Kavli Announces 2025 NeuroData Discovery Grant Recipients

The Kavli Foundation announces the recipients of its 2025 NeuroData Discovery Grants, supporting creative reanalysis of publicly available neuroscience datasets. These grants reflect Kavli’s commitment to accelerating discovery through use of open data, enabling projects that explore existing, standardized datasets to yield new scientific insights.

NeuroData Discovery Grants support projects that emerge from NeuroDataReHack, a community workshop organized by the Neurodata Without Borders (NWB) initiative and co-sponsored by organizations including The Kavli Foundation, the Allen Institute, and the Howard Hughes Medical Institute. The workshop trains participants to access, analyze, and combine neurophysiology datasets in the NWB standard format, and develop new project ideas. These grants extend promising concepts from the workshop into full research proposals, transforming data into impactful scientific knowledge.

“Vast amounts of high-quality data have already been generated by neuroscientists, and the value of that data multiplies when it is made open and reuseable,” says Dr. Stephanie Albin, Senior Program Officer at The Kavli Foundation. “These grants showcase the creativity of researchers who are turning existing datasets into new discoveries.”

The NeuroData Discovery Grants are part of Kavli’s Open Data in Neuroscience program, which is dedicated to creating mechanisms to leverage the vast quantities of data produced by neuroscientists and fueling novel discoveries through open, collaborative exploration.

"Many of our scientific questions can be addressed, either in part or in whole, by data that already exists,” says Dr. Saskia de Vries, Associate Director at the Allen Institute for Neural Dynamics and advocate for open, collaborative neuroscience. “By creating opportunities and incentives for scientists to reuse existing data, this program accelerates discovery for individual team and encourages different analyses of the same data, leading to deeper collective insights."

2025 Grants
Now in its third year, the NeuroData Discovery Grant portfolio has supported projects that span diverse species, data modalities, and scientific questions, each exemplifying how secondary analysis of open data can push the frontiers of neuroscience.

This year’s cohort of grantees are:

• A neurocentric account for context-dependent neural geometry. Zilu Liang, Mia Whitefield, and Sumeda Nalluru (University of Oxford) will explore how neural representations shift across brain regions under different contextual influences.

• CoNDENS: A unified framework for defining neural states. Ergi Spiro and Wuwei Feng (Duke University) will develop a novel framework to analyze and quantify stimulation-induced stat transitions.

• Disentangling cell type from state in motor cortex. Peter Hogg (Harvard University) will develop a framework to understand transcriptomic diversity in the brain and the impact of activity-dependent plasticity states.

• Noise Meets Signal: Cross-species neural encoding and decoding. Yunglong (Draco) Xu and Brent Doiron (University of Chicago) will investigate how signal and noise interact to shape neural coding and behavior across brain regions and species.

• Validating interneuron role in hippocampal theta oscillation. Eryn Sale and Wen-Hao Zhang (University of Texas Southwestern Medical Center) will probe mechanisms underlying theta oscillations and their modulation by speed.

Previous Grants

• Depth-specific organization of cortical inhibitory neurons. Felipe Yáñez (Max Planck Institute for Neurobiology of Behavior)

• GraNNet – Graph Neuronal Networks based on a shared activity. Noga Mudrik and Adam Charles (Johns Hopkins University)

• Identification and characterization of neuronal ensembles. Ricardo Velázquez Contreras and Luis Carrillo-Reid (National Autonomous University of Mexico)

• Mapping functional neuronal networks to behavioral states. Tzu-Chi Yen (University of Colorado) and Yi-Yun Ho (Massachusetts Institute of Technology)

• Pareto optimality to define the topology of brain states. Sarah Ruediger (University College London)