  The study of attentional processing in vision has a long and deep history.
Recently, several papers have presented insightful perspectives into how the
coordination of multiple attentional functions in the brain might occur. These
begin with experimental observations and the authors propose structures,
processes, and computations that might explain those observations. Here, we
consider a perspective that past works have not, as a complementary approach to
the experimentally-grounded ones. We approach the same problem as past authors
but from the other end of the computational spectrum, from the problem nature,
as Marr's Computational Level would prescribe. What problem must the brain
solve when orchestrating attentional processes in order to successfully
complete one of the myriad possible visuospatial tasks at which we as humans
excel? The hope, of course, is for the approaches to eventually meet and thus
form a complete theory, but this is likely not soon. We make the first steps
towards this by addressing the necessity of attentional control, examining the
breadth and computational difficulty of the visuospatial and attentional tasks
seen in human behavior, and suggesting a sketch of how attentional control
might arise in the brain. The key conclusions of this paper are that an
executive controller is necessary for human attentional function in vision, and
that there is a 'first principles' computational approach to its understanding
that is complementary to the previous approaches that focus on modelling or
learning from experimental observations directly.
