Andres de Vicente

Nethobench evaluates neural forecasting models using structural metrics across multiple families, revealing how design choices affect model performance on mouse and human neural data.

This study shows that equivalent learning outcomes emerge through different population dynamics in motor cortex and hippocampus during volitional control tasks.