Topic: Normative neural network models

Normative neural network models provide a valuable tool for answering principled ‘why’ questions about neural structure, function, and organisation from an optimization perspective. However, typical approaches often compare models without controlling for differences in architecture, training dataset or model objective. As a result, it is often difficult to make strong conclusions relating variation in model performance to a given characteristic. Here we ask what factors tend to make models predict neural responses most effectively?To investigate this, we explored how hyperparameter choice impa