Abstract
We studied the emergence of cell assemblies out of locally connected random networks of integrate-and-fire units distributed on a 2D lattice stimulated with a spatiotemporal pattern in presence of independent random background noise. Networks were composed of 80% excitatory and 20% inhibitory units with initially balanced synaptic weights. Excitatory–excitatory synapses were modified according to a spike-timing-dependent synaptic plasticity (stdp) rule associated with synaptic pruning. We show that the application, in presence of background noise, of a recurrent pattern of stimulation let appear cell assemblies characterized by an internal pattern of converging projections and a feed-forward topology not observed with an equivalent random stimulation.
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Iglesias, J., Eriksson, J., Pardo, B., Tomassini, M., Villa, A.E.P. (2005). Stimulus-Driven Unsupervised Synaptic Pruning in Large Neural Networks. In: De Gregorio, M., Di Maio, V., Frucci, M., Musio, C. (eds) Brain, Vision, and Artificial Intelligence. BVAI 2005. Lecture Notes in Computer Science, vol 3704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11565123_6
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DOI: https://doi.org/10.1007/11565123_6
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