cell and cell-environment interactions are controlled by a set of local rules that dictate cell behavior. With such local rules, emergence of computationally meaningful building blocks and hierarchies can be observed. For example, at the cellular level organization in the visual system, receptive field of a retinal ganglion cell displays an activation inhibition behavior that can be modeled as Mexican Hat wavelet or Difference of Gaussians. This precise organization is the product of a harmonious collaboration of different cell types located at the lower levels in a hierarchical structure for each ganglion cell. Moreover, a similar hierarchical organization is observed at higher levels in the visual system. This thesis investigates the visual system from several perspectives in an effort to explore the biological/computational principles underlying these local rules. The investigation results in a hybrid computer model that can combine the advantages of evolutionary and developmental principles to explore the effects of local rules on cellular differentiation, retinal mosaics, layered structures and network topology.

Subject Keywords

Visual pathways., Entropy (Information theory)., Computational neuroscience., Retinal ganglion cells., Neurosciences., Neuroinformatics.

URI

http://etd.lib.metu.edu.tr/upload/12614712/index.pdf
https://hdl.handle.net/11511/21919

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Graduate School of Informatics, Thesis

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Citation Formats

A. G. Polat, “ Modeling neurons that can self organize into building blocks and hierarchies : an exploration based on visual systems,” M.S. - Master of Science, Middle East Technical University, 2012.