[ Facebook Research - Engineering Approaches to Responsible Neural Interface Design Request For Proposals | Research Funding ]

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Date 14.07.2021
Category Call for proposal
Aim: Facebook is pleased to invite university faculty to respond to the new call for research proposals on Engineering Approaches to Responsible Neural Interface Design, focusing on the development of noninvasive neurotechnologies for human use -animal studies not in scope-. Successful proposals will contribute to the development of inclusive interfaces by considering diversity and broad representation in the proposed research studies. Areas of interest include, but are not limited to:
1. Inclusive optical neurotechnologies:
This topic aims to both identify and address barriers to achieving reliable Functional near-infrared spectroscopy (fNIRS) performance across diverse individuals. The focus might be:
  • Quantifying performance variability. How does technical performance (e.g. light absorption, photon count) change across different physical characteristics? What metrics or frameworks should be used to evaluate performance across demographics and why?
  • Designing for generalizability. What design features (e.g. cap design, source-detector configurations) promote generalizable system performance across different physical characteristics? How is this implemented?
  • Handling hair. What methods improve optode contact and system fit across different hair types? Evaluations of interest include: different amounts of hair, different hair textures, and different hair colors. Forehead and/or wrist measurements to provide baseline data are within scope.
2. Inclusive surface EMG wristband technology
This topic focuses on accounting for differences in forearm characteristics across the global population. While the proposals should focus on surface electromyography (EMG) systems, intramuscular recordings to provide ground truth signals are within scope as well.
  • Quantifying performance variability. How does technical performance (signal quality and/or decoding performance) of EMG recorded at the wrist change across different physical characteristics (e.g. wrist size, arm hair, muscle anatomy differences)? What metrics or frameworks should be used to evaluate performance across demographics and why?
  • Designing for generalizability. What hardware features (e.g. electrode type, configurations) or decoding algorithms promote generalizable system performance across different physical characteristics? How is this implemented?
3. Privacy-preserving methods for handling neural data
Privacy by design is an important aspect of responsible neurotechnology development, and benefits from the proactive consideration and development of privacy-preserving methods and tools. Successful proposals for this topic will surface the privacy considerations related to the chosen technology and demonstrate the feasibility of a method/methods to protect these data (e.g. differential privacy, federated learning, or other creative methodologies).
Areas of interest include the following:
  • fNIRS data privacy: how does one collect only the minimum data needed for brain-computer interactions? Is there sensitive information that can be decoded from fNIRS data (e.g. cardiovascular information) and what methods can be used to protect these data while maintaining their functionality for AR/VR interactions?
  • EMG data privacy: how does one collect only the minimum data needed for motor human-computer interactions? Is there sensitive information that can be decoded from electromyography (EMG)/motor unit data and what methods can be used to protect these data while maintaining their functionality for AR/VR interactions?

A total of up to five awards are available, worth up to $150,000 each. Payment will be made to the proposer’s host university as an unrestricted gift

Funding:  up to $150’000

Eligibility: Awards must comply with applicable US and international laws, regulations and policies. Applicants must be current full-time faculty at an accredited academic institution that awards research degrees to PhD students. Applicants must be the Principal Investigator on any resulting award.

How to Apply: Proposals should include:
A summary of the project (1-2 pages) explaining the area of focus, a description of techniques, any relevant prior work, and a timeline with milestones and expected outcomes.
A draft budget description (1 page) including an approximate cost of the award and explanation of how funds would be spent
Curriculum Vitae for all project participants.
Organization details; this will include tax information and administrative contact details -please contact the Research Office-. Budgets should be formulated to include 5% overhead (the maximum allowed in the program guidelines).
Deadline:         July 14, 2021, 5:00 p.m. AOE
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PhD fellowship

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