arXiv Computer Vision By Yingtian Tang, Sogand Salehi, Ming Zhou, Amir Zamir, Leyla Isik, Martin Schrimpf

NEvo: Neural-Guided Evolutionary Video Synthesis for Dynamic Visual Selectivity

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NEvo is a neural‑guided evolutionary video synthesis framework that generates dynamic stimuli optimized for specific brain regions in the visual cortex. It performs evolutionary search over a structured prompt space, guided by a dynamic encoding model that predicts voxel‑level responses to video inputs, thereby discovering hyper‑activating videos that outperform handcrafted localizers. The synthesized videos recover known selectivities across ventral, dorsal, and lateral pathways and reveal systematic differences in sensitivity to temporal dynamics, offering new insights into the progression of social‑dynamic features along the lateral stream.

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