xTechBolt

The U.S. Army Medical Research and Development Command (USAMRDC) is announcing the xTech Brain Operant Learning Technology – xTechBOLT – prize competition.

1ST PLACE WINNER
Vanderbilt University
Enhancement of Classroom Medical Learning in the Army Visit Website
2ND PLACE WINNER
Drexel University
Neuroergonomic Training with Interpersonal Brain Interfaces Visit Website
3RD PLACE WINNER
SPARK Neuro
EEG Based Learning Accelerator Visit Website
4TH PLACE WINNER
University of California at Berkeley
High-Resolution, High Dimensional Functional Mapping Visit Website
5TH PLACE WINNER
SkillPower
Future Self-Avatar and Personalized Training Visit Website

DESCRIPTION

The U.S. Army Medical Research and Development Command (USAMRDC) is announcing the xTech Brain Operant Learning Technology – xTechBOLT – prize competition. The prize competition is designed to incentivize industry to develop and demonstrate the use of one or more tool(s) (e.g., QEEG, fMRI, MEG, BIOMRK, NIRS, PET, MEA, SPECT, or other) to locate, track, and trace four types of learning traits, including explicit and implicit knowledge, from exposure to storage, and use those neural pathways to capture emotions and empathy and research a proof of concept mechanism (software or hardware, or both) that could be developed to promote optimal retention and access to memories.

The goals for this competition are to understand the effects of emotion and empathy on learning and memory and the functional roles played by various brain regions and their mutual interactions in relation to emotional and empathetic processing and effect on both implicit and explicit learning. Understanding these effects will help build the United States Military of the future, by revolutionizing how we teach and train Warfighters, how we build better medical providers, and how we utilize novel brain operant learning technologies.

The Army (and more broadly the U.S. Department of Defense) seek “path finding” teams and technologies through this competition. Therefore, xTechBOLT is not interested in low-risk, repackaged approaches of tried and true techniques. We aim to find early-stage innovations with the potential to dramatically improve military training outcomes with novel hardware- and/or software-based technologies.

The prize authority the competition falls under is Title 10, US Code (USC) Section 2374a.

Problem Statement

xTechBOLT is seeking participants to use one or more tool(s) (e.g., QEEG, fMRI, MEG, BIOMRK, NIRS, PET, MEA, SPECT, or other) to:

Locate, track, and trace four types of learning traits including explicit and implicit knowledge from exposure to storage, and use those neural pathways to capture emotions and empathy from exposure to storage;
Research a proof of concept technology which may include software or hardware, or both that could be developed to promote optimal retention and access to memories.

Applicant technologies must:

be independently verified as either: mature Basic Research, at a Technology Readiness Level (TRL) of 2, and ready to move into Applied Research; or can be verified at a TRL for 3 or 4,
have an executable strategy to mature to a TRL of 6 and
have a transition strategy, for movement to a Program Management Office (PMO).