  Economies are complex man-made systems where organisms and markets interact
according to motivations and principles not entirely understood yet. The
increasing dissatisfaction with the postulates of traditional economics i.e.
perfectly rational agents, interacting through efficient markets in the search
of equilibrium, has created new incentives for different approaches in
economics. The science of complexity may provide the platform to cross
disciplinary boundaries in seemingly disparate fields such as brain science and
economics. In this paper we take an integrative stance, fostering new insights
into the economic character of neural activity. The objective here is to
precisely delineate common topics in both neural and economic science, within a
systemic outlook grounded in empirical basis that jolts the unification across
the science of complex systems. It is argued that this mainly relies on the
study of the inverse problem in complex system with a truly Bayesian approach.
