Predictive Coding Dynamics Enhance Model-Brain Similarity

Predictive coding-a popular theory in neuroscience-has garnered significant attention in the machine learning community aiming to incorporate brain-inspired components in neural networks.While various proposals have demonstrated the ability of predictive dynamics to render robustness and entail human-like perception of illusions, it remains unclear if they improve the alignment between brain and artificial representations.Here, we systematically investigate the conditions under which brain-inspired modifications in predictive processing improve alignment between model and neural representations in the brain.Our results reveal that the feedback component significantly increases similarity between model representations and those found in higher-level visual brain areas, especially when processing complex visual scenes. Feature extraction ROIsRegression