IEEE Transactions on Computers
Study of nitric oxide effect in the Hebbian learning: towards a diffusive Hebb’s law
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
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At present, a new type of process for signalling between cells seems to be emerging, the diffusion or volume transmission. The volume transmission is performed by means of a gas diffusion process, which is obtained with a diffusive type of signal (NO). We present in this paper a CAST approach, in order to develop a NOdi ffusion model, away from a biologically plausible morphology, that provides a formal framework for the establishing of neural signalling capacity of NOin biological and artificial neural environments. It is also presented a study which shows implications of volume transmission in the emergence of complex structures and self-organisation processes in both biological and artificial neural netwoks. Finally, we present the diffusion version of the Associative Network (AN) [6], the Diffusion Associative Network (DAN), where a more general framework of neural learning, which is based in synaptic and volume transmission, is considered.