Modeling of Non-Linearities in Neuronal Dendritic Structures and Their Role in Feature Extraction
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In order to achieve type-specific functionality, the study examines the role that homogenous morphology and electrophysiological play in type-specific neurons. In order to mimic the formation, propagation, and cell-field interaction of action potentials, two types of membrane dynamics are studied: active and passive. To mimic class-specific neurons, a hierarchical linear-nonlinear structure is created. To replicate scotopic and color vision edge estimates in the human visual cortex, an orientation-selective ganglion cell network is constructed and simulated. The model sheds light on similar ne...
In order to achieve type-specific functionality, the study examines the role that homogenous morphology and electrophysiological play in type-specific neurons. In order to mimic the formation, propagation, and cell-field interaction of action potentials, two types of membrane dynamics are studied: active and passive. To mimic class-specific neurons, a hierarchical linear-nonlinear structure is created. To replicate scotopic and color vision edge estimates in the human visual cortex, an orientation-selective ganglion cell network is constructed and simulated. The model sheds light on similar networks' receptive field widths and bandwidth tuning capacity. The research study demonstrates how signals in the magnocellular layer might influence the behavior of contour recognition and boundary estimation.
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