@ithobani.bsky.social
Neuroscience postdoc at Stanford and Enigma (enigmaproject.ai), previously philosophy of neuroscience PhD. Building large-scale brain models using deep learning.
5/X So what is the IATC for the brain? In a simulated setting, we found that the neuronal activation function causes subjects’ activation patterns to diverge at each layer before re-converging. Correctly accounting for this “Zippering Effect” leads to a better IATC estimate.
October 6, 2025 at 3:24 PM
5/X So what is the IATC for the brain? In a simulated setting, we found that the neuronal activation function causes subjects’ activation patterns to diverge at each layer before re-converging. Correctly accounting for this “Zippering Effect” leads to a better IATC estimate.
4/X We propose the Inter-Animal Transform Class (IATC)—the strictest set of functions needed to map neural responses accurately between any two actual brains. We can use the IATC to align models to brains, effectively asking if a model can masquerade as a typical subject.
October 6, 2025 at 3:24 PM
4/X We propose the Inter-Animal Transform Class (IATC)—the strictest set of functions needed to map neural responses accurately between any two actual brains. We can use the IATC to align models to brains, effectively asking if a model can masquerade as a typical subject.
1/X Our new method, the Inter-Animal Transform Class (IATC), is a principled way to compare neural network models to the brain. It's the first to ensure both accurate brain activity predictions and specific identification of neural mechanisms.
Preprint: arxiv.org/abs/2510.02523
Preprint: arxiv.org/abs/2510.02523
October 6, 2025 at 3:22 PM
1/X Our new method, the Inter-Animal Transform Class (IATC), is a principled way to compare neural network models to the brain. It's the first to ensure both accurate brain activity predictions and specific identification of neural mechanisms.
Preprint: arxiv.org/abs/2510.02523
Preprint: arxiv.org/abs/2510.02523