NeuroAI trainees often feel caught between AI and neuro groups, lacking dedicated programs. Our work explores this, offering survey results & resources for trainees and institutions. We provide a living list of trainee resources in our GitHub: github.com/8erberg/NeuroAI_Trainee_Resources

SOTA in reconstructing seen images from fMRI brain activity, achieved via shared-subject modeling and fine-tuning SDXL.

Retrieval and reconstruction of seen images from fMRI brain activity using contrastive learning and diffusion modeling.

Violation & principles refinement can address pink elephant problem in large language models, illustrated via short interactive murder mystery game built with React.

Browser visualization tool. User can visualize anatomical areas of the brain and use our meta-analysis interface to overlay functional specializations.

Interactive textbook on computational neuroimaging methods using flowcharts, high-level method summaries, and practical Python examples using simulated data.

Python package for inverted encoding models to improve flexibility and interpretability of stimulus reconstructions.

We show how memories interact with each other to sometimes unconscious systematic repulsion biases.

We show it takes longer for attention to spread across a 10-inch picture of a car compared to a 10-inch picture of an eraser.