Data on the Brain & Mind

Concrete Applications of AI to Neuroscience and Cognitive Science
NeurIPS 2025, San Diego CA

Email: data-brain-mind@googlegroups.com

Overview

Our workshop aims to connect machine learning researchers with neuroscientists and cognitive scientists by focusing on concrete, open problems grounded in emerging neural datasets. Large-scale, open datasets are transforming the practice of research in a variety of neuroscience and cognitive science subdomains, including whole-brain circuitry (FlyWire; IBL; WormID), visual–motor cortical processing (MICrONS), human development (BabyView), and natural speech processing (MEG-MASC).

A key differentiator of our workshop is its focus on the rich diversity and heterogeneity of emerging neuroscience and cognitive science datasets. These are not your standard ML benchmarks; they span a wide array of data types including time series, images, videos, text, and even unconventional structures like connectome graphs from MICrONS. Each dataset possesses highly idiosyncratic meta-information, such as the spatial coordinates of electrodes in MEG recordings, that invites the development of tailored, sophisticated AI solutions. This departure from generic datasets encourages a move beyond one-size-fits-all foundation models, precisely the kinds of directions we aim to explore.

We believe a workshop focused on ML applied to such datasets is timely and presents a clear opportunity to help forge collaborations. Thus, we designed the workshop to be highly interactive. In addition, we invited speakers who have led large, open-sourced data initiatives or analyzed key datasets like those mentioned above.

There are three aims that shape the content and format of the workshop:


Datasets

Invited Speakers

Dan Yamins
Dan Yamins
Stanford University
Ila Fiete
Ila Fiete
MIT
Laura Gwilliams
Laura Gwilliams
Stanford University
Cengiz Pehlevan
Cengiz Pehlevan
Harvard University
Rajesh Rao
Rajesh Rao
University of Washington

Event Schedule

Time Event Details/Speakers
9:00 - 9:10am

Opening Remarks

9:10 - 9:50am

Lightning Talks

2-minute talks by authors of accepted papers.
9:50 - 10:20am

Invited Talk 1

Dan Yamins (Stanford)
Deep learning & visual cortex models

10:20 - 10:50am

Invited Talk 2

Ila Fiete (MIT)
Neural computation, spatial navigation & memory

11:00 - 11:50am

Discussion Sessions

Dataset-focused discussions on: Language in the brain, Visual & spatial intelligence, Brain-wide circuits, Human-like learning, and Human cognitive behaviors.

11:50 - 1:00pm

Mentoring Lunch

Connect with senior colleagues in small themed groups (PhD applications, work/life balance, research transitions).

1:00 - 1:30pm

Invited Talk 3

Laura Gwilliams (Stanford)
Cognitive neuroscience of language processing

1:30 - 2:00pm

Invited Talk 4

Cengiz Pehlevan (Harvard)
Models of neural computation & learning rules

2:00 - 2:40pm

Poster Session I

Contributed Works

2:50 - 3:20pm

Invited Talk 5

Rajesh Rao (University of Washington)
Computational models of perception & decision-making

3:20 - 3:50pm

Invited Talk 6

TBD

3:50 - 4:20pm

Un-Poster Session (Poster Session II)

Interactive session: visit other posters, discuss negative results, desired datasets/methods.

4:30 - 5:00pm

TBD

TBD

5:10 - 5:45pm

Moderated Panel

Discussion with invited speakers and panelists.

Call for Papers

We invite submissions in the following two tracks.
The review process is double-blind through our OpenReview portal for each track, and the submissions should be anonymized.

Reciprocal Review: To help ensure a fair and high-quality review process, we ask that each submission nominate at least one author to be available as a reviewer for the DBM workshop during September 9-19. It is sufficient if the nominated author has already signed up as a reviewer for the workshop.

Findings Track

Submissions should present original research on computational methods, theoretical frameworks, or quantitative findings that are applicable to neuroscience or cognitive science. We welcome 4-page or 8-page submissions of unpublished work (including work currently under review elsewhere). Previously published work is not eligible.

Examples:
  • Adaptations of existing methods to domain-specific problems
  • New insights gleaned from existing neural/cognitive experimental data
  • Theoretical or computational frameworks that could guide experimental design
  • Tools for standardized evaluation—building toward an "ImageNet for neuroscience"

Submission Template

Please use our official submission template when preparing your paper for the Findings track. Submissions not using the template may be desk-rejected. For authors new to LaTeX, we recommend using Overleaf. If you have any questions, please reach out to us.

Download the submission template (.zip)

Tutorials Track

Submissions should present pedagogical notebooks or blog posts discussing ML methods, neuroscience / cognitive science datasets, or conceptual frameworks, with the goal of facilitating interdisciplinary collaboration.

Examples:
  • Providing a well-formatted dataset of neural recordings, along with a Jupyter notebook showing how to load and use the dataset
  • Walking through how an ML method could be applied to a problem or class of problems in neuroscience or cognitive science
  • A blog post introducing a behavioral science dataset, and describing open questions and hypotheses that could be explored by ML practitioners

Requirements

Submissions to the tutorials track will be evaluated on pedagogical quality and relevance to the themes of the workshop. Tutorials do not need to be original research—it is fine to present existing datasets or methods (with appropriate attribution) in a more accessible way. Any dependencies (code, data, etc.) should be included in the submission with clear instructions for use.

Additional instructions for submitting tutorials are provided here.

Important Dates

Paper submission deadline September 4, 2025
Paper acceptance September 22, 2025
Camera-ready version due October 8, 2025 (AoE)

Frequently Asked Questions

Yes, please anonymize your submission.
We welcome concurrent submissions to both tracks, but each submission should stand on its own in content and contribution (and meet the standards of the track). Please see the calls for contributions for more details. We provide an option on OpenReview to indicate concurrent submission. In the case that the concurrent submissions of the same work are accepted to both tracks, the author(s) may consider presenting a single poster. We will help indicate that the poster presents both findings and a tutorial at the workshop.
The accepted papers for both tracks are considered non-archival and do not conflict with any future publications. The accepted papers will show up on OpenReview and can be cited from there. Work under review elsewhere is welcome.
For both tracks, all accepted submissions will be presented in the form of posters. Among the accepted submissions for both tracks, we will select and highlight the top submissions as oral talks in the workshop.
Yes, double submission is allowed as long as the work is on-topic for our workshop. At the same time, the goal of our workshop is to foster community participation and engagement. For that reason, we strongly encourage the presenting author to plan to attend the full workshop.

Organizers

Catherine Ji
Catherine Ji
Princeton University
Vivek Myers
Vivek Myers
UC Berkeley
Archer Wang
Archer Wang
MIT
Eva Yi Xie
Eva Yi Xie
Princeton University
Mahsa Bastankhah
Mahsa Bastankhah
Princeton University
Benjamin Eysenbach
Benjamin Eysenbach
Princeton University
Jenelle Feather
Jenelle Feather
Carnegie Mellon University
Erin Grant
Erin Grant
University College London
Richard Gao
Richard Gao
University of Tübingen