  This study is focused on the development of the cortex-like visual object
recognition system. We propose a general framework, which consists of three
hierarchical levels (modules). These modules functionally correspond to the V1,
V4 and IT areas. Both bottom-up and top-down connections between the
hierarchical levels V4 and IT are employed. The higher the degree of matching
between the input and the preferred stimulus, the shorter the response time of
the neuron. Therefore information about a single stimulus is distributed in
time and is transmitted by the waves of spikes. The reciprocal connections and
waves of spikes implement predictive coding: an initial hypothesis is generated
on the basis of information delivered by the first wave of spikes and is tested
with the information carried by the consecutive waves. The development is
considered as extraction and accumulation of features in V4 and objects in IT.
Once stored a feature can be disposed, if rarely activated. This cause update
of feature repository. Consequently, objects in IT are also updated. This
illustrates the growing process and dynamical change of topological structures
of V4, IT and connections between these areas.
