EPSCoR Research Fellows: NSF: Using Radio Frequency Identification to Study Learning and Memory in Wild Birds

This Research Infrastructure Improvement (RII) EPSCoR Research Fellows project provides a fellowship to an Assistant Professor and training for undergraduate students at Bennington College. This work is conducted in collaboration with Dr. Eli Bridge at the University of Oklahoma. Through the fellowship, the PI will develop radio frequency identification (RFID) technology to study how wild birds learn and make decisions. The project will focus on free-living songbirds to investigate how individuals learn from experience and environmental and social cues. Automated feeders will record visits by individually tagged birds, allowing researchers to track learning, memory, and decision-making without disturbing the animals. The project will expand research capacity at a small liberal arts college and provide undergraduate students with hands-on experience in field research, technology development, and data analysis. The work will also contribute to the development of affordable tools for studying animal cognition in natural ecosystems. This project will establish a research program investigating cognitive ecology and decision-making in free-living birds using automated radio frequency identification. The principal investigator will receive training in designing, constructing, and deploying RFID-enabled feeders and data recording systems; thus, allowing for continuous, non-invasive monitoring of individually tagged songbirds in natural environments. Field experiments will examine individual variation in social learning, associative learning, reversal learning, and episodic-like memory by measuring visit patterns, latency to correct choices, and error rates during automated feeder tasks. The project will establish RFID infrastructure and analytical capacity at Bennington College, enabling long-term field studies of cognition, behavior, and physiology in wild bird populations. Undergraduate students will participate in technology development, experimental design, and data collection and analysis. This project will advance research in cognitive ecology while expanding access to automated behavioral monitoring technologies at a primarily undergraduate institution. This project is supported by the EPSCoR Research Infrastructure Improvement Program: EPSCoR Research Fellows, which supports early- and mid-career investigators in eligible jurisdictions to develop collaborations at the nation’s private, government or academic research institutions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.