AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis
About This Grant
Project Summary The opioid epidemic and substance use disorders devastate millions of lives annually through addiction and overdose. While animal models are essential for understanding reward processing mechanisms, current behavioral analysis methods severely limit research progress. Existing approaches rely on basic movement tracking, subjective human annotation, or complex custom solutions, resulting in inconsistent data across laboratories. The industry standard still uses simple and outdated tracking technology, preventing researchers from detecting subtle yet crucial behavioral patterns that could reveal key insights about substance abuse mechanisms. BioSyft has developed an innovative AI behavioral analysis platform combining a customized multi- view chamber with optimized computer vision models. This system substantially increases to 29 tracking points across rodents compared to industry standards, enabling high-accuracy automated behavior classification. Built on a comprehensive and diverse behavioral dataset, our classification algorithms effectively analyze standard and nuanced behaviors while maintaining cost-effectiveness and research efficiency. Our focus on AI/ML technology development for digital health and behavioral phenotyping applications ensures the platform eliminates manual labeling requirements and standardizes behavioral quantification across laboratories. This proposal aims to validate and expand automated behavioral analysis through a systematic investigation of reward-related behaviors during Pavlovian conditioning, combining supervised and unsupervised AI approaches to detect novel behavioral signatures of addiction. By emphasizing the validation of AI/ML technologies and investigating the extent of their capabilities, the project will establish standardized metrics for reward-seeking behaviors while discovering previously undetectable patterns that could advance our understanding of substance abuse mechanisms.
Grant Summary
AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis is a NIDA - National Institute on Drug Abuse grant providing up to $301K for university, nonprofit, healthcare org. Applications are due 2027-06-30 (open). Check eligibility and apply with FindGrants.
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Focus Areas
Eligibility
How to Apply
Up to $301K
2027-06-30
- 1Confirm your organization is eligible for AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis from NIDA - National Institute on Drug Abuse, checking organization type, location, and any population or project requirements.
- 2Gather the required documents and information, including your organization details, project plan, and budget figures.
- 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
- 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NIDA - National Institute on Drug Abuse before the deadline.
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AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis: Frequently Asked Questions
Who is eligible for the AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis?
AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis is offered by NIDA - National Institute on Drug Abuse and is generally open to university, nonprofit, healthcare org. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.
How much funding does the AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis provide?
AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis provides up to $301K per award from NIDA - National Institute on Drug Abuse. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.
When is the AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis deadline?
Applications for AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis are due 2027-06-30 (open). Because deadlines can change, verify the date with the funder, NIDA - National Institute on Drug Abuse, and give yourself enough time to prepare a complete, competitive application before the close date.
How do you apply for the AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis?
To apply for AI-Driven Detection of Addiction-Like Reward Signatures Through Automated Multi-View Behavioral Analysis, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NIDA - National Institute on Drug Abuse.