Abstract
Recently, outstanding plasticity in the cat visual cortex after birth following a retinal lesion has been described. Previously, we have formulated a neural network model for the development of receptive fields in the mammal visual cortex prior to coherent visual experience. This model is based on self-organization rules, such as Hebbian and anti-Hebbian learning, spread of neural signal among neighbouring neurons, and limitation of the synaptic growth. Here we present how the same model is able to simulate plasticity after birth just tunning the conditions of the simulation to those of a retinal lesion. Thus, our model accounts for the experimentally described long-term plasticity as well as for the short-term one. The significance of the experimental results are discussed in the context of the neural self-organization theory.
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Morán, F., Andrade, M.A. (1995). A neural network model for plasticity in adult striate cortex. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_163
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DOI: https://doi.org/10.1007/3-540-59497-3_163
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