Dynamical Systems and Accurate Temporal Information Transmission in Neural Networks
We simulated the activity of hierarchically organized spiking neural networks characterized by an initial developmental phase featuring cell death followed by spike timing dependent synaptic plasticity in presence of background noise. Upstream networks receiving spatiotemporally organized external inputs projected to downstream networks disconnected from external inputs. The observation of precise firing sequences, formed by recurrent patterns of spikes intervals above chance levels, suggested the build-up of an unsupervised connectivity able to sustain and preserve temporal information processing.
KeywordsSpike Train Neural Stem Cell Proliferation Spike Timing Dependent Plasticity Temporal Information Processing Output Spike Train
The authors ackowledge the support by the EU FP6 grants #034632 PERPLEXUS and #043309 GABA.
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