  In this paper we present a brain-inspired cognitive architecture that
incorporates sensory processing, classification, contextual prediction, and
emotional tagging. The cognitive architecture is implemented as three modular
web-servers, meaning that it can be deployed centrally or across a network for
servers. The experiments reveal two distinct operations of behaviour, namely
high- and low-salience modes of operations, which closely model attention in
the brain. In addition to modelling the cortex, we have demonstrated that a
bio-inspired architecture introduced processing efficiencies. The software has
been published as an open source platform, and can be easily extended by future
research teams. This research lays the foundations for bio-realistic attention
direction and sensory selection, and we believe that it is a key step towards
achieving a bio-realistic artificial intelligent system.
