  The organizational principles behind the connectivity of a complex network
are known to influence its behavior. In this work we investigate, using the
Hopfield model, the influence of the network architecture on the performance
for associative recall while the network is under hub and edge attack. We show,
by using four different attack strategies, that although the importance of hubs
is more definite for Barab\'asi-Albert neuronal networks, the random removal of
the same amount of edges as in a hub may imply a greater reduction of memory
recall.
