Genetic Reactivation of Cone Photoreceptors Restores Visual Responses in Retinitis PigmentosaRetinitis pigmentosa refers to a diverse group of hereditary diseases that lead to incurable blindness, affecting two million people worldwide. As a common pathology, rod photoreceptors die early, whereas light-insensitive, morphologically altered cone photoreceptors persist longer. It is unknown if these cones are accessible for therapeutic intervention. Here, we show that expression of archaebacterial halorhodopsin in light-insensitive cones can substitute for the native phototransduction cascade and restore light sensitivity in mouse models of retinitis pigmentosa. Resensitized photoreceptors activate all retinal cone pathways, drive sophisticated retinal circuit functions (including directional selectivity), activate cortical circuits, and mediate visually guided behaviors. Using human ex vivo retinas, we show that halorhodopsin can reactivate light-insensitive human photoreceptors. Finally, we identified blind patients with persisting, light-insensitive cones for potential halorhodopsin-based therapy.
Light-activated channels targeted to ON bipolar cells restore visual function in retinal degenerationA CNN framework for modeling parallel processing in a mammalian retinaD. Bálya, Botond Roska, Tamás Roska et al.|International Journal of Circuit Theory and Applications|2002 Abstract We present here a simple multi‐layer cellular neural/non‐linear network (CNN) model of the mammalian retina, capable of implementation on CNN Universal Machine (CNN‐UM) chips. The basis of the model is a simple multi‐layer cellular neural/non‐linear Network ( IEEE Trans. Circuits Systems 1988; 35 :1257; IEEE Trans. Circuits Systems 1993; 40 :147). The characterization of the elements in the CNN model is based on anatomical and physiological studies performed in the rabbit retina. The living mammalian retina represents the visual world in a set of about a dozen different ‘feature detecting’ parallel representations ( Nature 2001; 410 :583–587). Our CNN model is capable of reproducing qualitatively the same full set of space–time patterns as the living retina in response to a flashed square. The modelling framework can then be used to predict the set of retinal responses to more complex patterns and is also applicable to studies of the other biological sensory systems. The work represents a major step forward in the complexity and programmability of retinal models. Copyright © 2002 John Wiley & Sons, Ltd.
Genetically timed, activity-sensor and rainbow transsynaptic viral toolsCellular neural networks: a paradigm for nonlinear spatio-temporal processingLuigi Fortuna, P. Arena, D. Bálya et al.|IEEE Circuits and Systems Magazine|2001 The paradigm of Cellular Neural Networks (CNNs)is going to achieve a complete maturity. In fact, from a methodological point of view, important results on their digitally programmable analog dynamics have been gained, completed with thousands of application routines. This has encouraged the spreading of a great number of applications in the most different disciplines. Moreover, their structure, tailor made for VLSI realization, has led to the production of some chip prototypes that, embedded in a computational infrastructure, have produced the first analogic cellular computers. This completes the framework and makes it possible to realize complex spatio-temporal and filtering tasks on a time scale of microseconds. In this paper some sketches on the main aspects of CNNs, from the formal to the hardware prototype point of view, are presented together with some appealing applications to illustrate complex image, visual and spatio-temporal dynamics processing.