Fig. 2. Benefits and trade-offs in using different models.

While exceptions may exist, the interpretability of models usually occurs at the price of prediction performance and vice versa. In neuroscience research, including understanding the neural circuits underlying psychiatric disorders, interpretability (defined as the ability to understand the cognitive and neurobiological underpinnings of a model’s features) offers the greatest utility. In contrast, prediction performance is a priority in many real-world products and applications. We argue that the target goal for neuroimaging-based predictive models on the interpretability/prediction performance trade-off is on the interpretability side. At the moment, interpretable predictive models are expected to better advance neuroimaging research in psychiatry and complement traditional approaches than models that sacrifice interpretation for prediction performance.