Deep networks become strong predictors of brain data across vision, touch, and language
aran_nayebi · x · 2026-07-23
A brain-science thread argues that deep networks are not just loose analogies to brains, but among the best quantitative predictors of large-scale neural data.
- The author says the theory is that networks become good brain predictors when they are minimal solutions to hard tasks.
- The attached slides summarize what AI-driven modeling has revealed across species and brain areas, including primate vision, mouse vision, rodent touch, auditory cortex, medial entorhinal cortex, mental simulation, autonomy, language, and learning rules.
- The claim is that this framework has produced insights about the brain that would not have been available otherwise.
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