  In spite of the large amount of existing neural models in the literature,
there is a lack of a systematic review of the possible effect of choosing
different initial conditions on the dynamic evolution of neural systems. In
this short review we intend to give insights into this topic by discussing some
published examples. First, we briefly introduce the different ingredients of a
neural dynamical model. Secondly, we introduce some concepts used to describe
the dynamic behavior of neural models, namely phase space and its portraits,
time series, spectra, multistability and bifurcations. We end with an analysis
of the irreversibility of processes and its implications on the functioning of
normal and pathological brains.
