National Institutes of Health

Description

EXplainable Artificial Intelligence (XAI) aims to provide strong predictive value along with mechanistic understanding by combining machine learning techniques with effective explanatory techniques. This Funding Opportunity Announcement (FOA) solicits applications in the area of XAI applied to neuroscientific questions of encoding, decoding, and modulation of neural circuits linked to behavior. This FOA encourages collaborations between computationally and experimentally-focused investigators. This FOA seeks machine learning algorithms able to mechanistically explain how experimental manipulations can improve cognitive, affective, or social processing in humans or animals. Proof-of-concept applications aimed at improving the current state of the technology that use XAI to provide unbiased, hierarchical explanations of causal relationships between complex neural and behavioral data are also responsive.

Who can apply

• State governments
• County governments
• City or township governments
• Special district governments
• Independent school districts
• Public and State controlled institutions of higher education
• Native American tribal governments (Federally recognized)
• Public housing authorities / Indian housing authorities
• Native American tribal organizations (other than Federally recognized)
• Nonprofits with 501(c)(3) status (other than higher education)
• Nonprofits without 501(c)(3) status (other than higher education)
• Private institutions of higher education
• For-profit organizations other than small businesses
• Small businesses
• Others

Contact

NIH OER Webmaster<br/>FBOWebmaster@OD.NIH.GOV
FBOWebmaster@OD.NIH.GOV