  Neural development represents not only an exciting and complex field of
study, with ongoing progress, but it also became the epicentre of neuroscience
and developmental biology, as it strives to describe the underlying cellular
and molecular mechanisms by which the central nervous system emerges during the
various levels of embryonic development phases. The nervous system is a dynamic
entity, where the genetic information plays an important role in shaping the
intra- and extracellular environments, which in turn offer a reliable
foundation for the stem cell precursors to divide and form neurons. Throughout
the embryonic development stages, the neurons undergo different processes:
migration at an immature level from the initial place in the embryo to a
predefined final position, axonal differentiation and guidance of the motile
growth cone towards a postsynaptic target, synaptic formation between axons and
target, and lastly long-term synaptic changes which underlie learning and
memory. In order to gain a better understanding of how the nervous system
develops, mathematical and computational models have been created and expanded
in order to bridge the gap between system-level dynamics and lower level
cellular and molecular processes. This research paper aims to illustrate the
potential of theoretical mathematical and computational models for analysing
one important stage of neural development - axonal growth and guidance
mechanisms in the presence of diffusion cues, through a visual simulation which
is optimized via the graphic processing unit and parallel programming
techniques.
