From model-based perceptual decision-making to spatial interference control

Model-based neuroscience is aimed at understanding latent cognitive processes using quantitative cognitive models in combination with neuroscientific measures. This approach has been successful in the domain of perceptual decision making, in which the properties of accumulator models of choice tasks have been related to neural networks that are involved in decision making. Here, we propose that this approach can also be applied to spatial interference control such as required in the Simon task. Spatial interference control is essential for understanding cognitive control processes. A model-based approach may aid in understanding the latent cognitive processes in spatial interference control. Ultimately this approach may uncover the relationship between decision making that requires interference control and default decision making such as perceptual choice.