Andrea Ivan Costantino

This study identifies three principles of expert brain representation using chess as a model, showing shifts in content, structure, and location of neural representations.

This study shows that early visual deprivation in humans impairs the early visual cortex but leaves the categorical coding in the ventral occipito-temporal cortex largely unaffected.

This study compares recurrent and feedforward DNNs in modeling human visual recognition behavior, finding that model size, not recurrence, better aligns with human-like confusion patterns.

The paper investigates feedback from peripheral to foveal visual cortex using fMRI and finds limited information transfer with local V1 circuits.

This study investigates the human bias toward perceiving zoomorphic objects as animal-like and shows that this bias can be induced in deep neural networks with specific training.