A tale of two architectures: Free energy, its models, and modularity

The paper presents a model-based defence of the partial functional/informational segregation of cognition in the context of the predictive architecture. The paper argues that the model-relativeness of modularity does not need to undermine its tenability. In fact, it holds that using models is indispensable to scientific practice, and it builds its argument about the indispensability of modularity to predictive architecture on the indispensability of scientific models. More specifically to defend the modularity thesis, the paper confutes two counterarguments that lie at the centre of Hipolito and Kirchhoff's (2019) recent confutation of the modularity thesis. The main insight of the paper is that Hipolito and Kirchhoff's counterarguments miss the mark because they dismiss a few rudimentary facts about the model-based nature of dynamical causal models and Markov blankets.