IBACS Seed Grants provide funding for collaborative research projects across the brain and cognitive sciences. Seed Grants also support applications for equipment, research workshops, events, and other activities compatible with the mission of the Institute.
2025-2026 Recipients
Learn about the PIs and projects that received IBACS Seed Grants this year.
Michael Kienzler, Chemistry
Title of Project: Photoswitchable activators and inhibitors for the modulation of KCNQ channel function
TBD
Deborah Schneider, Psychological Sciences
Title of Project: Stop, Feel, Go: How Emotions Affect Our Ability to Stop and Think
We all know emotions can interfere with decision-making, but exactly how does this work? This project tests how different types of emotional content—words we read or hear, and facial expressions—affect our ability to stop automatic responses. By understanding these relationships, we can better design research and interventions for people who struggle with impulse control and emotional regulation.
Natale Sciolino, Physiology and Neurobiology
Title of Project: Integrative Neuroscience of Addiction: Systems and Behavioral Effects of Ketamine Metabolites
Opioid use disorder causes severe withdrawal symptoms that current treatments often fail to address. Ketamine may ease these symptoms, but side effects limit its use. A metabolite, (2R,6R)-hydroxynorketamine (HNK), could offer a safer alternative, yet its role in withdrawal is unclear. Our project uses viral genetics, fiber photometry, and machine-learning behavior analysis to reveal how HNK influences key brain cell types during withdrawal—insights that could guide development of more effective therapies for opioid addiction.
Ian Stevenson, Psychological Sciences
Title of Project: Statistical Models of Neural Activity with Latent Variables
Neuroscience experiments typically measure only a small fraction of the neurons that might be relevant to a behavior or disorder. Our goal in this project is to develop new statistical models to describe measurements that are available (spikes and local fields) and, also, accurately identify hidden factors (latent variables) driving neural activity. We will test our data analysis using simulations and analyze public experimental datasets to better characterize neural function and dysfunction.
Hanlin Zhou, Geography, Sustainability, Community, and Urban Studies
Title of Project: Mapping the Mind's Flood Risk Map: An AI-driven Analysis of Human Flood Risk Perception
TBD
Ying Zhou, Statistics
Title of Project: How Alzheimer’s Proteins Affect Brain and Cognition
This project combines multiple types of brain data to understand how Alzheimer’s disease leads to memory and thinking problems. Using causal mediation analysis, we will separate the direct effects of toxic brain proteins from their indirect effects through changes in brain structure and function. By integrating this information, the study aims to clarify disease pathways and support earlier detection and better treatment strategies.