![](bg7.png)
is the first attempt on implemementing the inhibitory
“sombrero” learning for the memristive architecture
of neurons to represent the natural inhibitory synapse
learning (Vogels et al., 2013).
This way, preliminary results obtained from sim-
ulations have demonstrated the feasibility of the idea
enabling the implementation of complex determinis-
tic networks, based on organic memristive devices,
with two types of learning: Hebbian (excitatory) and
“sombrero” (inhibitory) ones. This finding opens new
perspectives for the better understanding of processes
in nervous system and for the implementation of a
“Robot brain”, allowing learning and decision mak-
ing on thinking machines and robots as well.
ACKNOWLEDGEMENTS
The work is performed according to the Russian Gov-
ernment Program of Competitive Growth of Kazan
Federal University. The work was partially supported
by the MaDEleNA project financed by the Provincia
Autonoma di Trento, call Grandi Progetti 2012.
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