  The enormous amount of data generated nowadays worldwide is increasingly
triggering the search for unconventional and more efficient ways of processing
and classifying information, eventually able to transcend the conventional
von-Neumann-Turing computational central dogma. It is, therefore, greatly
appealing to draw inspiration from less conventional but computationally more
powerful systems such as the neural architecture of the human brain. This
neuromorphic route has the potential to become one of the most influential and
long-lasting paradigms in the field of unconventional computing. The
material-based workhorse for current hardware platforms is largely based on
standard CMOS technologies, intrinsically following the above mentioned
von-Neumann-Turing prescription; we do know, however, that the brain hardware
operates in a massively parallel way through a densely interconnected physical
network of neurons. This requires challenging the intrinsic definition of the
single units and the architecture of computing machines. (...)
