Transitioning Brain Research - Neurotechnology in National Security and Defense - page 14

The results of new CR/NR efforts will be similarly at risk unless these requirements
are addressed early and explicitly in the S&T planning process. Two classes of issues
require consideration: (1) general challenges of the transition process and (2) potentially
unique challenges resulting from the unknown impact of the science itself.

BRAIN-MIND RESEARCH TRANSITION—GENERAL CHALLENGES
Regardless of the cognizant agency, or the specifics of the S&T product, certain themes
appear across all transition processes. The first of these is that transition is fundamen-
tally a needs-driven process. While S&T sponsors always welcome and encourage
disruptive “breakthroughs,” in a climate of conflicting budget priorities and transition
schedules, needs-based S&T products will almost always have priority. A needs-driven
product directly addresses an existing or anticipated capability shortfall, and S&T is
harnessed to solve a recognized problem; its value is apparent. An opportunity-driven
product, however, emerges from new discoveries and applications must be identified;
its ultimate value may be understood only as the product evolves. Although S&T pro-
grams typically include a mix of needs-driven (tech pull) and opportunity-driven (tech
push) efforts and because CR-NR generates a high level of fundamental new knowl-
edge, its applications are almost certain to be opportunity-driven. The most critical
outcomes may not be those that were anticipated when research began, and fitting to
a needs-driven process can therefore be extremely challenging (MacGillicuddy 2007).
All of the tasks required to validate a product for acquisition—for example, produc-
ibility, cost, and supportability—imply that transition is also an engineering process.
That is, DoD acquisition processes conform to a system engineering model, which
involves predictable steps of evaluation and gradual improvement toward a robust,
understood, and supportable outcome (Deputy Under Secretary of Defense for
Science and Technology 2005). Because the typical artifacts of such outcomes are
tangible hardware and software products with perceivable, measurable performance
effects, it can be difficult to cast the artifacts of CR-NR into such engineering forms
(with the exception of certain medical applications, where this research may simply
inform operational practices and technologies).
To realize the practical benefits of brain research for national security, the prod-
ucts of that research must relate to perceivable user needs and must be defined with
engineering constructs. These requirements can be illustrated with a representative
example—a human-machine interface system that uses direct physiological sensing
to determine a human operator's cognitive state in real time and adaptively modifies
system operation to enhance mission performance.
Measures of brain activity and psychological signals can reveal human states of
workload, comprehension, and fatigue that could be used by system processing rou-
tines to adjust information presentation rates or dynamically move manual tasks to
automated execution (Scerbo 2008). DoD interest in this form of neuroscience has
been both intense and long (Scott 1994). The brain-based interface application rep-
resents a candidate for near-term S&T transition, in that it

• Addresses known operational performance problems. Many military sys-

tems can tax the information-processing capabilities of human operators.