About this year

The 2027 school is the first installment supported by the NINDS R25 award and the first under the NeuroData AI name. It continues the format that NeuroDataReHack refined over five years: participants arrive with a reanalysis question, form teams around shared datasets, take instruction in the mornings, and spend most of the week on project work with faculty and dataset stewards on hand. Compared with earlier years, a larger share of the curriculum is devoted to AI methods for neural data.

The DANDI Archive now holds more than 550 neurophysiology datasets in the NWB format, spanning many species, brain areas, task designs, and recording modalities. These include releases from Allen Institute OpenScope, the MICrONS project, and the International Brain Laboratory Brain Wide Map. This school teaches participants how to find, access, and reanalyze these datasets so that data deposited in the archive is used to answer questions beyond those the original experiments were designed for.

Example projects:

Determine whether your result is present in another species or brain area.
Showcase the capabilities of your tool or analysis on existing data from another lab.
Explore follow-up questions to a published study.
Apply a foundation model or decoding approach across datasets.
Create educational content that uses open data.

The school focuses on analyzing existing data in NWB and on DANDI, not on converting data to NWB. If you want to learn how to convert data, consider an NWB data conversion workshop instead.

Eligibility and cost

The school is intended for PhD students, postdoctoral researchers, and faculty with some programming experience in Python or MATLAB and experience with neurophysiology research, from neuroscience or from computational fields. It is free: there is no application fee, lodging and meals on campus are provided, and travel is reimbursed up to $550. The apply page has the full eligibility criteria, what the application asks for, travel and visa details, and the timeline.

What to bring

Bring a laptop with Python installed. MATLAB is optional. Installation instructions for PyNWB and MatNWB are on the resources page. Accepted participants receive preparatory materials six to eight weeks before the school.