  Neuromorphic engineering concentrates the efforts of a large number of
researchers due to its great potential as a field of research, in a search for
the exploitation of the advantages of the biological nervous system and the
brain as a whole for the design of more efficient and real-time capable
applications. For the development of applications as close to biology as
possible, Spiking Neural Networks (SNNs) are used, considered
biologically-plausible and that form the third generation of Artificial Neural
Networks (ANNs). Since some SNN-based applications may need to store data in
order to use it later, something that is present both in digital circuits and,
in some form, in biology, a spiking memory is needed. This work presents a
spiking implementation of a memory, which is one of the most important
components in the computer architecture, and which could be essential in the
design of a fully spiking computer. In the process of designing this spiking
memory, different intermediate components were also implemented and tested. The
tests were carried out on the SpiNNaker neuromorphic platform and allow to
validate the approach used for the construction of the presented blocks. In
addition, this work studies in depth how to build spiking blocks using this
approach and includes a comparison between it and those used in other similar
works focused on the design of spiking components, which include both spiking
logic gates and spiking memory. All implemented blocks and developed tests are
available in a public repository.
