Nonlinear Analysis And Modeling Study On The Firing Activities Of Retinal Ganglion Cells

The initial visual information processing occurs in the retina. Photoreceptors convert the visual stimuli into electrical signals. These signals are propagated through the retinal circuit to the ganglion cells and then to the central visual system. As the output neurons of the retina, ganglion cells fire action potential trains which encode the visual information carried by the visual stimuli. Therefore, study on the firing activities of retinal ganglion cells helps to understand the information processing and encoding mechanism of the retina. This not only contributes to the understanding of the biology system, but also provides biology bases for the development and application of the artificial vision.Natural stimuli are important to explore the information processing and encoding mechanism of the retina under natural scenes. However, due to the complicated statistics of natural stimuli and the nonlinearity of neural system, the firing activities of retinal ganglion cells during response to natural stimuli are always aperiodic and irregular. Determinism detection in the aperiodic, irregular firing activities of retinal ganglion cells provides directions for future work. In the first part of this dissertation, the correlation dimension method and the nonlinear forecasting method were applied to analyze the firing activities of retinal ganglion cells during response to natural movie and checker-board flickering. Mainly three conclusions were drawn. Firstly, there exists determinism in the aperiodic, irregular firing activities of retinal ganglion cells. As a result, deterministic models should be employed to study the firing activities of retinal ganglion cells. Secondly, the difference operation of the inter-spike interval series makes it easier for determinism detection in the firing activities of retinal ganglion cells. Thirdly, the nonlinear forecasting method is more efficient than the correlation dimension method for determinism detection.In the experiment with repetitive light flashes, it was found that the firing activities of a subpopulation of chicken retinal ganglion cells show a particular temporal structure– dual-peak response. The generation mechanism of the dual-peak response remains unclear. In the second part of this dissertation, a retina model was developed to solve this question. Model results indicate that the dual-peak response results from an inhibitory input to a sustained ganglion cell from a fast transient ON/OFF amacrine cell inhibited by a slow transient ON/OFF amacrine cell, which inhibit the ganglion cell's sustained response at a certain time window. These results imply that the firing activities of ganglion cells are regulated by the amacrine cells and thus demonstrate rich temporal structure.The difference of Gaussian model describes the classical antagonistic center-surround receptive field structure of retinal ganglion cells. However, it has been reported that there exists an extensive disinhibitory region beyond the classical receptive field and this disinhibitory region attenuates the surround inhibition in the classical receptive field. The disinhibition model explains the intrinsic mechanism of the disinhibition. In the last part of this dissertation, a visual system model was developed to study the encoding quality of the two receptive field models. The visual system model includes a retinal module and a central visual system module. The retina module consists of an ensemble of spatial-temporal filters and each filter simulates an individual ganglion cell. Model results indicate that the central visual system module decodes more information from the action potential trains generated by the retina module when the spatial-temporal filters are implemented by the disinhibition model. Therefore, a conclusion was drawn that the encoding quality of the disinhibition model excels the difference of Gaussian model. These results imply that the disinhibitory region beyond the classical receptive field is of great significance to the information encoding of retinal ganglion cells. This provides reference for the development of image processing and application of artificial vision.