CCN 2026 Satellite Event: Modeling and Understanding Human Brain Computation at Scale

Modeling and Understanding Human Brain Computation at Scale

https://kriegeskorte-lab.github.io/ccn-satellite-human-brain-foundation-model

Organizers: Hossein Adeli (Columbia), Pinyuan Feng (Columbia), Fan Cheng (Columbia),  Andrew Luo (HKU), and Nikolaus Kriegeskorte (Columbia)

This satellite workshop brought together researchers to discuss “Modeling and Understanding Human Brain Computation at Scale for the benefit of humanity”. The event was organized into three talk sessions and a panel discussion. 

In the first session, Hossein Adeli (Columbia), Yao Wang (NYU), Paul Scotti (Sophont), and Andrew Luo (HKU) discussed the best methods to build high-performing and useful encoding and decoding models for vision, audition and actions, and how to make the models generalize across subjects, scanners and tasks. 

In the second session, Iris Groen (University of Amsterdam), Colin Conwell (MIT), and Ratan Murty (Georgia Tech) discussed how we can go beyond prediction and probe the models to extract insights about the brain. 

In the third session, Jim DiCarlo (MIT), Shalmali Joshi (Columbia), and Martin Schrimpf (EPFL) presented on how we can build applications that benefit humanity from models of the brain computations, ranging from medical diagnosis, building models of disease for in-silico brain stimulation experiments, and guiding treatments. 

The panel discussion with Patrick Mineault (Amaranth Foundation), Teon Brooks (Meta), Shalmali Joshi (Columbia), and Nikolaus Kriegeskorte (Columbia) discussed how we can leverage the many recent advances with neural network modeling toward theoretical insights. The panel also discussed the value of the “black box” models trained for prediction along with how we should think of and formalize foundation models in neuroscience.