  Neuroscience is undergoing dramatic progress because of the vast data streams
derived from the new technologies product of the BRAIN initiative and other
enterprises. As any other scientific field, neuroscience benefits from having
clear definitions of its theoretical components and their interactions. This
allows generating theories that integrate knowledge, provide mechanistic
insights, and predict results under new experimental conditions. However,
theoretical neuroscience is a heterogeneous field that has not yet agreed on
how to build theories or whether it is desirable to have an overarching theory
or whether theories are simply tools to understand the brain. Here we advocate
for the need of developing theoretical frameworks as a basis of generating
common theoretical structures. We enumerate the elements of theoretical
frameworks we deem necessary for any theory in neuroscience. In particular, we
address the notions of paradigms, models, and scales of organizations. We then
identify areas with pressing needs to develop brain theories: integration of
statistical and dynamic approaches; multi-scale integration; coding; and
interpretability in the context of Artificial Intelligence. We also point out
that future theoretical frameworks would benefit from the incorporation of the
principles of Evolution as a fundamental structure rather than purely
mathematical or engineering principles. Rather than providing definite answers,
the objective of this paper is to serve as an initial and succinct presentation
of these topics to encourage discussion and further in depth development of
each topic.
