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Sparsity and Robustness

Sparsity in neural representations enhances robustness by minimizing the overlap among active neurons. When classifying high-dimensional data, fewer active neurons lead to a greater challenge in fooling the system, as significant changes across multiple neurons are required to alter the representation. This insight sheds light on how the brain's architecture contributes to its resilience against noise and variability.