  Spike-timing-dependent plasticity (STDP) is a biological process in which the
precise order and timing of neuronal spikes affect the degree of synaptic
modification. While there has been numerous research focusing on the role of
STDP in neural coding, the functional implications of STDP at the macroscopic
level in the brain have not been fully explored yet. In this work, we propose
that STDP in an ensemble of spiking neurons renders storing high dimensional
information in the form of a `memory plane'. Neural activity based on STDP
transforms periodic spatio-temporal input patterns into the corresponding
memory plane, where the stored information can be dynamically revived with a
proper cue. Using the dynamical systems theory that shows the analytic relation
between the input and the memory plane, we were able to demonstrate a specific
memory process for high-dimensional associative data sets. In the
auto-associative memory task, a group of images that were continuously streamed
to the system can be retrieved from the oscillating neural state. The second
application deals with the process of semantic memory components that are
embedded from sentences. The results show that words can recall multiple
sentences simultaneously or one exclusively, depending on their grammatical
relations. This implies that the proposed framework is apt to process multiple
groups of associative memories with a composite structure.
