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This Notice is to inform the community that NIH has revised its approach to resuming operations after the government shutdown.

Explainable Artificial Intelligence (XAI) aims to provide strong predictive value along with mechanistic understanding of AI 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 the development of machine learning algorithms that are able to mechanistically explain how experimental manipulations affect cognitive, affective, or social processing in humans or animals. Proof-of-concept applications aimed at improving the current state of the technology that uses XAI to provide unbiased, hierarchical explanations of causal relationships between complex neural and behavioral data are also appropriate .

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.